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ewake · production6 signals today

Triaged · noise

search-indexer disk usage above 85%

87.4% used · 12.6% free · 30 min

Datadog Alert · env:production service:search-indexer

Prior firings11 in 30 daysBack under 70%9 minCustomer impactnone

What ewake did

✓Matched 11 prior firings
✓Checked the 4:00 AM merge job
✓Compared the threshold to staging
✓Closed it without paging

ewakeapp#prod-reliability

Marked as noise

Nobody paged. This monitor has never once caught a real problem.

Open investigation in ewakeTune this monitor

Was this noise?👍👎42

Ewake in action

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As soon as an alert fires or ewake catches a faulty release, it starts investigating autonomously: pulling and enriching context, reasoning across signals, and determining the root cause, impact, and recommended next steps.

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ewakeapp13:42

Investigated · cause found

Root cause found for the global 502 spike

Twenty-seven minutes from the CPU spike to a named cause, with the obvious explanation ruled out.

edge-gateway CPU at 100% across every region

4% → 100% CPU · all regions · 13:42 UTC

Tags: env:production service:edge-gateway

Datadog Alert

Root causemalformed WAF ruleConfidence96%

ruled outDDoS attacknetwork outageupstream dependency

What happened: CPU on every edge machine jumped from a few percent to 100% within about a minute of a new rule going live, and stayed pinned there for the next 27 minutes.

Customer impact: Around 82% of requests across the network came back as 502s until the rule was pulled, effectively a global outage for anything sitting behind it.

Root cause: The new rule shipped with .*(?:.*=.*). Its nested quantifiers triggered catastrophic backtracking on ordinary requests, turning routine traffic into a CPU-exhausting workload on every machine that evaluated it.

Open investigation in ewakeSee the evidence

Maya13:44

Wasn't this just a DDoS? The traffic graphs looked like one.

ewakeagent13:44

Request volume barely moved before the spike; it's processing time per request that exploded, not the number of requests. Every crashing worker's trace names the same WAF rule ID, and disabling only that rule brings CPU back to baseline just as fast as the global kill switch did.

Did this answer it?👍 Yes👎 No46

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ewakeapp11:08

Fix ready · awaiting review

A pull request, not a suggestion

Scoped to payment-api, tested against production, and stopped at your rule.

#291 Restore connection pool size on payment-api

ewake/revert-4821 → main · 1 file · +1 −1

Opened by ewake

services/payment-api/db.py

def get_pool():

- return Pool(max_size=8, timeout=2.0)

+ return Pool(max_size=32, timeout=5.0)

# reverts #4821: pool waits accounted for the p99 rise

✓unit tests412 passed✓build2m 14s✓policy checkwithin remit

The pool is back at max_size=32, where it sat before #4821. I ran the hypothesis against live traffic first: replaying the last hour at the old pool size clears the waits, at the new one it does not.

Blast radius is one file and one service. Nothing else reads this pool, and the change needs no migration and no restart of anything downstream.

Stopped hereauto-merge is off for payment-api, your rule, waiting on one approval.

Review PR #291Open investigation in ewake

Was this the right fix?👍 Yes👎 No73

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ewakeapp06:41

Caught on day 3

Regression from a release

checkout-api error rate drifting since deploy #4821

0.41% → 1.94% · 2 days · no monitor firing

Tags: env:production service:checkout-api

Release watch

deploy #4821 · watched since Monday

Day 1

Day 2

Day 3

Day 4

Day 5

From 03:10 today the error rate on checkout-api is running four times its baseline, and every failure is on the code path #4821 changed. Nothing has crossed a threshold yet, so no monitor has fired and nobody has been paged.

I compared it against the two releases either side of it: same traffic, same hosts, same hour of day. Only this one drifts. At the current rate it reaches the 2% alert threshold some time tomorrow afternoon, during peak, on the checkout path.

I have opened an investigation and I am watching it every five minutes.

Open investigation in ewakeSee the release

Was this worth flagging?👍 Yes👎 No53

Escalate

Only ping a human when one is needed.

When human judgment is required or there is customer impact, ewake wakes the on-call, with the investigation, the evidence, and the recommended action already attached.

ewakeapp11:12

Escalated · paged

Potential incident: review now and consider paging on-call

The fix needs a schema migration, outside what you have let me do on my own.

checkout-api 5xx rate above 2%

6.8% of requests · 14 min · investigation complete

Tags: env:production service:checkout-api

Datadog Alert

MPaged@maya chen

I can revert the config, but the revert alone leaves the orders written in the last fourteen minutes in a state the new schema does not read. Repairing them means an ALTER TABLE on orders, and migrations are on your list of things I do not run.

Declare an incidentOpen investigation in ewake

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“ewake proved extremely useful during production investigations, consistently pointing us to the right root cause and saving precious time, especially during on-call.”

Piyush S.

Lead Software Engineer, Brevo

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It shows its work. Every conclusion arrives with a confidence score, the evidence behind it, and what it ruled out along the way. Your engineers can challenge it in the thread and get the reasoning back. This is identical in every deployment.

It acts inside limits you set. You decide what it can do on its own, what needs an approving human, and what it should only ever suggest. Write access is off until you turn it on, per service. Auto-merge is off by default. Once a pattern has been resolved with your team and your rules allow it, ewake can handle a repeat on its own and tell you what it did. Your rules are the same rules whichever way you deploy.

Never. Your telemetry, your code, and your incidents are never used to train or fine-tune any model, in any deployment model, at any tier. There is no exception and no opt-out to manage.

It stays in Europe, always. Nothing crosses the Atlantic. On SaaS, telemetry is processed on EU infrastructure and raw data is discarded after analysis. On BYOC and on self-hosted, raw telemetry never leaves your own environment at all. Full breakdown of what crosses which boundary on our security page.

Yes. Three models: our EU SaaS, BYOC inside your own cloud account, and a gateway inside your own network perimeter for on-premise and hybrid estates.

Read-only by default, in every deployment. It reads metrics, logs, traces, and code to investigate, and it changes nothing in your infrastructure unless you grant write access. Write access is scoped per service, revocable, and gated behind your approval rules. The full permission list is published in our docs.

Your existing stack. Observability (Datadog, Grafana, Prometheus and others), alerting (PagerDuty, OpsGenie), code (GitHub, GitLab), and chat (Slack). No new tooling, no custom instrumentation, no code changes. The integration list is the same whichever way you deploy.

On SaaS, minutes. Connect your tools, pick your Slack channel, and ewake starts analysing. BYOC and self-hosted add one infrastructure step, which we run with your platform team. After that first step, day-to-day operation is identical across all three.

SOC 2 Type II certified, GDPR compliant with EU data residency, ISO 27001 controls aligned. The same controls apply to every deployment model. DPA, sub-processor list, pen-test report, data-flow diagram, and our contract annex covering data location, audit rights and exit are available on request. Visit trust.ewake.ai.