Agent Skillssupercheck-io/supercheck › supercheck-infrastructure-deployment

supercheck-infrastructure-deployment

GitHub

涵盖 Supercheck 基础设施部署全流程,包括 Docker Compose、K3s/K8s 集群管理、OpenTofu IaC、gVisor 安全执行及 Hetzner 云资源管理。

.agents/skills/infrastructure-deployment/SKILL.md supercheck-io/supercheck

Trigger Scenarios

需要配置或修改 Docker Compose 环境 进行 K3s 或 Kubernetes 集群部署与调试 使用 OpenTofu 管理云基础设施变更 处理 gVisor 沙箱执行作业配置 实施生产环境发布、备份或灾难恢复

Install

npx skills add supercheck-io/supercheck --skill supercheck-infrastructure-deployment -g -y
More Options

Non-standard path

npx skills add https://github.com/supercheck-io/supercheck/tree/main/.agents/skills/infrastructure-deployment -g -y

Use without installing

npx skills use supercheck-io/supercheck@supercheck-infrastructure-deployment

指定 Agent (Claude Code)

npx skills add supercheck-io/supercheck --skill supercheck-infrastructure-deployment -a claude-code -g -y

安装 repo 全部 skill

npx skills add supercheck-io/supercheck --all -g -y

预览 repo 内 skill

npx skills add supercheck-io/supercheck --list

SKILL.md

Frontmatter
{
    "name": "supercheck-infrastructure-deployment",
    "description": "Work on Supercheck Docker Compose, K3s, Kubernetes manifests, gVisor, OpenTofu\/Hetzner, secrets, external services, autoscaling, backups, disaster recovery, DNS\/TLS, or production deployment."
}

Supercheck infrastructure and deployment

flowchart TD
  RELEASE[Immutable app/worker release] --> CLUSTER[K3s cluster]
  TOFU[OpenTofu infrastructure] --> CLUSTER
  SECRETS[Secret manager] --> CLUSTER
  CLUSTER --> APP[App replicas and schedulers]
  CLUSTER --> WORK[Regional worker pools]
  WORK --> JOB[gVisor execution Jobs]
  APP --> EXT[(PostgreSQL, Redis, object storage)]
  WORK --> EXT
  KEDA[KEDA and cluster autoscaler] --> WORK

Deployment surfaces

  • deploy/docker contains public self-hosted Compose assets. Inspect current files to choose bundled dependencies, secure/TLS, external services, remote worker, or local-source behavior.
  • Production K3s/OpenTofu assets may be maintained outside this repository, but contributors must preserve the contracts described here when changing app/worker/deploy code.
  • Local macOS Kubernetes may use OrbStack. Local exceptions must not weaken production defaults.

Docker Compose and self-hosting

  • App, worker, PostgreSQL, Redis, MinIO/object storage, proxy/TLS, and K3s dependencies start in a health-aware order.
  • Generate unique auth/encryption/storage/Redis secrets and keep all .env files untracked.
  • Browser URL, API URL, OAuth callbacks, cookie domain, trusted proxy, status-page domain, and TLS routing must agree.
  • Bind stateful services privately; do not publish PostgreSQL, Redis, or object storage to the internet.
  • Remote workers use authenticated network paths, a unique supported location, and an app/worker-compatible release.
  • Capacity equals usable worker execution concurrency, not merely a replica count. Verify location queue routing and resource availability.

Kubernetes and gVisor

  • Production execution fails closed on the configured gVisor RuntimeClass.
  • Execution Jobs run in the dedicated namespace with zero-permission service account, non-root/read-only containers, dropped capabilities, no privilege escalation, resource requests/limits, deadlines, TTL cleanup, and bounded writable storage.
  • Namespace default-deny NetworkPolicy, DNS allowance, LimitRange, and ResourceQuota stay aligned with worker-generated Job resources.
  • App/worker workloads use probes, disruption/rollout settings, anti-affinity/topology behavior, and service accounts appropriate to their role.
  • Node-local DNS configuration must match cluster DNS IP, host paths, interface/listen behavior, and upstream configuration before rollout.

OpenTofu and Hetzner

  • Infrastructure is declarative; review plan output and exact targets before apply.
  • Keep control-plane/stateful nodes protected. Replaceable workers may scale down according to current availability/cost policy.
  • Never commit cloud tokens, kubeconfigs, generated secrets, private keys, state, or live inventory.
  • OpenTofu state is critical persistent data. Store it remotely with locking/versioning and never apply artifact lifecycle deletion to it.
  • Firewall and SSH/admin access use least privilege and restricted source networks. Prefer non-root administrative users with audited sudo.

External services and secrets

  • Supported deployments require PostgreSQL, BullMQ-compatible Redis, S3-compatible object storage, and optionally SMTP, OAuth, CAPTCHA, AI, billing, support, and observability providers.
  • Provider names, pricing, limits, product IDs, regions, and setup UI are drift-prone; verify live before operational decisions.
  • Redis uses maxmemory-policy noeviction and sufficient connection capacity.
  • PostgreSQL connection pooling/SSL must match the provider endpoint and migration strategy.
  • Secrets are injected through the approved secret manager/CI mechanism, rotated by environment, and unavailable to untrusted CI jobs.

Autoscaling

  • KEDA/worker scaling follows queue pressure and capacity policy; cluster autoscaler node pools must permit the corresponding location labels/taints and scale bounds.
  • Preserve the current pre-launch baseline unless explicitly changed: one warm EU worker for scheduled monitor availability; US/APAC may scale to zero.
  • Scale-to-zero acceptance proves node bootstrap, CNI/DNS readiness, image pull, worker registration, execution, and cleanup—not only VM creation.
  • Validate app schedulers and queue capacity independently from node autoscaling.

Disaster recovery

  • Define and test backups for PostgreSQL, object storage, infrastructure state, cluster configuration, and required secrets.
  • RPO/RTO claims require measured restore evidence; do not promise timings from an untested workstation bootstrap.
  • Never run cluster reset on a healthy control plane or delete a stateful PVC/host before validating off-host restore material.
  • Restore into an isolated environment when practical; verify integrity, migration compatibility, auth, queues, storage, and a disposable execution.

Deployment verification

  1. Use an explicit kubeconfig/context for every production command.
  2. Render/validate manifests or Compose config and review destructive/resource changes.
  3. Deploy an immutable exact SHA/version through a bounded rollout.
  4. Inspect pods, events, logs, probes, revision labels, migrations, KEDA/autoscaler/control-plane health, and pressure.
  5. Run disposable user and execution acceptance, then remove fixtures.
  6. Keep DNS/TLS, provider accounts, credentials, spending, destructive changes, and final production approval as explicit gates.

Version History

  • 974a753 Current 2026-09-22 16:21

Same Skill Collection

.agents/skills/architecture/SKILL.md
.agents/skills/code-review/SKILL.md
.agents/skills/data-storage/SKILL.md
.agents/skills/execution-engine/SKILL.md
.agents/skills/feature-implementation/SKILL.md
.agents/skills/integrations-extensions/SKILL.md
.agents/skills/monitoring-alerts/SKILL.md
.agents/skills/platform-features/SKILL.md
.agents/skills/security-auth/SKILL.md
.agents/skills/sre-operations/SKILL.md
.agents/skills/testing-qa/SKILL.md
.github/skills/code-review/SKILL.md
.github/skills/docker-compose-deployment/SKILL.md
.github/skills/feature-implementation/SKILL.md

Metadata

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Version
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Indexed
2026-09-22 16:21

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