Skills Over Resumes: How to Assess Real-World DevOps Talent

Introduction

Resumes might tell you where a candidate has worked, but they don’t always reveal how well they can actually perform in a real-world DevOps environment. In today’s fast-moving tech landscape, hiring DevOps engineers based on skills rather than just job titles or degrees is the smarter approach.

This blog post will guide you on assessing real-world DevOps talent beyond the traditional resume. We’ll explore the essential skills, practical assessments, and strategies for identifying the right DevOps engineers for your team.

Why Skills Matter More Than Resumes

A resume lists qualifications, but it doesn’t measure hands-on expertise. DevOps is a highly technical field that requires problem-solving, collaboration, and automation skills. When hiring a DevOps engineer, focusing on real-world capabilities ensures you get a candidate who can thrive in a dynamic environment.

Key Skills Every DevOps Engineer Needs

1. Automation and Scripting

A strong DevOps engineer must be proficient in automation tools like Ansible, Terraform, and Kubernetes. Scripting knowledge in languages such as Python, Bash, or PowerShell is essential for writing infrastructure-as-code and automating repetitive tasks.

2. CI/CD Pipelines

Understanding Continuous Integration/Continuous Deployment (CI/CD) pipelines is crucial for delivering reliable software quickly. DevOps professionals should be skilled in Jenkins, GitHub Actions, GitLab CI, or CircleCI to streamline software development and deployment.

3. Cloud Platforms

With most businesses moving to the cloud, experience with AWS, Azure, or Google Cloud is a must. A skilled DevOps engineer knows how to manage cloud resources efficiently and securely.

4. Containerization and Orchestration

Containers, especially Docker and Kubernetes, have revolutionized software deployment. Candidates should be able to build, deploy, and manage containerized applications effectively.

5. Infrastructure as Code (IaC)

Managing infrastructure through code ensures consistency and scalability. Familiarity with Terraform, CloudFormation, or Puppet is a major plus.

6. Monitoring and Logging

Real-time monitoring tools like Prometheus, Grafana, and ELK Stack help keep systems healthy. A DevOps engineer must be skilled in setting up and managing these tools.

7. Security Best Practices

Security should be integrated into every step of the DevOps lifecycle. Engineers must understand secrets management, secure coding practices, and compliance frameworks like SOC 2 or ISO 27001.

8. Collaboration and Communication

DevOps is as much about people as it is about technology. Engineers need strong collaboration skills to work effectively with development, operations, and security teams.

9. Problem-Solving and Adaptability

Things go wrong in tech—often. DevOps professionals need to be able to troubleshoot quickly and adapt to new technologies and workflows as they emerge.

How to Assess Real-World DevOps Skills

1. Practical Coding Challenges

Give candidates real-world problems to solve using automation scripts, CI/CD pipelines, or infrastructure as code.

2. Hands-on Labs or Take-Home Assignments

Set up a cloud environment and have them deploy a simple application, troubleshoot an issue, or set up monitoring.

3. Live Technical Interviews

Instead of just talking theory, have candidates share their screens and walk through a DevOps scenario in real-time.

4. Scenario-Based Questions

Ask how they would handle a major system failure, automate a repetitive task, or scale a cloud application under heavy load.

5. Open-Source Contributions or Past Projects

Review their GitHub repositories, DevOps blog posts, or open-source contributions to assess their real-world expertise.

FAQs about Skills Over Resumes: How to Assess Real-World DevOps Talent

1. Why is skills-based hiring important in DevOps?

Because DevOps is a hands-on field, real-world skills are more valuable than credentials. A candidate with practical experience can contribute faster and more effectively.

2. What are the best ways to assess DevOps skills?

Live coding challenges, hands-on projects, and reviewing past work (like GitHub repositories) are the best ways to gauge a candidate’s real abilities.

3. What tools should a DevOps engineer know?

Key tools include Kubernetes, Docker, Terraform, Ansible, Jenkins, AWS, Azure, Prometheus, and ELK Stack.

4. How can companies test problem-solving skills in DevOps?

Present candidates with real-world issues, such as debugging a failing deployment or optimizing a CI/CD pipeline.

5. How does DevOps hiring differ from traditional IT hiring?

Traditional hiring often relies on degrees and experience, whereas DevOps hiring focuses more on practical, hands-on skills.

FAQs about Brokee

1. What is Brokee?

Brokee is a leading platform that connects businesses with top DevOps talent through a skills-based hiring approach.

2. How does Brokee help companies hire better?

We offer hands-on skill assessments, live coding challenges, and AI-driven talent matching to ensure you hire the best DevOps engineers.

3. What makes Brokee different from traditional hiring platforms?

Unlike resume-based hiring platforms, Brokee focuses on real-world skills, providing companies with proven DevOps talent.

4. Does Brokee support remote hiring?

Yes! We connect businesses with top DevOps engineers worldwide for both remote and on-site roles.

5. How can I sign up for Brokee?

Visit our website, create a company profile, and start assessing top-tier DevOps talent today.

Conclusion

Hiring DevOps talent based on skills rather than resumes leads to stronger, more capable teams. By using real-world assessments, hands-on projects, and practical interviews, businesses can ensure they hire engineers who can perform under pressure. Whether you’re looking for your next DevOps hire or refining your own skills, focusing on hands-on expertise will set you up for success.

The Ultimate Guide to Hiring Top ReactJS Developers Using Skills Tests

Hiring the right ReactJS developer is a game-changer for businesses. But how do you ensure you’re bringing the right talent on board? Skills tests are the secret weapon that can streamline the hiring process and guarantee you’re picking the cream of the crop. In this guide, we’ll dive into everything you need to know about hiring top ReactJS developers using skills tests, from understanding React development to why testing and quality assurance (QA) are essential.

Understanding React Development

ReactJS is a powerful JavaScript library developed by Facebook for building dynamic user interfaces. Its component-based architecture and efficient virtual DOM make it a favorite for developers creating fast, scalable, and responsive web apps.

What Does a ReactJS Developer Do?

A ReactJS developer is responsible for:

• Developing reusable UI components.

• Managing application state using libraries like Redux or Context API.

• Optimizing application performance.

• Collaborating with designers and back-end developers to deliver a cohesive product.

However, a top-notch React developer goes beyond these basics. They have expertise in related tools, understand user experience, and are adept at testing and QA.

The Importance of Testing and Quality Assurance

In the fast-paced world of software development, functionality isn’t enough—reliability and user satisfaction are critical. That’s where testing and QA come in.

Why Are Testing and QA Crucial for React Development?

• Prevent Bugs: Early testing catches errors before they affect users.

• Enhance Stability: Quality assurance ensures your application remains stable and performs well under stress.

• Improve User Experience: A bug-free, intuitive app keeps users happy.

• Save Time and Money: Identifying issues early avoids costly fixes later.

By hiring a ReactJS developer with testing skills, you’re investing in a smoother development process and a better end product.

How Skills Tests Make Hiring Easier

Skills tests help you evaluate a candidate’s abilities in real-world scenarios. They’re more than just a buzzword—they’re your key to hiring success.

Benefits of Skills Tests

• Objective Assessment: Evaluate candidates based on their actual work, not just resumes.

• Time Efficiency: Filter out unqualified candidates quickly.

• Real-World Scenarios: See how candidates perform tasks similar to those they’ll handle on the job.

• Better Hiring Decisions: Focus on candidates who demonstrate the required skills and expertise.

Essential Skills to Test

When creating a skills test for ReactJS developers, consider including tasks that cover:

1. React Fundamentals: Building and managing components, state, and props.

2. JavaScript Proficiency: ES6+ syntax, promises, and async/await.

3. State Management: Redux, Context API, or other libraries.

4. Testing and QA: Writing unit and integration tests using Jest, Enzyme, or Cypress.

5. CSS and HTML Skills: Styling components and creating responsive designs.

Steps to Hire Top ReactJS Developers Using Skills Tests

Step 1: Write a Clear Job Description

Your job posting should specify:

• Project goals.

• Required skills (e.g., React, Redux, testing frameworks).

• Desired experience level.

• Details about the role and responsibilities.

Step 2: Screen Candidates

Look for:

• Relevant project experience.

• Strong portfolios showcasing React work.

• Knowledge of modern development tools and practices.

Step 3: Conduct a Skills Test

Create a test that mimics real-world challenges. Example tasks include:

• Debugging an existing React app.

• Building a small component with specific functionality.

• Writing unit tests for a given module.

Step 4: Hold a Technical Interview

Use the interview to:

• Discuss their approach to the skills test.

• Assess their understanding of testing and QA.

• Evaluate problem-solving and communication skills.

Step 5: Make the Hiring Decision

After reviewing test results and interview performance, choose the candidate who aligns with your project needs and team culture.

FAQs about The Ultimate Guide to Hiring Top ReactJS Developers Using Skills Tests

Why Use Skills Tests to Hire ReactJS Developers?

Skills tests provide a practical way to assess a candidate’s abilities, ensuring they have the technical expertise required for your project. They’re especially useful for identifying developers with strong testing and QA skills.

What Are the Key Skills for ReactJS Developers?

• Proficiency in React, JavaScript, HTML, and CSS.

• Experience with state management libraries like Redux.

• Familiarity with testing frameworks (Jest, Cypress).

• Knowledge of agile methodologies.

How Much Does It Cost to Hire a ReactJS Developer?

Costs vary by location and experience:

• North America: $80 – $150/hour.

• Western Europe: $50 – $100/hour.

• Eastern Europe: $30 – $60/hour.

• Asia: $20 – $40/hour.

Can I Save Money by Hiring Offshore Developers?

Yes! Offshore teams often offer competitive rates without compromising quality. Just ensure they have strong testing and QA processes in place.

How Does Brokee Help with Hiring ReactJS Developers?

At Brokee, we specialize in connecting businesses with top-tier developers. Our curated talent pool ensures you’ll find professionals with the exact skills you need, including ReactJS and testing expertise. We make hiring stress-free by handling the screening and vetting for you.

What Makes Brokee Different?

• Customized Talent Matching: We match developers to your specific needs.

• Pre-Vetted Experts: All candidates are rigorously screened.

• Support Throughout the Hiring Process: From job posting to onboarding, we’ve got you covered.

Conclusion

Hiring a top ReactJS developer doesn’t have to be daunting. By leveraging skills tests, you can objectively assess candidates’ abilities and find the perfect match for your project. Whether you’re building a dynamic web app or scaling an existing product, a skilled React developer with strong testing and QA expertise is your ticket to success.

Ready to hire your next ReactJS superstar? Let Brokee help you find the right fit today!

How to Build an Effective DevOps Hiring Strategy with Skills Assessments

By George Goodwin

Recruiting the right DevOps engineer is a critical step for companies aiming to streamline their software delivery and improve operational efficiency. But how can you make sure your hiring strategy is effective? The secret lies in combining targeted recruitment strategies with real-world skills assessments. Let’s break it down.

Understanding DevOps and Its Importance

What is DevOps?

DevOps is a culture and set of practices that bridge the gap between development and operations teams. It focuses on collaboration, automation, and continuous delivery. DevOps engineers play a key role in ensuring smooth workflows, reduced development cycles, and high-quality software delivery.

Why is DevOps Recruitment Challenging?

The demand for skilled DevOps professionals is skyrocketing, with roles growing by 25% annually. This makes recruitment competitive and requires companies to stand out with a well-defined hiring strategy and attractive employer branding.

