How does this skill help reduce alert fatigue?

It implements multi-window burn rate alerting, which combines short and long time windows to ensure alerts only trigger for significant, sustained reliability issues.

Does it provide guidance on error budget policies?

Yes, it includes a policy framework that suggests specific team actions (like feature freezes or reliability focus) based on the remaining error budget.

Can I use this for both availability and latency targets?

Yes, it includes specific implementation patterns for Availability (request success rates) and Latency (percentile-based performance) SLIs.

What monitoring tools are supported by this skill?

This skill focuses on industry-standard Prometheus and Grafana environments, providing PromQL expressions and YAML recording rules.

SLO & SLI Implementation Framework

Name: SLO & SLI Implementation Framework
Author: as4584

byas4584

分析与监控

Defines and implements Service Level Indicators (SLIs) and Objectives (SLOs) with error budgets and alerting for reliable service performance.

关于

This skill provides a comprehensive framework for establishing Site Reliability Engineering (SRE) practices by defining measurable reliability targets. It helps developers and SREs implement SLIs, SLOs, and error budgets using PromQL and Prometheus recording rules. By balancing innovation velocity with service stability, it enables data-driven decisions on when to freeze features or prioritize reliability based on real-time error budget burn rates and sophisticated multi-window alerting strategies.

主要功能

Standardized SLI/SLO definition patterns for availability, latency, and durability
Prometheus recording rules for tracking long-term reliability metrics
Grafana dashboard structures for real-time observability and compliance tracking
Automated error budget calculation and development policy templates
Multi-window burn rate alerting rules to reduce notification noise
0 GitHub stars

使用场景

Implementing automated error budget policies to balance feature velocity and stability
Establishing internal reliability targets and measurement for microservices
Configuring high-precision SRE alerts using PromQL burn rate calculations

关于

主要功能

Standardized SLI/SLO definition patterns for availability, latency, and durability
Prometheus recording rules for tracking long-term reliability metrics
Grafana dashboard structures for real-time observability and compliance tracking
Automated error budget calculation and development policy templates
Multi-window burn rate alerting rules to reduce notification noise
0 GitHub stars

使用场景

Implementing automated error budget policies to balance feature velocity and stability
Establishing internal reliability targets and measurement for microservices
Configuring high-precision SRE alerts using PromQL burn rate calculations