SRE Agent for Cloud Operations: US Retail
Automated the full incident lifecycle, from detection and troubleshooting through root-cause analysis, fixes and postmortems, with human approval preserved at the one point that matters.
Client US-based retail company (anonymised, permission not sought)·Service lines AgenticOps / SRE automation·Stack Google Cloud MCP servers · Agentic AI · Cloud Monitoring · Cloud Logging
The Challenge
A US retail company running production infrastructure on Google Cloud had cloud operations that depended on manual effort at every stage of the incident lifecycle.
Every stage was manual
Monitoring, troubleshooting, fixing and root-cause analysis all required an engineer. Every incident meant someone watching for it, diagnosing it, fixing it, then writing the postmortem by hand.
Response quality depended on who was on call
Outcomes varied with the individual engineer's experience and availability rather than with the severity of the incident.
It showed up in the numbers that matter
Slow, person-dependent response translated directly into extended recovery times and avoidable downtime.
Our Approach
Automate the toil, keep the human at the decision point.
TechTrapture designed and built an AgenticOps platform, an SRE Agent running on Google Cloud's own MCP servers, that automates the incident lifecycle end to end.
Everything around the decision is toil and should be automated. The decision to change production is not. Approval before a fix lands is preserved deliberately, and it is the only manual step left in the loop.
What We Built
Continuous monitoring and detection
The agent watches production infrastructure continuously and detects issues without waiting for a human to notice them.
Automated troubleshooting and root-cause analysis
Diagnosis runs automatically, correlating signals to establish likely cause rather than simply raising an alert.
Alerts that reach both audiences
Root-cause and business-impact emails go straight to engineering and business stakeholders, so the people who need to act and the people who need to know are informed at the same time, not after a manual write-up.
Fixes applied, gated on human approval
The platform can apply fixes automatically, but only after a human approves. That gate is the safety design, not a limitation.
Postmortems as part of the workflow
Postmortem reports are generated as part of the same workflow rather than written up separately afterwards.
The Outcome
| Before | After |
|---|---|
| Manual, reactive firefighting | Agentic, largely automated incident workflow |
| Detection dependent on someone noticing | Continuous automated monitoring and detection |
| Communication after a manual write-up | Engineering and business stakeholders alerted immediately |
| Postmortems written by hand, inconsistently | Consistent documentation at no added engineering effort |
| Response quality varied by who was on call | Consistent handling, with human oversight at the approval point |
Before
Manual, reactive firefighting
After
Agentic, largely automated incident workflow
Before
Detection dependent on someone noticing
After
Continuous automated monitoring and detection
Before
Communication after a manual write-up
After
Engineering and business stakeholders alerted immediately
Before
Postmortems written by hand, inconsistently
After
Consistent documentation at no added engineering effort
Before
Response quality varied by who was on call
After
Consistent handling, with human oversight at the approval point
- Agentic operations in a customer production environment·
- MCP orchestration·
- Human-in-the-loop safety design·
- Google Cloud MCP server integration
What It Runs On
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