Strategy to Hire a Skilled DevOps Engineer

1. Define Your Needs

Before starting your search, get clear about the role requirements. Ask yourself:

• What are the technologies and tools the candidate must know (e.g., Docker, Kubernetes, CI/CD systems)?

• What kind of projects will they work on?

• Are there specific challenges they need to address?

2. Create a Compelling Job Description

A good job description can attract the right candidates. Highlight:

• Responsibilities and expectations.

• Skills and experience required.

• Your company culture and values.

• Opportunities for growth and innovation.

3. Leverage Multiple Recruitment Channels

Don’t rely solely on traditional job boards. Use:

• Online forums and communities for DevOps professionals.

• LinkedIn and other networking platforms.

• Employee referrals to tap into trusted talent pools.

Top Skills and Qualities for DevOps Engineer Professionals

Technical Skills to Look For

• Cloud Expertise: AWS, Azure, or GCP knowledge.

• Containerization: Mastery of Docker and Kubernetes.

• CI/CD Pipelines: Experience with Jenkins, GitLab CI/CD, or similar tools.

• Infrastructure as Code (IaC): Skills in Terraform or Ansible.

• Scripting Languages: Python, Bash, or PowerShell proficiency.

Soft Skills to Prioritize

• Strong problem-solving abilities.

• Excellent communication and collaboration.

• Adaptability and a learning mindset.

• Resilience under pressure.

How to Conduct Online Assessments for DevOps Hiring

Online assessments are essential for evaluating candidates’ skills in real-world scenarios. Here’s how to do it effectively:

1. Create Scenario-Based Tests

Present candidates with challenges they might face in the role, such as optimizing a CI/CD pipeline or resolving an outage.

2. Evaluate Technical Skills

Use coding exercises and system simulations to test programming and systems management knowledge.

3. Assess Collaboration and Communication

Include tasks that require teamwork or explain decision-making processes. This helps gauge how well they’ll fit into your team.

Why Do Companies Use Real-World DevOps Tasks to Judge Engineers?

Practical Insight

Real-world tasks reveal how candidates think, troubleshoot, and apply their knowledge in practical situations. It’s a better indicator of their abilities than theoretical questions.

Cultural Fit

Seeing how candidates handle collaborative scenarios can show how well they align with your company’s culture and workflow.

Problem-Solving Skills

DevOps often involves solving unexpected problems. Scenario-based assessments help you understand how candidates approach challenges.

Future Aspects of DevOps Engineers

The role of DevOps engineers is evolving rapidly. Future trends include:

• Greater emphasis on automation and AI-driven DevOps tools.

• Increased demand for security expertise in DevOps pipelines.

• Growth in hybrid cloud and multi-cloud environments, requiring broader skillsets.

Investing in ongoing training and professional development for your DevOps team will ensure they stay ahead in this fast-changing field.

FAQs About How to Build an Effective DevOps Hiring Strategy with Skills Assessments

Why are skills assessments important in DevOps hiring?

Skills assessments provide practical insights into candidates’ abilities, ensuring they have the technical expertise and problem-solving skills required for the role.

How do I attract top DevOps talent?

Focus on employer branding, offer competitive compensation, and showcase opportunities for growth and innovation in your company.

What tools can I use for online skills assessments?

Platforms like Codility, HackerRank, or custom tools tailored to DevOps challenges can help design effective assessments.

How can I ensure a cultural fit?

Use behavioral interview questions to explore candidates’ teamwork, adaptability, and past experiences in collaborative environments.

About Brokee

What is Brokee?

Brokee is a cutting-edge platform designed to simplify hiring for technical roles, including DevOps engineers. We offer:

• Real-world skills assessments tailored to your hiring needs.

• Advanced analytics to help you identify the best candidates.

• Seamless integration with your existing hiring process.

How does Brokee help with DevOps hiring?

Brokee provides scenario-based tests and technical assessments to evaluate DevOps candidates effectively. Our tools save time and ensure you hire the right talent for your team.

Building an effective DevOps hiring strategy requires a mix of clear planning, targeted recruitment, and practical assessments. By focusing on the right skills, leveraging real-world tasks, and prioritizing cultural fit, you can build a team that drives innovation and success. Ready to transform your DevOps hiring? Contact us today!

Integrating NATS and JetStream: Modernizing Our Internal Communication

High-level NATS architecture

Introduction

Brokee was built using microservice architecture from day one as the initial focus for skills assessment was Kubernetes, and later we expanded to other technologies. At the same time, as new services were added, we sometimes took shortcuts with design decisions. Over the years, it resulted in a spaghetti architecture where many services were interconnected with each other and it became harder and harder to reason about dependencies and figure out which functionality should go to which service.

Discover how we improved our system's communication by integrating NATS messaging system and their JetStream functionality. We delve into the challenges we faced, the lessons we learned, and how we simplified our setup to make it more efficient. This integration has laid the foundation for a more scalable and resilient infrastructure, enabling us to adapt and innovate as our platform grows.

Why Change?

Our previous architecture relied heavily on a synchronous request-response model. While this served us well initially, it began to show limitations as our platform grew:

• Scalability issues: Increasing traffic caused bottlenecks in our services.

• Lack of flexibility: Adding new features required significant changes to the existing communication flow.

• Reduced reliability: Single points of failure in the system led to occasional downtime.

Even though we use backoff and retry strategies in our APIs, requests can still fail if the server is unreachable, unable to handle them, or overwhelmed by too many requests. We needed a more robust, asynchronous system that could scale effortlessly. That’s when we turned to NATS and JetStream, which offered persistence.

Old architecture: tightly coupled services using synchronous request-response communication.

What is NATS and JetStream?

NATS is a lightweight, high-performance messaging system that supports pub/sub communication. JetStream extends NATS by adding durable message storage and stream processing capabilities, making it ideal for modern, distributed systems. For developers using the SDK, NATS offers support for a variety of programming languages, making it a flexible solution for integrating messaging capabilities.

With NATS and JetStream, we could:

• Decouple services: Allow services to communicate without direct dependencies.

• Enable persistence: Use JetStream’s durable subscriptions to ensure no messages are lost.

• Simplify scaling: Seamlessly handle spikes in traffic without major architectural changes.

New architecture: decoupled services with asynchronous pub/sub communication via NATS.

The Integration Process

Here’s how we integrated NATS into our platform:

1. Setting Up NATS

We deployed NATS using Helm. Helm made the installation and configuration straightforward, allowing us to define resources and dependencies in a consistent, repeatable way.

To ensure reliability and scalability, we set up 3 running server instances of NATS, leveraging its clustering capabilities and the Raft consensus algorithm to handle increased traffic and provide fault tolerance.

For storage, we used persistent volumes, ensuring durability. NATS also offers the option to use memory-based storage. However, to optimize memory usage and prevent overload on our nodes, we decided to switch to persistent volume storage.

Additionally, we made the deployment more resilient by ensuring NATS instances were safely scheduled on separate nodes to avoid single points of failure and ensure high availability. We opted for the NATS headless service type as NATS clients need to be able to talk to server instances directly without load balancing.

config:
  jetstream:
    enabled: true
    fileStore:
      enabled: true
      pvc:
        enabled: true
        size: 10Gi
        storageClassName: premium-rwo-retain
  cluster:
    enabled: true
    replicas: 3

statefulSet:
  merge:
    spec:
      template:
        metadata:
          annotations:
            cluster-autoscaler.kubernetes.io/safe-to-evict: "false"

podTemplate:
  topologySpreadConstraints:
    kubernetes.io/hostname:
      maxSkew: 1
      whenUnsatisfiable: "DoNotSchedule"

2. Migrating to Pub/Sub

Our first step was replacing direct request-response calls with pub/sub communication. For example:

• Before: Common Service would send an HTTP request directly to Auth Service and await a response.

• After: Common Service publishes a message to the subject auth.users.roles.assign, which is then processed asynchronously by the Auth Service that subscribes to this subject.

We incorporated the Request-Reply pattern, which NATS makes simple and efficient using its core pub/sub mechanism. In this pattern, a request is published on a subject with a unique "inbox" reply subject. Responders send their replies to the inbox, enabling real-time responses. This approach is particularly useful for scenarios requiring immediate feedback.

To distribute the workload randomly across multiple instances, the Auth Service subscribes as part of a queue group, ensuring messages are distributed to different instances. NATS automatically manages to scale responders through these groups and ensures reliability with features like "drain before exiting" to process pending messages.

In the next Golang example, we prepare a payload and publish it as a request to a mentioned subject from the Common service using NATS. This demonstrates how the Request-Reply pattern enables sending data to a subject and awaiting a response.

---

func NATSRequestAssignCompanyRoleForUser(
    nc *nats.Conn,
    userID string,
    roleID string,
    timeout int,
) error {
    // subject -> 'auth.users.roles.assign'
    subject := models.Nats.Subjects.UsersRoleAssign
    
    payload := models.RoleAssignmentPayload{
        UserID:  userID,
        RoleIDs: []string{roleID},
    }

    payloadBytes, err := json.Marshal(payload)
    if err != nil {
        return fmt.Errorf("failed to marshal payload: %w", err)
    }

    msg, err := nc.Request(subject, payloadBytes, time.Duration(timeout)*time.Second)
    if err != nil {
        return fmt.Errorf("failed to send NATS request: %w", err)
    }
    
    var response map[string]interface{}
    if err := json.Unmarshal(msg.Data, &response); err != nil {
        return fmt.Errorf("failed to unmarshal response: %w", err)

    }
    
    success, ok := response["success"].(bool)
    if !ok || !success {
        return fmt.Errorf("role assignment failed, response: %v", response)
    }

    return nil
}

---

In this example, we set up a subscriber with a queue group that listens to the same subject in the Auth service. The queue group ensures load balancing among subscribers, while the handler processes the requests with the relevant business logic, sending responses back to the requester.

---

func SubscribeToRoleAssignQueue(
    nc *nats.Conn, handler func(msg *nats.Msg),
) error {
    _, err := nc.QueueSubscribe(
        models.Nats.Subjects.UsersRoleAssign,
        models.Nats.Queues.UserRolesAssign,
        func(msg *nats.Msg) {
            handler(msg)
        })
    if err != nil {
        return err
    }
    return nil
}

---

In a typical pub/sub setup, if a service fails or is unavailable, there’s no automatic way to repeat the message, and it can fail silently. To address this, we turned to JetStream, which provides message persistence and reliable delivery. With JetStream, even if a service goes down, messages can be reprocessed once the service is back online, ensuring no data is lost and improving overall system reliability.

3. Implementing JetStream

JetStream added persistence to our messaging:

• Streams: We defined streams to capture messages, grouping related data for efficient processing. For example, an stack.delete could store all stacks destroying messages, ensuring messages are retained and available for subscribers even during downtime.

  In the example below, we defined a JetStream stream named STACKS for managing testing stack operations. It subscribes to a single subject, stack.delete but multiple subjects can be specified. The stream has a 1GB storage limit (maxBytes) and uses file storage with three replicas for fault tolerance. The retention policy is set to workqueue, ensuring messages are retained until processed, and once a message is acknowledged, it will be deleted from the stream. It connects to the specified NATS server instances for message handling.

---

apiVersion: jetstream.nats.io/v1beta2
kind: Stream
metadata:
  name: stacks
spec:
  name: STACKS
  description: "Manage stack operations"
  subjects: ["stack.delete"]
  maxBytes: 1073741824
  storage: file
  replicas: 3
  retention: workqueue
  servers:
    - "nats://nats-headless.nats-system:4222"

---

• Durable Subscriptions: Services could subscribe to streams and resume from where they left off, ensuring no data loss.

