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Sleuth

by Sleuth

DORA metrics and deployment intelligence platform that tracks deployments across APAC CI/CD pipelines, source control, and feature flag systems — APAC engineering teams use Sleuth to correlate APAC deployments with errors and monitoring alerts, measure DORA metrics per service, and identify APAC changes that caused incidents.

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AIMenta verdict
Decent fit
4/5

"DORA metrics and deployment tracking platform — connects to APAC CI/CD pipelines, source control, and monitoring to track deployment frequency, lead time, and MTTR per APAC team and service. APAC engineering managers use Sleuth to measure and improve delivery performance."

Features
6
Use cases
3
Watch outs
3
What it does

Key features

  • Deployment tracking — APAC CI/CD pipeline, feature flag, and git change correlation
  • DORA metrics — automated APAC deployment frequency, lead time, CFR, MTTR calculation
  • Impact analysis — APAC deploy-to-incident correlation from Datadog/PagerDuty/Sentry
  • Change failure detection — automatic APAC unhealthy deploy classification
  • Slack integration — APAC deployment notifications with impact status in team channels
  • Multi-service — APAC per-service DORA dashboards across all registered services
When to reach for it

Best for

  • APAC SRE teams wanting deployment-to-incident correlation — Sleuth's impact analysis connects APAC deploy events to monitoring signals without manual post-deployment review
  • APAC engineering teams using feature flags alongside code deploys — Sleuth tracks feature flag changes as deployments, giving APAC teams unified change history including flag toggles
  • APAC teams at earlier DORA measurement maturity — Sleuth's deployment tracking setup is simpler than LinearB's full engineering intelligence suite for APAC teams starting DORA measurement
Don't get burned

Limitations to know

  • ! Less APAC developer workflow integration than LinearB — Sleuth focuses on deployment tracking and DORA metrics; APAC PR cycle time analysis, team planning, and WIP limits are LinearB strengths
  • ! Incident correlation accuracy — Sleuth's APAC deploy impact classification depends on monitoring signal quality; APAC teams with noisy monitoring may get inaccurate APAC change failure rate metrics
  • ! APAC smaller community and ecosystem — Sleuth has a smaller APAC user base than LinearB; APAC teams should evaluate APAC product roadmap velocity and APAC support responsiveness
Context

About Sleuth

Sleuth is a DORA metrics and deployment tracking platform that connects to APAC CI/CD pipelines (GitHub Actions, CircleCI, Jenkins), source control (GitHub, GitLab), feature flag systems (LaunchDarkly, Flagsmith), and monitoring tools (Datadog, PagerDuty, Sentry) to provide APAC engineering teams a unified view of software change activity and its correlation with APAC production incidents.

Sleuth's deployment tracking model — where APAC teams register their APAC services with Sleuth specifying the git repository, deployment trigger (GitHub Actions workflow, CircleCI pipeline), and change categorization rules, and Sleuth automatically records each APAC deployment with the associated commits, APAC pull requests, feature flags changed, and authors — provides APAC engineering managers a complete APAC deployment history showing who deployed what and when across all APAC services without manual deployment logging.

Sleuth's impact analysis — where Sleuth correlates each APAC deployment with monitoring signals (Datadog error rate spikes, PagerDuty incidents, Sentry error volume) in the 30-60 minutes following the APAC deployment, automatically classifying the deploy's impact as healthy, ailing, or unhealthy and calculating the APAC change failure rate metric — provides APAC SRE teams automated APAC deployment-to-incident correlation without manually reviewing Datadog dashboards after each APAC deploy.

Sleuth's DORA metrics dashboards — where APAC engineering managers view deployment frequency (APAC deploys per day/week per service), lead time for changes (APAC commit-to-deploy time), change failure rate (percentage of APAC deploys causing incidents), and MTTR (APAC time from incident to resolution deploy) per team and time period — provide APAC engineering leadership quarterly DORA trend data for benchmarking APAC delivery improvement against the DORA Elite/High/Medium/Low categories.

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