Amazon MQ Tooling

As one of the lead Amazon MQ subject matter experts, I owned internal operational tooling built with React on AWS—closing reliability gaps engineers hit during live investigations and shaping features around how support actually triages brokers.

That meant prioritizing defect work that produced wrong signals or brittle flows, shipping production-aligned affordances such as fast paths into broker VPC, subnet, and network ACL context plus working console links to broker EC2 instances, and iterating with stakeholders using real incidents so the UI stayed trustworthy under pressure.

Internal support relied on Amazon MQ–related tooling that had accumulated bugs and gaps. Troubleshooting was slow and repetitive, which stretched incident response and pulled engineers away from higher-value customer work.

As one of the lead Amazon MQ subject matter experts, I took initiative to own improvements to that AWS tooling so it was more reliable and useful: fix defects, add capabilities that matched real troubleshooting workflows, and measurably shorten time-to-diagnosis for teams globally.

Prioritized and fixed tooling bugs that caused wrong signals, broken flows, or extra manual steps.

Shipped new features aligned with how engineers debug MQ in production, including clearer paths into broker networking—VPC, subnet, and access control lists—and functioning hyperlinks to broker EC2 instances in the AWS console.

Collaborated with stakeholders to validate behavior against real incidents and iterated based on feedback.

The improvements saved over 1,000 minutes of troubleshooting time per month globally—time engineers could reinvest in other customers and deeper technical work instead of repetitive manual triage.

That efficiency showed up as both engineering throughput and downstream revenue impact, because faster diagnosis and fewer tooling dead-ends reduced drag on customer-impacting investigations.