  To provide flexibility and control over JetStream and consumer (a component that subscribes to a stream and processes the messages stored in that stream), we manage configurations through a manifest chart using JetStream Kubernetes controller called NACK, minimizing the need for code editing and rebuilding.

  In the code, only minimal edits are required for specifying the subject, consumer, and queue group names. This approach ensures the configuration of streams and consumers is easily adjustable.

  Additionally, we use push mode for streams, where messages are handled when placed in the queue. For durable queue consumers, the consumer and delivery group names must be the same to maintain consistency and work as expected.

• Backoff and Acknowledgments: We use backoff in consumer configuration to control the number of retry attempts for message redelivery. Additionally, we set ackWait and maxDeliver to define how long to wait before knowing if a message is acknowledged and after will be delivered.

  In some places, we use backoff, while in others, we use ackWait with maxDeliver. You can use either backoff or ackWait, but not both together: for multiple retries, backoff is preferred; for fewer retries, ackWait is set to the execution time of your handler plus an additional 20-30% buffer, ensuring sufficient time to prevent premature exits and unacknowledged message.

  We also manually acknowledge messages after executing code, particularly in cases where validation fails due to invalid data, as there’s no need to redeliver the message. This helps to avoid unnecessary retries.

  The next configuration sets up a JetStream consumer named stack-delete for the deletion of infrastructure stacks. It subscribes to the stack.delete subject same as in stream subjects(via filterSubject) and uses a durable name STACK_DELETE, ensuring message delivery resumes from where it left off.

---

apiVersion: jetstream.nats.io/v1beta2
kind: Consumer
metadata:
  name: stack-delete
spec:
  ackPolicy: explicit
  ackWait: 20m
  deliverGroup: STACK_DELETE
  deliverSubject: deliver.stack.delete
  deliverPolicy: all
  description: Delete stack resources
  durableName: STACK_DELETE
  filterSubject: stack.delete
  maxAckPending: 1000
  maxDeliver: 5
  replayPolicy: instant
  servers:
    - "nats://nats-headless.nats-system:4222"
  streamName: STACKS

An example of using backoff instead of ackWait: By setting the desired retry interval instead of using ackWait, we ensure the total backoff interval is less than the maxDeliver value, or it will fail during creation/update. If there’s free interval capacity, it will reattempt with the last backoff interval.

...
spec:
  ackPolicy: explicit
  backoff:
    - 1m
    - 5m
    - 10m

---

Key settings include:

• ackPolicy: Explicit acknowledgment ensures messages are redelivered if not acknowledged.

• ackWait: Set to 20 minutes to accommodate infrastructure destruction that can take up to 10-15 minutes in some cases.

• deliverGroup & deliverSubject: Enables queue group-based delivery to STACK_DELETE, ensuring load balancing among subscribers.

• maxAckPending: Limits unacknowledged messages to 1,000.

• maxDeliver: Allows up to 5 delivery attempts per message, retrying every 20 minutes. If the message is not acknowledged after 5 attempts, it will remain in the stream.

• replayPolicy: Instant replay delivers messages as quickly as possible.

• servers: The consumer connects to the STACKS stream on specified NATS servers for processing messages.

Next, we send a message to the stack.delete subject to request the deletion of a stack (the following example is written in Python). The process is straightforward: we create a message with the necessary information (userhash and test_id), and then publish it to the NATS server. Once the message is sent, we close the connection and return a response indicating whether the operation was successful or not.

---

async def delete_infra_stack(
    userhash: str,
    test_id: str,
) -> Dict[str, str]:

    try:
        nc = NATS()
        await nc.connect(servers=[NATSConfig.server_url])

        message = {"candidateId": userhash, "testId": test_id}

        await nc.publish(
            subject=NATSConfig.sub_stack_delete,
            payload=json.dumps(message).encode("utf-8"),
        )

        await nc.close()

        response = {
            "success": True,
            "message": f"Published {NATSConfig.sub_stack_delete} for {userhash}-{test_id}",
        }
    except Exception as e:
        response = {
            "success": False,
            "message": str(e),
        }

    return response

In the next code snippet written in Golang (we use multiple languages for our backend code), the consumer subscribes to the stack.delete subject using the STACK_DELETE durable name. This allows the consumer to handle stack deletion requests while maintaining message persistence and retry logic as configured in JetStream. As you may notice subscribing is pretty straightforward as we manage the consumer configuration through the chart, which simplifies setup and allows easy adjustments without complex code changes.

---

func SubscribeToJSDestroyStack(js nats.JetStreamContext, svc Service) error {
    subject := Nats.Subjects.StackDelete
    durableName := Nats.DurableName.StackDelete

    _, err := js.QueueSubscribe(subject, durableName, func(msg *nats.Msg) {
        handleDeleteStack(msg, svc)
    }, nats.Durable(durableName), nats.ManualAck())

    if err != nil {
        return fmt.Errorf("Error subscribing to %s: %v", subject, err)
    }

    return nil
}

func handleDeleteStack(msg *nats.Msg, svc Service) {
    var req deleteStackRequest
    if err := json.Unmarshal(msg.Data, &req); err != nil {
        // ack on bad request data
        msg.Ack()
        return
    }

    if _, err := svc.DeleteStack(context.Background(), req.TestId, req.CandidateId, msg); err == nil {
        // ack on success
        msg.Ack()
    }
}

---

4. Testing and Optimisation

We rigorously tested the system under load to ensure reliability and fine-tuned the configurations for optimal performance. Through this process, we identified the ideal settings for our message flow, ensuring efficient redelivery and minimal retries.

Challenges and Lessons Learned

Integrating NATS into our system posed several challenges, each of which provided valuable lessons in how to leverage NATS' features more effectively:

1. Request/Reply and Durable Subscriptions:
   

   Initially, we thought the request/reply pattern would work well for durable subscriptions, as it seemed like a good way to ensure that every request would be retried in case of failure. However, we quickly realized that request/reply is more suited for real-time, immediate communication rather than long-term durability.

   For durability, JetStream turned out to be the better option, as it ensures messages are stored persistently and retried until successfully processed. However, JetStream only delivers each message to a single designated consumer (the one configured to handle it), rather than broadcasting it to all subscribers.

2. Consumer and Queue Group Names:

   
   We learned that for durable consumers to function properly, the consumer name and the queue group must be the same. If they don't match, the consumer won't subscribe to the stream, leading to issues in message delivery and distribution.

   This realization came after some trial and error. We tried subscribing to durable subscriptions but encountered errors. To understand what went wrong, we dug into the source code of the SDK and discovered the importance of matching the consumer name and queue group. Surprisingly, we didn’t find this mentioned clearly in the documentation, or perhaps we missed it.

3. Backoff vs. AckWait:
   

   At first, we experimented with using both backoff and ackWait together, thinking it would allow us to fine-tune the retry behavior. We expected ackWait to control the waiting period for message acknowledgment, and then back off would manage retries with delays.

   We first applied changes to the settings through Helm, and there were no errors, so we thought the changes were successfully applied. However, during testing, we noticed that the behavior wasn't as expected. When we checked the settings using NATS-Box Kubernetes pod, we found that the changes hadn’t taken effect. We then tried to edit the configurations directly in NATS-Box but encountered an error stating that the settings were not editable. This led to further investigation, as we realized that only one of either ackWait or backoff should be used to make it work.

4. Manual Acknowledgment:
   

   One of the key lessons was the importance of manual acknowledgment. During our tests, we encountered situations where, even though the handler failed for some subscriptions, the message was still automatically acknowledged.

   For instance, when an internal server error occurred, the message was considered acknowledged even though it wasn’t fully processed. We initially assumed that the acknowledgment would happen automatically if the message was successfully handled, similar to how HTTP requests typically behave.

   However, when we moved to manual acknowledgment and controlled the timing ourselves, it worked perfectly. This change prevented false positives and ensured that messages weren’t prematurely acknowledged, even when an error or timeout occurred.

5. Testing with NATS-Box:
   

   NATS-Box(available as part of NATS deployment) became an invaluable tool for us in testing and creating configurations. It allowed us to experiment and understand the impact of different settings on system behavior, helping us refine our approach to ensure optimal performance in real-world scenarios.

   As we mentioned earlier, it helped us uncover small misunderstandings and nuances that weren't immediately obvious, giving us a deeper insight into how our configurations were being applied.

Conclusion

In conclusion, integrating NATS into our system proved to be a fast and efficient solution for our messaging needs. It wasn't without its challenges, but through testing and exploration, we were able to fine-tune the configurations to fit our needs. While we started with a simple setup, we may expand the use of NATS beyond internal communication to incorporate more features like monitoring and dead-letter queues. Additionally, we are considering replacing more of our internal architecture communication with NATS' pub/sub, and even potentially using NATS for external communication, replacing some of our REST APIs.

Based on our experience, using NATS with JetStream for durable messaging has proven to be a solid solution for ensuring reliable communication in our system. If you're looking to improve your system’s communication and explore event-driven architecture, we recommend considering NATS as a scalable and dependable choice, particularly for internal communication needs.

Building a Strong IT and DevOps Team for Grocery Stores and Retail Businesses During Natural Disasters

Natural disasters, particularly in high-risk regions like Southern California, create challenges not just for physical infrastructure but also for businesses’ digital systems. Wildfires, in particular, pose a significant threat to businesses, including grocery stores, by damaging physical locations and disrupting supply chains. But what about your digital infrastructure? As we’ve seen, many businesses struggle to maintain cybersecurity and operational continuity during a disaster.

This is where a strong DevOps team and IT systems come into play, especially in industries like grocery retail. In this post, we’ll explore how grocery stores and other retail businesses can leverage Brokee.io software tools to build, develop, and hire a resilient DevOps team, ensuring they stay operational through even the most challenging circumstances.

The Importance of IT and DevOps Teams in Disaster Preparedness

Grocery stores and retail businesses are increasingly reliant on technology, from maintaining inventory systems and processing transactions to managing customer data. During a natural disaster like a wildfire, IT systems can be disrupted by power outages, cyberattacks, or physical damage to infrastructure. A strong DevOps team ensures that businesses are prepared for these challenges by focusing on:

• Cybersecurity: Protecting sensitive data and preventing cyberattacks that increase during emergencies.

• Data Backup and Disaster Recovery: Ensuring systems are backed up and can be restored quickly after a disaster.

• Cloud Infrastructure: Moving critical systems to the cloud for better resilience and remote access during crises.

This level of preparedness is not just crucial for larger companies; even small and medium-sized grocery stores can benefit significantly from a well-organized IT and DevOps strategy.

How Brokee.io Can Support Your IT Needs During a Disaster

When you need to build or strengthen your DevOps team, Brokee.io can be an invaluable resource. They specialize in training, building, and even hiring IT professionals who can support your business through challenging times. Here’s how Brokee.io can assist:

1. Training and Upskilling Your IT Team

Brokee.io offers comprehensive training for DevOps engineers, ensuring they are well-equipped to handle emergency scenarios, manage cloud infrastructure, and maintain cybersecurity.

2. Developing Resilient Systems

Through their tools and resources, Brokee.io helps businesses design disaster recovery protocols, automated backup systems, and cloud-based solutions that ensure business continuity in case of emergencies.

