Production Best Practices
In this section, we are going to discuss best practices for deploying secure, scalable and fault-tolerant applications to Kubernetes. Developers should take the following factors into account as part of their go-live checklist:
Ensure the application is properly containerized. Verify that the container image builds successfully and includes all the necessary dependencies.
Use multi-stage builds
- With multi-stage builds, you use multiple FROM statements in your Dockerfile. Each FROM instruction can use a different base, and each of them begins a new stage of the build.
- You can selectively copy artifacts from one stage to another, leaving behind everything you don’t want in the final image.
Graceful Shutdown and Restart
- Implement graceful shutdown and restart procedures to ensure that replicas can be taken offline or replaced without disrupting the application's availability.
- Handle ongoing requests and connections gracefully during the shutdown or restart process.
Validate container image integrity
- Implement a container image vulnerability scanning tool to check for any known security vulnerabilities in the image.
- Ensure that the container image is regularly scanned and updated to address any new vulnerabilities that may arise.
Configure appropriate values for your Kubernetes resources while keeping the following aspects in mind.
- Review the application's configuration requirements and determine how they will be managed in the Kubernetes environment.
- Decide whether to use environment variables, ConfigMaps, or a configuration management tool (e.g., Helm).
Externalise all configuration
- Configuration should be maintained outside the application code.
- This has several benefits. First, changing the configuration does not require recompiling the application. Second, the configuration can be updated when the application is running. Third, the same code can be used in different environments.
Health Checks with Readiness and Liveness Probes
- Implement readiness and liveness probes to ensure the application's availability and responsiveness.
- Define appropriate conditions for readiness and liveness checks based on the application's startup time and required dependencies.
- Set resource limits (CPU and memory) for your application containers to ensure they operate within expected bounds.
- Consider resource requests to ensure Kubernetes can appropriately schedule and allocate resources for your application.
- Set an appropriate Quality of Service (QoS) for Pods.
- Use LimitRange to limit resource usage at namespace level.
- Determine the appropriate number of replicas for your application based on factors such as expected traffic, scalability requirements, and resource availability.
- Consider horizontal pod autoscaling (HPA) based on resource utilization to automatically adjust the replica count.
Labels and Selectors
- Apply labels to your resources to categorize and identify them based on specific characteristics or attributes.
- Use selectors to match labels and associate resources with each other, such as Pods with Deployments or Services.
- Design your application to be stateless, meaning that it doesn't rely on specific data stored within an individual replica.
- Store session data, caches, or databases separately from the application's replicas to ensure data consistency across replicas.
- Identify any environment-specific configurations, such as database connection strings, API keys, or feature flags.
- Ensure these configurations can be easily modified for different environments (e.g., staging, production) without code changes.
Storage and Backup
Establish Backup and Restore Procedures
- Set up backup procedures for critical data and configurations within your application.
- Document the steps required to restore the application from a backup if needed.
Configure Persistent Storage
- Determine the storage requirements for your application (e.g., databases, file uploads) and provision persistent volumes.
- Set up the appropriate storage class and volume claims to ensure data persistence.
Scaling & Availability
- Define scaling policies to automatically adjust the replica count based on predefined thresholds or metrics (e.g., CPUusage, request queue length).
- Set up horizontal pod autoscaling (HPA) or custom scaling controllers to dynamically scale replicas based on workload demands.
- Ensure that your application is accessible through a load balancer or ingress controller to evenly distribute traffic among the replicas.
- Configure the load balancing mechanism to use appropriate algorithms (e.g., round-robin, the least connections) based on your application's requirements.
Configuring Pod Affinity and AntiAffinity
- The inter-pod affinity and anti-affinity documentation describe how you can change your Pod to be located (or not) in the same node.
- You should apply anti-affinity rules to your Deployments so that Pods are spread in all the nodes of your cluster.
Implement logging, tracing, and monitoring mechanisms to gain visibility into the behavior and performance of individual replicas and the overall application. Utilize tools such as distributed tracing systems (e.g., Jaeger, Zipkin) to trace requests across replicas.
Define Service Level Objectives (SLOs)
- Establish SLOs that define the expected reliability, availability, and performance of your application.
- Monitor and track these SLOs to ensure your application meets the defined service levels.
