Learn the essential Kubernetes best practices to improve security, stability, scalability, and cost management.
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Kubernetes Best Practices

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Kubernetes is one of the most used open-source container orchestration platforms for deploying and managing containerized applications. It offers a robust set of features that simplify the management of large-scale container deployments.

Despite the platform’s popularity, deploying and managing Kubernetes can be challenging. Following Kubernetes best practices helps to ensure the successful deployment and management of your cluster and applications. It can improve your deployment's security, stability, scalability, maintainability, and compatibility, leading to more efficient and effective containerized workloads.

Summary of Kubernetes best practices

Kubernetes best practices are the most effective and efficient methods for performing a task or achieving a specific outcome based on experience and are widely accepted by industry experts and practitioners. Below is a summary of the top 10 Kubernetes best practices we will explore in this article.

Kubernetes best practice category Description
Kubernetes Setup Kubernetes is a complex system that operates with a variety of components. Choosing the right version, deployment model, and network communication services are essential to successful Kuberntetes setup and configuration.
Application Deployment As a best practice, use declarative configuration files (such as YAML) to define your desired state and apply them using a tool like kubectl or GitOps methodologies. Alternatively, you can also use imperative methods using the command line.
Container Images Kubernetes is all about running containers. You need to adopt best practices when creating and managing container images, including keeping the images small, using a standard base image, and limiting the number of layers.
Multi-tenancy Namespaces provide a way to isolate resources and organize your Kubernetes cluster. Using Namespaces, you can segment your applications and services into logical groups, which helps simplify your Kubernetes cluster's management.
Security One best practice for security in Kubernetes is applying the principle of least privilege, using RBAC to grant only the necessary permissions to users and services, using container images from trusted sources, and implementing network policies to control traffic flow between pods.
Reliability One of the most significant advantages of Kubernetes is its ability to scale in and out pods quickly. Implement auto-scaling in your Kubernetes deployment so that your application can handle varying traffic loads without experiencing downtime.
High Availability Kubernetes provides several mechanisms to ensure high availability, such as replication controllers and readiness probes. Implement these mechanisms to ensure your application is available to users without significant downtime.
Networking Use a service mesh to manage traffic between services, implement observability, and use Kubernetes network policies to control traffic flow and enforce security policies at the network level.
Storage Use dynamic volume provisioning, and persistent volume claims to provide storage resources to applications and use storage classes to define different storage levels based on performance, availability, and cost.
Cost Management Kubernetes provides many features that developers and administrators can easily use, resulting in high costs. It is essential to have a cost management tool like Kubecost and strategy in place.

Kubernetes best practices

Adopting Kubernetes best practices can be a relatively straightforward process as long as you understand Kubernetes fundamentals well and are willing to invest some time in learning and implementing best practices. Combining your organization's standards, policies, and the industry-wide accepted best practices would be the right way to proceed with any Kubernetes deployment. The following section will cover the standard Kubernetes best practices in detail.

Best practices for Kubernetes setup

Setting up a Kubernetes cluster can be complex, but following best practices can help ensure your cluster is secure, stable, and scalable. Here are three best practices to consider when setting up your Kubernetes cluster:

  1. Use the latest version of Kubernetes. Always use the latest stable version of Kubernetes to take advantage of the latest features, performance improvements, and security patches.
  2. Choose a suitable deployment model. Choose the deployment model that best suits your use case: a self-hosted Kubernetes cluster, a managed Kubernetes service, or a hybrid model.
  3. Implement secure network communications. Secure network communication between Kubernetes components and other services using Transport Layer Security (TLS) and secure network architecture.

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Kubernetes best practices for application deployment

Deploying applications on a Kubernetes cluster can be complex, but following best practices can help ensure your deployment is secure, stable, and scalable.

Here are nine best practices to consider when deploying your applications on a Kubernetes cluster:

  1. Use Kubernetes Deployments to manage the lifecycle of your application. This includes using deployments for managing scaling, rolling updates, and rollbacks.
  2. Set resource requests and limits for your pods. Resource requests ensure pods have sufficient resources to run effectively, while limits ensure that they do not consume excessive resources.
  3. Leverage automatic scaling. Automatically scale the number of pods based on workload demand using horizontal pod autoscaling.
  4. Use ConfigMaps and Secrets for sensitive information. Kubernetes ConfigMaps help administrators store configuration data, whereas secrets help to store sensitive information such as credentials and keys.
  5. Check pod health with probes. Use liveness and readiness probes to ensure your pods are healthy and ready to serve traffic.
  6. Implement namespaces for segregation. Use Kubernetes namespaces to partition resources and segregate workloads, which can improve security and resource management.
  7. Adopt network policies that securely isolate traffic. Use network policies to restrict network traffic between pods and services, which can improve security.
  8. Follow container image security best practices. Ensure your container images adhere to the best practices, such as keeping them up to date, scanning for vulnerabilities, and avoiding hard-coded credentials.
  9. Use logging and real-time monitoring to improve visibility. Use monitoring and logging tools to track the performance and stability of your application, detect issues, and troubleshoot problems.