3. Hiring Skilled DevOps Engineers

Whether you need short-term expertise during wildfire season or long-term hires, Brokee.io connects businesses with skilled DevOps engineers who are experts in disaster recovery, cybersecurity, and scalable cloud infrastructure.

By integrating these tools and resources into your business’s IT strategy, you’ll be able to build a strong, resilient DevOps team that can maintain operations even in the midst of a disaster.

Grocery Store Preparedness: How DevOps Can Help During Wildfires

For grocery stores, especially those in Southern California, the threat of wildfires is a major concern. Stores may face evacuation orders, supply chain disruptions, and even physical damage to their properties. However, by implementing the strategies outlined above, grocery stores can safeguard their digital systems and minimize downtime.

Here are a few key strategies for grocery store owners:

1. Use Cloud Infrastructure for Backup and Access

Migrating critical systems (such as point-of-sale systems and inventory management) to the cloud ensures that employees can access these systems remotely, even if the physical store is closed or compromised.

2. Cybersecurity Measures for Remote Work

As grocery store staff may need to work remotely, DevOps teams can establish secure VPNs and implement multi-factor authentication to ensure safe access to systems and customer data.

3. Automate Disaster Recovery and Backup Plans

Automated recovery protocols allow grocery stores to restore essential systems quickly and efficiently. These protocols should include regular backups of all business-critical data to secure cloud storage.

4. Communicate With Customers

During a wildfire, it’s essential to maintain communication with your customers. Use your website, email newsletters, and social media to inform customers about store hours, closures, or available services. A DevOps team can set up automated systems for real-time updates to ensure customers are always in the loop.

Building Your Resilient DevOps Team with Brokee.io

Whether you’re a grocery store owner, retail business manager, or any other industry leader, having a skilled DevOps team can make a world of difference when disaster strikes. Brokee.io offers tailored solutions to help businesses develop, train, and hire the right professionals for your IT needs. From cloud migration to disaster recovery and cybersecurity, Brokee.io ensures that your systems are ready to withstand the impact of wildfires or other natural disasters.

By using Brokee.io’s tools and expertise, grocery stores can rest assured that their IT infrastructure is prepared for the worst, allowing them to quickly recover and maintain operations when their physical stores are affected.

Resources to Help Your Grocery Store Prepare:

• AWS Disaster Recovery Solutions: aws.amazon.com

• Google Cloud for Disaster Recovery: cloud.google.com

• Brokee.io’s DevOps Training & Hiring Services: brokee.io

• FEMA’s Business Continuity Plan Guide: ready.gov/business

• NIST Cybersecurity Framework: nist.gov

Conclusion: Invest in Your IT Team for Future Resilience

The impact of natural disasters on businesses can be severe, but with the right preparation, you can ensure that your grocery store or retail business is ready to weather any storm. By strengthening your IT infrastructure and building a capable DevOps team with Brokee.io’s support, you can safeguard your operations and keep your business running smoothly, no matter what challenges lie ahead.

To learn more about how Brokee.io can help you build your IT team, check out their services or contact us for a consultation on how to integrate these practices into your business continuity plan.

Need more help with your business preparedness check out this blog on readiness by Innovar Agency’s for more tips on building resilience and leveraging technology for business success during natural disasters like wildfires.

Key Takeaways for Grocery Stores and Retailers:

• Prepare your IT infrastructure for remote work, backup, and cloud solutions to ensure business continuity during a natural disaster.

• Invest in a strong DevOps team to handle disaster recovery, cybersecurity, and scalable systems during emergencies.

• Use Brokee.io to build and train a team of professionals that will ensure your business stays operational and secure during and after a disaster.

The Essential Skills Every DevOps Engineer Needs to Succeed in 2025

1. Cloud Proficiency (AWS, Azure, GCP)

Understanding Cloud Platforms

Proficiency in cloud platforms like AWS, Azure, and Google Cloud Platform (GCP) is critical for any DevOps engineer. This includes tasks such as deploying infrastructure, managing services, and monitoring cloud environments.

Why Cloud Skills Matter

With companies shifting to the cloud, being skilled in cloud platforms is no longer optional. Engineers need hands-on experience with infrastructure-as-code, serverless applications, and cloud monitoring to ensure efficiency and scalability.

Brookee’s cloud-based DevOps assessments give engineers real-world, hands-on experience with AWS, Azure, and GCP preparing them for the tasks they’ll face on the job. Try it for free.

2. Continuous Integration and Continuous Deployment (CI/CD)

Mastering CI/CD Tools

CI/CD tools like Jenkins, GitLab CI, and GitHub Actions allow for automating code integration and deployment. Engineers should be proficient in setting up and maintaining pipelines to streamline the software delivery process.

Why CI/CD Skills Matter

CI/CD practices reduce deployment risks, accelerate feedback loops, and help deliver software updates frequently and reliably.

3. Containerization and Orchestration (Docker, Kubernetes)

Building and Orchestrating Containers

With the rise of microservices and cloud-native architectures, engineers need to be skilled in Docker for containerization and Kubernetes for orchestrating and scaling these containers.

Why Containerization Skills Matter

Containers allow consistent deployment across environments, and Kubernetes automates the scaling and management of these containers, ensuring uptime and reliability.

4. Infrastructure as Code (IaC)

Automating Infrastructure

Using Terraform and Ansible, engineers can automate infrastructure provisioning and management. This approach ensures consistency and makes it easy to manage infrastructure at scale.

Why IaC Skills Matter

By treating infrastructure as code, you can automate deployment and ensure version control, which leads to more predictable and reliable systems.

5. Monitoring and Observability

Implementing Monitoring Tools

Proficiency with tools like Prometheus, Grafana, and ELK Stack is essential for setting up monitoring and observability frameworks. Engineers need to track performance metrics and respond to incidents before they become critical.

Why Monitoring Matters

Proactive monitoring ensures system reliability and reduces downtime by identifying issues early.

6. Automation and Scripting

Automating Workflows

Knowing how to script in languages like Python, Bash, or PowerShell is crucial for automating repetitive tasks, configuring systems, and managing cloud environments.

Why Automation Matters

Automation saves time, reduces human error, and frees up engineers to focus on more strategic tasks.

7. Security (DevSecOps)

Embedding Security in DevOps

Security is now a core part of the DevOps process, known as DevSecOps. Engineers must be familiar with security practices, including vulnerability scanning, encryption, and automated security testing to safeguard infrastructure.

Why Security Skills Matter

In a world where breaches can cripple companies, embedding security into the DevOps process is crucial for both compliance and safeguarding sensitive data.

8. Soft Skills: Communication and Collaboration

Working Across Teams

Beyond technical expertise, DevOps engineers need excellent communication and collaboration skills. This ensures that operations and development teams work smoothly together to solve problems and meet objectives.

Why Soft Skills Matter

DevOps is about breaking down silos. Engineers who can communicate effectively and collaborate with cross-functional teams will thrive in complex, fast-paced environments.

Ready for DevOps Success?

In 2025, successful DevOps engineers will need a blend of technical expertise and communication skills to thrive. By mastering cloud platforms, CI/CD, automation, and security, engineers will be ready to make a significant impact from day one.

If you’re looking to sharpen your skills, consider Brokee as your secret weapon. Brokee’s DevOps assessments mirror real-world cloud environments, giving engineers and companies the hands-on experience they need to succeed.

The Best DevOps Tools to Streamline Software Development in 2025

What are DevOps Tools and Their Importance?

DevOps tools are essential components in modern software development practices, bridging the gap between development and operations teams.

These tools automate and streamline various aspects of the software delivery process, enhancing collaboration and efficiency within organizations. The importance of DevOps tools lies in their ability to accelerate deployment, improve code quality, and facilitate continuous integration and delivery.

Integrating DevOps tools allows teams to automate repetitive tasks, reduce human errors, and maintain consistency throughout the development lifecycle. By incorporating these tools, organizations can achieve faster time-to-market, increased productivity, and better overall software quality.

Read More: Essential DevOps Statistics and Trends for Hiring in 2025

Role of DevOps Tools in Improving Software Development Practices

DevOps tools serve as enablers for implementing DevOps practices effectively. These tools automate manual processes, enable version control, and enhance workflow visibility, promoting a collaborative and efficient development environment. By leveraging tools that support automation, organizations can achieve faster delivery cycles and improved software quality.

Benefits of Using DevOps Tools for Software Development

The benefits of utilizing DevOps tools in software development are manifold. These tools promote collaboration, automation, and efficiency, leading to faster delivery cycles, reduced time-to-market, and enhanced product quality. By incorporating DevOps tools into development workflows, organizations can streamline processes, eliminate manual errors, and enhance team productivity.

DevOps tools also enable organizations to adopt best practices in software development, such as continuous integration, continuous delivery, and automated testing. These practices contribute to increased code quality, faster feedback loops, and overall project success.

Key Features to Look for in DevOps Tools

When selecting DevOps tools for your organization, it's essential to consider key features that align with your specific requirements and objectives. Features such as automation capabilities, integrations with popular platforms like AWS and Azure, scalability, and flexibility are crucial for optimizing development workflows.

Configuration management tools play a vital role in managing infrastructure as code, ensuring consistency across environments, and enabling quick provisioning of resources. Additionally, collaboration features, reporting capabilities, and user-friendly interfaces are key aspects to consider when evaluating DevOps tools for your organization.

Choosing the Right DevOps Tools for Your Project

When selecting DevOps tools for a project, consider the following factors:

• Integration Capabilities: Ensure the tool integrates seamlessly with your existing technology stack and other DevOps tools.

• Scalability: Choose tools that can scale with your project as it grows.

• Community and Support: Opt for tools with active community support and comprehensive documentation.

• Ease of Use: Select tools that are user-friendly and require minimal learning curve.

• Cost: Evaluate the cost of the tool relative to your budget and the value it provides.

Factors to Consider When Selecting a DevOps Management Tool

When selecting a DevOps management tool, it's crucial to consider the following key aspects:

• Integration Capabilities: Ensure the tool integrates seamlessly with your existing technology stack, other DevOps tools, and services to maintain a cohesive workflow.

• Scalability and Flexibility: Choose a tool that can easily scale with your project’s growth and adapt to changing requirements without significant reconfiguration.

• User Community and Support: Opt for tools with an active community, comprehensive documentation, and robust support channels to aid in troubleshooting and best practices.

• Ease of Use and Learning Curve: Evaluate how user-friendly the tool is, considering the skill level of your team, and how quickly they can get up to speed.

• Cost and Licensing: Assess the total cost of ownership, including initial investment, maintenance, and potential licensing fees, to ensure it aligns with your budget and provides good value.

Read More: Hidden Costs of Your Hiring Pipeline

List of Best DevOps Tools for 2025

As we look ahead to 2025, the landscape of DevOps tools continues to evolve, offering a plethora of options to streamline development processes and enhance productivity.

Exploring Automation in DevOps Tools

Automation plays a pivotal role in DevOps practices, allowing teams to streamline workflows, reduce manual errors, and accelerate software delivery. Automation tools like Jenkins, GitLab CI/CD, and Bamboo enable teams to automate build, test, and deployment processes, enhancing efficiency and reliability.

By automating repetitive tasks, teams can free up resources, focus on high-impact activities, and iterate quickly on software updates. Automation tools also support continuous integration and continuous delivery (CI/CD) practices, ensuring that code changes are tested, integrated, and deployed in a timely manner.

