Seven Best Practices for Kubernetes Deployment


    Kubernetes (K8s) is a powerful solution for deploying, managing, and scaling containerized apps. Hence, following K8’s best practices is essential to ensure seamless deployments, efficient operations, and robust security.

    While there are many ways to configure K8s, its growing cluster makes the deployment process hard. Building a secure and manageable cluster for the workload is essential to reduce complexity.

    Here are a few best practices for K8s deployment.

    1. Use K8s Native Resources, Labels, and Annotations

    K8s offers diverse native resources like pods, deployments, services, and volumes to manage containerized apps. It is essential to use these native resources rather than creating custom scripts or workarounds.

    Native resources help developers work seamlessly around K8s to provide better manageability, scalability, and security. Furthermore, labels and annotations allow them to attach metadata to the K8s for better resource management.

    Developers can also use labels to tag resources with valuable data like app, name, environment, and version.

    2. Follow the Principle of RBAC and Single Responsibility

    As per a recent report by Red Hat, “State of Kubernetes Security Report 2023,” –

    State of Kubernetes Security Report 2023

    Role-Based Access Control (RBAC) allows developers to define access control rules for users and groups within a K8s cluster. Using RBAC restricts access to sensitive resources and operations and grants authorization only for the necessary permissions.

    More importantly, do not use the default cluster-admin role for regular users or services to reduce the risk of unauthorized access.

    At the same time, each containerized app must have a single responsibility. This means it must conduct only one task or function. Hence, avoid bundling multiple services or apps into one container and use separate containers or pods for each component. It makes management and scaling easy.

    3. Define PVs, PVCs, Resource Limits, and Requests 

    Define Persistent Volumes (PVs) and Persistent Volume Claims (PVCs) to store data persistently in the cluster. PVs represent physical storage resources, while PVCs are used to request storage from a PV.

    Defining these factors ensures that the app data is conserved even if the container or pod is rescheduled to a different node. Resource limits and requests allow developers to assign the right resources to the containers. This prevents resource contention and ensures optimal performance.

    4. Define Resource Minimums and Configure Integrated Logging

    Although it’s not a requirement, K8s lets developers define resource minimums for workloads. Defining resource minimums for every workload ensures enough resources to deploy the workload.

    A single K8s cluster could host many apps using many individual containers. Therefore, gathering logs from every container is challenging because log files disappear permanently when containers shut down. This means developers must collect the logs in real-time to avoid the risk of loss of log data.

    5. Deploy an Integrated Secrets Vault

    A digital secrets vault is a special app or service that stores passwords, access keys, and other sensitive data required to access restricted resources. While this data is stored securely in the vault, it can be exposed on an as-needed basis to apps and services.

    However, this is a poor practice as the sensitive data can be viewed by anyone accessing the deployment files. In addition to security issues, the secrets defined directly within K8s are not easily accessible by non-K8s workloads.

    To overcome these bottlenecks, ensure the K8s environment is integrated with the secrets vault at deployment time. It helps manage sensitive information securely. It also makes it simple to share that information between multiple resources when needed.

    6. Use Namespaces and Rolling Updates for Deployment

    Namespaces allow developers to create logical partitions within a cluster for resource isolation and access control. Use namespaces to group resources per projects, teams, or environments to prevent resource name clashes.

    Moreover, using rolling updates for deployments ensures zero downtime. This updates the app gradually, minimizing disruptions and ensuring that the app remains available during updates.

    7. Track, Observe, and Run Health Checks

    Tracking and observing the cluster helps ensure good health and performance of the apps. Developers can use Prometheus, Grafana, or K8s-native monitoring tools like Kubernetes Metrics Server to assess the metrics from the CPU usage, memory usage, and network traffic. Setting up alerts and notifications helps proactively track your cluster when any issues arise.

    Running health checks using readiness and liveliness probes ensures the containers are running correctly and ready to serve traffic. Health checks help K8s detect and recover from failures, ensuring the high availability of the apps.

    Also Read: Navigating Kubernetes Costs: Practical Tips for Real-World Deployments


    K8s is a robust yet complex container orchestration platform. Hence, it requires efficient configuration and management to facilitate the smooth operation of apps. As per a recent report by Pepperdata, “The State of Kubernetes 2023,”

    The State of Kubernetes 2023

    Developers can optimize K8s clusters’ performance, reliability, and security by adopting these seven best practices. It helps streamline the app deployment and management processes.

    Developers must strictly follow K8s documentation and stay updated with the latest practices and security upgrades. Pepperdata’s report also states the top challenges the firms faced when adopting K8s were

    • Significant or unexpected spending on computing, storage, networking infrastructure, and or cloud-based IaaS (57%)
    • A steep learning curve required for employees to upskill across software development, operations, and security (56%)
    • Limited support for stateful apps (52%)

    Review and audit K8s configurations regularly to overcome these challenges to detect likely security risks, performance issues, and potential spending costs. Lastly, use monitoring and observability tools to track clusters and address possible issues. All this ensures that the K8s deployments are efficient, reliable, secure, and smooth running of apps in a production environment.


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