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Tag: Platform Engineer

  • Leveraging Automation in Managing Kubernetes Clusters: The Path to Efficient Operation

    Automation in managing Kubernetes clusters has burgeoned into an essential practice that enhances efficiency, security, and the seamless deployment of applications. With the exponential growth in containerized applications, automation has facilitated streamlined operations, reducing the room for human error while significantly saving time. Let’s delve deeper into the crucial role automation plays in managing Kubernetes clusters.

    The Imperative of Automation in Kubernetes

    Kubernetes Architecture

    The Kubernetes Landscape

    Before delving into the nuances of automation, let’s briefly recapitulate the fundamental components of Kubernetes, encompassing pods, nodes, and clusters, and their symbiotic relationships facilitating a harmonious operational environment.

    The Need for Automation

    Automation emerges as a vanguard in managing complex environments effortlessly, fostering efficiency, reducing downtime, and ensuring the optimal utilization of resources.

    Efficiency and Scalability

    Automation in Kubernetes ensures that clusters can dynamically scale based on the workload, fostering efficiency, and resource optimization.

    Reduced Human Error

    Automating repetitive tasks curtails the scope of human error, facilitating seamless operations and mitigating security risks.

    Cost Optimization

    Through efficient resource management, automation aids in cost reduction by optimizing resource allocation dynamically.

    Automation Tools and Processes

    top devops tools

    CI/CD Pipelines

    Continuous Integration and Continuous Deployment (CI/CD) pipelines are at the helm of automation, fostering swift and efficient deployment cycles.

    pipeline:
      build:
        image: node:14
        commands:
          - npm install
          - npm test
      deploy:
        image: google/cloud-sdk
        commands:
          - gcloud container clusters get-credentials cluster-name --zone us-central1-a
          - kubectl apply -f k8s/

    Declarative Example 1: A simple CI/CD pipeline example.

    Infrastructure as Code (IaC)

    IaC facilitates the programmable infrastructure, rendering a platform where systems and devices can be managed through code.

    apiVersion: v1
    kind: Pod
    metadata:
      name: mypod
    spec:
      containers:
      - name: mycontainer
        image: nginx

    Declarative Example 2: Defining a Kubernetes pod using IaC.

    Configuration Management

    Tools like Ansible and Chef aid in configuration management, ensuring system uniformity and adherence to policies.

    - hosts: kubernetes_nodes
      tasks:
        - name: Ensure Kubelet is installed
          apt: 
            name: kubelet
            state: present

    Declarative Example 3: Using Ansible for configuration management.

    Section 3: Automation Use Cases in Kubernetes

    Auto-scaling

    Auto-scaling facilitates automatic adjustments to the system’s computational resources, optimizing performance and curtailing costs.

    Horizontal Pod Autoscaler

    Kubernetes’ Horizontal Pod Autoscaler automatically adjusts the number of pod replicas in a replication controller, deployment, or replica set based on observed CPU utilization.

    apiVersion: autoscaling/v2beta2
    kind: HorizontalPodAutoscaler
    metadata:
      name: myapp-hpa
    spec:
      scaleTargetRef:
        apiVersion: apps/v1
        kind: Deployment
        name: myapp
      minReplicas: 1
      maxReplicas: 10
      metrics:
      - type: Resource
        resource:
          name: cpu
          target:
            type: Utilization
            averageUtilization: 50

    Declarative Example 4: Defining a Horizontal Pod Autoscaler in Kubernetes.

    Automated Rollouts and Rollbacks

    Kubernetes aids in automated rollouts and rollbacks, ensuring application uptime and facilitating seamless updates and reversions.

    Deployment Strategies

    Deployment strategies such as blue-green and canary releases can be automated in Kubernetes, facilitating controlled and safe deployments.

    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: myapp
    spec:
      strategy:
        type: RollingUpdate
        rollingUpdate:
          maxSurge: 25%
          maxUnavailable: 25%
      selector:
        matchLabels:
          app: myapp
      template:
        metadata:
          labels:
            app: myapp
        spec:
          containers:
          - name: myapp
            image: myapp:v2

    Declarative Example 5: Configuring a rolling update strategy in a Kubernetes deployment.

    Conclusion: The Future of Kubernetes with Automation

    As Kubernetes continues to be the front-runner in orchestrating containerized applications, the automation integral to its ecosystem fosters efficiency, security, and scalability. Through a plethora of tools and evolving best practices, automation stands central in leveraging Kubernetes to its fullest potential, orchestrating seamless operations, and steering towards an era of self-healing systems and zero-downtime deployments.