Kubernetes best practices for container images

Container images are a fundamental component of deploying applications on Kubernetes, and these seven best practices for creating and managing container images can help ensure your deployment is secure, stable, and scalable:

  1. Minimize attack surface with base images. Use a minimal base image for your container, such as Alpine Linux, to reduce the attack surface and improve performance.
  2. Patch early and often. Regularly patch container images to ensure they contain the latest security patches and bug fixes.
  3. Store images in a secure registry. Use a secure registry to store your container images, and use TLS to secure communication between the registry and the Kubernetes cluster.
  4. Scan images for vulnerabilities. Use image scanning tools to detect vulnerabilities and ensure your container images are secure.
  5. Don’t hard code sensitive data. Avoid hard-coding credentials and other sensitive information in your container images, and use Kubernetes Secrets to store such information.
  6. Prefer private registries over public registries. A private registry ensures that only approved container images are used. This Kubernetes best practice is especially in a production environment.
  7. Verify container integrity and authenticity. Use the content trust to verify the integrity and authenticity of your container images, and ensure that they have not been tampered with.

Kubernetes best practices for multi-tenancy

Multi-tenancy is running multiple applications on a shared Kubernetes cluster.

Here are some best practices for multi-tenancy in Kubernetes:

  1. Isolate tenants with Kubernetes namespaces. Namespaces provide a way to group related resources and provide a level of logical separation between different tenants.
  2. Limit access to resources with Role-Based Access Control (RBAC). RBAC allows you to define roles and permissions for different users or groups, ensuring tenants can access only needed resources.
  3. Manage and restrict traffic with network policies. Network policies allow you to define rules that restrict or allow traffic based on various criteria, such as pod labels, IP addresses, and ports.
  4. Cap resource usage with Kubernetes resource quotas. Resource quotas allow you to control CPU, memory, and storage usage per tenant, ensuring no tenant can consume too many resources.
  5. Control security settings within a namespace using Pod Security Policies (PSPs). PSPs allow you to enforce security policies for each tenant, ensuring each tenant has a secure environment.
  6. Track resource utilization and application performance with monitoring and logging for each tenant (namespace). Monitoring each tenant allows you to identify potential issues and ensure each tenant performs optimally.
  7. Create and manage resources with automation tools. Using Kubernetes automation tools to manage resources for each tenant helps ensure consistent and reliable provisioning.

Kubernetes best practices for security

Kubernetes is designed to provide different levels of access and permissions to different users and processes. Organizations should always follow the principle of least privilege and only grant the minimum necessary permissions to users, processes, and containers. Here are seven essential Kubernetes best practices for security organizations should adopt:

  1. Enforce the principle of least privilege with RBAC. RBAC allows you to define roles and permissions for users and services, limiting access to Kubernetes resources. This helps ensure that only authorized users and services can access sensitive data and resources.
  2. Define granular network policies. Network policies define rules for network traffic between pods and services in Kubernetes. Using network policies can help limit the exposure of sensitive services and data to the outside world.
  3. Encrypt traffic in transit. Use secure protocols for all communication between Kubernetes components and API servers. Use Transport Layer Security (TLS) certificates to encrypt traffic and authenticate Kubernetes components and services.
  4. Only deploy secure container images. Ensure that container images used in Kubernetes are secure and free from vulnerabilities. Use tools for Container image scanning to detect vulnerabilities in your container images.
  5. Implement PSPs. Pod Security Policies (PSPs) provide a way to enforce security standards for the pods running in your Kubernetes cluster. You can use Pod Security Policies to limit what a container can do, like dropping capabilities and preventing privileged mode.
  6. Store and manage secrets securely. Secrets are a way to securely store and manage sensitive data such as passwords, tokens, and keys. Ensure that secrets are encrypted and stored securely in ETCD.
  7. Patch regularly. Regularly update and patch your Kubernetes cluster to address security vulnerabilities.
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Kubernetes best practices for reliability

In Kubernetes, reliability refers to the ability of the system to consistently and predictably provide the desired functionality to its users. Specifically, reliability in Kubernetes means that the system can perform its intended tasks and services without failure or downtime, even in the face of various types of failures or disruptions.

Here are six Kubernetes best practices for reliability to help maximize workload health.

