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Stefan KolesnikowiczIncident Response
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Rootly App 1:30 PM
Customer cannot complete purchase
Sharp drop in successful transactions, likely caused by recent changes in the payment authorization flow. Eng team investigating.
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AR
Allen Ruiz 1:31 PM
@Rootly show me your root cause analysis
Rootly App 1:31 PM
Investigating…Root cause analysis
Deploy v2.41.0 of payments-service at 14:30 UTC introduced a connection leak on the payments Postgres primary, exhausting the pool. Error rate rose from 0.2% to 18% within two minutes.
High confidenceSuggested fix: roll back to v2.40.3
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Rootly App 1:45 PM
Checkout failures: customers unable to complete purchase
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Allen Ruiz 1:45 PM
We're seeing a spike in failures in the past ~30 minutes. Customers are getting stuck on the checkout "place order" step.
FI
Florence Ito 1:46 PM
@Rootly looks familiar. Are there any related incidents open right now?
Rootly App 1:46 PM
#incident-20250915-payment-gateway-timeouts was opened at 1:10 PM.
- Status Investigating elevated checkout failure rate
- Suspected cause Upstream payment provider timeouts after deploy
v2025.09.15 - Next steps @Alex is rolling back checkout-api
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Tyler Moss 1:56 PM
@Rootly I joined late. What's going on?
Rootly App 1:56 PM
Here's what you missed
- Customers have been unable to complete purchases due to checkout failures.
- The cause is intermittent timeouts with our payment provider's API, starting about 45 minutes before detection.
- Alex is rolling back, and Florence just updated the status page.
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Typeis Security - When
Severityis SEV0 - When
Serviceis Updated - When
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Some customers are unable to check out. We've identified the issue and are working on a fix. Next update in 30 min.
Sent to 2 audiences
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incident-20250915-customer-cannot-checkoutPostsFilesIncident Dashboard
Rootly App 1:45 PM
Checkout failures: customers unable to complete purchase
UpdateAction ItemsAssign RolesEscalate
Zoom Jira
AR
Allen Ruiz 1:45 PM
We're seeing a spike in failures in the past ~30 minutes. Customers are getting stuck on the checkout "place order" step.
FI
Florence Ito 1:46 PM
@Rootly looks familiar. Are there any related incidents open right now?
Rootly App 1:46 PM
#incident-20250915-payment-gateway-timeouts was opened at 1:10 PM.
- Status Investigating elevated checkout failure rate
- Suspected cause Upstream payment provider timeouts after deploy
v2025.09.15 - Next steps @Alex is rolling back checkout-api
FI
Florence Ito 1:47 PM
@Rootly can you help me draft an external status page update?
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Some customers are unable to check out. We've identified the issue and are working on a fix. Next update in 30 min.
Sent to 2 audiences
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JT
JJ Tang 11:29 AM
@Rootly what action items did I forget to document? Assign them to Jamie Baker.
Rootly App 11:29 AM
The undocumented action items from this thread are captured and assigned to Jamie Baker.
High priority
- 1Page Data Platform on-call for DLQ replayJamie B.
- 2Confirm 11 missing fields in v5 mappingJamie B.
- 3Re-update status page, which still shows resolvedJamie B.
- 4Notify affected merchantsJamie B.
Medium priority
- 5Add an Elasticsearch field count alertJamie B.
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Rootly App 3:15 PM
Investigating…What I've found so far
Likely root cause
- A transient spike in message production is the primary trigger, with the producer rate up to 31 messages inside the alert's 5-minute window.
- Network latency may have contributed, with a spike to 975.63 ms.
Recommendations
- Review the alert threshold, which looks sensitive next to the documented warning level.
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API Latency Degradation (INC-2034) Edited just nowShareExport
API Latency Degradation (INC-2034)
Summary
Between 14:03 and 15:45 UTC on July 9, the public API experienced elevated latency and intermittent 5xx errors across all regions. A runaway Redis connection pool exhausted backend thread workers, leading to cascading timeouts in downstream services.
Root cause
A deployment on July 8 introduced a usage-metrics feature that stored high-frequency user events in Redis.
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9:41
Rootly · nowHigh: Redis Engine CPU High
production-redis-002 · You're on call for Messaging
Slide to ack‹ #jetdhv · Leader · High
Redis | Engine CPU High production-redis-002 [PRODUCTION]
DetailsTimelineGroupPayload
Summary Generated 10:22 AM
Redis CPU on production-redis-002 spiked to 96% after a message queue storm from one customer's rescheduled jobs. Messaging updates are delayed for several customers, and CPU is falling as mitigations land.
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What I've found so far
Likely root cause
A transient spike in message production is the primary trigger, at 23:09 UTC within the alert's 5-minute window.
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Frequently asked questions
Everything you need to know about Incident Response.
What is Rootly Incident Response?
Rootly enables engineering teams run the entire incident inside Slack or Microsoft Teams — declaring, assigning roles, coordinating the fix, updating stakeholders, capturing the timeline, and more. Because it's part of one platform, each incident inherits context from on-call, the service catalog, and past incidents, so response starts a step ahead.
Does Rootly work in both Slack, Google Chat, and Microsoft Teams?
Yes. The full incident lifecycle runs natively in Slack, Google Chat, and Microsoft Teams—declaration, coordination, comms, AI assistance, and retrospectives—without switching to a separate interface.
What can Rootly's AI agent actually do?
Chat with Rootly and the agent answers questions in natural language and can take action as your user, within your permissions—paging, changing severity or status, managing action items, and drafting comms. It also offers catchup summaries for late joiners, incident summaries, and a meeting scribe that captures bridge-call transcripts. It confirms destructive actions before running them.
How does Rootly keep stakeholders updated during an incident?
Rootly automates stakeholder, leadership, and customer communication, and keeps status pages current as the incident changes state—so responders stay focused on the fix instead of writing updates.
Is my data safe with Rootly AI?
Yes. Sensitive information like links, emails, and passwords is redacted before being sent to AI providers, AI access respects incident privacy settings, and Rootly never uses customer data to train models for other customers. Teams can also bring their own LLM keys for single-turn features.
How does Rootly handle the post-incident process?
Rootly captures the incident timeline live and drafts the retrospective from it — summary, impact, root cause, mitigation, and a curated timeline, all editable. Action items are tracked to completion. Rootly uses blameless retrospectives, not postmortems.
Can I manage incident response programmatically?
Yes. Rootly offers a full API and Terraform provider, plus an MCP server, so you can configure and drive incident response as code and through your AI tooling.