error-budget-tracker

Compute live error-budget metrics for a specified SLO across multiple rolling windows.

1|Updated Apr 16, 2026
One-click install
npx skills add https://github.com/FrogAi/Xenopus --skill error-budget-tracker
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: error-budget-tracker
Source: https://github.com/FrogAi/Xenopus/tree/main/Gemini/Skills/Gemini%203.1%20Pro/error-budget-tracker
Command: npx skills add https://github.com/FrogAi/Xenopus --skill error-budget-tracker

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

SREs and reliability engineers often lack a clear, auditable view of how much error-budget remains for a given SLO and when it might exhaust under current conditions. This Skill provides a production-grade, read-only error-budget tracker that computes consumption, burn rate, and projections across multiple rolling windows.

Core Features & Use Cases

  • Live SLO budget computation from current metrics (Dynatrace / Prometheus / Datadog / CloudWatch) aligned with Google SRE guidance.
  • Multi-window visibility (1h, 6h, 24h, 7d, 30d) with burn-rate thresholds and exhaustion time projections.
  • Read-only operation to support safe deployments, incident reviews, and capacity planning.

Quick Start

Invoke the tracker for a target SLO to generate a live budget report and recommended actions.

Frequently Asked Questions about error-budget-tracker

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I track my SLO error budget and burn rate across different observability platforms?

You can track your SLO error budget and burn rate by querying live observability data from Dynatrace, Prometheus, Datadog, or CloudWatch. The tracker computes current consumption and budget remaining across multiple rolling windows with explicit citations.

What is SLO error budget burn rate and how is it calculated over rolling windows?

SLO error budget burn rate measures how quickly your reliability target is being consumed over rolling windows like 1h, 6h, 24h, 7d, and 30d. It is calculated by comparing live metrics against canonical SRE guidance to flag discrepancies and project exhaustion time.

Can I calculate SLO time-to-exhaustion projections using Datadog or CloudWatch metrics?

Yes, you can calculate time-to-exhaustion projections using Datadog or CloudWatch metrics. The tracker compares live data sources against SRE thresholds to project when your error budget will exhaust and returns a recommended action.

How do I generate a live error budget report for incident reviews without modifying production data?

You generate a live error budget report for incident reviews through read-only operation, ensuring safe deployments without modifying production data. It returns a structured report including budget remaining, burn rate, and time-to-exhaustion projections with explicit metric citations.

Why does my error budget tracking show discrepancies between Prometheus and Dynatrace sources?

Error budget tracking shows discrepancies between Prometheus and Dynatrace sources due to differences in live metric collection and calculation methods. The tracker explicitly compares these observability data sources and flags any discrepancies found during the SLO budget computation.

Does error budget tracking work for capacity planning across 30-day rolling windows?

Yes, error budget tracking works for capacity planning across 30-day rolling windows. It provides multi-window visibility into burn-rate thresholds and exhaustion time projections, supporting safe deployments and long-term reliability planning.