An observability approach for banking and securities: layered collection, trace correlation, alert governance, and minute-level root cause analysis, all within compliance and data-security constraints.
Three Hard Constraints
Observability in finance isn't like a consumer internet company. Three constraints shape everything:
- Compliance: MLPS 2.0 and the Data Security Law require log redaction, access auditing, and explicit retention windows. You can't just "collect everything and figure it out later."
- High availability: core transaction paths demand 99.99% uptime, and the observability platform can't become a new single point of failure.
- Network isolation: production is isolated from office networks and data can't leave the production zone, so collection and storage must live in the same data center.
These constraints drive the design, not the other way around.
Layered Collection and Correlation
We recommend three layers:
- Application: OpenTelemetry agents auto-instrument trading, accounting, and payment systems to produce traces and metrics.
- Middleware: collect Kafka, Redis, and database metrics plus slow-query logs, aligned on the same timeline as traces.
- Infrastructure: host, container, and network metrics feed into one monitoring view.
Correlation is the whole game: a transaction's trace ID flows through logs, metrics, and alerts. When an alert fires, you jump straight to that trace, then drill into the specific SQL or downstream call — turning root-cause analysis from hours into minutes.
Alert Governance
Financial systems generate a flood of alerts; the last thing you want is alarm fatigue. Our recommendations:
- Tiered routing: P0 (money-related) goes to phone + SMS, P1 to IM, P2 to the dashboard only. Don't treat everything equally.
- Deduplication and silencing: same-kind alerts fire once per five minutes; release windows auto-silence known noise.
- Context-rich alerts: every alert carries the trace ID, related logs, and the last deployed version, cutting back-and-forth during incidents.
Compliance and Data Security
- Redaction: ID numbers, card numbers, and phone numbers are masked at the collection agent — raw values never reach storage.
- Auditing: every search and export is logged — who, when, and what — so access is fully traceable.
- On-prem deployment: data never leaves the production network, satisfying data-residency requirements.
- Retention tiers: hot data 7 days, warm 90 days, cold data archived per regulatory requirements, tiered automatically.
The end goal of financial observability isn't just visibility — it's being able to find the root cause within the context of a single transaction, in a way that stays compliant the whole time. Hit all three and the platform is actually doing its job.