Kubernetes configs




git.io/k8s-configs
Intro
Advanced Kubernetes YAML configurations & templates, based on my experiences running Kubernetes in production at different companies.
The top-level directory contains standard Kubernetes object templates with many Best Practices, Tips & Tricks learned over time across production environments.
The sub-directories contain ready-to-run real world apps that I’ve run across environments.
Templates
Start with deployment.yaml / statefulset.yaml, for advanced users see kustomization.yaml.
The service.yaml and
ingress.yaml configs contain settings
for using static public IP addresses and locking down your cloud load balancer’s firewall rules eg. to private IP
addresses, and patches for Cloudflare Proxied or VPN IPs. You may need to extend those IP lists to your office /
VPN / public addresses if really want to permit direct internet access to your ingresses and aren’t proxying them
through a WAF in proxied mode etc.
See also the Dockerfile template in the
HariSekhon/Templates repo to containerize your custom apps for deploying
on to Kubernetes.
Apps
Real-world app deployments are found in the more specific <app>/ directories.
These follow the standard Kustomize <app>/base/ and <app>/overlay/ layout to make it easy to use as-is by just tweaking a couple settings in the overlay to your specific environment.
CI/CD
Advanced auto-scaling production-grade CI/CD on Kubernetes:
Helm Repos
Helm repos you should probably have installed:
Table generated from helm-repos.txt
by script generate_repos_markdown_table.sh
These repos can quickly installed in one command using script install_repos.sh:
./install_repos.sh
Helm + Kustomize integration
See kustomization.yaml for 2 methods provided:
- template the Helm chart using a
values.yaml to Git and serve from there (see DevOps Bash Tools for the helm_template.sh convenience script)
- dynamically load the Helm chart from upstream with a
values.yaml
…then patch override anything the chart doesn’t directly support using the standard Kustomize patching examples given in the kustomization.yaml.
Production Ready Checklist
This section has been moved and enhanced in my amazing
Knowledge-Base
repo:
Kubernetes Production Ready Checklist
Further Documentation
The best documentation links are provided at the top of each yaml for fast referencing (my advanced .vimrc can open these URLs from the current file via a hotkey!)
See also HariSekhon/Knowledge-Base, especially:
Datree Kubernetes ArgoCD best practices
Environment Enhancements
.envrc - use with direnv to auto-load correct Kubernetes context isolated to current shell to avoid race conditions between shells and scripts caused by naively changing the global ~/.kube/config context
Shortcut symlinks are for faster instantiation from these configs using the standard kubernetes shortcuts such as new pvc.yaml - see the Templates repo for more details on the new command to fast create new files from templates.
Diagrams
For more amazing diagrams see HariSekhon/Diagrams-as-Code
Kubernetes Deployment with Horizontal Pod Autoscaler and Ingress

Kubernetes Stateful Architecture with persistent volumes

Kubernetes Service External Traffic Policy

Kubernetes on Premise

with MetalLB:
Is it just me or do MetaLB think they’re Starfleet? (compare their logos)

Traefik Ingress on GKE
A Traefik deployment I did for a client using:

alternative diagram:

Kong API Gateway on AWS EKS
A Kong API Gateway deployment I did for a client using:

Jenkins on Kubernetes
A production Jenkins on Kubernetes I built for a client with auto-spawning agents for horizontal scaling and integration with Docker, SonarQube, Clair, Grype and Trivy for code & container scanning.
Useful Notes
HariSekhon/Knowledge-Base - Jenkins
HariSekhon/Knowledge-Base - Jenkins-on-Kubernetes

screenshot:

ArgoCD - GitOps for Kubernetes
argocd.d2:

OpenTSDB on Kubernetes and HBase
A high scale production OpenTSDB replatform I did to Kubernetes for a client, ingesting 9 billion data points per day and serving 3 million queries per day.
I also had to do advanced performance tuning of their production HBase cluster which was suffering from frequent outages at this scale due to being set up by a non-SME on the wrong hardware (I had to make do with the existing hardware of course).
This was the second client I did in-depth performance tuning of HBase for - I’ve published a selection of useful HBase tools - see hbase_*.py and opentsdb_*.py in my DevOps Python tools repo.

History
Forked from the Templates repo.
Star History

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The rest of my original source repos are
here.
Pre-built Docker images are available on my DockerHub
and can be re-generated using the my Dockerfiles repo.
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