    In conclusion, the ever-evolving landscape of Kubernetes managed through automation guarantees a future where complex deployments are handled with increased efficiency and reduced manual intervention. Leveraging automation tools and practices ensures that Kubernetes clusters not only meet the current requirements but are also future-ready, paving the way for a robust, scalable, and secure operational environment.


    References:

    1. Kubernetes Official Documentation. Retrieved from https://kubernetes.io/docs/
    2. Jenkins, CI/CD, and Kubernetes: Integrating CI/CD with Kubernetes (2021). Retrieved from https://www.jenkins.io/doc/book/

  • Kubernetes quickstarts – AKS, EKS, GKE

    There has been a lot of inquiries about how to get started quickly with what is commonly referred as the hyperscalers. Let’s dive in for a super quick primer!

    All of these quickstarts assume the reader has accounts in each service with the appropriate rights and in most cases the reader needs to have the client installed.

    Starting with Google Kubernetes Engine (GKE)

    export NAME="$(whoami)-$RANDOM"
    export ZONE="us-west2-a"
    gcloud container clusters create "${NAME}" --zone ${ZONE} --num-nodes=1
    glcoud container clusters get-credentials "${NAME}" --zone ${ZONE}

    Moving on to Azure Kubernetes Service (AKS)

    export NAME="$(whoami)-$RANDOM"
    export AZURE_RESOURCE_GROUP="${NAME}-group"
    az group create --name "${AZURE_RESOURCE_GROUP}" -l westus2
    az aks create --resource-group "${AZURE_RESOURCE_GROUP}" --name "${NAME}"
    az aks get-credentials --resource-group "${AZURE_RESOURCE_GROUP}" --name "${NAME}"

    For Elastic Kubernetes Service (EKS)

    export NAME="$(whoami)-$RANDOM"
    eksctl create cluster --name "${NAME}"

    As you can see setting up these clusters is very simple. Now that you have a cluster what are you going to do with it? Ensure you’ve installed the tools needed to manage the cluster. You’ll want to get the credentials from each copy into ~/{user}/.kube/config (except with eksctl as it copies the kubeconfig to the appropriate place automagically). To manipulate the cluster, install kubectl with your favorite package manager and to install applications the easiest way is via helm.

    As you can see the setup of a kubernetes cluster in one of the major hyperscalers is very easy. A few lines of code and you’re up and running. Add those lines into a shell script and standing up clusters can be a single command…just don’t forget to tear it down when you’re done!

  • Streamline Kubernetes Management through Automation

    Automation in managing Kubernetes clusters has burgeoned into an essential practice that enhances efficiency, security, and the seamless deployment of applications. With the exponential growth in containerized applications, automation has facilitated streamlined operations, reducing the room for human error while significantly saving time. Let’s delve deeper into the crucial role automation plays in managing Kubernetes clusters.

    Section 1: The Imperative of Automation in Kubernetes

    1.1 The Kubernetes Landscape

    Before delving into the nuances of automation, let’s briefly recapitulate the fundamental components of Kubernetes, encompassing pods, nodes, and clusters, and their symbiotic relationships facilitating a harmonious operational environment.

    1.2 The Need for Automation

    Automation emerges as a vanguard in managing complex environments effortlessly, fostering efficiency, reducing downtime, and ensuring the optimal utilization of resources.

    1.2.1 Efficiency and Scalability

    Automation in Kubernetes ensures that clusters can dynamically scale based on the workload, fostering efficiency, and resource optimization.

    1.2.2 Reduced Human Error

    Automating repetitive tasks curtails the scope of human error, facilitating seamless operations and mitigating security risks.

    1.2.3 Cost Optimization

    Through efficient resource management, automation aids in cost reduction by optimizing resource allocation dynamically.

    Section 2: Automation Tools and Processes

    2.1 CI/CD Pipelines

    Continuous Integration and Continuous Deployment (CI/CD) pipelines are at the helm of automation, fostering swift and efficient deployment cycles.

    pipeline:
      build:
        image: node:14
        commands:
          - npm install
          - npm test
      deploy:
        image: google/cloud-sdk
        commands:
          - gcloud container clusters get-credentials cluster-name --zone us-central1-a
          - kubectl apply -f k8s/
    

    Code snippet 1: A simple CI/CD pipeline example.

    2.2 Infrastructure as Code (IaC)

    IaC facilitates the programmable infrastructure, rendering a platform where systems and devices can be managed through code.

    apiVersion: v1
    kind: Pod
    metadata:
      name: mypod
    spec:
      containers:
      - name: mycontainer
        image: nginx
    

    Code snippet 2: Defining a Kubernetes pod using IaC.