CI/CD Automation Tools

Bamboo helps practice continuous delivery by tying automated builds, tests, and releases into a single workflow. Features include multi-stage build plans, triggers for starting builds upon commits, parallel automated tests, and tight integration with Jira and Bitbucket.

Jenkins is essential for automating CI/CD pipelines, building, testing, and deploying code changes efficiently. Its flexibility and extensive plugin library make it adaptable to diverse development environments, supporting seamless automation and delivery.

CodeFresh is a Kubernetes-native CI/CD platform that streamlines the building, testing, and deployment of applications. It offers advanced features like built-in GitOps, support for multiple pipelines, and robust integration with popular DevOps tools. CodeFresh excels in managing microservices and complex workflows, making it ideal for cloud-native environments.

ArgoCD is a declarative, GitOps continuous delivery tool for Kubernetes. It automates the deployment of desired application states from a Git repository, ensuring consistency and reliability. ArgoCD supports multiple deployment strategies, integrates seamlessly with other Kubernetes tools, and provides a rich UI for managing application deployments and rollbacks.

Configuration Management in DevOps Tools

Ansible stands out for its simplicity and versatility in automating repetitive tasks, provisioning infrastructure, and managing configurations. Its agentless architecture, using SSH for communication, and declarative language make it accessible for both beginners and seasoned professionals. Ansible's extensive library of pre-built modules supports diverse environments, enabling efficient, scalable, and rapid deployment of applications and services while minimizing manual errors and enhancing security.

Chef automates server provisioning, configuration, and maintenance, enhancing efficiency and consistency across infrastructure. Its integration with cloud providers and containerization technologies makes it adaptable to evolving tech landscapes. It features “cookbooks” for infrastructure coding, integration with cloud platforms like AWS, Azure, and GCP, and configuration as code.

Puppet automates and simplifies critical manual tasks by managing and extracting configuration details across various operating systems and platforms, helping scale and maintain servers efficiently.

Version Control Tools

GitHub is one of the largest and most advanced development platforms globally, enabling millions of developers and companies to build, ship, and maintain their software. Its key features include collaborative coding, automation for CI/CD, enhanced security for enterprise customers, and project management capabilities.

GitLab is an all-in-one DevOps tool for rapid software delivery, supporting tasks from planning to SCM, delivery, monitoring, and security. It features a single interface for project management, CI/CD for automation, and built-in functionality for automated security, code quality, and vulnerability management.

Bitbucket is popular with over 10 million registered users, offering a platform for hosting code and beyond. It enables teams to plan projects, collaborate, test, and deploy from a single interface. Notable features are tight integration with Jira and Trello, built-in CI/CD, efficient pull requests and code reviews, and robust cloud security with IP whitelisting and two-step verification.

Infrastructure as Code (IaC)

Terraform brings consistency, version control, and automation to infrastructure operations, reducing manual errors and streamlining DevOps workflows. Its ability to define and deploy infrastructure as code ensures efficient and reliable application deployment.

Pulumi allows you to write Infrastructure as Code (IaC) using familiar programming languages like Python, Go, and JavaScript. It offers flexibility and ease of use, especially for developers already familiar with these languages. Pulumi integrates seamlessly with existing development workflows and tools, making it ideal for software development teams adopting IaC practices.

Monitoring and Logging Tools in DevOps

Prometheus is renowned for its robust metric collection and analysis capabilities, crucial for dynamic scaling and cloud-native environments. Its open-source nature and active community support make it an adaptable solution for diverse infrastructure needs, providing visibility into containerized and microservices architectures.

Grafana is a powerful open-source platform for monitoring and observability, offering rich visualizations and dashboards. It integrates seamlessly with various data sources, including Prometheus, Elasticsearch, and InfluxDB, providing a unified view of metrics and logs for better analysis and alerting.

ELK (Elasticsearch, Logstash, Kibana) ELK is essential for effective log management, real-time data indexing, and visualization. Elasticsearch’s scalability, combined with Logstash’s data processing and Kibana’s user-friendly interface, offers comprehensive insights, enabling quick problem resolution and proactive monitoring.

EFK (Elasticsearch, Fluentd, Kibana) is a robust logging solution that enables efficient log collection, storage, and visualization. Fluentd aggregates logs from various sources, Elasticsearch indexes and stores them, and Kibana provides an intuitive interface for searching and visualizing log data, enhancing troubleshooting and monitoring.

SignalFx excels in real-time monitoring and observability, allowing organizations to proactively detect anomalies and trace issues across microservices. Its advanced alerting and incident response capabilities ensure high availability and optimal resource utilization, addressing performance issues before they impact end-users.

Raygun focuses on application performance monitoring and error tracking. It provides actionable insights into application errors and performance bottlenecks, enabling proactive issue resolution and enhancing user satisfaction through improved software quality.

Security DevOps Tools

Splunk is used for monitoring and exploring SaaS and on-premises infrastructure. Features include monitoring across physical, virtual, and cloud infrastructures, modernizing applications for better customer experiences, predictive alerting and auto-remediation with AIOps and machine learning, and improved MTTA with automated incident response.

Phantom Phantom enhances security automation and incident response, reducing response times and increasing consistency in incident handling. It automates security workflows, from threat detection to risk mitigation, freeing up resources from repetitive tasks.

Security features offered by tools like SonarQube, Fortify, and Checkmarx are critical for protecting applications from vulnerabilities, ensuring code quality, and adhering to security best practices. By integrating security tools into the development pipeline, organizations can identify and remediate security threats early in the software development lifecycle.

Container Management Tools

Docker is a lightweight tool designed to simplify and accelerate various workflows in the SDLC with an integrated approach. Docker container images include everything needed to run an application, offering standardized packaging, container runtime for multiple OSs, collaborative development, and Docker Hub for exploring millions of images.

Kubernetes is an open-source tool for automating the deployment and management of containerized applications. Its features include automated rollouts and rollbacks, service delivery and load balancing, storage orchestration, and self-healing capabilities.

Read More: We've Added New Tests: Kubernetes and GPC Tests

Mesos is a tool for managing computer clusters, functioning as a distributed systems kernel for resource management across datacenter and cloud environments. It supports launching containers with Docker and AppC images, running cloud-native and legacy applications in the same cluster, and scaling to tens of thousands of nodes.

Nomad is a flexible, easy-to-use container orchestration tool that simplifies the deployment and management of containerized and non-containerized applications. It supports diverse workloads, offers native integrations with Consul and Vault, and provides a single, consistent workflow for deploying applications across multiple datacenters and cloud environments.

Build Tools

Maven is a pivotal tool for managing project dependencies, building, and lifecycle management in Java-based development environments. It simplifies complex build processes by streamlining compilation, testing, packaging, and distribution. Maven ensures consistent and reproducible builds, making it easier for development teams to collaborate efficiently and deliver high-quality software.

Gradle Build Tool is the most popular build tool for open source JVM projects on GitHub. Many popular projects, including Spring Boot, have migrated from Maven to Gradle.

Application Lifecycle Management

Jira is a well-known platform for tracking issues and managing projects, available as both a SaaS and on-premises solution. It allows for agile software development with drag-and-drop interface for creating automation rules.

Cloud Computing and Storage (AWS)

AWS offers a robust set of tools for implementing DevOps practices, focusing on continuous integration, deployment, and cloud solutions. Here are the top AWS DevOps tools:

AWS Cloud Development Kit: An open-source tool for modeling and provisioning cloud application resources.

AWS CodePipeline: Continuously delivers code, providing a visual representation of the entire delivery process.

AWS CodeCommit: Allows developers to create and clone repositories locally, facilitating efficient code management.

AWS CodeBuild: A cloud-based integration service that scales builds, runs tests, and prepares software packages for deployment, automating various processes.

AWS Device Farm: Ensures the quality of web and mobile apps by testing across different devices and AWS cloud desktop versions.

AWS CodeStar: Provides a user-friendly interface for building, developing, and deploying applications in AWS.

Other notable AWS microservices include AWS Lambda, Amazon Elastic Kubernetes Service, AWS Fargate, Amazon Elastic Container Service, Amazon CloudWatch, AWS X-Ray, AWS CloudTrail, and AWS Elastic Beanstalk. These tools support various DevOps tasks and enhance cloud solutions.

Read More: AWS DevOps Interview Questions and Answers for 2025

Best Test Orchestration Tools

Katalon TestOps is an orchestration platform for automated testing that unites test management, planning, execution, and quality analytics. TestOps connects the team with feedback loops that are instant, actionable, and insightful for both QA, product, and DevOps teams.

Application Performance Monitoring Tools

Dynatrace covers application performance, digital experience, business analytics, AIOps, and infrastructure monitoring. Key features are automated orchestration with open APIs, extensive cloud support, automatic quality checks and KPIs, and AI-driven problem detection and resolution.

AppDynamics provides real-time insights into application performance, monitoring all transactions flowing through applications. Features include intelligent agents, analytics-driven performance problem solving, automatic performance normalization, and system-wide data recording.

Deployment & Server Monitoring Tools

Datadog is a SaaS-based tool for server and app monitoring in hybrid cloud environments, including Docker containers. Its features include seamless aggregation of metrics and events across the DevOps stack, end-to-end user experience visibility, prioritization of business and engineering decisions with user metrics, and visibility across teams.

Sensu is an open-source tool for monitoring cloud environments, easily deployable through Puppet and Chef. Features include the Sensu Observability Pipeline for integrated, secure, and scalable monitoring, declarative configurations, and a service-based approach to automating workflows.

Test Automation Tools

Test.ai is an AI-powered automation testing tool that builds tests without coding, accelerates testing to match DevOps speed, scales testing across platforms, and maintains tests automatically to improve quality.

Ranorex offers an all-in-one solution for automated testing across browsers and devices, with tools included in a single license, support for real devices or simulators, and integration with CI servers and issue tracking tools.

Selenium automates web applications for testing with components like WebDriver for browser-based regression automation, IDE for simple record-and-playback, and Grid for scaling tests across multiple machines and environments.

Artifact Management Tools

Sonatype Nexus efficiently distributes parts and containers to developers as a single source of truth for all components, binaries, and build artifacts. Features include universal support for popular build tools and flexibility to empower development teams.

JFrog Artifactory serves as a single source of truth for container images, packages, and Helm charts, with features like active/active clustering, multi-site replication, tool stack integration, and pipeline automation via powerful REST APIs.

CloudRepo manages and shares private Maven and Python repositories, ensuring high availability with multi-server storage, client access control, and integration with major CI tools.

AI and Codeless Test Automation Tools

AccelQ leads in codeless test automation, allowing testers to develop test logic without programming syntax concerns. It supports a design-first approach, handles dynamic controls, and supports advanced interactions for robust test development.

QuerySurge is a continuous data testing solution with a robust API, seamless DevOps pipeline integration, quick data verification, transformation rule validation, and detailed data intelligence and analytics.

Appvance is an AI and ML-powered autonomous testing platform that performs end-to-end testing with self-healing scripts, AI-generated tests, and continuous testing capabilities.

Testim.io is an AI-based UI testing tool that integrates with Saucelabs, Jira, and GitHub, eliminates flaky tests, pinpoints root causes of bugs, and efficiently expands testing operations with control, management, and insights.

