DEVOPS
Edge Canary: Dual Guard on Error Budget and Invocation Cost Spike
During a Cloudflare canary, watches both Honeycomb error budget and Cloudflare invocation/CPU metrics; pauses the rollout if either errors regress or per-request cost spikes.
How it runs
The automated pipeline, trigger to output.
- TriggerSchedule tick through canary window
- ActionQuery Honeycomb error-budget burn rateHoneycomb
- ActionQuery Cloudflare invocations and CPU per requestCloudflare
- LogicErrors regressed OR cost-per-request spiked?
- ActionPause Cloudflare gradual deploymentCloudflare
- OutputAppend decision to BigQuery and alert SlackBigQuery
What it does
Protects an edge rollout against two failure modes at once. On each check it reads the canary's error-budget burn from Honeycomb and the canary's invocation count and CPU-time-per-request from Cloudflare. Either a reliability regression or an unexpected cost/CPU spike (e.g. an accidental hot loop) trips the guard and pauses the deployment, so a version that is "correct but ruinously expensive" gets caught too.
When to use it
Use for edge functions where a regression can be silent on errors but visible on cost — runaway CPU time, retry storms, or a new dependency that doubles invocations. It pairs reliability and spend guardrails in one rollout gate.
How it works
- 1A schedule fires repeatedly through the canary window.
- 2The workflow queries Honeycomb for the canary error-budget burn rate.
- 3It queries Cloudflare analytics for canary invocations and CPU time per request.
- 4A logic branch trips if either errors regress or cost-per-request exceeds the stable baseline by your margin.
- 5On a trip it pauses the Cloudflare gradual deployment.
- 6It appends the full decision row (both metrics, action taken) to a BigQuery audit table and alerts Slack.
Set it up
What you configure once, before turning it on.
- 1Connect HoneycombDistributed traces and queries.
- 2Connect CloudflareWorkers, Pages, R2, KV — the edge stack.
- 3Connect BigQueryDatasets, queries, schemas.
- 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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