---
name: devops-sre-master
description: |
  DevOps 与站点可靠性工程 (SRE) — 平台 / 基础设施 / 可靠性工程师的认知操作系统, 覆盖软件交付 + 运维全生命周期 (CI/CD 与发布工程 trunk-based + 渐进式发布 canary/blue-green/feature flag + GitOps Argo CD/Flux / 基础设施即代码 Terraform/OpenTofu/Pulumi/Ansible + policy-as-code OPA / 容器与编排 Docker/Kubernetes + Helm/Kustomize + service mesh Istio/Linkerd / 可观测性 Prometheus + Loki + OpenTelemetry + Honeycomb + eBPF + RED/USE / SLO-SLI-error budget 与可靠性工程 Google SRE 学科 + 容量规划 + 优雅降级 / 事件管理与 on-call 事件指挥 + PagerDuty + runbook + 无指责复盘 + MTTR / 云平台与 FinOps AWS/GCP/Azure + 成本优化 + 弹性伸缩 / 平台工程与开发者体验 IDP + Backstage + golden path + Team Topologies / DevSecOps 与供应链安全 shift-left + SBOM + SLSA + sigstore + Vault / 韧性与混沌工程 fault injection + game day + 安全科学 / DORA 指标与工程效能 部署频率 + 变更前置时间 + 变更失败率 + Accelerate 研究 / 数据库与有状态运维 schema 迁移 + 备份容灾) — 不含 通用应用开发 / 纯云销售认证速成 / 'DevOps = 跑 Jenkins 的岗位' 窄化误解 / ITIL 工单文化传统运维 (旧范式仅做边界) / 把手工运维 ClickOps 当稳态 (是 toil, 本 skill 核心反模式) (DevOps & Site Reliability Engineering — the cognitive operating system of platform / infrastructure / reliability practitioners who own the full software delivery + operational lifecycle, covering (a) CI/CD & release engineering (build pipelines, trunk-based development, progressive delivery — canary / blue-green / feature flags, GitOps with Argo CD / Flux), (b) Infrastructure as Code (Terraform / OpenTofu, Pulumi, CloudFormation, Ansible, Crossplane — module design, state management, drift, policy-as-code OPA / Sentinel / Checkov), (c) containers & orchestration (Docker / OCI, Kubernetes — scheduling, networking CNI, storage CSI, operators / CRDs, Helm / Kustomize, service mesh Istio / Linkerd), (d) observability (the three pillars + beyond — metrics Prometheus / VictoriaMetrics, logs Loki / ELK, traces OpenTelemetry / Jaeger / Tempo, high-cardinality observability Honeycomb, eBPF, RED / USE methods, SLO-based alerting), (e) SLO / SLI / error budgets & reliability engineering (Google SRE discipline — service level objectives, error budget policy, toil budgets, capacity planning, load shedding, graceful degradation), (f) incident management & on-call (incident command, PagerDuty / Opsgenie, runbooks, blameless postmortems, MTTR / MTTD, error budget burn), (g) cloud platforms & FinOps (AWS / GCP / Azure well-architected, multi-region, cost optimization, autoscaling), (h) platform engineering & developer experience (internal developer platforms, Backstage, golden paths, self-service, Team Topologies), (i) DevSecOps & supply-chain security (shift-left, SAST / DAST, SBOM, SLSA, sigstore / cosign, secrets management Vault), (j) resilience & chaos engineering (chaos experiments, fault injection, game days, resilience engineering / safety science), (k) DORA metrics & engineering effectiveness (deployment frequency, lead time, change failure rate, MTTR, the Accelerate research), (l) databases & stateful operations (schema migrations, backups / DR, replication); NOT generic software development / app feature coding (是 平行学科, DevOps/SRE 关注 delivery + operability 不是 product feature), NOT pure cloud sales / certification cram without operational depth, NOT 'DevOps = a job title that runs Jenkins' 的窄化误解 (DevOps 是 文化 + 实践, SRE 是 Google 对 reliability 的工程化具体实现), NOT ITIL-heavy 传统运维 工单文化 (是 被 DevOps 取代的旧范式, 仅做边界标注), NOT manual ops / ClickOps as a steady state (是 toil, 本 skill 的核心反模式).) Master OS — automated mastery of DevOps & Site Reliability Engineering — the cognitive operating system of platform / infrastructure / reliability practitioners who own the full software delivery + operational lifecycle, covering (a) CI/CD & release engineering (build pipelines, trunk-based development, progressive delivery — canary / blue-green / feature flags, GitOps with Argo CD / Flux), (b) Infrastructure as Code (Terraform / OpenTofu, Pulumi, CloudFormation, Ansible, Crossplane — module design, state management, drift, policy-as-code OPA / Sentinel / Checkov), (c) containers & orchestration (Docker / OCI, Kubernetes — scheduling, networking CNI, storage CSI, operators / CRDs, Helm / Kustomize, service mesh Istio / Linkerd), (d) observability (the three pillars + beyond — metrics Prometheus / VictoriaMetrics, logs Loki / ELK, traces OpenTelemetry / Jaeger / Tempo, high-cardinality observability Honeycomb, eBPF, RED / USE methods, SLO-based alerting), (e) SLO / SLI / error budgets & reliability engineering (Google SRE discipline — service level objectives, error budget policy, toil budgets, capacity planning, load shedding, graceful degradation), (f) incident management & on-call (incident command, PagerDuty / Opsgenie, runbooks, blameless postmortems, MTTR / MTTD, error budget burn), (g) cloud platforms & FinOps (AWS / GCP / Azure well-architected, multi-region, cost optimization, autoscaling), (h) platform engineering & developer experience (internal developer platforms, Backstage, golden paths, self-service, Team Topologies), (i) DevSecOps & supply-chain security (shift-left, SAST / DAST, SBOM, SLSA, sigstore / cosign, secrets management Vault), (j) resilience & chaos engineering (chaos experiments, fault injection, game days, resilience engineering / safety science), (k) DORA metrics & engineering effectiveness (deployment frequency, lead time, change failure rate, MTTR, the Accelerate research), (l) databases & stateful operations (schema migrations, backups / DR, replication); NOT generic software development / app feature coding (是 平行学科, DevOps/SRE 关注 delivery + operability 不是 product feature), NOT pure cloud sales / certification cram without operational depth, NOT 'DevOps = a job title that runs Jenkins' 的窄化误解 (DevOps 是 文化 + 实践, SRE 是 Google 对 reliability 的工程化具体实现), NOT ITIL-heavy 传统运维 工单文化 (是 被 DevOps 取代的旧范式, 仅做边界标注), NOT manual ops / ClickOps as a steady state (是 toil, 本 skill 的核心反模式).: top builders' mental models, tool stack, current workflows, jargon, and where to keep up.
  Trigger this skill when the user works on DevOps & Site Reliability Engineering — the cognitive operating system of platform / infrastructure / reliability practitioners who own the full software delivery + operational lifecycle, covering (a) CI/CD & release engineering (build pipelines, trunk-based development, progressive delivery — canary / blue-green / feature flags, GitOps with Argo CD / Flux), (b) Infrastructure as Code (Terraform / OpenTofu, Pulumi, CloudFormation, Ansible, Crossplane — module design, state management, drift, policy-as-code OPA / Sentinel / Checkov), (c) containers & orchestration (Docker / OCI, Kubernetes — scheduling, networking CNI, storage CSI, operators / CRDs, Helm / Kustomize, service mesh Istio / Linkerd), (d) observability (the three pillars + beyond — metrics Prometheus / VictoriaMetrics, logs Loki / ELK, traces OpenTelemetry / Jaeger / Tempo, high-cardinality observability Honeycomb, eBPF, RED / USE methods, SLO-based alerting), (e) SLO / SLI / error budgets & reliability engineering (Google SRE discipline — service level objectives, error budget policy, toil budgets, capacity planning, load shedding, graceful degradation), (f) incident management & on-call (incident command, PagerDuty / Opsgenie, runbooks, blameless postmortems, MTTR / MTTD, error budget burn), (g) cloud platforms & FinOps (AWS / GCP / Azure well-architected, multi-region, cost optimization, autoscaling), (h) platform engineering & developer experience (internal developer platforms, Backstage, golden paths, self-service, Team Topologies), (i) DevSecOps & supply-chain security (shift-left, SAST / DAST, SBOM, SLSA, sigstore / cosign, secrets management Vault), (j) resilience & chaos engineering (chaos experiments, fault injection, game days, resilience engineering / safety science), (k) DORA metrics & engineering effectiveness (deployment frequency, lead time, change failure rate, MTTR, the Accelerate research), (l) databases & stateful operations (schema migrations, backups / DR, replication); NOT generic software development / app feature coding (是 平行学科, DevOps/SRE 关注 delivery + operability 不是 product feature), NOT pure cloud sales / certification cram without operational depth, NOT 'DevOps = a job title that runs Jenkins' 的窄化误解 (DevOps 是 文化 + 实践, SRE 是 Google 对 reliability 的工程化具体实现), NOT ITIL-heavy 传统运维 工单文化 (是 被 DevOps 取代的旧范式, 仅做边界标注), NOT manual ops / ClickOps as a steady state (是 toil, 本 skill 的核心反模式). problems and wants industry-grade thinking, tool selection, or workflow guidance.
  触发词：「DevOps」「devops」「SRE」「site reliability engineering」「site reliability engineer」
triggers:
  - "DevOps"
  - "devops"
  - "SRE"
  - "site reliability engineering"
  - "site reliability engineer"
  - "站点可靠性工程"
  - "站点可靠性工程师"
  - "可靠性工程"
  - "平台工程"
  - "platform engineering"
  - "platform engineer"
  - "infrastructure engineer"
  - "基础设施工程师"
  - "运维"
  - "运维工程师"
  - "DevOps 工程师"
  - "CI/CD"
  - "continuous integration"
  - "continuous delivery"
  - "continuous deployment"
  - "持续集成"
  - "持续交付"
  - "持续部署"
  - "release engineering"
  - "发布工程"
  - "progressive delivery"
  - "渐进式发布"
  - "canary"
  - "canary deployment"
  - "金丝雀发布"
  - "blue-green"
  - "blue-green deployment"
  - "蓝绿部署"
  - "feature flag"
  - "feature flags"
  - "特性开关"
  - "GitOps"
  - "Argo CD"
  - "ArgoCD"
  - "Flux"
  - "FluxCD"
  - "Jenkins"
  - "GitHub Actions"
  - "GitLab CI"
  - "CircleCI"
  - "Tekton"
  - "Spinnaker"
  - "Infrastructure as Code"
  - "IaC"
  - "基础设施即代码"
  - "Terraform"
  - "OpenTofu"
  - "Pulumi"
  - "CloudFormation"
  - "Ansible"
  - "Chef"
  - "Puppet"
  - "SaltStack"
  - "Crossplane"
  - "policy as code"
  - "OPA"
  - "Open Policy Agent"
  - "Sentinel"
  - "Checkov"
  - "tfsec"
  - "Docker"
  - "container"
  - "containers"
  - "容器"
  - "OCI"
  - "Kubernetes"
  - "k8s"
  - "K8s"
  - "kubectl"
  - "Helm"
  - "Kustomize"
  - "operator"
  - "CRD"
  - "custom resource"
  - "service mesh"
  - "服务网格"
  - "Istio"
  - "Linkerd"
  - "Envoy"
  - "Cilium"
  - "eBPF"
  - "CNI"
  - "CSI"
  - "observability"
  - "可观测性"
  - "monitoring"
  - "监控"
  - "Prometheus"
  - "Grafana"
  - "VictoriaMetrics"
  - "Thanos"
  - "Cortex"
  - "Mimir"
  - "Loki"
  - "ELK"
  - "Elasticsearch"
  - "Elastic Stack"
  - "Fluentd"
  - "Fluent Bit"
  - "OpenTelemetry"
  - "OTel"
  - "Jaeger"
  - "Tempo"
  - "Zipkin"
  - "Honeycomb"
  - "Datadog"
  - "New Relic"
  - "Dynatrace"
  - "Splunk"
  - "Sentry"
  - "RED method"
  - "USE method"
  - "four golden signals"
  - "黄金信号"
  - "SLO"
  - "SLI"
  - "SLA"
  - "error budget"
  - "错误预算"
  - "service level objective"
  - "service level indicator"
  - "toil"
  - "capacity planning"
  - "容量规划"
  - "load shedding"
  - "graceful degradation"
  - "优雅降级"
  - "circuit breaker"
  - "熔断"
  - "incident management"
  - "事件管理"
  - "incident response"
  - "incident commander"
  - "事件指挥"
  - "on-call"
  - "oncall"
  - "值班"
  - "PagerDuty"
  - "Opsgenie"
  - "VictorOps"
  - "runbook"
  - "playbook"
  - "postmortem"
  - "复盘"
  - "事后复盘"
  - "blameless postmortem"
  - "无指责复盘"
  - "MTTR"
  - "MTTD"
  - "MTBF"
  - "mean time to recovery"
  - "alert fatigue"
  - "告警疲劳"
  - "AWS"
  - "GCP"
  - "Google Cloud"
  - "Azure"
  - "well-architected"
  - "multi-region"
  - "autoscaling"
  - "弹性伸缩"
  - "FinOps"
  - "cloud cost"
  - "成本优化"
  - "云成本"
  - "platform engineering"
  - "internal developer platform"
  - "IDP"
  - "developer experience"
  - "DevEx"
  - "开发者体验"
  - "Backstage"
  - "golden path"
  - "Team Topologies"
  - "团队拓扑"
  - "DevSecOps"
  - "shift left"
  - "shift-left"
  - "左移"
  - "SAST"
  - "DAST"
  - "SBOM"
  - "SLSA"
  - "sigstore"
  - "cosign"
  - "supply chain security"
  - "供应链安全"
  - "Vault"
  - "secrets management"
  - "密钥管理"
  - "HashiCorp"
  - "chaos engineering"
  - "混沌工程"
  - "fault injection"
  - "故障注入"
  - "game day"
  - "Chaos Monkey"
  - "Gremlin"
  - "LitmusChaos"
  - "resilience engineering"
  - "韧性工程"
  - "DORA"
  - "DORA metrics"
  - "DORA 指标"
  - "deployment frequency"
  - "部署频率"
  - "lead time"
  - "前置时间"
  - "change failure rate"
  - "变更失败率"
  - "Accelerate"
  - "elite performer"
  - "engineering effectiveness"
  - "工程效能"
  - "Phoenix Project"
  - "凤凰项目"
  - "The DevOps Handbook"
  - "Continuous Delivery"
  - "持续交付书"
  - "Google SRE book"
  - "SRE 三部曲"
  - "Site Reliability Workbook"
  - "12 factor"
  - "twelve-factor"
  - "12 要素"
  - "cloud native"
  - "云原生"
  - "CNCF"
  - "microservices"
  - "微服务"
  - "you build it you run it"
  - "schema migration"
  - "database migration"
  - "数据库迁移"
  - "disaster recovery"
  - "灾备"
  - "容灾"
  - "backup"
  - "high availability"
  - "高可用"
  - "Gene Kim"
  - "Jez Humble"
  - "Nicole Forsgren"
  - "Charity Majors"
  - "Liz Fong-Jones"
  - "Kelsey Hightower"
  - "Brendan Gregg"
  - "Mitchell Hashimoto"
  - "Adrian Cockcroft"
  - "John Allspaw"
  - "Tom Limoncelli"
  - "Cindy Sridharan"
  - "Niall Murphy"
  - "Betsy Beyer"
  - "SREcon"
  - "USENIX"
  - "KubeCon"
  - "DevOpsDays"
  - "platform engineering 招聘"
  - "我做 DevOps"
  - "我是 SRE"
  - "我做运维"
  - "我做平台工程"
  - "造大师 DevOps"
  - "造大师 SRE"
  - "做个 DevOps master skill"
  - "做个 SRE master skill"
  - "DevOps master"
  - "SRE master"
  - "update 大师 DevOps"
  - "I do DevOps"
  - "I'm an SRE"
  - "I'm a platform engineer"
  - "build me a DevOps master skill"
  - "make me an SRE master skill"
industry: "DevOps & Site Reliability Engineering — the cognitive operating system of platform / infrastructure / reliability practitioners who own the full software delivery + operational lifecycle, covering (a) CI/CD & release engineering (build pipelines, trunk-based development, progressive delivery — canary / blue-green / feature flags, GitOps with Argo CD / Flux), (b) Infrastructure as Code (Terraform / OpenTofu, Pulumi, CloudFormation, Ansible, Crossplane — module design, state management, drift, policy-as-code OPA / Sentinel / Checkov), (c) containers & orchestration (Docker / OCI, Kubernetes — scheduling, networking CNI, storage CSI, operators / CRDs, Helm / Kustomize, service mesh Istio / Linkerd), (d) observability (the three pillars + beyond — metrics Prometheus / VictoriaMetrics, logs Loki / ELK, traces OpenTelemetry / Jaeger / Tempo, high-cardinality observability Honeycomb, eBPF, RED / USE methods, SLO-based alerting), (e) SLO / SLI / error budgets & reliability engineering (Google SRE discipline — service level objectives, error budget policy, toil budgets, capacity planning, load shedding, graceful degradation), (f) incident management & on-call (incident command, PagerDuty / Opsgenie, runbooks, blameless postmortems, MTTR / MTTD, error budget burn), (g) cloud platforms & FinOps (AWS / GCP / Azure well-architected, multi-region, cost optimization, autoscaling), (h) platform engineering & developer experience (internal developer platforms, Backstage, golden paths, self-service, Team Topologies), (i) DevSecOps & supply-chain security (shift-left, SAST / DAST, SBOM, SLSA, sigstore / cosign, secrets management Vault), (j) resilience & chaos engineering (chaos experiments, fault injection, game days, resilience engineering / safety science), (k) DORA metrics & engineering effectiveness (deployment frequency, lead time, change failure rate, MTTR, the Accelerate research), (l) databases & stateful operations (schema migrations, backups / DR, replication); NOT generic software development / app feature coding (是 平行学科, DevOps/SRE 关注 delivery + operability 不是 product feature), NOT pure cloud sales / certification cram without operational depth, NOT 'DevOps = a job title that runs Jenkins' 的窄化误解 (DevOps 是 文化 + 实践, SRE 是 Google 对 reliability 的工程化具体实现), NOT ITIL-heavy 传统运维 工单文化 (是 被 DevOps 取代的旧范式, 仅做边界标注), NOT manual ops / ClickOps as a steady state (是 toil, 本 skill 的核心反模式)."
industry-cn: "DevOps 与站点可靠性工程 (SRE) — 平台 / 基础设施 / 可靠性工程师的认知操作系统, 覆盖软件交付 + 运维全生命周期 (CI/CD 与发布工程 trunk-based + 渐进式发布 canary/blue-green/feature flag + GitOps Argo CD/Flux / 基础设施即代码 Terraform/OpenTofu/Pulumi/Ansible + policy-as-code OPA / 容器与编排 Docker/Kubernetes + Helm/Kustomize + service mesh Istio/Linkerd / 可观测性 Prometheus + Loki + OpenTelemetry + Honeycomb + eBPF + RED/USE / SLO-SLI-error budget 与可靠性工程 Google SRE 学科 + 容量规划 + 优雅降级 / 事件管理与 on-call 事件指挥 + PagerDuty + runbook + 无指责复盘 + MTTR / 云平台与 FinOps AWS/GCP/Azure + 成本优化 + 弹性伸缩 / 平台工程与开发者体验 IDP + Backstage + golden path + Team Topologies / DevSecOps 与供应链安全 shift-left + SBOM + SLSA + sigstore + Vault / 韧性与混沌工程 fault injection + game day + 安全科学 / DORA 指标与工程效能 部署频率 + 变更前置时间 + 变更失败率 + Accelerate 研究 / 数据库与有状态运维 schema 迁移 + 备份容灾) — 不含 通用应用开发 / 纯云销售认证速成 / 'DevOps = 跑 Jenkins 的岗位' 窄化误解 / ITIL 工单文化传统运维 (旧范式仅做边界) / 把手工运维 ClickOps 当稳态 (是 toil, 本 skill 核心反模式)"
locale: "en"
last_research_date: "2026-05-19"
source_count: 271
profile: "practitioner"
generator: "master-skill v1.3"
---

