123 points by bigk8suser 7 months ago flag hide 26 comments
k8smaster 7 months ago next
Some best practices I've found are:\n1. Implementing thorough monitoring and logging\n2. Using Ingress controllers for load balancing\n3. Implementing autoscaling
containerguru 7 months ago next
Great points! I'd also add\n4. Labeling and organizing objects for easier management\n5. Using Helm charts for consistent deployments.
k8smaster 7 months ago next
That's a good one! I'd love to hear more suggestions from the community.
devopsdude 7 months ago prev next
I've had success with\n6. Implementing a CI/CD pipeline with tools like Jenkins\n7. Implementing canary releases for testing new deployments
k8sgal 7 months ago next
I agree with canary releases, and I would also add\n8. Using GitOps practices for version control\n9. Setting up network policies for security
devopsdude 7 months ago next
@k8sGal Absolutely, both GitOps and network policies are important! I would also recommend using Istio for managing traffic between services.
cloudexpert 7 months ago prev next
For managing resources at scale, I recommend\n10. Implementing resource quotas for efficient resource utilization\n11. Using Kubernetes Operators for automating day-to-day tasks
k8sgal 7 months ago next
@cloudExpert Yes, resource quotas and Operators are crucial for large deployments! Also, make sure to use a centralized storage solution like NFS for shared storage.
automationgod 7 months ago prev next
To ensure high availability of your applications, 12. Implementing multi-region deployments 13. Using Kubernetes Federation for centralized management Of course, make sure to thoroughly test your disaster recovery plan!
k8smaster 7 months ago next
@automationGod Excellent suggestions! Always be sure to prioritize high availability and disaster recovery. What's your preferred monitoring solution for keeping track of your deployments?
automationgod 7 months ago next
I'm a fan of Prometheus for monitoring and alerting, it has great integration with Grafana for visualizing your monitoring data. What do you use for your deployments?
k8smaster 7 months ago next
@automationGod I prefer Nagios, it's very customizable and has a lot of community support. I'll have to give Prometheus a try, thanks for the recommendation!
securityexpert 7 months ago prev next
From a security perspective, make sure to 14. Implementing role-based access control (RBAC) 15. Regularly scanning for vulnerabilities in your images 16. Using secrets and config maps for sensitive data
devopsdude 7 months ago next
@securityExpert Secrets and config maps are crucial for handling sensitive data. Do you have a recommended scanning tool for vulnerabilities?
securityexpert 7 months ago next
@devopsDude I'm a fan of Trivy for image vulnerability scanning, it's very fast and accurate. Also, check out Open Policy Agent for enforcing security policies.
continuousdeployer 7 months ago prev next
Continuous integration and delivery should be a priority, 17. Implementing blue/green deployments 18. Using automated rollouts and rollbacks with tools like Kubernetes Rolling Update
k8sgal 7 months ago next
@continuousDeployer Yes! Automated rollouts and rollbacks are critical for a smooth deployment process. I would also recommend using Review Apps for visualizing your changes before deployment.
continuousdeployer 7 months ago next
@k8sGal Absolutely, Review Apps are a great way to ensure your changes are correct and functional. I would also add using pre- and post-deployment hooks for additional automation tasks.
scalesquad 7 months ago prev next
To manage large-scale deployments, consider 19. Using Kubernetes clusters per environment 20. Implementing Continuous Integration and Continuous Deployment (CI/CD) pipelines 21. Using a container image management system like Google Container Registry (GCR)
cloudexpert 7 months ago next
@scaleSquad That's a good point about running separate clusters per environment. Having a container image management system is also crucial for managing the increasing number of images.
containerpro 7 months ago prev next
To optimize performance, 22. Implementing horizontal pod autoscaling 23. Using Kubernetes service meshes like Istio for traffic management 24. Implementing performance monitoring and profiling at the container level
securityexpert 7 months ago next
@containerPro Service meshes are a powerful tool for managing traffic, and implementing performance monitoring at the container level is crucial for identifying bottlenecks and performance issues.
askhnuser 7 months ago prev next
What about storage management? How do you handle data persistence and backups in a k8s cluster?
cloudexpert 7 months ago next
For storage management, I recommend 25. Using persistent volumes (PV) and persistent volume claims (PVC) 26. Implementing a backup and restore strategy using tools like Velero or Velostrata 27. Using snapshotting for backup and disaster recovery.
askhnuser 7 months ago next
Great tips! Are there any strategies for speeding up development of a k8s cluster?
devopswiz 7 months ago next
@AskHNUser Yes, definitely! Some strategies I recommend for speeding up development include 28. Using cloud-native tools like Skaffold, Helm, and Kind for building and deploying your cluster 29. Implementing a code-centric approach with tools like kustomize or jsonnet 30. Using Automated Canary or Blue/Green deployment strategies using tools like Jenkins X, Argo, or Flagger