Read More: A Guide to AI Tools in DevOps and Cloud Hiring

DevOps Training Tools

Brokee offers hands-on cloud labs designed to provide real-world DevOps training experiences. Unlike traditional learning platforms that focus on theoretical knowledge, Brokee emphasizes practical skills through interactive labs. These labs simulate real-world scenarios, allowing engineers to tackle challenges they would face in their daily work. This makes it an excellent choice for both beginners and seasoned professionals looking to stay ahead in the industry.

In the rapidly evolving field of DevOps, continuous learning and hands-on practice are crucial for keeping up with the latest technologies and methodologies.

Final Word: Explore the Capabilities of Top DevOps Tools

As we move into 2025, the landscape of DevOps tools continues to evolve and expand, offering more sophisticated and integrated solutions to streamline the software development process. 

The future of DevOps tools lies in greater automation, more seamless integrations, and enhanced capabilities that address the complexities of modern software development. 

Stay ahead of the curve by continually exploring and adopting the latest DevOps tools, thereby expanding and refining your arsenal to meet the demands of modern software development.

Read More: Now Providing DevOps Tests for All Major Cloud Providers

7 Signs You Need to Hire a DevOps Engineer in 2025

Discover the top 7 signs that indicate your business needs to hire a DevOps engineer. Plus, we'll explore why DevOps is crucial for businesses seeking to improve their development processes and enhance productivity in 2025.

What is DevOps and Why is it Important?

A modern approach to software development, DevOps combines development and operations to streamline the software delivery process.

Definition of DevOps

DevOps, a combination of "development" and "operations," refers to a set of practices, principles, and cultural philosophies aimed at improving collaboration and communication between software development (Dev) and IT operations (Ops) teams.

The primary goal of DevOps is to streamline the software delivery lifecycle, from initial development through testing, deployment, and maintenance, fostering a more efficient and collaborative approach to delivering high-quality software at a faster pace.

A DevOps approach emphasizes automation, continuous integration, continuous delivery, and a culture of shared responsibility, enabling organizations to respond rapidly to changing business requirements and deliver value to end-users more effectively.

Why You Need DevOps Engineers

Signs That Indicate You Need to Hire a DevOps Team

1. Deployment Failures and Slow Time-to-Market:

Frequent deployment failures coupled with a slow time-to-market can be indicative of underlying inefficiencies in the development and deployment pipeline. Delays in bringing products or features to market can significantly impact your competitiveness. A DevOps engineer can address this by implementing robust CI/CD pipelines, ensuring quicker and more reliable releases.

2. Ineffective Collaboration and Low Developer Productivity:

Issues in collaboration between development and operations teams can lead to low developer productivity. A DevOps engineer excels in fostering collaboration, breaking down silos, and implementing automation to enhance overall productivity.

3. Manual and Repetitive Processes

If your organization relies heavily on manual and repetitive processes for tasks like configuration management, provisioning, and scaling, a DevOps engineer can automate these processes, saving time and reducing the risk of human error.

4. High Infrastructure Costs

Rising infrastructure costs without a clear understanding of resource utilization may signal the need for a DevOps engineer. These professionals can optimize infrastructure, implement cloud solutions, and leverage containerization technologies to ensure efficient resource allocation.

5. Lack of Monitoring and Logging

Insufficient monitoring and logging can lead to delayed identification and resolution of issues, affecting system reliability. A DevOps engineer can implement robust monitoring and logging solutions to proactively detect and address potential problems.

6. Security Concerns

Security is a critical aspect of any IT infrastructure. If your organization is grappling with security vulnerabilities or lacks a comprehensive security strategy, a DevOps engineer can integrate security measures into the development and deployment processes, ensuring a more secure and resilient system.

7. Scalability Challenges with Increasing Workloads:

As your business grows, scalability challenges may arise. A DevOps engineer is well-equipped to design scalable architectures, implement auto-scaling solutions, and ensure your systems can handle increased workloads seamlessly.

DevOps Versus Traditional Software Development

The evolution of development and operations teams in DevOps marks a significant departure from traditional software development methods. DevOps culture emphasizes collaboration, transparency, and shared ownership, leading to a more cohesive and efficient development process.

When it comes to the difference between roles, DevOps engineers focus on the development and maintenance of software release systems, collaboration with the software development team, aligning with industry standards, and employing DevOps tools.

In contrast, software engineers focus on developing applications and solutions that operate on different operating systems, catering to specific user needs.

Read More: Cloud Engineer vs Software Engineer

The Role of a Full-Time DevOps Engineer

A DevOps engineer plays a pivotal role in driving the successful implementation of DevOps practices within an organization. Their key responsibilities include promoting collaboration between development and operations teams, automating processes to streamline product delivery, and ensuring the continuous integration and deployment of software.

Organizations need DevOps engineers to harness the full potential of DevOps principles. With their expertise in automation, deployment, and infrastructure management, a dedicated DevOps engineer can transform a conventional development team into a highly efficient and productive unit. 

How many DevOps engineers do you need for your team? While there's not an official number, the ideal Developer to DevOps engineer ratio is 5:1, and in large software organizations, like Google, the ratio is 6:1.

The Benefits of DevOps for Your Business

Benefits of DevOps

Employing a DevOps engineer or team offers numerous benefits, including:

• Improved deployment frequency

• Faster time to market

• Lower failure rate of new releases

• Shortened lead time between fixes

• Enhanced developer productivity

• Contribution to delivering more reliable and customer-friendly software

• Positive shift in customer satisfaction and overall product quality

Additionally, for most modern businesses that have moved to the cloud – such as GPC, AWS, or Azure-- DevOps engineers play a crucial role in managing and optimizing cloud environments. Their expertise extends to various aspects of cloud infrastructure and services, such as FinOps, automation, CI/CD, and more, and they contribute significantly to the effective implementation of DevOps practices in the cloud.

These advantages make having a DevOps engineer or team essential for organizations aiming to stay competitive in a rapidly evolving technological landscape.

Importance for Modern Businesses

DevOps is rapidly transitioning from a specialized approach to a mainstream strategy. Its adoption soared from 33% of companies in 2017 to an estimated 80% in 2024, mirroring the broader shift towards cloud computing.

The importance of DevOps in modern businesses cannot be overstated. It is instrumental in creating a culture of collaboration and shared responsibility among development and operations teams. This approach fosters a more efficient and effective workflow, leading to faster product development and deployment.

Read More: Essential DevOps Statistics and Trends for Hiring in 2025

Challenges of DevOps Implementation

Identifying the challenges of DevOps adoption is crucial for businesses looking to implement this methodology successfully. Common obstacles include resistance to change, cultural barriers within the organization, the cost of hiring DevOps engineers, and the complexity of integrating new tools and processes into existing workflows.

To overcome obstacles in implementing DevOps, organizations need to focus on fostering a culture of collaboration and openness to change. Encouraging transparency and communication across teams, providing adequate training and resources, and gradually introducing DevOps practices can help mitigate these challenges.

Another difficulty is hiring high-quality DevOps engineers who can do this complicated and highly technical work. A best practice for hiring DevOps engineers is to use DevOps assessments to ensure you select high-caliber candidates.

Read More: Case Study: DevOps Assessments Streamlined EclecticIQ's Hiring Process

Many Businesses are Adopting Cloud and DevOps Processes

Future of DevOps

The future of DevOps is significant, especially as businesses increasingly rely on software development to drive innovation and competitiveness. 

By 2025, over 85% of organizations are expected to adopt a cloud computing strategy, aligning closely with the integration of DevOps practices. The need to hire a DevOps engineer is more pronounced than ever, given the rapid evolution of technology and the increasing demand for scalable and reliable software solutions.

Embracing DevOps is not just an option; it is a necessity for organizations striving to stay relevant and agile in a constantly evolving marketplace.

The Best Tech Recruitment Platforms & Technical Screening Tools in 2025

In this rapidly evolving digital era, hiring top technical talent has become a major challenge, for both startups and enterprises. We explored the top tech recruitment platforms, tools, and software solutions that can help your company source, screen, and eventually hire the best talent in 2025.

Why is Technical Recruitment a Significant Challenge for Many Companies?

Technical recruitment poses a unique challenge for recruiters and employers. Among various processes in the corporate world, tech recruitment introduces one of the toughest tasks to fulfill, especially when there's an abundance of job seekers with more new technologies evolving day by day.

Understanding the Unique Issues for Technical Recruiters

There are several challenges in tech recruitment, including sourcing candidates with the right competency in advanced technologies, understanding specific job requirements like DevOps engineering, translating tech jargon into understandable information for non-tech recruiters, proper technical assessment and testing, and offering competitive salary packages.

Common IT recruitment problems include:

• Difficult and expensive to extend search beyond traditional platforms like LinkedIn and Indeed.

• Deciding how much to spend on subscription packages and platforms.

• Properly assessing candidates' skills.

• Understanding and minimizing the costs of your hiring pipeline.

How Can Tech Recruitment Tools Give a Competitive Edge in Hiring?

Tech recruitment tools equip employers with data-driven insights, automation, and AI-powered features that can significantly enhance their ability to source, screen, interview, and hire top tech talent.

What are the top 10 Tech Recruitment Platforms in 2025?

The best tech tools might vary based on the needs of the company or hiring team, however, we've put together our top picks for recruiting technology and tools for 2025. 

How Did We Choose Our "Top Picks"?

What constitutes the 'best' recruitment tool or platform? Prime factors we considered included user-friendly interfaces, cost-effectiveness, AI-driven candidate matching, advanced candidate sourcing features, and a robust tech stack. Additionally, great customer service, reasonable pricing, and the reviews and reputations of the platforms came into play as well.

Each platform has its pros and cons based on various considerations like the type of tech talent you are sourcing, ease of integration with other tools, and features specific to your needs. However, we felt this guide would be especially helpful as it contains the top picks from technical experts who work with many of these tools and technologies every day.

Without further ado, let's get to the rankings!

Applicant Tracking Systems

An Applicant Tracking System (ATS) is the backbone of any recruitment operation. It serves as a centralized hub for managing candidates and streamlining recruiting activities. In 2025, ATS tools have evolved to not only store candidate data but also enhance productivity by automating various aspects of the hiring process.

SmartRecruiters

• Pros:

• Offers a wide range of features, including automation, analytics, and customizable job postings.

  1. Can streamline the hiring process, saving time and reducing manual effort.

  2. Provides powerful analytics for recruitment efforts.

• Cons:

• Design could have a better user experience with improved navigation.

  1. Lacks some customization features that users want.

  2. It's missing some common integrations.

• Pricing: The specific pricing information for SmartRecruiters is not available.

Lever

• Pros:

• Offers features such as interview scheduling, candidate scoring, and analytics.

  1. Can simplify the hiring process and save time when used effectively.

• Cons:

• Customer support can be lacking at times.

  1. Setup can take a while, and tools have a bit of a learning curve.

  2. Many reviewers mentioned wanting more features.

• Pricing: Pricing for Lever ranges from around $3,500 to $140,000 per year, depending on the number of employees.

iCIMS

• Pros:

• Offers a wide range of features, including automation, analytics, and customizable job postings.

  1. Can streamline the hiring process, saving time and reducing manual effort.

  2. Provides powerful analytics for recruitment efforts.

• Cons:

• The reporting functions can be limited to standard reports, and customization can be challenging

  1. Search capabilities could be improved.

  2. Interface design could be improved for better user experience.

• Pricing: iCIMS pricing ranges from $6,000 per year for 51 to 100 employees to $140,000 per year for 5,000+ employees. They also charge "connector fees" for 3rd party integration partners.