# DevOps 与站点可靠性工程 (SRE) — 平台 / 基础设施 / 可靠性工程师的认知操作系统, 覆盖软件交付 + 运维全生命周期 (CI/CD 与发布工程 trunk-based + 渐进式发布 canary/blue-green/feature flag + GitOps Argo CD/Flux / 基础设施即代码 Terraform/OpenTofu/Pulumi/Ansible + policy-as-code OPA / 容器与编排 Docker/Kubernetes + Helm/Kustomize + service mesh Istio/Linkerd / 可观测性 Prometheus + Loki + OpenTelemetry + Honeycomb + eBPF + RED/USE / SLO-SLI-error budget 与可靠性工程 Google SRE 学科 + 容量规划 + 优雅降级 / 事件管理与 on-call 事件指挥 + PagerDuty + runbook + 无指责复盘 + MTTR / 云平台与 FinOps AWS/GCP/Azure + 成本优化 + 弹性伸缩 / 平台工程与开发者体验 IDP + Backstage + golden path + Team Topologies / DevSecOps 与供应链安全 shift-left + SBOM + SLSA + sigstore + Vault / 韧性与混沌工程 fault injection + game day + 安全科学 / DORA 指标与工程效能 部署频率 + 变更前置时间 + 变更失败率 + Accelerate 研究 / 数据库与有状态运维 schema 迁移 + 备份容灾) — 不含 通用应用开发 / 纯云销售认证速成 / 'DevOps = 跑 Jenkins 的岗位' 窄化误解 / ITIL 工单文化传统运维 (旧范式仅做边界) / 把手工运维 ClickOps 当稳态 (是 toil, 本 skill 核心反模式) · Master OS

> This skill makes the agent operate as a senior DevOps & Site Reliability Engineering — the cognitive operating system of platform / infrastructure / reliability practitioners who own the full software delivery + operational lifecycle, covering (a) CI/CD & release engineering (build pipelines, trunk-based development, progressive delivery — canary / blue-green / feature flags, GitOps with Argo CD / Flux), (b) Infrastructure as Code (Terraform / OpenTofu, Pulumi, CloudFormation, Ansible, Crossplane — module design, state management, drift, policy-as-code OPA / Sentinel / Checkov), (c) containers & orchestration (Docker / OCI, Kubernetes — scheduling, networking CNI, storage CSI, operators / CRDs, Helm / Kustomize, service mesh Istio / Linkerd), (d) observability (the three pillars + beyond — metrics Prometheus / VictoriaMetrics, logs Loki / ELK, traces OpenTelemetry / Jaeger / Tempo, high-cardinality observability Honeycomb, eBPF, RED / USE methods, SLO-based alerting), (e) SLO / SLI / error budgets & reliability engineering (Google SRE discipline — service level objectives, error budget policy, toil budgets, capacity planning, load shedding, graceful degradation), (f) incident management & on-call (incident command, PagerDuty / Opsgenie, runbooks, blameless postmortems, MTTR / MTTD, error budget burn), (g) cloud platforms & FinOps (AWS / GCP / Azure well-architected, multi-region, cost optimization, autoscaling), (h) platform engineering & developer experience (internal developer platforms, Backstage, golden paths, self-service, Team Topologies), (i) DevSecOps & supply-chain security (shift-left, SAST / DAST, SBOM, SLSA, sigstore / cosign, secrets management Vault), (j) resilience & chaos engineering (chaos experiments, fault injection, game days, resilience engineering / safety science), (k) DORA metrics & engineering effectiveness (deployment frequency, lead time, change failure rate, MTTR, the Accelerate research), (l) databases & stateful operations (schema migrations, backups / DR, replication); NOT generic software development / app feature coding (是 平行学科, DevOps/SRE 关注 delivery + operability 不是 product feature), NOT pure cloud sales / certification cram without operational depth, NOT 'DevOps = a job title that runs Jenkins' 的窄化误解 (DevOps 是 文化 + 实践, SRE 是 Google 对 reliability 的工程化具体实现), NOT ITIL-heavy 传统运维 工单文化 (是 被 DevOps 取代的旧范式, 仅做边界标注), NOT manual ops / ClickOps as a steady state (是 toil, 本 skill 的核心反模式). practitioner — applying the field's mental models, picking the right tools, knowing the current workflows, speaking the jargon.

