How does this skill handle security best practices?

It enforces security standards such as using Kubernetes Secrets for sensitive data, avoiding the 'latest' tag, and preventing containers from running as root.

Can I use this for stateful applications like databases?

Absolutely. It includes specific patterns for StatefulSets to manage applications requiring persistent storage and stable network identifiers.

What deployment strategies are covered by this skill?

This skill provides templates and guidance for Rolling Updates, Recreate, Blue-Green, and Canary deployment strategies to minimize risk and maximize availability.

Does this skill help with Kubernetes resource management?

Yes, it assists in setting appropriate CPU/memory requests and limits, as well as configuring Horizontal Pod Autoscalers (HPA) and Vertical Pod Autoscalers (VPA).

Kubernetes Deployment Patterns

Name: Kubernetes Deployment Patterns
Author: NickCrew

byNickCrew

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Despliegue y DevOps

Implements production-grade Kubernetes deployment strategies and optimizes cloud-native workload architectures for high availability.

Acerca de

This skill provides expert guidance for architecting and deploying applications on Kubernetes with a focus on production readiness. It helps developers select the correct workload types (Deployments, StatefulSets, DaemonSets), implement advanced rollout strategies like Blue-Green or Canary releases, and manage resources through HPA/VPA autoscaling. By following established patterns and avoiding common pitfalls like resource starvation or security vulnerabilities, it ensures that your containerized applications are resilient, scalable, and conform to cloud-native best practices.

Características Principales

Comprehensive workload configuration for stateless, stateful, and batch processing
Secure configuration management using ConfigMaps and Kubernetes Secrets
Production-grade health check implementation via liveness and readiness probes
Advanced rollout strategies including rolling updates, blue-green, and canary releases
Automated resource optimization using requests, limits, and autoscaling patterns
7 GitHub stars

Casos de Uso

Configuring stateful workloads like databases with persistent identity and storage
Optimizing cluster resource utilization and cost management through horizontal and vertical autoscaling
Designing zero-downtime deployment pipelines for microservices

Acerca de

Características Principales

Comprehensive workload configuration for stateless, stateful, and batch processing
Secure configuration management using ConfigMaps and Kubernetes Secrets
Production-grade health check implementation via liveness and readiness probes
Advanced rollout strategies including rolling updates, blue-green, and canary releases
Automated resource optimization using requests, limits, and autoscaling patterns
7 GitHub stars

Casos de Uso

Configuring stateful workloads like databases with persistent identity and storage
Optimizing cluster resource utilization and cost management through horizontal and vertical autoscaling
Designing zero-downtime deployment pipelines for microservices