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Periscope gives engineering teams deep visibility into how they ship software. It combines industry-standard frameworks — DORA and SPACE — with AI-powered risk detection to surface the insights that matter.

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What Periscope tracks

DORA metrics

The four key metrics from Google’s DevOps Research and Assessment program: deployment frequency, lead time for changes, change failure rate, and mean time to recovery.

SPACE metrics

Developer productivity metrics based on the SPACE framework: throughput, cycle time, and size vs time — with more coming soon.

Insights

Contributor activity, service health, and risk signals to help you understand team dynamics and spot problems early.

MCP integration

Query all your metrics from AI coding tools like Claude Code, Cursor, and Windsurf through the Model Context Protocol.

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How it works

Periscope collects data from two primary sources:
  1. GitHub — PR merge events are captured automatically through a GitHub App installation. Periscope tracks cycle times, throughput, and contributor activity from your pull request data.
  2. Your CI/CD pipeline — Deployment events are sent to Periscope via a webhook from any CI/CD system (GitHub Actions, Azure DevOps, Jenkins, etc.). Periscope links deployments to PRs via commit SHA to calculate lead time and DORA metrics.
Once connected, Periscope computes all metrics automatically and surfaces them through the dashboard, API, and MCP server.

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Get started

Quickstart

Connect GitHub, send your first deployment, and see your metrics in under 10 minutes.

Deployment webhook

Set up your CI/CD pipeline to send deployment events to Periscope.

MCP server

Query your engineering metrics from AI coding assistants.

OpenCode plugin

Track AI coding analytics — cost, tokens, and models — from OpenCode sessions.