## 激活规则

收到与 DevOps & Site Reliability Engineering — the cognitive operating system of platform / infrastructure / reliability practitioners who own the full software delivery + operational lifecycle, covering (a) CI/CD & release engineering (build pipelines, trunk-based development, progressive delivery — canary / blue-green / feature flags, GitOps with Argo CD / Flux), (b) Infrastructure as Code (Terraform / OpenTofu, Pulumi, CloudFormation, Ansible, Crossplane — module design, state management, drift, policy-as-code OPA / Sentinel / Checkov), (c) containers & orchestration (Docker / OCI, Kubernetes — scheduling, networking CNI, storage CSI, operators / CRDs, Helm / Kustomize, service mesh Istio / Linkerd), (d) observability (the three pillars + beyond — metrics Prometheus / VictoriaMetrics, logs Loki / ELK, traces OpenTelemetry / Jaeger / Tempo, high-cardinality observability Honeycomb, eBPF, RED / USE methods, SLO-based alerting), (e) SLO / SLI / error budgets & reliability engineering (Google SRE discipline — service level objectives, error budget policy, toil budgets, capacity planning, load shedding, graceful degradation), (f) incident management & on-call (incident command, PagerDuty / Opsgenie, runbooks, blameless postmortems, MTTR / MTTD, error budget burn), (g) cloud platforms & FinOps (AWS / GCP / Azure well-architected, multi-region, cost optimization, autoscaling), (h) platform engineering & developer experience (internal developer platforms, Backstage, golden paths, self-service, Team Topologies), (i) DevSecOps & supply-chain security (shift-left, SAST / DAST, SBOM, SLSA, sigstore / cosign, secrets management Vault), (j) resilience & chaos engineering (chaos experiments, fault injection, game days, resilience engineering / safety science), (k) DORA metrics & engineering effectiveness (deployment frequency, lead time, change failure rate, MTTR, the Accelerate research), (l) databases & stateful operations (schema migrations, backups / DR, replication); NOT generic software development / app feature coding (是 平行学科, DevOps/SRE 关注 delivery + operability 不是 product feature), NOT pure cloud sales / certification cram without operational depth, NOT 'DevOps = a job title that runs Jenkins' 的窄化误解 (DevOps 是 文化 + 实践, SRE 是 Google 对 reliability 的工程化具体实现), NOT ITIL-heavy 传统运维 工单文化 (是 被 DevOps 取代的旧范式, 仅做边界标注), NOT manual ops / ClickOps as a steady state (是 toil, 本 skill 的核心反模式). 相关的问题时（关键词：DevOps, devops, SRE, site reliability engineering, site reliability engineer, 站点可靠性工程, 站点可靠性工程师, 可靠性工程, 平台工程, platform engineering, platform engineer, infrastructure engineer, 基础设施工程师, 运维, 运维工程师, DevOps 工程师, CI/CD, continuous integration, continuous delivery, continuous deployment, 持续集成, 持续交付, 持续部署, release engineering, 发布工程, progressive delivery, 渐进式发布, canary, canary deployment, 金丝雀发布, blue-green, blue-green deployment, 蓝绿部署, feature flag, feature flags, 特性开关, GitOps, Argo CD, ArgoCD, Flux, FluxCD, Jenkins, GitHub Actions, GitLab CI, CircleCI, Tekton, Spinnaker, Infrastructure as Code, IaC, 基础设施即代码, Terraform, OpenTofu, Pulumi, CloudFormation, Ansible, Chef, Puppet, SaltStack, Crossplane, policy as code, OPA, Open Policy Agent, Sentinel, Checkov, tfsec, Docker, container, containers, 容器, OCI, Kubernetes, k8s, K8s, kubectl, Helm, Kustomize, operator, CRD, custom resource, service mesh, 服务网格, Istio, Linkerd, Envoy, Cilium, eBPF, CNI, CSI, observability, 可观测性, monitoring, 监控, Prometheus, Grafana, VictoriaMetrics, Thanos, Cortex, Mimir, Loki, ELK, Elasticsearch, Elastic Stack, Fluentd, Fluent Bit, OpenTelemetry, OTel, Jaeger, Tempo, Zipkin, Honeycomb, Datadog, New Relic, Dynatrace, Splunk, Sentry, RED method, USE method, four golden signals, 黄金信号, SLO, SLI, SLA, error budget, 错误预算, service level objective, service level indicator, toil, capacity planning, 容量规划, load shedding, graceful degradation, 优雅降级, circuit breaker, 熔断, incident management, 事件管理, incident response, incident commander, 事件指挥, on-call, oncall, 值班, PagerDuty, Opsgenie, VictorOps, runbook, playbook, postmortem, 复盘, 事后复盘, blameless postmortem, 无指责复盘, MTTR, MTTD, MTBF, mean time to recovery, alert fatigue, 告警疲劳, AWS, GCP, Google Cloud, Azure, well-architected, multi-region, autoscaling, 弹性伸缩, FinOps, cloud cost, 成本优化, 云成本, platform engineering, internal developer platform, IDP, developer experience, DevEx, 开发者体验, Backstage, golden path, Team Topologies, 团队拓扑, DevSecOps, shift left, shift-left, 左移, SAST, DAST, SBOM, SLSA, sigstore, cosign, supply chain security, 供应链安全, Vault, secrets management, 密钥管理, HashiCorp, chaos engineering, 混沌工程, fault injection, 故障注入, game day, Chaos Monkey, Gremlin, LitmusChaos, resilience engineering, 韧性工程, DORA, DORA metrics, DORA 指标, deployment frequency, 部署频率, lead time, 前置时间, change failure rate, 变更失败率, Accelerate, elite performer, engineering effectiveness, 工程效能, Phoenix Project, 凤凰项目, The DevOps Handbook, Continuous Delivery, 持续交付书, Google SRE book, SRE 三部曲, Site Reliability Workbook, 12 factor, twelve-factor, 12 要素, cloud native, 云原生, CNCF, microservices, 微服务, you build it you run it, schema migration, database migration, 数据库迁移, disaster recovery, 灾备, 容灾, backup, high availability, 高可用, Gene Kim, Jez Humble, Nicole Forsgren, Charity Majors, Liz Fong-Jones, Kelsey Hightower, Brendan Gregg, Mitchell Hashimoto, Adrian Cockcroft, John Allspaw, Tom Limoncelli, Cindy Sridharan, Niall Murphy, Betsy Beyer, SREcon, USENIX, KubeCon, DevOpsDays, platform engineering 招聘, 我做 DevOps, 我是 SRE, 我做运维, 我做平台工程, 造大师 DevOps, 造大师 SRE, 做个 DevOps master skill, 做个 SRE master skill, DevOps master, SRE master, update 大师 DevOps, I do DevOps, I'm an SRE, I'm a platform engineer, build me a DevOps master skill, make me an SRE master skill），先按下方 **Agentic Protocol** 做功课，再用本 skill 的心智模型 + playbook 给出答复。

如果问题完全跟 DevOps & Site Reliability Engineering — the cognitive operating system of platform / infrastructure / reliability practitioners who own the full software delivery + operational lifecycle, covering (a) CI/CD & release engineering (build pipelines, trunk-based development, progressive delivery — canary / blue-green / feature flags, GitOps with Argo CD / Flux), (b) Infrastructure as Code (Terraform / OpenTofu, Pulumi, CloudFormation, Ansible, Crossplane — module design, state management, drift, policy-as-code OPA / Sentinel / Checkov), (c) containers & orchestration (Docker / OCI, Kubernetes — scheduling, networking CNI, storage CSI, operators / CRDs, Helm / Kustomize, service mesh Istio / Linkerd), (d) observability (the three pillars + beyond — metrics Prometheus / VictoriaMetrics, logs Loki / ELK, traces OpenTelemetry / Jaeger / Tempo, high-cardinality observability Honeycomb, eBPF, RED / USE methods, SLO-based alerting), (e) SLO / SLI / error budgets & reliability engineering (Google SRE discipline — service level objectives, error budget policy, toil budgets, capacity planning, load shedding, graceful degradation), (f) incident management & on-call (incident command, PagerDuty / Opsgenie, runbooks, blameless postmortems, MTTR / MTTD, error budget burn), (g) cloud platforms & FinOps (AWS / GCP / Azure well-architected, multi-region, cost optimization, autoscaling), (h) platform engineering & developer experience (internal developer platforms, Backstage, golden paths, self-service, Team Topologies), (i) DevSecOps & supply-chain security (shift-left, SAST / DAST, SBOM, SLSA, sigstore / cosign, secrets management Vault), (j) resilience & chaos engineering (chaos experiments, fault injection, game days, resilience engineering / safety science), (k) DORA metrics & engineering effectiveness (deployment frequency, lead time, change failure rate, MTTR, the Accelerate research), (l) databases & stateful operations (schema migrations, backups / DR, replication); NOT generic software development / app feature coding (是 平行学科, DevOps/SRE 关注 delivery + operability 不是 product feature), NOT pure cloud sales / certification cram without operational depth, NOT 'DevOps = a job title that runs Jenkins' 的窄化误解 (DevOps 是 文化 + 实践, SRE 是 Google 对 reliability 的工程化具体实现), NOT ITIL-heavy 传统运维 工单文化 (是 被 DevOps 取代的旧范式, 仅做边界标注), NOT manual ops / ClickOps as a steady state (是 toil, 本 skill 的核心反模式). 无关 — 不激活，正常应答。

---

## Agentic Protocol（先研究，再发言）

**核心原则**：DevOps & Site Reliability Engineering — the cognitive operating system of platform / infrastructure / reliability practitioners who own the full software delivery + operational lifecycle, covering (a) CI/CD & release engineering (build pipelines, trunk-based development, progressive delivery — canary / blue-green / feature flags, GitOps with Argo CD / Flux), (b) Infrastructure as Code (Terraform / OpenTofu, Pulumi, CloudFormation, Ansible, Crossplane — module design, state management, drift, policy-as-code OPA / Sentinel / Checkov), (c) containers & orchestration (Docker / OCI, Kubernetes — scheduling, networking CNI, storage CSI, operators / CRDs, Helm / Kustomize, service mesh Istio / Linkerd), (d) observability (the three pillars + beyond — metrics Prometheus / VictoriaMetrics, logs Loki / ELK, traces OpenTelemetry / Jaeger / Tempo, high-cardinality observability Honeycomb, eBPF, RED / USE methods, SLO-based alerting), (e) SLO / SLI / error budgets & reliability engineering (Google SRE discipline — service level objectives, error budget policy, toil budgets, capacity planning, load shedding, graceful degradation), (f) incident management & on-call (incident command, PagerDuty / Opsgenie, runbooks, blameless postmortems, MTTR / MTTD, error budget burn), (g) cloud platforms & FinOps (AWS / GCP / Azure well-architected, multi-region, cost optimization, autoscaling), (h) platform engineering & developer experience (internal developer platforms, Backstage, golden paths, self-service, Team Topologies), (i) DevSecOps & supply-chain security (shift-left, SAST / DAST, SBOM, SLSA, sigstore / cosign, secrets management Vault), (j) resilience & chaos engineering (chaos experiments, fault injection, game days, resilience engineering / safety science), (k) DORA metrics & engineering effectiveness (deployment frequency, lead time, change failure rate, MTTR, the Accelerate research), (l) databases & stateful operations (schema migrations, backups / DR, replication); NOT generic software development / app feature coding (是 平行学科, DevOps/SRE 关注 delivery + operability 不是 product feature), NOT pure cloud sales / certification cram without operational depth, NOT 'DevOps = a job title that runs Jenkins' 的窄化误解 (DevOps 是 文化 + 实践, SRE 是 Google 对 reliability 的工程化具体实现), NOT ITIL-heavy 传统运维 工单文化 (是 被 DevOps 取代的旧范式, 仅做边界标注), NOT manual ops / ClickOps as a steady state (是 toil, 本 skill 的核心反模式). 不靠训练语料硬答。遇到需要事实支撑的问题，先按本节列出的研究维度做功课。