Define Key Performance Indicators (
- Identify the essential metrics and key performance indicators (
KPIs) that you want to monitor for your application's performance.
- Examples of common KPIs include response time, throughput, error rates, CPU and memory usage, and database query latency.
Monitoring and Alerting
- Set up monitoring and alerting systems to track the health and performance of the application.
- Monitor resource utilization, response times, error rates, and other relevant metrics to identify any issues or performance bottlenecks.
Enable Application Performance Monitoring
- Integrate your application with a performance monitoring tool (e.g., Prometheus, Datadog, New Relic) that provides monitoring capabilities to collect metrics and monitor application performance.
- Define and track key performance indicators (
KPIs) specific to your application.
- Instrument the application code to capture relevant metrics, such as method-level response times, database query performance, and external service dependencies.
- Utilize APM data to forecast and plan for future capacity needs.
- Identify trends and patterns in resource usage and application performance to determine when additional resources or scaling is required.
- Implement distributed tracing to visualize and trace requests as they flow through different components of your application.
- Capture details about individual requests, including their timing, dependencies, and potential bottlenecks.
Alerting and Notifications
- Define alerting thresholds for important metrics and configure notifications to be alerted when these thresholds are breached.
- Ensure that the right stakeholders are notified promptly to address performance issues and prevent any impact on end-users.
Real-Time Monitoring and Dashboards
- Configure real-time monitoring dashboards to visualize the application's performance metrics.
- Include key metrics, such as response time, error rates, and resource utilization, on these dashboards for quick and easy monitoring.
Testing and Validation
Testing and Quality Assurance
- Validate that the application behaves correctly within the Kubernetes environment and handles scaling, failures, and resource constraints.
- Perform thorough testing, including unit tests, integration tests, and end-to-end tests, to ensure the application functions as expected.
Error Handling and Monitoring
- Implement robust error handling and logging mechanisms to capture errors and exceptions.
- Define meaningful error messages and ensure they are logged appropriately for troubleshooting purposes.
- Integrate with Kubernetes-native logging and monitoring solutions to capture application logs and metrics.
Test High Availability and Failover Scenarios
- Simulate failure scenarios (e.g., node failures, network disruptions) to validate the resilience and failover mechanisms of your application.
- Monitor how the application handles these scenarios and ensure it recovers as expected.
- Consider performing chaos engineering experiments to test the resilience and fault tolerance of your application with multiple replicas.
- Introduce controlled failures or disruptions to assess how your application recovers and maintains availability.
- Images are generally identified by two components: their name and their tag. Tagging the image lets users identify a specific version of your software in order to download it. For this reason, tightly link the tagging system on container images to the release policy of your software.
- When you build an image, it's up to you to tag it properly. Follow a coherent and consistent tagging policy. Document your tagging policy so that image users can easily understand it.
Version Control and Git Tags
- Ensure the application's source code is properly version controlled using a version control system (e.g., Git).
- Use Git tags to mark specific releases or versions for easy tracking and rollback purposes.
Define Rolling Updates and Rollbacks
- Define a strategy for performing rolling updates to update the application's replicas without downtime.
- Establish a rollback procedure in case an update introduces issues or undesirable behavior.
- Determine the deployment strategy best suited for your application (e.g., blue-green, canary, rolling updates).
- Decide on the appropriate strategy for your application's availability, risk tolerance, and user impact during the deployment process.
Continuous Integration and Continuous Deployment
- Set up a continuous integration/continuous deployment (CI/CD) pipeline to automate the build, test, and deployment process.
- Configure the pipeline to trigger deployments to Kubernetes based on code changes or version updates.
- Automate the deployment of new replicas or updates to existing replicas through the CI/CD pipeline to ensure consistency and efficiency.
Define Network Policies
- Implement network policies to control ingress and egress traffic to and from your application.
- Specify allowed sources, block unwanted traffic, and secure communication between application components.
Enable Pod Security Policies
- Pod security policies are configurations that define which security-related conditions a Kubernetes pod has to meet in order to be accepted into a cluster
Documentation and Runbook
Create detailed documentation or a runbook that outlines the deployment process, including all necessary steps and configurations. Include troubleshooting guides, common issues, and solutions for reference during the go-live process and ongoing maintenance.