What metrics can this skill track?

It helps define and track Service Level Indicators (SLIs) such as latency, availability, error rate, and throughput.

Can I use this for existing services?

Yes, you can apply this skill to both new and legacy services to establish performance baselines and improvement targets.

How does it help with error budgets?

The skill calculates error budgets based on your defined SLOs, helping you decide when to prioritize stability over new features.

Why use SLOs instead of just general monitoring?

SLOs provide a business-aligned target for performance, ensuring that technical metrics reflect the actual user experience and business requirements.

Does it integrate with external monitoring tools?

While it defines the structures, it is designed to be integrated with tools like Prometheus or Datadog to automate the collection of actual SLI data.

Service Reliability & SLO Tracker

Name: Service Reliability & SLO Tracker
Author: BbgnsurfTech

byBbgnsurfTech

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Analytics & Monitoring

Establishes and monitors service level agreements, indicators, and objectives to maintain high system reliability and performance.

About

The Service Reliability & SLO Tracker skill empowers developers to implement Site Reliability Engineering (SRE) best practices directly within their workflow. It assists in defining critical metrics like latency and availability, setting achievable targets (SLOs), and calculating error budgets to balance innovation with stability. By automating the structuring of performance data and providing guided frameworks for service monitoring, this skill helps teams proactively identify bottlenecks and maintain consistent service quality for their end-users.

Key Features

1 GitHub stars
Integration-ready frameworks for monitoring tool alignment
Guided formalization of customer-facing SLAs
Strategic SLO target setting and performance benchmarking
Error budget calculation and management
Automated SLI definition for latency, error rate, and availability

Use Cases

Defining performance benchmarks for a new microservice
Calculating error budgets to determine deployment frequency
Establishing formal SLAs for customer-facing APIs

About

Key Features

1 GitHub stars
Integration-ready frameworks for monitoring tool alignment
Guided formalization of customer-facing SLAs
Strategic SLO target setting and performance benchmarking
Error budget calculation and management
Automated SLI definition for latency, error rate, and availability

Use Cases

Defining performance benchmarks for a new microservice
Calculating error budgets to determine deployment frequency
Establishing formal SLAs for customer-facing APIs