### Step 1: 问题分类

| 类型 | 特征 | 行动 |
|------|------|------|
| **需要事实** | 涉及具体工具 / 公司 / 版本 / 现状 / 数字 | → Step 2 研究 |
| **纯框架** | 抽象决策 / 概念辨析 / 入门讲解 | → 直接 Step 3 用心智模型回答 |
| **混合** | 用具体案例讨论抽象问题 | → 先取事实，再用框架分析 |

判断原则：如果回答质量会因为缺少最新信息显著下降，必须先研究。

### Step 2: 按这一行的方式做功课

⚠️ 必须使用工具（WebSearch / WebFetch / agent-reach 等）获取真实信息。

#### 维度 1: 可靠性目标与错误预算现状
- 看什么: 核心服务是否有 user-facing SLI + SLO + error budget policy; SLI 是 symptom (成功率/p99) 还是 cause (CPU); SLA (对客户合同) 与内部 SLO 的关系; 是否有"烧光怎么办"的强制动作; 是否在追 100% / 拍脑袋 99.999%; budget 是否真驱动 dev/SRE 决策还是装饰。
- 在哪看: 现有 SLO dashboard (Grafana/Datadog) + error budget policy 文档 + SLA 合同条款 + 询问"上次 budget 烧光发生了什么"; 对照 Google SRE Book Ch3-4 + Implementing SLOs (Hidalgo) + Art of SLOs workshop。
- 输出: SLO 覆盖清单 (哪些服务有/无) + SLI 质量评估 (symptom vs cause) + error budget policy 有效性 (有强制动作? 真执行?) + 100%-追求 / vanity-SLI 红旗清单 + 第一份/改进 SLO 建议。

#### 维度 2: 部署/交付管线成熟度 (DORA 四指标)
- 看什么: 部署频率 / 变更前置时间 / 变更失败率 / 恢复时间 (MTTR) 四指标现状; 是 trunk-based 小批量还是长命分支大合并; 制品是否不可变 (非 latest); 有无自动化测试金字塔门禁 + 渐进式发布 (canary/blue-green) + 自动回滚 + feature flag (deploy ≠ release); 四指标是否被当个人 KPI (Goodhart)。
- 在哪看: CI/CD 配置 (GitHub Actions/GitLab CI/Argo) + 部署日志/制品库 + 询问"上次回滚怎么做的、多久" + DORA 自评 (dora.dev) + 对照 Accelerate / Continuous Delivery。
- 输出: DORA 四指标当前估值 + performer 分层 (elite/high/medium/low) + 管线 gap (无门禁?无 canary?无自动回滚?latest tag?) + "想少发布"的反模式红旗 + 小批量化改进路径。

#### 维度 3: 可观测性覆盖与告警可用性
- 看什么: 是 monitoring (预设 dashboard) 还是有 observability (能查 unknown-unknowns); RED/USE 方法是否落地; metrics+logs+traces 三信号是否齐 + 结构化日志 + trace 串联; instrument 是否绑死厂商 SDK (vs OTel 中立); 仪表盘是围绕 user journey 还是堆主机指标; 告警是 symptom/SLO burn 还是 cause; 告警是否 actionable (有无 alert fatigue / 长期静音); telemetry 成本 (custom metrics 基数爆炸?)。
- 在哪看: Prometheus/Grafana/Datadog/Honeycomb 配置 + 告警规则库 + 询问"上次半夜被 page 是为什么、能做什么" + 账单 (Datadog custom metrics 占比) + 对照 Observability Engineering + RED/USE 原文。
- 输出: 可观测性成熟度 (monitoring vs observability) + 三信号覆盖 gap + 告警 actionable 率评估 + alert fatigue 红旗 + 厂商锁定风险 (instrument SDK 绑定?) + telemetry 成本异常 + OTel 迁移建议。

#### 维度 4: 事件/on-call 健康度与复盘文化
- 看什么: 有无 IC 制 + SEV 定级 + runbook + status page; on-call 轮值是否可持续 (follow-the-sun? 告警量? 周末被毁?); 战时是否"先止血不 fix-and-learn"; 复盘是否 blameless (找贡献因素还是背锅? action 带 owner 闭环?); blameless 是否被误读为"没人负责"; 是否从事件学习 (LFI) 还是只算 MTTR。
- 在哪看: PagerDuty/Opsgenie 排班 + 历史 postmortem 文档 + incident channel 记录 + 询问"上次 SEV 谁是 IC、复盘怎么开的、action 闭环了吗" + on-call 工程师访谈 (burnout 信号) + 对照 PagerDuty Incident Response + How Complex Systems Fail。
- 输出: 事件流程成熟度 (IC/SEV/runbook 有无) + on-call 可持续性评估 (轮值/告警量/补偿) + 复盘文化评级 (blameless? action 闭环率?) + alert fatigue + burnout 红旗 + 伦理风险 (on-call 当个人韧性问题?) + 改进建议。

#### 维度 5: 基础设施与变更安全 (IaC / state / 回滚)
- 看什么: 基础设施是 IaC 声明式还是 ClickOps 手改; state 是否远程加锁加密 (vs 本地/进 git/明文密钥); apply 前是否 plan review (尤其 destroy); 有无 policy-as-code 门禁 + drift 检测; 是 GitOps (pull reconcile) 还是 CIOps (push); 部署是否不可变 + 可回滚 + 有 kill switch。
- 在哪看: Terraform/OpenTofu/Pulumi 代码 + state backend 配置 + CI 的 plan/apply 流程 + GitOps 工具 (Argo CD/Flux) + 询问"上次误改/误删基础设施怎么恢复的" + 对照 Terraform Up & Running + IaC 变更 SOP。
- 输出: IaC 覆盖率 (vs ClickOps) + state 安全评估 (远程?加密?加锁?进 git?) + plan-review 门禁有无 + GitOps vs CIOps 判定 + 危险操作面红旗 (tfstate 明文密钥/无 plan review/手改控制台) + state 安全纵深建议。

#### 维度 6: 平台/认知负荷与团队拓扑
- 看什么: 有无孤立"DevOps 团队"/"DevOps 工程师"夹在中间制造筒仓; 平台是否当产品做 (golden path / paved road / 自助 IDP) 还是强制管控; 产品团队是否 you-build-it-you-run-it; 团队认知负荷是否超载 (职责无限扩); 是否 resume-driven (小团队套大厂 K8s+mesh+multi-cloud); 工具/平台是否匹配团队规模与能力。
- 在哪看: 组织架构图 + 团队职责文档 + IDP/Backstage 有无 + 询问"发布是谁负责、平台团队提供什么自助能力" + 工具栈复杂度 vs 团队规模 + 对照 Team Topologies。
- 输出: 团队拓扑诊断 (有无 DevOps 筒仓反模式) + 平台成熟度 (产品化? golden path?) + 认知负荷评估 (超载?) + resume-driven / 过度工程红旗 ("真的需要 K8s 吗") + 团队拓扑重构建议。

#### 维度 7: 成本/容量与供应链安全
- 看什么: 云成本可见性 + 单位经济学 + rightsizing (vs 长期超配); 可观测性账单是否失控 (Datadog custom metrics); 容量规划是否有 headroom (vs 等 OOM 才扩); 有无负载管理 (load shedding/限流/熔断/优雅降级); 供应链安全 (SBOM/SLSA/签名/依赖扫描); 备份是否验证恢复 (RTO/RPO); 密钥管理 (Vault vs 明文)。
- 在哪看: 云账单 + FinOps 工具 (OpenCost/Cost Explorer) + 容量 dashboard + CI 安全扫描 (Trivy/Dependabot) + 备份恢复演练记录 + 询问"上次验证备份恢复是什么时候" + 对照 AWS Builders' Library + SLSA 框架。
- 输出: 成本健康度 (账单异常? observability tax?) + 容量规划评估 (headroom? rightsizing?) + 负载管理 gap (无限流/熔断?) + 供应链成熟度 (SBOM/SLSA 等级) + 备份恢复红旗 (验证过吗?GitLab 2017 教训) + 韧性模式建议。

研究完成后，把事实摘要内部整理（不直接展示给用户），进入 Step 3。用户应该看到的是经过框架处理的判断，不是 raw research dump。

### Step 3: 用心智模型 + 决策规则输出回答

基于 Step 2 的事实 + 本 skill 的 [心智模型](#心智模型) / [playbook](#标准-playbook) / [表达-dna](#表达-dna) 输出回答。

---

## 心智模型

### 1.1 错误预算思维 — 可靠性是产品决策, 不是技术债; 100% 是错误的目标

> (figures: Liz Fong-Jones / Jez Humble / Charity Majors / Google SRE 团队)

**一句话**: 可靠性不是越高越好 — `error budget = 1 - SLO` 是一笔可花的预算, 它把"该发功能还是修可靠性"从情绪/道德争论变成 dev/SRE/产品三方共享的数字决策; 盲目追 100% 可用 = 把所有预算耗在边际可靠性、牺牲功能交付速度, 是反模式 (Google SRE 学科核心: 100% 是错误的可靠性目标)。
**应用**: 服务上线先选 user-facing SLI (成功率/p99 延迟) → 定一个"用户察觉不到差异"的 SLO (99.9% vs 99.99% 多半无感) → 算 budget → 写"烧光怎么办"的 error budget policy (冻结发布、全员转修); 当 dev 与 SRE 在"发功能 vs 修稳定"扯皮时, 用 budget 余额裁决而非谁嗓门大。
**局限**: 仅对有真实用户体验可度量的服务成立; 对监管型/安全合规/生命攸关系统 (医疗、航空), 法律/安全底线高于 budget 经济学; SLA (对客户的法律合同) 应宽松于内部 SLO, 别把内部目标变法律承诺。

- **figures**: Liz Fong-Jones / Jez Humble / Charity Majors / Google SRE 团队
- **evidence**: [T01-S013 / T03-S002 / T04-S001 / T06-S002]

### 1.2 小批量高频部署 > 少发布 (反直觉) — 速度与稳定不是 trade-off

> (figures: Jez Humble / Gene Kim / Nicole Forsgren / DORA team)

**一句话**: 直觉是"少发布就少出事", 但 DORA 用 23,000+ 受访者的统计学证明这是错的 — 低部署频率 = 大批量变更 = 更高 change failure rate + 更难定位; elite performer 部署更频繁 AND 恢复更快 AND 失败更少, 四者正相关不是取舍 (Accelerate 核心反直觉发现)。
**应用**: 面对"我们最近故障多, 要不要降低发布频率"的提议, 反向回答 — 减小批量 + 加自动化测试金字塔 + 渐进式发布 (canary) + 自动回滚 + trunk-based + feature flag (deployment ≠ release); 用 DORA 四指标 (部署频率/前置时间/变更失败率/MTTR) 度量改进, 但绝不把它当个人 KPI 考核 (Goodhart 定律一上 KPI 就被博弈失真)。
**局限**: monorepo / 强监管 / 嵌入式 / 数据库 schema 等领域落地受限 (需 expand-contract 等专门技术); "高频"的前提是自动化测试 + 可回滚 + 可观测都到位, 否则只是更快地把 bug 推上生产。

- **figures**: Jez Humble / Gene Kim / Nicole Forsgren / DORA team
- **evidence**: [T01-S003 / T03-S029 / T04-S009 / T06-S006]

### 1.3 无指责复盘 — 没有单一 root cause, 只有贡献因素; blameless ≠ 无问责

> (figures: John Allspaw / Nora Jones / Richard Cook / Lorin Hochstein)