  1. Replicate and Distribute. Utilize Kubernetes replication controllers, deployments, or stateful sets to ensure workload replication across multiple nodes. Replicating your application instances helps in achieving high availability and fault tolerance. Distribute replicas across different availability zones or failure domains to minimize the impact of node failures.
  2. Detect and respond to pod problems with liveness, readiness and startup probes. Implement liveness, readiness and startup probes for your pods to ensure that Kubernetes can detect and respond to any problems with your application. Liveness probes help kubelet to determine when to restart a container, readiness probes tell the kubelet when a container is ready to accept traffic whereas the startup probe informs the kubelet when an application in the container has started.
  3. Scale based on resource utilization. Use Horizontal Pod Autoscaling (HPA) to automatically scale your application based on resource usage, ensuring that your application is always available to users, even during high traffic.
  4. Avoid downtime during updates with Rolling Updates. Use Rolling Updates to deploy new versions of your application without downtime. Rolling updates allow Kubernetes to gradually replace old pods with new ones, minimizing the impact on your application's availability.
  5. Persist data that is required across restarts and deployments. Use persistent storage to store data that needs to persist across pod restarts and deployments. Use a distributed storage solution such as a distributed file system or a cloud-native storage solution to ensure your application's data is always available and reliable.
  6. Reduce mean time to resolution (MTTR) with monitoring and debugging tools. Implement a monitoring and troubleshooting solution for your Kubernetes cluster and application. Monitor logs and metrics to detect and respond to any problems with your application or cluster. Use tools like Kubernetes Dashboard, Prometheus, and Grafana to monitor and troubleshoot your Kubernetes cluster.

Kubernetes best practices for high availability

High availability (HA) in Kubernetes refers to the ability of the system to maintain a high level of service availability and reliability, even in the face of failures or disruptions.

These eight Kubernetes high availability best practices can help organizations improve application uptime.

  1. Implement horizontal scaling to account for load fluctuations. Use HPA to scale down or up the replicas of a pod based on resource utilization to ensure that your application can handle varying levels of traffic and load.
  2. Manage application rollouts and scaling with Kubernetes deployments. Deployments provide a declarative way to manage updates and rollbacks of your application.
  3. Configure Kubernetes services to provide a stable IP address and DNS name for your application. A stable IP address and DNS name allow the application to be accessible by clients even if the underlying replicas are replaced or moved.
  4. Implement stateless architectures to allow for easy application scaling. You can scale Stateless applications by adding more replicas of the same pod without requiring any changes to the underlying infrastructure.
  5. Use vertical scaling to increase the resources available to a single pod. Vertical scaling works by increasing the CPU or memory resources assigned to a pod. You can use Vertical Pod Autoscaler to help you with this.
  6. Adopt a microservice architecture. Use microservices to break down your application into smaller, independently deployable components to scale each microservice independently based on resource requirements.
  7. Use resource requests and limits to ensure your application has enough resources to run smoothly. Resource requests guarantee that your application has access to the resources it needs, while resource limits prevent it from using too many resources and impacting the performance of other applications on the same node.
  8. Avoid resource contention with node anti-affinity to ensure pods are not scheduled on a node as other pods with similar resource requirements. Resource requests guarantee that your application has access to the resources it needs, while resource limits prevent it from using too many resources and impacting the performance of other applications on the same node.

Kubernetes best practices for networking

Kubernetes networking is the set of rules and protocols used to connect and manage the network traffic between the components of a Kubernetes cluster. Kubernetes uses a flat, virtual network that allows pods and nodes to communicate with each other regardless of their physical location. This network is created using software-defined networking (SDN) technologies, which provide a flexible, scalable, and reliable way to manage network traffic in a Kubernetes environment.

Here are ten Kubernetes networking best practices that can help administrators ensure their network services are secure and performant:

  1. Enable containers on different nodes to communicate using a Container Network Interface (CNI) plugin. Kubernetes supports several CNI plugins, including Calico, Flannel, and Weave Net.
  2. Create a dedicated network interface for your Kubernetes cluster to isolate traffic and reduce network congestion. You can achieve this using a separate network interface card (NIC) or virtual LANs (VLANs).
  3. Control traffic flows with network policies in your Kubernetes cluster. Network policies allow you to specify rules for inbound and outbound traffic, restricting access to specific pods or services.
  4. Manage traffic between services in a distributed application with a service mesh. A service mesh provides load balancing, traffic shaping, and service discovery.
  5. Expose services to the outside world (when needed) using ingress controllers. Ingress controllers allow you to specify routing rules and provide SSL termination for incoming traffic.
  6. Perform service discovery within your cluster with DNS. Kubernetes provides a built-in DNS service to resolve service names to IP addresses. However, using External DNS to manage records using Kubernetes resources in a DNS provider-agnostic way is recommended.
  7. Distribute traffic across multiple application instances using load balancing. Kubernetes provides built-in load balancing for services, distributing traffic across multiple service replicas.
  8. Distribute traffic across multiple nodes with external load balancers. External load balancers can be integrated with Kubernetes using cloud provider-specific integrations or Kubernetes Ingress.
  9. Prioritize traffic for critical applications with Quality of Service (QoS) classes. Kubernetes provides three QoS classes: guaranteed, burstable, and best effort.
  10. Test your Kubernetes cluster's network throughput to ensure it can handle the expected traffic load. Use tools like iperf to test network performance between nodes in your Kubernetes cluster.
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Kubernetes best practices for storage