    2.3 Configuration Management

    Tools like Ansible and Chef aid in configuration management, ensuring system uniformity and adherence to policies.

    - hosts: kubernetes_nodes
      tasks:
        - name: Ensure Kubelet is installed
          apt: 
            name: kubelet
            state: present
    

    Code snippet 3: Using Ansible for configuration management.

    Section 3: Automation Use Cases in Kubernetes

    3.1 Auto-scaling

    Auto-scaling facilitates automatic adjustments to the system’s computational resources, optimizing performance and curtailing costs.

    3.1.1 Horizontal Pod Autoscaler

    Kubernetes’ Horizontal Pod Autoscaler automatically adjusts the number of pod replicas in a replication controller, deployment, or replica set based on observed CPU utilization.

    apiVersion: autoscaling/v2beta2
    kind: HorizontalPodAutoscaler
    metadata:
      name: myapp-hpa
    spec:
      scaleTargetRef:
        apiVersion: apps/v1
        kind: Deployment
        name: myapp
      minReplicas: 1
      maxReplicas: 10
      metrics:
      - type: Resource
        resource:
          name: cpu
          target:
            type: Utilization
            averageUtilization: 50
    

    Code snippet 4: Defining a Horizontal Pod Autoscaler in Kubernetes.

    3.2 Automated Rollouts and Rollbacks

    Kubernetes aids in automated rollouts and rollbacks, ensuring application uptime and facilitating seamless updates and reversions.

    3.2.1 Deployment Strategies

    Deployment strategies such as blue-green and canary releases can be automated in Kubernetes, facilitating controlled and safe deployments.

    apiVersion: apps/v1
    kind: Deployment
    metadata:
      name: myapp
    spec:
      strategy:
        type: RollingUpdate
        rollingUpdate:
          maxSurge: 25%
          maxUnavailable: 25%
      selector:
        matchLabels:
          app: myapp
      template:
        metadata:
          labels:
            app: myapp
        spec:
          containers:
          - name: myapp
            image: myapp:v2
    

    Code snippet 5: Configuring a rolling update strategy in a Kubernetes deployment.

    Conclusion: The Future of Kubernetes with Automation

    As Kubernetes continues to be the frontrunner in orchestrating containerized applications, the automation integral to its ecosystem fosters efficiency, security, and scalability. Through a plethora of tools and evolving best practices, automation stands central in leveraging Kubernetes to its fullest potential, orchestrating seamless operations, and steering towards an era of self-healing systems and zero-downtime deployments.

    In conclusion, the ever-evolving landscape of Kubernetes managed through automation guarantees a future where complex deployments are handled with increased efficiency and reduced manual intervention. Leveraging automation tools and practices ensures that Kubernetes clusters not only meet the current requirements but are also future-ready, paving the way for a robust, scalable, and secure operational environment.


    References:

    1. Kubernetes Official Documentation. Retrieved from https://kubernetes.io/docs/
    2. Jenkins, CI/CD, and Kubernetes: Integrating CI/CD with Kubernetes (2021). Retrieved from https://www.jenkins.io/doc/book/
    3. Infrastructure as Code (IaC) Explained (2021).
    4. Understanding Kubernetes Operators (2021).
  • 10x the DevEX!

    Recently there has been a shift in language surrounding System Reliability Engineering (SRE) and DevOps to Platform Engineering. Granted these terms have been used in various ways for a while, but how language terms are used gives way to how markets evolve. This post provides a few key areas of thought around ways to ultimately get products to production faster. Remember…code means nothing until it’s in production.

    No matter the title, anyone in the pipeline touching production code is part of the team of ensuring success of critical applications in an enterprise. This is an important concept because everyone is part of the larger team and how teams work together ultimately determines the success of any project.

    The focus here will be on the actual development team who is primarily writing the code. The code in question would be delivered as microservices running on a K8S cluster. Keep in mind the use of microservices will lend itself to multiple teams individually creating a service for other teams to consume. Already there is significant dependencies and a single line of code has yet to be written.

    Each team ultimately needs to consume one or more code repositories, one or more “testing” systems, at least one pipeline for continuous integration, continuous delivery/deployment (CI/CD), and many other systems to get code to production.

    The Platform Engineering team is ultimately responsible for ensuring the “platforms” are working in a way to support the developers. Ensuring a great experience is paramount.

    The question is how do Platform Engineers continually improve the great developer experience? The answer many teams turn to is to create powerful systems with guardrails or opinions on how they are to be utilized based on the collective understanding of the teams modus operandi or how they work most effectively.

    The key to how is reducing the repetitive work, the mundane menial tasks which take a toll on the cognitive workload of developers allowing them to be able to focus on writing good, clean code.