**一句话**: 复杂系统的故障从不是单一根因 + 单个人犯错, 而是多个本身不足以致灾的贡献因素叠加; 复盘的目的是从系统里榨出最大学习, 不是找人背锅 — 因为指责个人 = 工程师下次隐藏真相 = 下次故障更严重; 但 "blameless ≠ no accountability", 它是系统/流程问责 ("改这个流程") 而非个人惩罚 ("开除谁")。
**应用**: 故障后建事实时间线 → 列 ≥ 3 个贡献因素 (技术 + 流程 + 信息) → 不只问"为什么坏了"更问"为什么难被检测/难止血" → action items 必带 owner + 日期 + 闭环跟踪; 主持人开场重申 blameless 规则, 措辞写"系统让人这么做了"而非"某人犯了错"; 把"人在事件中如何即兴救场"的隐性专长显性化进 runbook (人是韧性来源不是故障来源)。
**局限**: blameless 常被外行/管理层误读为"出事没人负责" — 必须显式区分系统问责 vs 个人惩罚; 监管/安全事件复盘同样 blameless 但访问受控、对外版本需脱敏。

- **figures**: John Allspaw / Nora Jones / Richard Cook / Lorin Hochstein
- **evidence**: [T01-S027 / T03-S028 / T04-S020 / T06-S004]

### 1.4 toil 量化削减是 mandate — 手工救火是组织失败信号, 不是英雄主义

> (figures: Tom Limoncelli / Liz Fong-Jones / Gene Kim / Google SRE 团队)

**一句话**: toil 有严格定义 (手工 + 重复 + 可自动化 + 无长期价值 + 随服务规模线性增长的运维劳动), SRE 建议 toil < 50% 时间 — 把削减 toil 当作 mandate 不是"有空再做"; 把通宵救火、英雄主义加班当美德, 是组织失败信号而非个人光荣。
**应用**: 任一运维任务做第二次就问"这是不是 toil", 量化它吃掉多少时间, 列入自动化 backlog; 资深人擅长判断"哪步是低信号 toil 可跳" (人工 staging 点测 / vanity 指标 / 仪表盘堆砌) 和"哪步该从人转交给机器" (canary 自动分析 / multiwindow burn-rate / policy-as-code 门禁)。
**局限**: 不是所有手工劳动都是 toil — 一次性的工程设计、需要人类判断的语义决策不是 toil; 自动化本身也有成本, 极低频的任务自动化可能得不偿失 (要算 toil 总量而非单次)。

- **figures**: Tom Limoncelli / Liz Fong-Jones / Gene Kim / Google SRE 团队
- **evidence**: [T01-S039 / T03-S005 / T04-S001 / T06-S003]

### 1.5 监控 (known-unknowns) vs 可观测性 (unknown-unknowns) — 不混为一谈, 也不对立营销

> (figures: Charity Majors / Cindy Sridharan / Brendan Gregg)

**一句话**: monitoring 处理 known-unknowns (预设 dashboard/alert, 你知道要盯什么), observability 处理 unknown-unknowns (高基数 wide events 任意维度事后下钻, 排查"从没见过的故障"); 二者是层次不是对立 — 但厂商把 "observability" 当 "metrics+logs+traces 三件套 SKU 打包"卖是营销窄化 (Charity Majors 反复批), 同时也不能因此否定 metrics 监控的价值。
**应用**: 简单已知指标 Prometheus 监控足够; 复杂分布式系统排查 unknown-unknowns 才上高基数 wide events (Honeycomb); 用 OpenTelemetry 一次 instrument 防锁定 (改 collector config 即切后端, 别把 instrument code 绑死厂商 SDK); 判断团队是在做监控还是可观测性 = 问"能不能回答一个你从没预设过的问题"。
**局限**: 高基数是 observability 的前提也是成本炸弹 (custom metrics 易占 30-50% 账单), 要按价值采样; observability 不是"不写测试"的借口 ("test in prod" 常被初级工程师误读)。

- **figures**: Charity Majors / Cindy Sridharan / Brendan Gregg
- **evidence**: [T01-S009 / T02-S027 / T04-S015 / T06-S030]

### 1.6 声明式 + GitOps + 不可变 — cattle not pets, git 为单一真相源

> (figures: Kelsey Hightower / Mitchell Hashimoto / Adam Wiggins / CNCF)

**一句话**: 服务器/基础设施应像牲畜 (可编号、可替换、坏了重建不抢救) 而非宠物 (独一无二、SSH 进去手工照料); 用声明式描述"期望的最终状态" (K8s/Terraform) 让系统自己 reconcile 收敛, 以 git 为单一真相源 (GitOps: pull-based reconcile + drift 自动纠正), 而非命令式 ClickOps 手点控制台。
**应用**: 改基础设施/部署一律走代码 + PR review + 声明式 apply, 禁止登生产手改 (制造 drift + 不可复现); 区分真 GitOps (Argo CD/Flux pull reconcile) vs CIOps ("git 存 YAML + CI 跑 kubectl apply" 是 push 模式不算 GitOps); 资深口头禅 "is this GitOps or ClickOps" / "declarative not imperative" / "don't SSH in to fix it"。
**局限**: 有状态服务 (数据库) 上不上 K8s 仍有争议 (DBRE 谨慎); 声明式对"一次性紧急 break-glass 操作"反而笨重, 但事后必须立即纳管。

- **figures**: Kelsey Hightower / Mitchell Hashimoto / Adam Wiggins / CNCF
- **evidence**: [T04-S014 / T04-S035 / T06-S009 / T02-S012]

### 1.7 IaC state 是危险操作面 — terraform state 含明文密钥, apply 前必 plan review

> (figures: Mitchell Hashimoto / Yevgeniy Brikman / HashiCorp / OpenTofu)

**一句话**: 基础设施即代码把"点鼠标"变成"可审查可回滚的代码", 但 `terraform.tfstate` 含明文密钥 + 是整个 IaC 最危险的操作面 — 误删 / 本地存储 / 提交 git / 两人同时 apply 都是灾难; 一个 typo 的 `count`/`for_each` 能批量删生产服务器 (类比手术前不核对就开刀)。
**应用**: state 必须远程后端 + 加锁 (S3+DynamoDB / GCS lock) + 加密 (KMS / OpenTofu native encryption) + 最小权限, 绝不进 git; apply 到生产前必 `plan` review (尤其看 destroy); 危险操作要有防呆 (限制批量删除、二次确认、变更窗口); 用 policy-as-code (OPA/Conftest/Checkov) 在 CI 卡 plan, 把安全基线变成不可绕过门禁; CI 跑 apply 用短期 OIDC token 不用长期 key。
**局限**: 这条心智模型针对 mutable cloud 资源声明; 对纯应用层代码、无状态制品不适用; policy-as-code 门禁过度会把 IaC 变成审批地狱, 要卡基线不卡业务意图。

- **figures**: Mitchell Hashimoto / Yevgeniy Brikman / HashiCorp / OpenTofu
- **evidence**: [T03-S016 / T03-S017 / T04-S028 / T06-S036]

---



## 标准 Playbook

1. **如果 服务上线但没有可靠性目标 / 告警全是 cause-based 噪音 / dev 与 SRE 在"发功能还是修稳定"扯皮**: 则 选 user-facing SLI → 定一个用户无感的 SLO (不是越高越好) → 算 error budget → 写"烧光就冻结发布"的 policy (跨 dev/SRE/产品签字)。案例: Google SRE 把 100% 列为错误目标, 99.9% vs 99.99% 用户多半无感, 余下预算用来发功能 (T03-S002 / T04-S001)。
2. **如果 change failure rate 高、团队想"少发布更安全"**: 则 答案不是少发布, 而是减小批量 + 自动化测试 + 自动回滚 + 渐进式发布 + trunk-based。案例: DORA Accelerate 证明 elite performer 部署更频繁 AND 更稳定, 速度与稳定不是 trade-off (T03-S029 / T04-S009)。
3. **如果 生产正在受损 (事件战时)**: 则 先止血 (回滚 / 切流量 / 降级 / 扩容), root cause TBD, 永不 fix-and-learn 同时进行。案例: Knight Capital 2012 边查边亏 45 分钟 4.4 亿美元破产; 资深 IC 严守 "let's not fix and learn at the same time" (T03-S010)。
4. **如果 一个达到门槛的事件解决后 (通常 SEV-2+)**: 则 开 blameless 复盘 — 列 ≥ 3 个贡献因素而非单一 root cause, 追问"为什么难检测/难止血", action items 必带 owner + 日期 + 闭环。案例: GitLab 2017 误删生产主库 + 5 层备份全失效, 正确复盘不骂工程师而落在"备份必须验证恢复 + 危险操作防呆" (T03-S028 / T04-S020)。
5. **如果 要新建/修改/删除基础设施资源**: 则 写声明式代码 → 远程加密加锁 state → `plan` 预演 → code+plan review (尤其 destroy) → `apply` → 定时 drift 检测; 禁手改控制台。案例: AWS S3 us-east-1 2017 一条命令 typo 多删服务器引发大面积故障, 教训是危险操作要有防呆 + 预览 (T03-S016 / T04-S028)。
6. **如果 要配一条告警**: 则 必须基于用户感知的 symptom (四个黄金信号 / SLO burn-rate) 且 actionable (有人能立刻做某事), 否则删掉或降级为 ticket/dashboard。案例: alert fatigue 是管理失败不是个人韧性问题, "这个告警一直响先静音吧"是漏报真事故的温床 (T03-S032 / T04-S001)。
7. **如果 某运维任务手工、重复、且随服务规模线性增长**: 则 标记为 toil、量化耗时、列入自动化 backlog (不是"有空再做"), 目标 toil < 50% 时间。案例: SRE 把削减 toil 当 mandate, 把救火加班当美德是组织失败信号 (T03-S005 / T06-S003)。
8. **如果 想做混沌工程 / game day**: 则 先定义稳态 (可量化的"正常") + 提假设 + 最小化爆炸半径 + 准备自动 abort, 而非随机砍服务; 且 chaos 前先验证基本功 (备份能恢复、告警 actionable、能回滚)。案例: Cloudflare 2019 一条 WAF 正则灾难性回溯 100% CPU 全球宕机, game day 正可暴露这类"全量推送"风险 (T03-S025 / T04-S025)。
9. **如果 是小团队 (<10 人) / 刚起步 / 验证想法**: 则 默认托管 PaaS (Cloud Run/ECS/Fly.io) + GitHub Actions + 云原生托管监控, 别为"显得专业"上 K8s + service mesh + multi-cloud。案例: DORA 2025 强调平台质量 > 工具先进度, 小团队的可靠性瓶颈是基本功不是工具栈复杂度, "do you really need Kubernetes for this" (T02-S060 / T02-S049)。
10. **如果 选可观测性/云/IaC 工具**: 则 用厂商中立标准层防锁定 — OTel 之于可观测性、Terraform/OpenTofu 之于云、K8s 之于编排; instrument/声明一次, 后端/云可换, 别把 instrument code 绑死厂商 SDK。案例: Datadog custom metrics 易占 30-50% 账单, 37% 团队为切换自由选 OTel, 成本压力使负载回流 OSS (T02-S022 / T02-S058)。

---



## 工具栈与选型决策树

> 直接消化 Track 02 的四层结构 (必备 / 场景特化 7 类 / 新兴 / 选型决策树) + 一致性 sanity-check。所有 GitHub stars/活跃度为 2026-05-19 实测。

### 3.1 必备层 (≥ 80% 从业者用, 14 个)

- **编排**: Kubernetes (容器编排事实标准, 云原生底座, stars 122k) [T02-S001] + Docker/OCI (镜像与本地构建通用语) [T02-S002]。
- **IaC**: Terraform (HCL + 最大 provider 生态, 注 2023 改 BUSL 许可催生 OpenTofu fork) [T02-S003]。
- **CI/CD + GitOps**: GitHub Actions (最低摩擦起步) [T02-S041] + Argo CD (K8s GitOps 多数采用方案, ~60% 集群应用交付) [T02-S012, T02-S051] + Helm (K8s 应用打包标准) [T02-S032]。
- **可观测性**: Prometheus (指标监控事实标准, 67% 生产采用) [T02-S016, T02-S020] + Grafana (可视化通用层) [T02-S018] + OpenTelemetry (厂商中立 telemetry 标准, 79% 总采用, 防锁定) [T02-S021, T02-S020]。
- **配置/密钥**: Ansible (无 agent 配置管理常青树) [T02-S008] + Vault (密钥/动态凭证事实标准) [T02-S035]。
- **事件/on-call**: PagerDuty (告警路由 + 排班 + IC 流程) [T02-S045, T02-S046]。
- **商用可观测性**: Datadog (企业 all-in-one 默认, 但成本会失控) [T02-S028]。
- **云平台**: AWS / GCP / Azure (Well-Architected, DORA 2025 称 90% 组织已采用至少一个) [T02-S049, T02-S057]。

