Project Case Study
LegalTech Workflow Reliability Improvements
Reliability improvements for finance-critical LegalTech workflows—focused on observability, safer releases, and faster incident triage so operations teams can trust the system.
Context
Workflow disruptions were impacting critical finance operations and integrations. Even small failures can create rework, delays, and high-pressure firefighting—especially around orchestration, batch jobs, and data movement.
Problem
- Low observability: failures were hard to pinpoint; teams relied on manual checks.
- Inconsistent error handling: failures surfaced late and lacked actionable context.
- Release risk: changes shipped without consistent readiness checks.
- Slow triage: logs existed, but didn’t answer “what broke, where, and why” quickly.
Approach
- Monitoring + alerting: clear health signals (success/failure, latency, retries, backlogs).
- Structured error patterns: standardised exceptions + added step/context + correlation ids.
- Runbooks: “first 15 minutes” triage steps so support can act fast and consistently.
- Release readiness gates: config validation, smoke checks, rollback readiness.
- Learning loop: removed repeat failure modes and tuned alerts to reduce noise.
Key Reliability Decisions
- Correlation everywhere: trace workflow execution end-to-end.
- Actionable alerts: include “what to check next”, not just “it failed”.
- Fail-safe defaults: safer behaviour when configuration is missing/mismatched.
- Operability is product quality: reliability treated as delivery work, not “support work”.
Learnings
Operability must be designed in. If it’s bolted on after go-live, you get a system that “works” but can’t be supported calmly when it matters most.
Next Enhancements
- Proactive drift detection for configuration mismatches before workflows run.
- Self-serve diagnostics for ops teams (health, last failures, recommended actions).
- SLO reporting to track reliability trends and prioritise fixes by impact.