DEVOPS
Cloudflare Worker Cold-Start Regression Gate on Deploy
On every Cloudflare Worker deploy, compares post-deploy cold-start p95 against the previous deploy tag's baseline and blocks/flags the release in GitHub if latency regressed past…
How it runs
The automated pipeline, trigger to output.
- TriggerCloudflare Worker deploy webhookCloudflare
- ActionFetch new version cold-start p95Cloudflare
- ActionLoad previous deploy tag baselinePostgres
- LogicRegression if delta exceeds threshold
- ActionSet failing GitHub commit statusGitHub
- OutputAlert team in Slack with tag deltaSlack
What it does
Each time a new Worker version is deployed, this workflow measures the cold-start p95 for the freshly deployed version, looks up the cold-start baseline stored for the previous deploy tag, and decides whether the new release introduced a latency regression. If it did, it posts a failing commit status on the triggering GitHub commit and alerts the team; if not, it records the new tag as the accepted baseline.
When to use it
Use it when you ship Workers frequently and want an automatic guardrail so a code change that doubles cold-start time never silently reaches production. It turns "someone noticed prod felt slow" into a deploy-time gate tied to the exact tag that caused it.
How it works
- 1A Cloudflare deployment webhook fires with the new version and deploy tag.
- 2Query Cloudflare analytics for the new version's cold-start p95 over a short bake window.
- 3Read the stored baseline for the prior deploy tag from Postgres.
- 4Branch: if p95 exceeds baseline by more than the allowed percentage, mark it a regression; otherwise persist the new baseline.
- 5On regression, set a failing GitHub commit status and notify Slack with both tags and the delta.
Set it up
What you configure once, before turning it on.
- 1Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect GitHubRepos, issues, pull requests, actions.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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