Automation, security, and scaling: managing Kubernetes in production

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Production Kubernetes clusters have stronger requirements than developers or staging environments.

1. Production environments don’t tolerate many manual operations and require maximum automation. You should automate as much as possible, including CI/CD, deployment through Git hosting, IaC management, and more. Manual control and intervention in infrastructure elements are highly risky in production due to the possibility of failures and human error.
2. The architecture of the container infrastructure in production usually differs from development and staging environments, as it is optimized and tuned for fault tolerance and security requirements. Especially for large teams, it requires reorganizing secure access schemes for multiple users, constant availability, etc.
3. Well-thought-out and tested auto-scaling is essential for the infrastructure to scale effectively and use costly resources properly during high loads. It’s also important to think about cost optimization: analyzing cluster load, removing outdated containers, moving non-critical services to on-demand resources, and consolidating workloads within the cluster without sacrificing performance.
4. Production requires the most informative monitoring of all vital processes in the infrastructure. It involves more than just the usual CPU/RAM/Storage load indicators on the cluster nodes. An important metric might be the status of running containers compared to those configured in deployments/daemonsets/cronjobs. If there are issues in microservices, discrepancies in statuses will appear. In this case, it’s necessary to analyze alerts and notifications, set up grouping, and visualize the metrics ratio. Many DevOps engineers aim for around 80% coverage of various key indicators.
5. The backup system must also be unified, automated, and tested. The problem of data and service recovery in Kubernetes cannot always be solved by backing up virtual machines on the master nodes. A cluster may contain stateful applications and databases, so the container backup tool must ensure the integrity of data and configurations to allow services to run properly after recovery. For backing up configurations and persistent storage, you can use snapshots, side-car containers, and pre/post scripts. Depending on your requirements, you can choose internal or external backup tools. Internal tools (like Velero and Kasten) run directly inside Kubernetes, while external ones (e.g., Commvault) connect to the cluster from the outside. The backup and recovery mechanism should be simplified and automated for quick and convenient replication in working conditions.

All these points, along with security measures and high availability guarantees, distinguish production from other stages and are managed in Kubernetes environments.

Good luck with your integrations!