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LinearB

by LinearB

Engineering intelligence platform that connects to APAC GitHub, GitLab, and Jira to automatically calculate DORA metrics (deployment frequency, lead time for changes, MTTR, change failure rate) and team productivity signals — APAC engineering managers and VPs use LinearB to benchmark APAC team delivery performance and identify bottlenecks without manual data collection.

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AIMenta verdict
Recommended
5/5

"Engineering intelligence platform tracking DORA metrics and APAC team productivity — measures deployment frequency, lead time, MTTR, and change failure rate from GitHub/GitLab. APAC engineering leaders use LinearB to improve delivery performance with data-driven team planning."

Features
6
Use cases
3
Watch outs
3
What it does

Key features

  • DORA metrics — automatic APAC deployment frequency, lead time, MTTR, CFR calculation
  • PR cycle time breakdown — APAC coding/review/merge/deploy phase bottleneck identification
  • GitHub/GitLab/Jira — native APAC integration without pipeline instrumentation
  • APAC benchmark comparison — Elite/High/Medium/Low DORA performance classification
  • WorkerB — APAC WIP limits, PR aging alerts, Slack notifications for APAC teams
  • Investment distribution — APAC feature vs bug vs tech debt work time allocation
When to reach for it

Best for

  • APAC engineering directors and VPs measuring team delivery performance — LinearB provides objective DORA metrics without requiring APAC engineering teams to manually report productivity
  • APAC engineering managers identifying PR cycle time bottlenecks — phase breakdown shows which APAC review or coding step is the primary constraint per team
  • APAC organizations scaling from 20 to 200+ engineers — LinearB's APAC team benchmarking and planning features scale with APAC engineering organization growth
Don't get burned

Limitations to know

  • ! GitHub/GitLab-centric — LinearB requires APAC source control integration; APAC teams on Azure DevOps repos or self-hosted APAC Bitbucket may have limited metric coverage
  • ! APAC metric gaming risk — DORA metrics visible to APAC management can drive metric optimization rather than genuine APAC delivery improvement; APAC leaders should use as diagnostic not performance KPI
  • ! Pricing scales with APAC team size — LinearB's commercial tiers price per active APAC developer; APAC organizations with large engineering headcounts evaluate total APAC contract cost
Context

About LinearB

LinearB is an engineering intelligence platform that automatically measures DORA metrics and engineering productivity signals for APAC software teams by connecting to GitHub, GitLab, Bitbucket, and Jira — analyzing APAC pull request cycle time, deployment frequency, mean time to restore, and change failure rate without requiring APAC engineers to manually track or report metrics.

LinearB's DORA metrics calculation — where LinearB ingests APAC git history, pull request metadata, CI/CD deployment events, and Jira issue data to calculate the four DORA metrics per APAC team, service, and repository, classifying each APAC team into Elite/High/Medium/Low DORA performance categories against APAC industry benchmarks — provides APAC engineering leaders an objective, automatically-updated measurement of APAC delivery performance without relying on self-reported team productivity surveys.

LinearB's pull request cycle time breakdown — where LinearB decomposes APAC PR cycle time into coding time (time from first commit to PR open), review time (time from PR open to first review), review-to-merge time (time from first review to merge), and deploy time (time from merge to production deployment), identifying which APAC cycle time phase is the primary bottleneck for each APAC team — provides APAC engineering managers specific, actionable APAC improvement targets (e.g., "APAC payments team review time is 2.3 days vs 0.8 days APAC benchmark") rather than aggregate cycle time metrics.

LinearB's team planning integration — where APAC engineering managers use LinearB's WorkerB features to set per-engineer work in progress limits, automatically detect APAC PRs that have been waiting for review more than a configurable threshold, and receive Slack notifications when APAC PRs are at risk of cycle time violation — provides APAC engineering teams lightweight process enforcement that reduces APAC PR aging and improves APAC review turnaround without heavyweight APAC project management overhead.

Beyond this tool

Where this category meets practice depth.

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