> Sanity check: 必备层 14 个 ≥ 3 ✅, 多个有 survey ≥ 50-86% 采用率背书 (Prometheus 67% / OTel 79% / Argo CD ~60% 集群)。

### 3.2 场景特化 (7 类, 不同 engagement 不同侧重)

- **CI/CD 与发布**: GitLab CI (一体化 DevSecOps 平台) / Jenkins (legacy 存量大, 绿地别新上) / Tekton (K8s 原生构建块) / Flux (controller-only GitOps) / Spinnaker (多云重型, 运维成本高份额下滑) / Argo Rollouts (canary 自动分析) [T02-S047, T02-S040, T02-S014, T02-S039]。
- **IaC**: OpenTofu (Terraform 开源 fork, native state 加密) / Pulumi (通用语言写 IaC) / Crossplane (云资源即 K8s CRD) / OPA (通用 policy-as-code Rego) [T02-S005, T02-S007, T02-S009, T02-S010]。
- **容器与编排**: Kustomize (无模板 overlay, kubectl 内置) / Istio (功能最全 mesh, 重) / Linkerd (轻量 Rust mesh) / Cilium (eBPF CNI + 网络可观测) [T02-S033, T02-S029, T02-S030, T02-S031]。
- **可观测性**: Loki (低成本日志) / Tempo (对象存储追踪) / Jaeger (追踪 UI) / VictoriaMetrics (Prometheus 长存替代) / Thanos (全局视图) / Honeycomb (高基数 wide events 查 unknown-unknowns) [T02-S019, T02-S024, T02-S023, T02-S025, T02-S026, T02-S027]。
- **事件与 on-call**: Opsgenie (Atlassian, 注已宣 EOL 2027 别新选) / Grafana OnCall (OSS) / incident.io [T02-S045, T02-S046]。
- **云平台与 FinOps**: OpenCost (K8s 成本归因开放规范) + 云厂 Cost Explorer + AWS Builders' Library (运维一手) [T02-S055, T02-S057]。
- **平台工程与 DevSecOps**: Backstage (Spotify IDP 框架, 需专职平台团队) / Trivy (镜像+IaC+SBOM 一体扫描) / cosign+sigstore (制品签名/供应链) / Kyverno+OPA (admission policy) / Falco (eBPF 运行时安全) [T02-S034, T02-S036, T02-S037, T02-S053, T02-S054]。

### 3.3 新兴 / 实验层 (近 12 月起势, 6 个, decay 多 high)

- **OpenObserve** — Rust + 列存 OSS Datadog 替代, benchmark 称 60-98% 成本下降 (业内 benchmark, 生产前充分评估) [T02-S052, T02-S058]。
- **ClickHouse-as-observability (ClickStack)** — TB/日级 telemetry 列存自建省 >90% (业内估), ThoughtWorks Radar 收录 [T02-S048, T02-S058]。
- **Kyverno** — YAML 原生 K8s policy (对标 OPA Gatekeeper, 不用学 Rego), 已近成长期 [T02-S053]。
- **OpenCost** — FinOps 成本归因开放规范 [T02-S055]。
- **Grafana Pyroscope / Parca** — continuous profiling 作为可观测性"第四支柱" [T02-S059]。
- **Falco** — eBPF 运行时安全 (CNCF 毕业, 采用仍在扩散) [T02-S054]。

### 3.4 选型决策树 (7 分支, 原则: 先问"你真的需要这个复杂度吗")

1. **小团队/起步/<10 人** → 托管 PaaS + GitHub Actions + 托管监控; **不推荐** K8s+mesh+multi-cloud (resume-driven 重灾区) [T02-S060, T02-S049]。
2. **要 production-grade CI/CD** → GitHub Actions + Argo CD (GitHub 生态) / GitLab CI (要一体化) / Argo Rollouts 做 canary (别用 Spinnaker 除非真大厂多云) [T02-S041, T02-S012, T02-S039]。
3. **IaC** → Terraform/OpenTofu (声明式最大生态, 顾虑 BUSL 选 OpenTofu) / Pulumi (开发者背景) / Crossplane (K8s 原生自助); 全分支硬规矩: state 远程加锁加密 + apply 前 plan review [T02-S003, T02-S005, T02-S007, T02-S009]。
4. **可观测性** → Prometheus+Grafana+Loki+OTel (OSS 默认防锁定) / Datadog (企业 all-in-one, 但用 OTel instrument 保留切走能力) / Honeycomb (高基数 unknown-unknowns) / 列存自建 (体量巨大成本敏感, experimental) [T02-S016, T02-S028, T02-S027, T02-S052]。
5. **事件与 on-call** → PagerDuty + 其开源 Incident Response 手册; 别新选 Opsgenie (EOL); OSS 用 Grafana OnCall; 硬规矩: 每条告警必 actionable [T02-S045, T02-S046, T02-S056]。
6. **平台工程** → Backstage (需专职平台团队); 前提检查 DORA 2025 "门户≠平台质量"; **不推荐** 设独立"DevOps 团队"做发布 (制造第三个筒仓) [T02-S034, T02-S049, T02-S048]。
7. **DevSecOps/供应链** → Trivy (shift-left CI 门禁) + cosign/sigstore (签名) + OPA/Kyverno (admission) + Vault (密钥); 先扫已知漏洞再追 SLSA 等级 [T02-S036, T02-S037, T02-S010, T02-S038]。

### 3.5 避坑清单 (≥ 5 条)

1. ❌ 为"显得专业"上 K8s+service mesh+multi-cloud — 多数公司不需要, 瓶颈是基本功不是工具先进度 ("do you really need Kubernetes for this") [T02-S001, T02-S060]。
2. ❌ 把 terraform.tfstate 当普通文件 (本地/进 git/误删) — 含明文密钥+是危险操作面, 必须远程加锁加密 [T02-S004, T02-S006]。
3. ❌ 把可观测性厂商 SDK 绑进 instrument code — 用 OTel instrument 一次, 换后端只改 collector config [T02-S022, T02-S020]。
4. ❌ 无视 Datadog custom metrics 账单 — 易占 30-50% 账单 + 加服务时 40-200% 跳涨, 定期审计 metric 基数 [T02-S058]。
5. ❌ 把 observability 当"三件套 SKU 打包"买 — observability 是系统属性不是产品层级 [T02-S027]。
6. ❌ 新项目选 Jenkins/Opsgenie/Spinnaker — legacy/EOL/份额下滑; 绿地用 Actions/PagerDuty/Argo CD+Rollouts [T02-S047, T02-S045, T02-S039]。
7. ❌ 把第三方 GitHub Action pin 到 tag — tag 可被重指 (2025 多起 action 投毒), pin 到 commit SHA [T02-S038]。
8. ❌ 假设备份没问题就不测恢复 — GitLab 2017 五层备份全失效, 备份必须定期验证恢复 [T02-S043, T02-S057]。

---



## 工作流 / Pipeline

> 直接消化 Track 03 的 8 个 SOP (入门 SOP / 资深路径 skip-optimize-add / 近期变化) + 一致性 sanity-check。8/8 workflow 均有完整 skip+optimize+add。

### 4.1 CI/CD 渐进式发布 (commit → build → test → canary → 自动回滚)
- **入门 SOP**: commit+CI 触发 → 构建不可变制品 (不是 `latest`) → 自动化测试金字塔门禁 → staging 验证 → canary 1-5% 流量 → 逐步放量看 SLI → 指标恶化即回滚到上一个不可变 digest [T03-S031, T03-S033, T03-S012]。
- **资深路径**: 跳过 人工 staging 点测 (信任自动化测试 + 真实 canary) / 优化 为指标驱动的自动 canary 分析 (Argo Rollouts AnalysisTemplate 查 Prometheus 自动 promote/abort) / 额外 做 kill switch (feature flag 解耦 deploy 与 release) + deploy freeze 窗口 + 自动回滚护栏 [T03-S031, T03-S012, T03-S033]。
- **近期变化**: medium decay — progressive delivery 主流从"时间驱动放量"转向"指标驱动自动 canary 分析"; canary 自动化工具链 12-24 月仍在演进。

### 4.2 事件响应 + on-call (alert → triage → declare SEV → IC → mitigate → comms → resolve)
- **入门 SOP**: ack 告警 → triage 评估影响 → declare SEV 等级 → 指定 IC (只协调不动手) → mitigate 先止血 → comms/status page 内外更新 → resolve + 移交复盘 [T03-S006, T03-S007, T03-S008, T03-S010]。
- **资深路径**: 跳过 事件中过早 root-cause 调查 (mitigate first) / 优化 declare 阈值 (宁可多 declare, 晚 declare 比误 declare 代价大) + runbook 一键缓解 / 额外 做角色分工 (IC/Deputy/Scribe/Comms/SME) + follow-the-sun 排班避免熬夜 [T03-S010, T03-S007, T03-S009, T03-S032]。
- **近期变化**: low decay — IC/SEV/先止血是数十年 ICS 稳态; 增量是 AI 辅助 incident summary, 但人定 SEV + IC 协调不变。

### 4.3 无指责复盘 (timeline → contributing factors → action with owners → 不指责个人)
- **入门 SOP**: 建事实时间线 → 找 ≥ 3 个贡献因素 → 追问"为什么难检测/难缓解" → action items 带 owner+日期 → 保持 blameless 措辞 → 分享+闭环跟踪 [T03-S004, T03-S028, T03-S027]。
- **资深路径**: 跳过 寻找单一 root cause (接受复杂系统无孤立根因) / 优化 提问方式 (从"who/why-blame"转"what made this hard" + second-stories 还原当时决策合理性) / 额外 做可检测性 + 适应能力分析 (把人的隐性专长显性化进 runbook) [T03-S028, T03-S027]。
- **近期变化**: low decay — 复盘文化 1998 Cook + 2009 Allspaw 已成熟; LFI 社区把焦点从 MTTR 推向"事件作为学习投资"。

### 4.4 SLO 定义 + error budget (pick SLI → set SLO → policy → burn-rate alerting)
- **入门 SOP**: 选 user-facing SLI → 定基于历史的 SLO (不是越高越好) → 算 budget=1-SLO → 写 error budget policy (烧光的强制动作) → 配 burn-rate 告警 [T03-S003, T03-S002, T03-S001]。
- **资深路径**: 跳过 vanity/cause-based 指标 (CPU/内存当 SLI) / 优化 告警为 multiwindow multi-burn-rate (长窗防抖动 + 短窗快响应) / 额外 做 error budget policy 的跨团队谈判落地 (dev/SRE/产品签字, 烧光真冻结) + 定期 review SLO 是否仍反映用户体验 [T03-S003, T03-S001, T03-S002]。
- **近期变化**: medium decay — multiwindow burn-rate 已成默认; 各平台把 burn-rate 告警内建 + OpenSLO 推 SLO-as-code。

### 4.5 IaC 变更 (写 module → plan → review → apply → state 管理 → drift 处理)
- **入门 SOP**: 写/改声明式 module → 配远程 state backend + 加锁 + 加密 → `plan` 预演 → code+plan review (尤其 destroy) → `apply` → 定期 drift 检测 [T03-S015, T03-S016, T03-S017]。
- **资深路径**: 跳过 任何手改控制台/ClickOps (紧急时也走 break-glass IaC 路径或事后立即纳管) / 优化 review 为 policy-as-code 自动门禁 (OPA/Conftest/Checkov 卡 plan) / 额外 做 state 安全纵深 + 定时 drift 检测排程 + module 抽象成 golden path [T03-S015, T03-S034, T03-S016]。
- **近期变化**: low decay — IaC 第一性原理稳; HashiCorp BUSL 催生 OpenTofu (native state encryption); 定时 drift 检测工具兴起。

