Case study · Tier-1 U.S. Banking Institution
Automating observability rollout across thousands of services
Manual APM agent installation could not keep pace with a microservices estate measured in thousands. Automated deployment brought deep application-server metrics to every node — with zero manual intervention.
- of microservices & servers covered
- 1000s
- of microservices & servers covered
- manual agent interventions
- Zero
- manual agent interventions
- observability rollout timeline
- Faster
- observability rollout timeline
- application-server metrics at scale
- Deeper
- application-server metrics at scale
The challenge
The bank's application portfolio spanned thousands of microservices and servers, but observability coverage was patchy because every APM agent rollout meant slow, error-prone manual installation windows.
Blind spots slowed incident triage, and regulators expected evidence of operational visibility that ad-hoc coverage simply could not provide.
What we did
- 01
Deployment architecture
We designed an automated agent-deployment pipeline covering VMs, containers, and Kubernetes workloads with consistent tagging for service-level rollups.
- 02
Infrastructure-as-code rollout
Agent installation, versioning, and configuration were codified and pushed through existing CI/CD gates — turning a months-long manual program into a repeatable pipeline stage.
- 03
Standardized dashboards & alerting
Deep application-server metrics flowed into standardized dashboards, giving every squad the same view of health, latency, and dependency maps.
- 04
Governance & drift control
Version drift, orphaned agents, and coverage gaps became automated reports — keeping the estate observable as it kept growing.
More results
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