Kubernetes storage is how Kubernetes manages and provisions storage resources for containerized applications running on a Kubernetes cluster. Kubernetes provides a flexible storage architecture that allows users to deploy and manage different storage solutions, including local, network-attached, and cloud-based storage.

The eight Kubernetes storage best practices below help organizations manage container storage effectively, even in multi-cloud environments.

  1. Abstract the underlying storage infrastructure from the application with Kubernetes storage classes. Storage classes allow you to define different storage levels based on performance and cost.
  2. Deploy stateful applications with Kubernetes StatefulSets. StatefulSets provide stable, unique network identities for each pod, making managing storage volumes for stateful applications easier.
  3. Use distributed storage solutions for fault tolerance and scalability across multiple nodes. Distributed storage solutions like Ceph and GlusterFS enable scalable and fault-tolerant storage in Kubernetes that can span multiple cluster nodes.
  4. Implement ReadWriteMany volumes for shared read/write access to stateful data. If your stateful applications require shared access to the same data, Use ReadWriteMany volumes to enable multiple pods to read and write to the same volume simultaneously.
  5. Implement ReadOnlyMany volumes for shared read access to data without allowing write access. If your applications require read-only access to the same data, use ReadOnlyMany volumes to enable multiple pods to read from the same volume simultaneously but not write.
  6. Use ReadWriteOnce to enable exclusive access to volumes. If your applications require exclusive access to the same data, use ReadWriteOnce volumes to enable a single pod to read and write to a volume.
  7. Create quotas to avoid runaway pods overutilizing storage. Use storage quotas to limit a pod's storage amount, preventing runaway pods from consuming all available storage resources.
  8. Request storage resources for your application with PVCs. PVCs abstract the underlying storage infrastructure from the application, allowing you to switch between different storage classes or providers easily.

Kubernetes best practices for cost management

Kubernetes is a powerful platform for running containerized applications, but it can also be complex and challenging to manage, leading to unexpected costs if not adequately monitored and controlled. One of the critical benefits of Kubernetes is its ability to scale applications dynamically based on demand. However, scaling up or down can significantly impact resource usage, affecting costs.

  1. Right size applications. Ensure your Kubernetes resources are right-sized for your applications. Overprovisioning resources can lead to unnecessary costs, while underprovisioning can cause performance issues. Use tools like Kubernetes Dashboard or Prometheus to monitor resource usage and adjust resource allocations as needed.
  2. Scale up and down based on demand. Reduce costs during periods of low demand by configuring your Kubernetes cluster to automatically scale up or down based on your workload's needs.
  3. Leverage smaller containers to reduce dependencies and size. Optimize your containers using smaller images, avoiding unnecessary dependencies.
  4. Deploy spot instances when practical. If your application can tolerate interruptions, consider using spot instances on cloud providers like AWS, Azure or Google Cloud.
  5. Proactively monitor costs. Use tools like Kubernetes Dashboard, Prometheus, and Grafana to monitor and analyze your Kubernetes usage and identify areas where you can optimize resource usage and reduce costs.
  6. Use tools to optimize cost rather than leave it to individuals. Kubecost is a powerful tool to help you manage costs and resources and gain visibility into your Kubernetes cluster's use. In addition to cost optimization, Kubecost can help you manage resource allocation in your cluster, quickly implement chargeback or showback models, monitor and alerting features, and extend cost management to multi-cloud and hybrid-cloud scenarios using a single pane of glass.

Conclusion

Adopting Kubernetes' best practices is essential for organizations that want to get the most out of their containerized applications and ensure optimal performance, scalability, and security. Kubernetes is a powerful platform, but it can also be complex and challenging to manage, especially for organizations new to containerization and orchestration.

To successfully adopt Kubernetes' best practices, organizations must invest in training and education for their teams and specific tools and services to help automate and streamline Kubernetes management tasks. By following best practices, organizations can ensure that their Kubernetes clusters are secure, reliable, and efficient and get the most out of their cloud resources. This, in turn, allows organizations to focus on delivering high-quality applications and services without worrying about the complexities of Kubernetes management.

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