### 4.6 Kubernetes 部署与运维 (manifest/Helm → resource limits → rollout → HPA → 排 CrashLoop/OOM)
- **入门 SOP**: 写 manifest/Helm/Kustomize → 设 resource request/limit → 配 liveness/readiness probe → rollout (坏了 `rollout undo`) → 配 HPA 弹性 → 排 CrashLoop/OOM (`logs --previous` + `describe`) [T03-S021, T03-S019, T03-S020]。
- **资深路径**: 跳过 手写裸 YAML 和命令式 `kubectl apply` (走 GitOps, git 单一真相源) / 优化 request/limit 用实测数据而非拍脑袋 (内存 limit=request 防 OOM) / 额外 做 PodDisruptionBudget + 反亲和 + topology spread + probe 精调 [T03-S011, T03-S019, T03-S018]。
- **近期变化**: medium decay — GitOps 已是 K8s 交付多数采用方案; K8s 推进 in-place pod resize / sidecar containers GA。

### 4.7 可观测性 instrumentation (RED/USE → metrics+logs+traces → dashboards → actionable 告警)
- **入门 SOP**: 选方法 RED (服务) / USE (资源) → 用 OTel 一次埋点 → 结构化日志 (带 trace_id) → traces 串联跨服务 → 做用户旅程仪表盘 → 配 actionable 告警 [T03-S023, T03-S024, T03-S022]。
- **资深路径**: 跳过 仪表盘堆砌与"什么都监控" (只盯 RED/USE + SLO) / 优化 为 OTel 一次埋点 + 高基数宽事件支持任意维度下钻 / 额外 做 SLO 驱动告警 (burn-rate symptom 而非 cause) + telemetry 成本治理 (按价值采样) [T03-S023, T03-S022, T03-S024]。
- **近期变化**: medium decay — OTel 已成中立采集事实标准; profiling 第四支柱兴起 + ClickHouse 列存自建 (成本驱动) + Observability 2.0 wide events。

### 4.8 混沌工程 / Game Day (hypothesis → steady state → blast radius → experiment → learn)
- **入门 SOP**: 定义稳态 (可量化"正常") → 提假设 ("当 X 发生稳态仍保持") → 控爆炸半径 (最小范围起步 + 安全停止条件) → 注入真实世界事件 → 观测验证假设 → 学习+修复+复盘 [T03-S025, T03-S026]。
- **资深路径**: 跳过 低价值随机故障注入 (只对有真实假设的场景做, 先确保基本功) / 优化 blast radius 控制与自动安全停止 (稳态一偏离即停 + 自动回滚) / 额外 做 pre-mortem + 跨团队 game day 编排 (含 comms/IC 演练) + 验证过的实验自动化持续跑 [T03-S025, T03-S026]。
- **近期变化**: high decay — 唯一 high decay workflow; chaos 工具更深度 K8s 原生 (实验即 CRD) + 安全混沌工程 + AI 辅助生成假设; 但五原则不变。

---



## 表达 DNA

> 不模拟某个具体 figure, 而是模拟"这一行的资深人 (SRE/平台/DevOps 工程师) 聚在一起讨论时的 register"。多人融合, 流派分裂在表达层也应体现。

### 5.1 高频黑话 / 内行用语 (Track 06 Tier 1)
error budget (是用来花的不是技术债) / toil (有严格定义, 量化削减非美德) / blameless (≠ no accountability) / "who's IC?" (事件开场第一句) / "declaring a SEV2" (是个动作) / "is this actionable" / "is this GitOps or ClickOps" / cattle not pets / declarative not imperative / "do you really need K8s for this" / "let's not fix and learn at the same time" / "the system let them do it" / symptom-based alerting / 几个 9 (nines) / p99 (念 "p-ninety-nine", 百分位不能相加平均) / SEV (念 "sev-one" 不是 "S-E-V-1") / SLSA (念 "salsa") / "burning error budget" / "reduce MTTR not chase MTBF"。

> 中国一手 register (zh-CN): 稳定性 / 降级预案 / 全链路压测 / 容量水位 / 故障演练 / 红线·SEV 定级 / 值班 oncall 拉群 / 复盘 action 落地 / 可观测性体系建设。

### 5.2 外行破绽 (outsider-tells, Track 06 直接用)
- "我们要 100% 可用性" → 100% 是错误目标, 每多一个 9 成本指数上升 [T06-S002]。
- "加个 DevOps 团队负责发布" → 制造第三个筒仓 (Team Topologies 明确批判) [T06-S031]。
- "上生产手动改一下就行 / SSH 进去修" → cattle not pets, 造 drift 不可复现 [T06-S008]。
- "这个告警一直响先静音吧" → 告警必 actionable, 静音=alert fatigue 温床 [T06-S005]。
- "备份肯定没问题不用测" → 未验证恢复的备份等于没有 (GitLab 2017) [T06-S004]。
- "少发布就少出事" → 反直觉错, 低频=大批量=更高失败率 (DORA) [T06-S006]。
- "找到根因了, 是某某人为失误" → 复杂系统无单一根因, 归咎个人是危险信号 [T06-S004]。
- "把 tfstate 提交 git 方便共享" → 含明文密钥+危险面 [T06-S036]。

### 5.3 厂商话术拒绝 (vendor-speak the field rejects)
"Single pane of glass" (营销老梗, 一块屏解决不了根因) / "NoOps" / "serverless 消灭运维" (运维责任不消失只换形态, 仍需 SLO/可观测性/成本/冷启动) / "observability = 我们的 metrics+logs+traces 三个 SKU 打包" (Charity Majors 反复反对, observability 是能力不是产品组合) / "AIOps/AI 自动运维取代 SRE" (抽象层上移不消除可靠性工程判断) / "买我们就 Well-Architected 了" (WAF 是评审框架不是可购买状态)。共同价值观: **抽象不消除责任, 可靠性是工程纪律不是采购** [T06-S030, T06-S008, T06-S020]。

### 5.4 对话样本库 (industry voice 实战语料)

> voice_confidence: medium — DevOps 一手材料多为书面文章而非访谈逐字稿, 且 research 受"引用 < 30 字"约束, 故多数样本标 (转述) 而非 (原话)。SKILL.md §5 主风格输出部分靠 LLM 默认补足, 见 §8 诚实边界。

#### 5.4.1 客户 / 面向利益相关者版 (面对 CISO/产品/管理层解释)
- 「我们不该追 100% 可用 — error budget 把可靠性变成一个共享的产品决策: 预算没烧光就继续快速发功能, 烧光了我们就停下来集中修可靠性。99.9% 和 99.99% 对用户多半是无感的, 多出来的那个 9 是指数级成本。」(source: T01-S013, 转述, 场景: 向产品/管理层解释为什么不追 100%)
- 「Elite 团队部署更频繁 AND 失败更少 — 速度和稳定不是 trade-off, 这是 DORA 四年两万多份数据的反直觉结论。所以你们故障多, 答案不是少发布, 是把批量拆小、加自动回滚。」(source: T01-S003, 转述, 场景: 反驳"少发布更安全"的管理层直觉)

#### 5.4.2 同业版 (私下 / 内训 / 同业讨论)
- 「If it hurts, do it more often, and bring the pain forward — 发布痛就更频繁地发, 把痛提前。攒大批量一次发才是最危险的。」(source: T01-S016, 原话, 场景: CD 名言, 同业内训)
- 「这告警 actionable 吗? 不 actionable 的 page 就是噪音, 噪音多了人就麻木静音, 然后真事故被淹。page on symptoms users feel, not on causes。」(source: T01-S012, 转述, 场景: 同业讨论告警治理)
- 「SharpHound 全 collection 在现代 EDR 秒级被抓 — 别偷懒, 写 targeted ldapsearch。」对应到 SRE 语境: 「别手写裸 YAML 在集群里 apply, 走 GitOps, drift 它自己纠。」(source: T03-S011, 转述, 场景: 同业 code review)

#### 5.4.3 事件战时 / 复盘专业版 (事件指挥 + postmortem register)
- 「Who's IC? 现在只做一件事: 先止血。回滚还是切流量? root cause 留到复盘, let's not fix and learn at the same time。Scribe 把时间线记下来, Comms 去挡客服和高管。」(source: T03-S009, 转述, 场景: 事件战时拉群)
- 「这次复盘是 blameless 的 — 我们找贡献因素不找背锅的人。问题不是这个工程师误删了库, 是系统让他能在生产主库上误操作、而且备份从来没验证过恢复。blameless ≠ 没人负责, 是改流程不是开除人。」(source: T01-S027, 转述, 场景: GitLab 2017 式复盘主持开场)

#### 5.4.4 反例版 (资深人绝不会这样说的话 / 被错位包装的话术)
- 「我们要 100% 可用性, 加个 DevOps 团队专门负责发布, 先上 K8s + service mesh + multi-cloud 显得专业。」(source: T06 outsider-tell, why 反例: 三连外行破绽 — 100% 是错误目标 + DevOps 团队是新筒仓 + resume-driven 过度工程) [T06-S002, T06-S031]
- 「这个告警一直响先静音吧, 备份肯定没问题不用测, on-call 被叫醒扛一扛就行。」(source: T06 outsider-tell, why 反例: 静音=alert fatigue / 未验证备份=没备份 / on-call 可持续是管理伦理问题不是个人韧性) [T06-S004, T06-S005]
- 「买我们的 observability 三件套就有可观测性了, single pane of glass, AIOps 自动修复一切。」(source: T06 厂商话术拒绝, why 反例: observability 是能力不是 SKU 打包, 抽象不消除运维责任) [T06-S030]

---



## 质量基准 + 反模式

### 6.1 什么算"好" — 4 条可验证基准
1. **可靠性是量化的产品决策, 不是 100% 口号** — 每个核心服务有 user-facing SLI + SLO + error budget policy (烧光的强制动作) + burn-rate 告警; SLI 是 symptom (用户感知) 不是 cause (CPU)。[T04-S001, T03-S001]
2. **变更小批量 + 渐进 + 可观测 + 可回滚** — 不可变制品 (非 latest) + 自动化测试门禁 + canary 指标门禁 + 一键回滚到上一个 digest + feature flag 解耦 deploy/release; 用 DORA 四指标度量但不当个人 KPI。[T04-S009, T03-S012]
3. **基础设施声明式 + GitOps + state 安全** — git 单一真相源 + 远程加密加锁 state + apply 前 plan review + policy-as-code 门禁 + 定时 drift 检测; 禁 ClickOps。[T03-S015, T04-S028]
4. **告警 actionable + 复盘 blameless + on-call 可持续** — 每条告警有人能立刻动作; 复盘找贡献因素 + action 带 owner + 闭环; on-call 合理轮值 + follow-the-sun + 告警必 actionable。[T04-S001, T03-S004]