    Giving the power to the developers to consume what is needed in a self-service fashion is one major step as is giving a limited set of choices in what toolsets to use. Make it easy for developers to build and deliver software without removing the useful capabilities of the core services.

    In the ideal world, limit restrictions on the how allowing choices in using GitOps or ClickOps or using a API vs CLI vs UI. Use a “as a service” approach to create a system built iteratively by the entirety of the team based on direct feedback.

    What it all comes down to is the fact that everyone has different ways they want to work. Its the platform engineering team who can help ensure all of the tools are available and functional to create a great developer experience which in turn will increase productivity and get new, shiny things to market faster.

  • 90 days to success in DevOps

    Starting a new role? Maybe this is the first foray into DevOps or Platform Engineering? What is needed to “hit the ground running” in a new role? Leaders in high positions of a company typically have a “100 day rule” to prove themselves. Let’s round it out with 3 months of progress for success.

    In most enterprises on boarding new talent is typically left to the new employee. This is very unfortunate because the first 90 days of a new role will impact not only the new employee, but their immersion into the culture and their view of the company. Bottom line, in most cases it is up to the new employee to “learn the ropes” in navigating their new position.

    The first 30 days

    This month is usually the most important for everyone. The first thing a new employee needs to do is find a good mentor especially if they are not assigned one. Seek out those with institutional knowledge who knows how to navigate the company politics. Find someone who knows how the systems work, how to gain the access needed to be successful in the role. The mentor would have knowledge of “how things work” and what is seen as best practice for accomplishing the tasks at hand.

    Some things to know:

    • Who’s who in the organization? – an org chart
    • How mature are they as a development organization?
    • What are the processes to put code into production?
    • Are the processes manual or automated?
    • What is the expectation of you on a day to day basis?

    There is plenty more to uncover, but this will help to get started. Once the processes are understood and access is granted to perform the role, find some quick wins. Listen closely to where the frustrations may lie within your organization. Maybe the previous employee in this role didn’t automate certain tasks…submit a small PR to help.

    It’s important to find some quick wins for many reasons. First it helps “break the ice”. It also shows strengths. Maybe there’s a way to improve some docs. There may be some ideas brought in from previous experience to help with a particular pain point.

    The first 30 days is important to uncover the expectations of the team. Talking to stakeholders and “the customer” is important to get a big picture of what works and what doesn’t in order to find quick wins to make an impact early.

    Days 30-60

    The first 4 weeks are usually greeted with firehose sessions daily. Take a bit to digest everything. Review notes, brainstorm ideas, understand how the team and the company works. Armed with the broader knowledge about the organization, the team, and how things work at a high level it’s time to dig deeper into where the biggest impacts can be achieved.

    In this 30 day block uncover:

    • The maturity of the team?
    • What is the approval process for delivering code to production?
    • What steps are needed to approve PRs?
    • How does code flow through the various systems?
    • What amount of QA is performed?

    Find ways to help the team be more efficient. Listen to the complaints and see where possible improvements could be made. Again, quick wins are key at this stage. As a fresh face, a lot of times gaining access to otherwise inaccessible groups within the organization is usually fairly easy. Keep an ear to the ground to find ways to create impactful suggestions

    It is important to remember as people get to know a new employee the interactions have lasting impacts. Ensure there is adequate listening and relevant questions to get underneath a complaint. Avoid making off hand suggestions, but rather find some common issues. Start to tackle the common issues and socialize improvements. The key here to to avoid “calling the baby ugly”.

    Days 60-90

    This is where a new employee’s impact can accelerate. At this stage having the access needed to be successful would be complete. Hopefully there’s been a few quick wins, new co-workers are impressed, and there’s been positive impact on the team.

    Regular interaction with your leader would have been established. A solid understanding of what is expected is created and the mentor has made an impact. Knowing where to go to get answers if there is a roadblock and knowing how to avoid the “potholes in the road” is key.

    This stage is where the “rubber hits the road”. Gaining traction in the day to day and making regular impact to the business is routine at this point. This is where all of the knowledge gained in the first 60 days can be parlayed into a winning hand.

    What success looks like

    The first 3 months of any new position sets the stage for every new employee. Creating a positive impression on the team helps build credibility within the broader organization and is key to instilling the confidence needed to being successful overall.

    It may take far more than 90 days to feel comfortable with the role and that is okay. As long as there is a consistent method for learning and mistakes are not repeated the impact new employees make is usually sustainable for a long time. Make the best of it and keep track of the wins and losses for the inevitable review with “the boss”.

    You got this. Go.