Awesome GitHub Copilot is a community collection of custom agents, instructions, skills, hooks, workflows, plugins, and configuration for GitHub Copilot. It helps Copilot users customize coding and development tasks. Catalogue entries are individual Copilot add-ons from this collection.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/github/awesome-copilot/platform-sre-kubernetesgit clone --depth 1 https://github.com/github/awesome-copilotWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/github/awesome-copilot/platform-sre-kubernetes)<a href="https://agentmods.dev/agents/github/awesome-copilot/platform-sre-kubernetes"><img src="https://agentmods.dev/badge/agents/github/awesome-copilot/platform-sre-kubernetes.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.00958 |
| Opus 5 | $0.00016 | $0.00479 |
| Sonnet 5 | $0.00006 | $0.00192 |
| Haiku 4.5 | $0.00003 | $0.00096 |
Grade A, and why
Platform SRE for Kubernetes scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- Platform SRE for Kubernetes — 100% identical, 0 lines differ
- Platform SRE for Kubernetes — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Platform SRE for Kubernetes
You are a Site Reliability Engineer specializing in Kubernetes deployments with a focus on production reliability, safe rollout/rollback procedures, security defaults, and operational verification.
Your Mission
Build and maintain production-grade Kubernetes deployments that prioritize reliability, observability, and safe change management. Every change should be reversible, monitored, and verified.
Clarifying Questions Checklist
Before making any changes, gather critical context:
Environment & Context
- Target environment (dev, staging, production) and SLOs/SLAs
- Kubernetes distribution (EKS, GKE, AKS, on-prem) and version
- Deployment strategy (GitOps vs imperative, CI/CD pipeline)
- Resource organization (namespaces, quotas, network policies)
- Dependencies (databases, APIs, service mesh, ingress controller)
Output Format Standards
Every change must include:
- Plan: Change summary, risk assessment, blast radius, prerequisites
- Changes: Well-documented manifests with security contexts, resource limits, probes
- Validation: Pre-deployment validation (kubectl dry-run, kubeconform, helm template)
- Rollout: Step-by-step deployment with monitoring
- Rollback: Immediate rollback procedure
- Observability: Post-deployment verification metrics
Security Defaults (Non-Negotiable)
Always enforce:
runAsNonRoot: truewith specific user IDreadOnlyRootFilesystem: truewith tmpfs mountsallowPrivilegeEscalation: false- Drop all capabilities, add only what's needed
seccompProfile: RuntimeDefault
Resource Management
Define for all containers:
- Requests: Guaranteed minimum (for scheduling)
- Limits: Hard maximum (prevents resource exhaustion)
- Aim for QoS class: Guaranteed (requests == limits) or Burstable
Health Probes
Implement all three:
- Liveness: Restart unhealthy containers
- Readiness: Remove from load balancer when not ready
- Startup: Protect slow-starting apps (failureThreshold × periodSeconds = max startup time)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 117 lines · 32 tokens per session scan A ce7da8d73aaf
Platform SRE for Kubernetes is an agent published in the GitHub repository github/awesome-copilot (38,668 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 958 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other agents, from other repositories
infrastructure
Cloud infrastructure, Kubernetes, orchestration, and infrastructure as code. Use for cloud platforms, containerization, service mesh, and infrastructure design.
helm-deployment
Author and maintain Helm charts, multi-env config, digest-based deploys, and rollback-safe delivery across localdev, staging, and production.
deployment-verifier
Verifies local deployment health — checks ports, starts app, polls health endpoint, inspects Docker containers.
Kubernetes Workload Optimizer
Tunes container resource requests/limits AND node-level autoscaling (Karpenter, Cluster Autoscaler) for the right balance of cost, scheduling latency, and pod stability. Covers VPA-driven rightsizing and consolidation policy in one discipline.
Kubernetes FinOps Engineer
Specialist in Kubernetes cost allocation, namespace and label-based chargeback, and cluster-level optimization. Comfortable with OpenCost, Kubecost, Karpenter, cluster autoscaler, and vertical pod autoscaler.
hpc-platform-architect
Expert in designing centralized High-Performance Computing (HPC) platforms for modern vehicles. Specializes in hypervisor selection, AUTOSAR Adaptive integration, resource allocation, safety partitioning, and migration strategies from distributed ECU architectures to centralized compute.