A collection templates ported from the SRE Workbook
A simple service level calculator
Calculator to view detection time using error budget consumption rates, based on lessons from Site Reliability Engineering Workbook
Stop burning your error budget. SRE config as code — SLOs, error budgets, runbooks, on-call, and dashboards in one sre.yaml file. Auto-remediates before alerts fire.
端到端 SLO (服务级别目标) 治理平台，集成 MeterSphere 拨测数据，自动计算误差预算，并由 AI 辅助输出结构化诊断报告
Материалы по SRE: принципы надёжности, наблюдаемость, инциденты и метрики. Разборы подходов и вопросы для подготовки к собеседованию.
Azure-native SLO/SLI engine with error budget tracking, burn-rate alerts, and CLI for Azure Monitor, Application Insights & Log Analytics
Identifies underutilized service-level objectives by detecting SLOs that consistently maintain error budget thresholds,generating actionable Excel reports with historical performance trends and optimization recommendations.
Azure SLO Dashboard with AI-powered error budget explainer — Application Insights + Container Apps + Claude
SRE on AWS: SLOs/SLAs/error budgets, runbooks, incident response playbooks, chaos engineering, observability stack
SLO-based alerting for Kubernetes - burn rate alerts, policy guardrails and an error budget release gate, all unit tested without a cluster
Semantic SLO monitoring for LLM apps: quality regression detection, behavioral drift alarms, and error budget burn from traces
Error-budget-driven release gating for Prometheus: one SLO spec generates burn-rate alerts, a Grafana dashboard, and a CI/CD gate that freezes deploys when you're out of budget. Go.
Production-inspired Site Reliability Engineering practices covering SLIs, SLOs, incident management, reliability engineering, operational excellence, alerting, and disaster recovery.
Hands-on SRE practice lab for learning golden signals, observability, SLI/SLOs, error budgets, tracing, resilience, and capacity planning.
Audit API SLO and error-budget docs for targets, SLIs, burn-rate alerts, incidents, exclusions, status reporting, telemetry, owners, and rollout safety.
Multi-window multi-burn-rate SLO alerting over spans, with an honest 3-regime benchmark: a naive threshold detects real regressions faster, but raises 3 false pages on healthy spiky traffic where multi-window raises 0. The value is precision, not speed, and the benchmark proves it both ways.
Reliability analytics for a live microservice fleet: DORA release metrics, SLO error-budget tracking, statistical anomaly detection, root-cause vs cascade classification, and priced incident impact, measured on a real Kubernetes cluster.
SLO tracker with multi-window burn rate alerting — Google SRE Workbook model in Python
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