SysDev Automation
CI/CD workflow analytics that delivery teams can defend in planning.
We review how your pipelines emit lead time, build health, and recovery signals — then hand you a findings brief you can act on.
Flagship engagement
Delivery Pipeline Analytics Assessment
A two-to-three-week review of the timestamps, failure labels, and deploy records your CI/CD already produces. Built for engineering managers and release leads who need measurement they can trust before the next planning cycle.
Related work
Other ways teams work with us
Each engagement stays close to application analytics for CI/CD — clinics, focused build reviews, or a quarterly retainer when you want ongoing signal checks.
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Release Metrics Clinic
A half-day facilitated session that helps delivery teams agree on which release metrics matter, how to read them honestly, and which vanity counters to retire.
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Build Health Review
Focused examination of flaky tests, queue wait times, and failed-job patterns that distort your delivery analytics and slow feedback to developers.
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Quarterly Delivery Analytics Retainer
Recurring advisory support: monthly metric reviews, release post-mortem signal checks, and guidance when you change pipelines or add new product lines.
From recent work
What clients noticed after the first review
“The pipeline assessment showed our deploy-success metric was counting retries as separate wins. We corrected the definition before our next planning cycle.” Hyejin Park · Engineering manager · Delivery Pipeline Analytics Assessment
Field notes
Guides from delivery analytics practice
Short pieces on lead time segments, flaky-test noise, and recovery clocks — written for people who own release decisions.
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Recovery signals after a bad release
Mean time to recovery is only as good as the clocks you start when something goes wrong. A look at incident markers that survive contact with real on-call practice.
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What to ask in a pipeline telemetry walkthrough
A field checklist for the first hour with a new delivery team: where the logs live, who owns each stage, and which clocks actually tick.
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Flaky tests and crooked deployment charts
Unstable suites inflate change-failure rates and train teams to ignore red builds. Here is how to isolate noise before you trust the analytics.