Our Top Pick: Greenhouse Software

• Pros:

• Offers a comprehensive set of features for recruitment, including interview scheduling, candidate scoring, and analytics.

  1. Provides powerful analytics and customizable job postings.

  2. Can simplify the hiring process and save time when used effectively.

• Cons:

• Automated screening may eliminate good candidates, as the system sticks within set boundaries.

  1. May lack desired one-on-one contact with applicants, potentially affecting the candidate experience.

  2. Might require a lengthy implementation, which can be a potential disadvantage.

• Pricing: Pricing ranges from around $6,000 to $25,000 per year for a couple of dozen employees to over $100,000 per year for larger enterprises.

Why it's our top pick: Among the ATS, Greenhouse Software emerges as a top contender. With a wide array of features, including interview scheduling, candidate scoring, and robust analytics, Greenhouse offers a comprehensive recruitment solution. Additionally, it provides customizable job postings and has received a great G2 rating of 4.4 out of 5 stars, indicating user satisfaction.

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CRM Tools

In this section, we explore CRM (Customer Relationship Management) platforms, keeping in mind how well they work for technical recruiters. We've highlighted their pros, cons, and pricing to help you make an informed choice for streamlining your hiring process.

Freshsales

• Pros: Affordable pricing, feature-rich CRM, extensive customization.

• Cons: Limited marketing automation, integration challenges, advanced customization learning curve, limited support for large teams.

• Pricing: Freshsales starts at $15/user/month.

Recruiterflow

• Pros: Highly customizable, responsive customer support, economical for small businesses, user-friendly.

• Cons: Limited marketing automation, integration challenges, and limited customization for large teams.

• Pricing: Recruiterflow ranges from $85/user/month to $96/user per year, with custom enterprise plans available.

Teamtailor (Our Pick for Best Recruitment Software for Startups!)

• Pros: Cost-effective, user-friendly, seamless social media integration.

• Cons: Varied quality in customer support, limited analytics, uneditable connect option.

• Pricing: Teamtailor starts at $200 per month.

Our Top Pick Overall: Zoho

• Pros: Efficient recruitment management, broad candidate engagement, robust sourcing, powerful analytics.

• Cons: Limited career site functionality, lack of full-time support, overwhelming features, limited free version.

• Pricing: Starts at approximately $17 to $52/user/month billed annually for small to mid-sized enterprises.

Why it's our top pick: While opinions may vary depending on individual preferences and specific needs, Zoho's combination of features, pricing, and user satisfaction ratings makes it a solid choice for organizations looking to enhance their recruitment efforts through CRM software. 

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AI Screening Tools - Candidate Background Checking Software

If you've ever had to sift through a mountain of CVs, you know how daunting the task can be. Thankfully, candidate screening software has emerged as a powerful tool to streamline the hiring process. These digital solutions leverage AI and automation to save time, verify backgrounds, and identify the best-fit candidates for technical roles. Let's take a closer look at some popular options:

CERTN:

• Pros: Offers comprehensive background checks and verification services.

• Cons: Some users have complained about background checks taking a long time.

• Pricing: Prices for CERTN range greatly, depending on the type of verification check. 

Sterling:

• Pros: Utilizes end-to-end automation for faster criminal background checks, seamless API integration, and a Quick Search tool.

• Cons: Some users have reported concerns about the "consider" status and discrepancies in background checks.

• Pricing: Sterling offers a range of pricing options, with background checks ranging from $3.99 for single reports to $59.95 for the Preferred Check.

Veremark:

• Pros: Offers a wide range of online background checks, convenient data collection through an app, and instant generation of professional reports.

• Cons: Pricing details are not openly shared, and it's primarily geared towards small businesses.

• Pricing: Veremark charges on a per candidate per check basis, pricing beyond this is unknown.

Our Top Pick: Checkr

• Pros: Provides easy candidate verification, efficient management of screenings, and education verification.

• Cons: Some users find pricing to be on the higher side.

• Pricing: Ranges from $29 to $79 per background check.

Why it's our top pick: We prefer Checkr over the others for its fast turnaround times, better user experience, and more pre-built integrations. This is backed up by a 4.5-star rating on G2.

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Candidate Sourcing Tools

In the quest to find the perfect candidate, digital tools have become indispensable for sourcing talent. The ideal candidate might not be actively job-hunting, but with the right approach, you can attract their attention. Recruiters now leverage multiple social media platforms to discover potential hires, with an average of 7.8 different sites in use.

Additionally, there are specialized sourcing platforms designed to help Talent Acquisition (TA) teams quickly identify qualified candidates. Here are some of our top picks:

TalentReef: (Our Pick for Best Enterprise Hiring Solution!)

• Pros: Mobile-friendly features, numerous time-saving automations, and is designed for sourcing hourly workers.
  Cons: Pricing details are not transparent and may not be best for hiring salaried workers.

• Pricing: TalentReef pricing information is available only on inquiry.

Entelo:

• Pros: It has a powerful candidate database search engine, with integrated features for candidate communication.

• Cons: Some customers have noticed that it's not highly efficient at pulling profiles from social media. Candidate information may not always be up to date.
  Pricing: Entelo ranges from $149 per month to $499 and beyond for custom pricing.

Our Top Pick: Fetcher

• Pros: It has a candidate curation feature, automated outreach, and excellent candidate search filters.
  Cons: Users don't like the inability to edit contact cards after adding them to searches.

• Pricing: Ranges from $149/user/mo to $549/user/mo depending on company size.

Why it's our top pick: If you prioritize candidate curation and automated outreach, Fetcher is a strong option. It offers robust search filters and automation features. Ultimately, the best candidate sourcing software for your organization should align with your specific requirements and provide the features and pricing that meet your needs.

Note: Don't forget about developer forums and hubs to source talent as well! For example, StackOverflow, Github, various LinkedIn groups, and even dedicated Subreddits, can be great places to get in touch with talented technical workers.

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Candidate Technical Prescreening & Coding Interviews

How can a recruiter tell if a candidate has technical knowledge? It's easy to write "coding experience" on a resume if you don't need to back it up with proof. This is why it's essential to use technical prescreening tools and coding tests that provide a gamut of coding tests for various features such as plagiarism checkers, tests for specific languages, and applicant screening.

Most of the platforms we write about in this section use live coding, multiple choice, or short answer tests -- these are great for qualifying junior engineers, but keep in mind they may not be sufficient for advanced IT roles. For Mid to Senior level roles, it's essential to use actual skills assessments, which we will cover in the next section - Best Technical Assessment Platforms.

TestGorilla: Automation for Applicant Screening

• Pros:

• Good accuracy to screen applicants in bulk.

  1. Easy to Use.

  2. Ability to customize assessments.

• Cons:

• Unresponsive customer service.

  1. Reviewers desire more integration with other systems.

  2. Tests are not practical (mainly theoretical).

• Pricing: Ranges from free trial to $1150 per month.

Imocha: Live Code Platform

• Pros:

• The Live Coding Interview feature allows tech hiring managers to interact and assess coding skills – in a completely language-agnostic manner.  

  1. They offer a free trial.

• Cons:

• Their pricing is not transparent.

  1. Difficult for non-technical employees to understand results.

  2. Not the best user-interface

• Pricing:

•  They offer several plans but do not show the price.

CoderPad: Technical Prescreening and Interview Platform 

• Pros:

• Provides a technical interview platform that can be used for technical screening.

  1. Quick and accurate assessment of candidate skills.

  2. Simple to use.

  3. Free basic account.

• Cons:

• The practice environment is not guarded.

  1. Reviewers mention the clunky whiteboard feature.

• Pricing:

• Team accounts start at $300/month.

Coderbyte: Code Challenge Site

• Pros:

• Interactive audio and video online environment.

  1. Plagiarism detection.

  2. Easy to set up.

• Cons:

•  They cannot be integrated into most common ATS.

  1. Poor user interface UI/UX.

  2. Candidate emails often go to spam.

• Pricing: Starts at $199 a month

Our Top Pick: Codility - Whiteboarding Tests

• Pros

• CodeLive tool lets you see problem-solve in real-time with live whiteboarding interviews.

  1. Tools to compare candidates' results.

  2. Good user interface.

• Cons

• Pricing is not transparent.

  1. Users say that result reports could be improved and better written in layman's terms.

  2. Doesn't test the candidates' use of frameworks or libraries, only math concepts.

• Pricing: Hidden Pricing (according to Select Hub, plans start from $5000).

Why it's our top pick: While pricing is a bit high for this one, when it comes to high quality tests and screening, Codility does a great job. It is rated high for its ease of setup as well as its helpful support. With high ratings from both recruiters and engineers on Capterra and G2, it's a great testing platform to add to your toolkit.

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Best Technical Assessment Platforms

For advanced technical roles, such as DevOps, System Engineers, and Senior-level positions, code assessments work well for ensuring candidates have the skills to do their daily work.

These skills aren't easily measured through multiple choice tests or basic question-and-answer interviews, instead, live assessments are needed to make sure only genuinely talented engineers make it to the next rounds.

When looking for the best technical assessment platform, double-check with your technical team to make sure the assessments reflect the type of work the candidates will be doing.

Read more: We Transformed Flatworld's DevOps Hiring Process

HackerRank: Smart Interviews

• Pros:

• Great tests for basic coding skills, as well as practice for coders to improve.

  1. Some assessments can be customized.

  2. Large variety of tests and live coding assessments.

• Cons:

• Tests don't reflect the work that engineers will do, as they are more similar to a coding puzzle.

  1. Candidates mention confusing coding interfaces and poorly worded questions that make exams difficult and frustrating.

  2. This platform can be polarizing, with many developers saying they don't like Hackerrank tests during the interview process.

• Pricing: Pricing ranges from $100 to $749 per month, depending on the number of users and tests.

CodeSignal: General Coding Assessments

• Pros:

• Precision, efficiency, and a level playing field to the interview process.

  1. Real-time feedback for candidates.

• Cons:

• Inability to replace human nuances in the interview process.

  1. Lack of live interview functionality and small code editors

  2. Many candidates report not enjoying tests or feeling it tested on useful, daily skills.

• Pricing: Pricing is not transparent.

DevSkiller: Live Coding Assessments

• Pros:

• Users compliment the helpful customer support.

  1. It has an easy-to-use interface.

  2. There are a large number of pre-defined tests that get frequent updates.

• Cons:

• The Candidature management doesn't work well when used on a large number of candidates.

  1. Some candidates have issues loading the tests and operating the coding challenge console.

  2. Parts of the tests aren't fully automated.

• Pricing: Ranges from $300 to $5000 per month (with candidate management). 

Our Top Pick: Brokee - DevOps Assessments

• Pros:

• AI-generated results that are easy for non-technical professionals to understand.

  1. Innovative live, broken environments test skills that are relevant for day-to-day work for system engineers.

  2. Easy recording and playback of candidates' test taking.

• Cons:

• For now, the testing library is limited to DevOps roles, such as DevSecOps, Cloud Engineers, and System Engineers.

  1. There is no interview feature, it currently only offers technical assessments.

  2. Tests currently can't be customized.

• Pricing: Brokee is priced at $0 to $99 per month.

Why it's our Top Pick: Brokee is the newest assessment company, and while it may not have as many tests as other players on the market, it is our top pick because of the high quality of the assessments.

It was created by experienced DevOps, for DevOps who knew they could make better tests than what is currently out there. Because the company is new, they provide personal customer service, free trials, and even demos with the Founder. Try it out for free! 