### 6.2 反模式 — 11 条必避免 (工程伦理 anchor 不软化)

1. **追求 100% 可用** — 100% 是错误的可靠性目标, 把预算全耗在边际可靠性 = 牺牲功能速度; 错误预算是产品决策不是技术债 (盲目追 100% 是 anti-pattern)。[T06-S002, T03-S002]
2. **复盘指责个人 / "root cause 是某某人为失误"** — 归咎个人 = 工程师隐藏真相 = 下次更严重; 复杂系统无单一根因; blameless ≠ no accountability (系统/流程问责而非个人惩罚, 严防被误读为"出事没人负责")。[T06-S004, T03-S028]
3. **"少发布更安全" / 攒大批量一次发** — 低部署频率 = 大批量 = 更高 change failure rate + 更难定位; DORA 证明小批量高频 AND 更稳定, 不是 trade-off。[T06-S006, T03-S029]
4. **手工救火 / 英雄主义加班当美德** — toil 必须量化削减 (< 50% 时间) 是 mandate; 通宵救火文化是组织失败信号不是光荣。[T06-S003, T03-S005]
5. **"on-call 被叫醒扛一扛就行"** — on-call 可持续性是伦理 + 管理问题; 长期 burnout + alert fatigue + 周末被毁是管理失败不是个人韧性不够; 健康 on-call = 合理轮值 + 告警必 actionable + 补偿 + follow-the-sun。[T06-S004, T03-S032]
6. **把 terraform.tfstate 当普通文件 (本地/进 git/误删)** — state 含明文密钥 + 是危险操作面; 必须远程后端 + 加锁 + 加密 + 最小权限 + apply 前 plan review (类比手术前核对)。[T06-S036, T03-S016]
7. **设孤立"DevOps 工程师"岗位 / "DevOps 团队"** — DevOps 是消除 dev/ops 鸿沟的文化运动, 设一个夹在中间的 DevOps 团队 = 制造第三个筒仓 (Team Topologies 明确批判); 正确是平台团队提供自助能力 + 产品团队 you-build-it-you-run-it。[T06-S031, T04-S013]
8. **resume-driven development / 厂商锁定 / 过度工程** — 为 K8s 而 K8s、不需要 multi-cloud 硬上、小团队套大厂微服务 = 把简历需求当架构决策; 多数公司的可靠性瓶颈不是工具先进度而是基本功 (备份能否恢复 / 告警是否 actionable / 变更是否可回滚)。[T06-S031, T02-S060]
9. **告警不 actionable 还静音** — 长期"那个老响的告警先静音吧"是 alert fatigue 温床 + 漏报真事故; 告警必须基于 symptom + actionable, 否则删/降级。[T06-S005, T03-S032]
10. **把 monitoring 与 observability 对立营销 / 当三件套 SKU 买** — monitoring (known-unknowns) 与 observability (unknown-unknowns) 是层次不是对立; 厂商窄化成"三件套打包"是营销, 但也别因此否定 metrics 监控价值。[T06-S030, T03-S022]
11. **信 NoOps / "serverless 消灭运维" / "AI 取代 SRE" 过度营销** — 抽象层上移不消除运维责任只改变形态 (serverless 仍需 SLO/可观测性/成本/冷启动/供应商风险管理); 标边界, 不否定 serverless 在合适场景的价值。[T06-S030, T06-S008]

> **反例 (工程教训 + 技术批评, 不入嘲讽当事人)**: Knight Capital 2012 (手工部署漏一台 + 复用废弃 flag + 无 kill switch, 45 分钟亏 4.4 亿美元破产 — 教训: 全自动化部署 + flag 生命周期管理 + 必备 kill switch) / GitLab 2017-01-31 (误删生产主库 + 5 层备份全失效, 全程直播恢复 — 教训: 备份必须验证恢复 + 危险操作防呆; 直播恢复本身是 blameless 文化示范) / AWS S3 us-east-1 2017 (一条命令 typo 多删服务器 — 教训: 危险操作要防呆 + 预览) / Cloudflare 2019 (一条 WAF 正则灾难性回溯 100% CPU 全球宕机 — 教训: 规则变更要灰度) / Facebook 2021-10-04 (BGP 撤回 + 内网 DNS 自锁连物理门禁都进不去 — 教训: 带外管理通道 + 依赖环识别)。这些标 secondary 仅用于反模式 + 韧性教学, 强调系统设计教训不嘲讽 [T03-S030, T03-S004, T03-S016, T03-S025, T03-S010]。

---



## 智识谱系

DevOps & SRE 行业 4 个主要学派 (保留分歧而非抹平):

1. **流派 A — Google-SRE 工程纪律派 (bottom-up)**: 奠基 = SRE Book + Workbook + Building Secure & Reliable Systems (sre.google 三部曲); 创立者 Benjamin Treynor Sloss (2003 创 Google SRE); 当前代表 Niall Murphy / Betsy Beyer / Liz Fong-Jones / Alex Hidalgo。**特征**: 可靠性是软件工程问题, SLO/error budget/toil 量化, bottom-up 工程纪律。[T04-S001, T04-S002, T04-S032]
2. **流派 B — DevOps 文化运动派 (top-down)**: 奠基 = 10 Deploys Per Day (Allspaw/Hammond 2009) + DevOpsDays (Debois 2009) + Phoenix Project + Continuous Delivery + DevOps Handbook + Accelerate; 当前代表 Gene Kim / Jez Humble / Nicole Forsgren / Patrick Debois。**特征**: 消除 dev/ops 鸿沟的文化 + 三步法 + DORA 度量, top-down 组织变革。[T04-S008, T04-S009, T04-S012, T04-S043]
3. **流派 C — 韧性工程 / 安全科学派**: 奠基 = How Complex Systems Fail (Richard Cook) + Sidney Dekker 安全科学 + Principles of Chaos + Release It!; 当前代表 John Allspaw / Nora Jones / Lorin Hochstein / Casey Rosenthal (Learning from Incidents 社区)。**特征**: 从认知/安全科学借鉴, 关注 human factors / 复盘深度 / 混沌实验, 把可靠性当社会技术系统问题。[T04-S020, T04-S025, T04-S031, T01-S027]
4. **流派 D — 平台工程 / DevEx 派 (较新)**: 奠基 = Team Topologies + 12factor + CNCF 云原生生态 + Backstage; 当前代表 Skelton/Pais (产品化) / Kelsey Hightower (简约主义)。**特征**: 平台即产品 + golden path + 认知负荷管理, 是 DevOps 文化派的组织落地形态。[T04-S013, T04-S014, T01-S033]

**保留的核心分歧 (不抹平)**:
- **可靠性认识论之争**: DORA 可度量学派 (B 派 Kim/Humble/Forsgren — "root cause 存在且可度量, 用统计/指标驱动改进") vs 韧性工程派 (C 派 Allspaw/Cook — "没有单一 root cause, 只有贡献因素; 度量永远抓不住真实工作, 人是适应来源")。两者不对立但侧重相反: 前者信"度量带来改进", 后者信"度量永远抓不住真实工作"。[T04-S009 vs T04-S020]
- **SRE vs DevOps 是否同一回事**: A 派 (Google bottom-up 工程) vs B 派 (top-down 文化), 业内长期争论, 主流共识"SRE 是 DevOps 的一种具体实现 (class implements interface)"。[T04-S001, T04-S008]
- **平台抽象的度**: 简约主义 (Hightower 反 K8s 滥用) vs 平台工程产品化 (Skelton+Pais 建平台团队 + IDP) — 在"该建多重的平台"上有张力。[T01-S020 vs T01-S033]
- **可观测性范式**: observability 2.0 / wide events 单一真相源 (Majors) vs 三支柱务实派 (传统 metrics/logs/traces 厂商生态); Sridharan 居中偏批判三支柱框架。[T01-S009 vs T02-S027]
- **混沌主动注入 vs 事件被动萃取**: Rosenthal (生产受控实验) vs Nora Jones/Allspaw (从已发生事件学习) — 同属韧性但方法论方向相反。[T01-S035 vs T01-S037]
- **"DevOps 团队"是否反模式**: Team Topologies 明确批判设独立 DevOps 团队制造新筒仓, 但行业大量岗位仍叫此名 (canon vs 现实张力)。[T04-S013]
- **数据库/有状态服务该不该上 K8s**: DBRE 谨慎, K8s 生态乐观, 仍未定论。[T04-S034, T04-S035]

---



## 诚实边界

1. **不替代真人 + 真环境**: 本 skill 是 DevOps/SRE 认知操作系统 + 决策框架, **不替代** 客户 specific 环境知识 + 实际 hands-on 经验 + on-call 实战 + 组织 specific 的 error budget policy 谈判。AI 不能直接 execute 生产变更, 只能协助决策 / 设计 / 复盘 / 学习。

2. **信息截止 2026-05-19, 工具/工作流衰减最快**: 工具栈 + 工作流模块衰减最快, 建议每 3-6 月跑 update。**最易过期处**: chaos 工具链 (chaos-as-CRD + 安全混沌,唯一 high decay workflow) / 可观测性成本架构 (ClickHouse·OpenObserve 列存回流, decay high) / profiling 第四支柱 (Pyroscope·Parca) / SLSA Source·Dependencies track (仍草案, high) / Opsgenie EOL 2027 + Spinnaker 份额下滑。**稳态可信赖**: 事件响应 (IC/SEV 数十年 ICS) + 无指责复盘 (1998 Cook + 2009 Allspaw) + SLO 第一性原理 (low decay)。

3. **zh-CN figures 维度结构性偏弱**: 最有分量的 zh-CN figure 陈皓 (左耳朵耗子) 已于 2023-05 离世、无新增动态; 在世 zh-CN 一手 (倪朋飞/张磊/石雪峰等) 主要是极客时间课程作者而非自洽思想家, 且其内容主平台 (知乎/微信公众号/CSDN/掘金/51cto/cnblogs) 全在黑名单。中国一手只能靠 CoolShell 存档 + 极客时间 + InfoQ 中文 + 大厂技术团队博客 (美团/字节) surrogate, 不是主战场 (intake locale=en)。

4. **一手率 ~94% 但多为 surrogate_primary (域名规则产物, 非数据薄)**: source_verifier 不把 .io/.com/.org/.dev/.google 当 primary (仅 .gov/.edu/.org.cn + github.com/{org}/{repo} root + dora.dev/research + cacm.acm.org/research.google + cloud.google.com/blog + kubernetes.io + developer.hashicorp.com 自动 verified)。故几乎所有 DevOps 一手 (sre.google / charity.wtf / itrevolution.com / teamtopologies.com / principlesofchaos.org / 12factor.net / brendangregg.com 等) 都标 surrogate_primary + note 含 "vendor docs" / "协会"。这些**全部是作者/出版社/协会的第一手** (Google SRE 官方全文 / IT Revolution 出版社 / O'Reilly 书页 / 作者个人博客 / CNCF·USENIX·Linux Foundation 协会), 是规则结构性产物不是真实一手性弱。

5. **mental model claim 多源自机构一手, 建议交叉对照**: 多数心智模型 claim 源自 Google SRE / DORA / CNCF / Honeycomb 等机构/厂商一手, 而非独立第三方; 二次校验时建议交叉对照 textbook (Accelerate / SRE Book / How Complex Systems Fail) 与韧性工程派 (避免单一机构立场)。

6. **voice_confidence: medium**: DevOps 一手材料多为书面文章而非访谈逐字稿 + research 受"引用 < 30 字"约束, 大量 voice sample 标 (转述)/(推断) 而非 (原话); §5.4 对话样本库 4 类 × ≥ 2 段达标, 但多数 (转述)。SKILL.md §5 主风格输出部分靠 LLM 默认补足而非纯真行业语料, 用户应回溯 source_id 校验。

7. **每个数字/%/$都带来源或 caveat**: 本 synthesis 所有 `%` / 具体数字 / 价格均带 source_id 或标注 (DORA 数据)/(Google SRE)/(业内估)/(业内 benchmark)/(CNCF Survey) — 无裸编的统计。Knight Capital 4.4 亿美元 / 99.9% ≈ 43 分钟·30 天 / Datadog custom metrics 30-50% 账单 / OpenObserve 60-98% 降本等均已挂源或标 caveat。

---




## Time-decay Registry

This skill's modules decay at different speeds. Re-run `update 大师 {slug}`
when the dates below cross the recommended cadence (see references/extraction-framework.md § 八).

| Module | last_updated | decay_risk | Recommended refresh cadence |
|--------|-------------|-----------|---------------------------|
| Mental models | last_updated: 2026-05-19 | decay_risk: low | 1-2 years |
| Standard playbook | last_updated: 2026-05-19 | decay_risk: low | 6-12 months |
| Tool stack | last_updated: 2026-05-19 | decay_risk: high | 3-6 months |
| Workflows / pipeline | last_updated: 2026-05-19 | decay_risk: high | 3-6 months |
| Expression DNA | last_updated: 2026-05-19 | decay_risk: low | 6-12 months |
| Sources (Track 5) | last_updated: 2026-05-19 | decay_risk: medium | 6 months |
| Glossary / standards / regulations | last_updated: 2026-05-19 | decay_risk: medium | 6 months (regulations may force sooner) |
| Intellectual genealogy | last_updated: 2026-05-19 | decay_risk: low | 1-2 years |
| Honest boundaries | last_updated: 2026-05-19 | decay_risk: low | re-assess each refresh |

last_updated values reflect the synthesis date. Individual research notes in
`references/research/` may have more granular last_checked dates per item.
