# Amazon — How Circle K accelerated DevOps incident triage to under 15 minutes with Amazon Bedrock

- Company: Amazon (amazon.com)
- Announced: 2026-11-02T17:00:58+00:00
- Category: not stated
- Coverage: not counted
- Announcement: no
- Group: routine
- Source: https://aws.amazon.com/blogs/machine-learning/how-circle-k-accelerated-devops-incident-triage-to-under-15-minutes-with-amazon-bedrock/
- Record: https://forck.live/items/30597-how-circle-k-accelerated-devops-incident-triage-to-under-15-minutes-with
- Subject: Bedrock / Nova

Circle K built an automated incident triage system on Amazon Bedrock that investigates alerts autonomously and posts a structured summary to Slack within minutes, cutting mean triage time to under 15 minutes. The convenience and fuel retailer operates more than 17,200 stores across 27 countries, and its cloud-native infrastructure supports point-of-sale, loyalty and EV charging applications on AWS, so growing alert volume had made manual investigation a bottleneck. Previously, an engineer spent 45–60 minutes pulling logs, checking service health and correlating symptoms across tools before remediation could start. The team chose Amazon Bedrock over open source agent frameworks on self-managed infrastructure because it avoided owning model hosting, prompt versioning, tool orchestration and security controls, and fit existing IAM policies, VPC configurations and logging pipelines. Amazon Bedrock Knowledge Bases handled ingestion and retrieval of internal product cards, so no separate vector database was needed, and the team says Amazon Bedrock does not share customer data with model providers or use it to train foundation models. The initial architecture used Amazon Bedrock Flows, with a Grafana alert publishing to Amazon SNS, forwarding to Amazon SQS, and a Lambda function invoking the Flow, which runs specialized agents in parallel; the team later migrated to Amazon Bedrock AgentCore. Circle K reports a 67–75 percent reduction in mean triage time based on its internal incident-response metrics.

## Evidence

Verbatim from https://aws.amazon.com/blogs/machine-learning/how-circle-k-accelerated-devops-incident-triage-to-under-15-minutes-with-amazon-bedrock/:

> This post was co-written with Marek Klatowicz, Cloud DevOps Engineer at Circle K.
> 
> Many DevOps teams know the incident triage pattern: An alert fires, and before anyone can fix the problem, an engineer spends 45–60 minutes figuring out what happened. They pull logs, check service health, and correlate symptoms across a handful of tools. All of this happens before remediation can begin.
> 
> At Circle K, this challenge scaled with the business. The company operates more than 17,200 convenience and fuel retail stores across 27 countries. Behind the storefronts, a cloud-native infrastructure supports point-of-sale systems, loyalty applications, and electric vehicle (EV) charging applications running on AWS. As the company expanded its digital operations, the triage overhead grew with it. More services meant more alerts, and each one required the same manual investigation before remediation could begin.
> 
> To address it, Circle K built an automated triage system using Amazon Bedrock , a fully managed service that makes foundation models (FMs) available through a single API. For model availability by AWS Region, refer to Supported models by AWS Region in Amazon Bedrock .

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