Read More: DevOps Assessments Streamlined EclecticIQ's Hiring Process

Making the Decision: Choosing the Right Tech Talent Recruiting Platforms

In the vast talent pool, sourcing the best tech talent is like locating a needle in the haystack. The right recruitment software can drive this process with exceptional precision.

Using Tools and Software for Advanced Talent Sourcing

Certain platforms leverage data analytics to vet resumes and process applications quickly and effectively. With these recruitment software solutions, managers can find resourceful profiles in the vast database by filtering multiple attributes related to job postings and candidates.

Screening candidates: AI vs. traditional methods

AI has revolutionized the candidate screening process in tech hiring. Tools powered with AI like Hootsuite, Jasper.ai, or Otter.ai can compare thousands of resumes, eliminating the need for manual shortlisting. They’re cost-effective, efficient, and less prone to human error than traditional methods. 

Integrations with ATS and Other Recruitment Software

Most recruitment platforms can integrate with widely used ATS systems, thus smoothing the recruitment process. Platforms like Regie.ai, SSO, or Nationwide Corp even offer single sign-on (SSO) capabilities to ease user management. Integrations should be a major aspect to keep in mind when it comes to choosing any tool or platform.

Make Technical Recruiting Easier

We hope this guide will be a helpful resource in guiding you toward the best recruiting tools and technologies for your company and team. The decision to implement new technologies can be tough, but with the right tools in your arsenal, you'll be on your way to recruiting and hiring with more ease than ever.

How We Reduced Our Google Cloud Bill by 65%

Google Cloud Cost Reduction

Introduction

No matter if you are running a startup or working at a big corporation, keeping infrastructure costs under control is always a good practice. But it’s especially important for startups to extend their runway. This was our goal.

We just got a bill from Google Cloud for the month of November and are happy to see that we reduced our costs by ~65%, from $687/month to $247/month.

Most of our infrastructure is running on Google Kubernetes Engine (GKE), so most savings tips are related to that. This is one of those situations on how to optimize at a small scale, but most of the things can be applied to big-scale setups as well.

TLDR

Here’s what we did, sorted from the biggest impact to the least amount of savings:

• Almost got rid of stable on-demand instances by moving part of the setup to spot instances and reducing the amount of time stable nodes have to be running to the bare minimum.

• Consolidated dev and prod environments

• Optimized logging

• Optimized workload scheduling

Some of these steps are interrelated, but they have a specific impact on your cloud bill. Let’s dive in.

Stable Instances

The biggest impact on our cloud costs was running stable servers. We needed them for several purposes:

• some services didn’t have a highly available (HA) setup (multiple instances of the same service)

• some of our skills assessments are running inside a single Kubernetes pod and we can’t allow pod restarts or the progress of the test will be lost

• we weren’t sure if all of our backend services could handle a shutdown gracefully in case of a node restart

For services that didn’t have a HA setup, we had the option to explore HA setup were possible (this often requires installing additional infrastructure components, especially for stateful applications, which in turn drives infrastructure costs up); migrating the service to a managed solution (e.g. offload Postgres setup to Google Cloud instead of managing it ourselves); accept that service may be down for 1-2 minutes a day if it’s not critical for the user experience.

For instance, we are running a small Postgres instance on Google Cloud and the load on this instance is very small. So, when some other backend component needs Postgres, we create a new database on the same instance instead of spinning up another instance on Google Cloud or running a Postgres pod on our Kubernetes cluster.

I know this approach is not for everyone, but it works for us as several Postgres databases all have a very light load. And remember, it’s not only about cost savings, this also allows us not to think about node restarts or basic database management.

At the same time, we are running a single instance of Grafana (monitoring tool). It’s not a big deal if it goes down during node restart as it is our internal tool and we can wait a few minutes before it comes back to life if we need to check some dashboards. A similar approach to the ArgoCD server that handles our deployments - it doesn’t have to be up all the time.

High Availability Setup

Here’s what we did for HA of our services on Kubernetes to be able to get rid of stable nodes, this can be applied to the majority of services:

• created multiple replicas of our services (at least 2), so if one pod goes down, another one can serve traffic

• configured pod anti-affinity based on the node name, so our service replicas are always running on different nodes:

affinity:
  podAntiAffinity:
    requiredDuringSchedulingIgnoredDuringExecution:
    - labelSelector:
        matchExpressions:
        - key: app.kubernetes.io/name
          operator: In
          values:
          - pgbouncer
      topologyKey: kubernetes.io/hostname

• added PodDistributionBudget with a minimum of 1 available pod (for services with 2 replicas). This doesn’t guarantee protection, but as we have automated node upgrades enabled, it can prevent GKE from killing our nodes when we don’t have a spare replica ready

• reviewed terminationGracePeriodSeconds settings for each service to make sure applications have enough time to shut down properly

• updated code in some apps to make sure they could be shut down unexpectedly. This is a separate topic, but you need to make sure no critical data is lost and you can recover from whatever happens during node shutdown

• moved these services to spot instances (the main cost-savings step, the other steps were just needed for reliable service operations)

Experienced Kubernetes engineers can suggest a few more improvements, but this is enough for us right now.

Temporary Stable Instances

Now we come to the part about our skills assessments that need stable nodes. We can’t easily circumvent this requirement (yet, we have some ideas for the future).

We decided to try node auto-provisioning on GKE. Instead of having always available stable servers, we would dynamically create node pools with specific characteristics to run our skills assessments.

This comes with certain drawbacks - candidates who start our skills assessments have to wait an extra minute while the server is being provisioned compared to the past setup where stable servers were just waiting for Kubernetes pods to start. It’s not ideal, but considering it saves us a lot of money, it’s acceptable.

As we want to make sure no other workloads are running on those stable nodes, we use node taints and tolerations for our tests. Here’s what we add to our deployment spec:

nodeSelector:
  type: stable
tolerations:
  - effect: NoSchedule
    key: type
    operator: Equal
    value: stable

We also add resource requests (and limits, where needed), so auto-provisioning can select the right-sized node pool for our workloads. So, when there is a pending pod, auto-provisioning creates a new node pool of specific size with correct labels and tolerations:

Node Taints and Labels

Our skills assessment are running a maximum of 3 hours at a time and then automatically removed, which allows Kubernetes autoscaler to scale down our nodes.

There are a few more important things to mention. You need to actively manage resources for you workloads or pods may get evicted by Kubernetes (kicked out of the node because they are using more resources than they should).

In our case, we are going through each skill assessment we develop and take a note of resource usage to define how much we need. If this was an always-on type of workload, we could have deployed vertical pod autscaler that can provide automatic recommendations of how much resources you need based on resource usage metrics.

Another important point, is that sometimes autoscaler can kick in and remove the node if the usage if quite low, so we had to add the following annotation to our deployments to make sure we don’t get accidental pod restarts:

spec:
  template:
    metadata:
      annotations:
        cluster-autoscaler.kubernetes.io/safe-to-evict: "false"

All of this allows us to have temporary stable nodes for our workloads. We use backend service to remove deployments after 3 hours maximum, but GKE auto-provisioning has its own mechanism where you can define how long these nodes can stay alive.

Optimizations

While testing this setup, we noticed that auto-provisioning was not perfect - it was choosing a little too big nodes for our liking.

Another problem, as expected, creating new node pools for every new workload takes some extra time, e.g. it takes 1m53s for a pending pod to start on an existing node pool vs 2m11s on a new node pool.

So, here’s what we did to save a bit more money:

• pre-created node pools of multiple sizes with 0 nodes by default and autoscaling enabled. All of these have the same labels and taints, so autoscaler chooses the most optimal one. This saves us a bit of money vs node auto-provisioning

• choose older instance types, e.g. N1 family vs N2 which is newer but a bit more expensive. Saved some more money

Plus, got faster test provisioning as node pools are already created, and we still have auto-provisioning as a backup option in case we forget to create a new node pool for future tests.

The last thing I wanted to mention here, we were considering 1-node per test semantics for resource-hungry tests, e.g. ReactJS environments. This can be achieved with additional labels and pod anti-affinity as discussed previously. We might add this on a case-by-case basis.

Consolidated Dev and Prod

We have a relatively simple setup for a small team: dev and prod. Each environment consists of a GKE cluster and a Postgres database (and some other things not related to cost savings).

I went to a Kubernetes meetup in San Franciso in September and discovered a cool tool called vcluster. It allows you to create virtual Kubernetes clusters within the same Kubernetes cluster, so developers can get access to fully isolated Kubernetes clusters and install whatever they want inside without messing up the main cluster.

They have nice documentation, so I will just share how it impacted our cost savings. We moved from a separate GKE cluster in another project for our dev environment to a virtual cluster inside our prod GKE cluster. What that means:

• We got rid of a full GKE cluster. Even not taking into account actual nodes, Google started charging a fee for cluster management recently.

• We can share nodes between dev and prod clusters. Even empty nodes require around 0.5 CPU and 0.5 GB RAM to operate, so the fewer nodes, the better.

• We save money on shared infrastructure, e.g. we don’t need two Grafana instances, Prometheus Operators, etc. because it is the same “physical” infrastructure and we can monitor it together. The isolation between virtual clusters happens on the namespace level and some smart renaming mechanics.

• We save money by avoiding paying for extra load balancers. Vcluster allows you to share ingress controllers (and other resources you’d like to share) between clusters, a kind of parent-child relationship.

• We don’t need another cloud database, we moved our dev database to the prod database instance. You don’t have to do this step, but our goal was aggressive cost savings.

We had some struggles with Identity and Access Management (IAM) set up during this migration as some functionality required a subscription to vcluster, but we found a workaround.

We understand that there are certain risks with such a setup, but we are small-scale for now and we can always improve isolation and availability concerns as we grow.

Cloud Logging

I was reviewing our billing last month and noticed something strange - daily charges for Cloud Logging even though I couldn’t remember enabling anything special like Managed Prometheus service.

Google Cloud Logging Billing

I got worried as this would mean spending almost $100/month for I don’t know what. I was also baffled why it started in the middle of the month, I thought maybe one of the developers enabled something and forgot.

After some investigation, I found what it was:

Google Cloud Logging Volume

GKE Control Plane components were generating 100GB of logs every month. The reason I saw some charges in the middle of the month is there is a free tier of 50GB, so for the first two weeks there wouldn’t be any charges, and once you cross the threshold, you start seeing it in billing.

We already had somewhat optimized setup by disabling logging for user worklods:

GKE Cloud Logging Setup

We want to have control plane logs in case there are some issues, but this was way too much. I started investigating deeper and found that the vast majority of logs are info-level logs from the API Server. Those are often very basic and don’t help much with troubleshooting.

To solve this, we added an exclusion rule to the _Default Log Router Sink to exclude info logs from the API server:

Log Router Sink Exclusion Filter

As you can see on one of the previous images, the logging generation flattened out after applying this filter and we now have GKE logging under control. I’ve also added a budget alert specifically for Cloud Logging to catch this earlier in the future.

Conclusion & Next Steps

I wanted to see how much we can achieve without relying on any committed-use discounts or reserved instances as those approaches still cost money and are associated with extra risks, depending on if you buy 1 or 3-year commitments. Now, that we reduced our costs a lot, we can consider applying committed use discounts as those will be a pretty low risk at this level of costs.

I hope this will give you a few fresh ideas on how to optimize your own infrastructure as most of these decisions can be applied to all major cloud providers.