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Vigil 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.

日本語版 README はこちら

Features

  • Detect SLOs where the error budget has never dropped below a configurable threshold over a given window
  • Detect SLOs where 50% or more of the total window has a negative error budget
  • Excel report generation with styled output (slo_report.xlsx)
  • Multi-cloud SLO monitoring
    • Google Cloud Monitoring
    • Datadog
  • i18n support for report output (English / Japanese)

screenshot

Install

go install github.com/rluisr/vigil@main

Authentication

GCP

Vigil uses Application Default Credentials (ADC). Ensure credentials are configured:

gcloud auth application-default login

Datadog

Set the following environment variables:

export DD_API_KEY="your-api-key"
export DD_APP_KEY="your-app-key"

Usage

Arguments

--cloud string
      cloud provider: "gcp" or "datadog" (default "gcp")
--gcp-project string
      GCP project ID (required for GCP)
--dd-site string
      Datadog site (e.g. datadoghq.com, ap1.datadoghq.com, datadoghq.eu)
--error-budget-threshold float
      error budget threshold, 0 to 1 (default 0.9)
--window duration
      target window, use "h" suffix (default 720h0m0s)
--lang string
      report language: "en" or "ja" (default "en")

Examples

GCP: Find SLOs that never dropped below 99% in 30 days

vigil --cloud gcp --gcp-project your-gcp-project-id --error-budget-threshold 0.99 --window 720h

Datadog: Find SLOs that never dropped below 95% in 14 days

vigil --cloud datadog --dd-site datadoghq.com --error-budget-threshold 0.95 --window 336h

Generate a Japanese report

vigil --cloud gcp --gcp-project your-gcp-project-id --lang ja

License

WTFPL

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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.

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