Financial technology / resilience

Automated data recovery

A replay and validation workflow that turned multi-day manual data recovery into a monitored, controlled process.

Leadership experience

Experience of BitIT leadership at a leading global financial-technology firm

Engineering leader over a six-month build inside a larger data platform

Delivered as an employee of a leading global financial-technology firm, not under a BitIT contract.

Context

The operating situation

A trading data platform where missing events had to be found and replayed by hand. Every hour of manual recovery extended customer exposure and pressed against contractual service levels.

Challenge

The operating problem

Missing-event recovery relied on manual source identification and replay, delaying restoration and increasing operational exposure.

Approach

Decisions that shaped it

  • Detected sequence gaps through writer services and Prometheus telemetry.
  • Automated source identification, replay coordination, and recovery-state management.
  • Ran post-recovery validation and escalated remaining exceptions for human action.

Solution

What was delivered

An automated replay and validation pipeline: sequence gaps detected in real time, sources identified and replayed without hand-holding, recovery state tracked, and integrity validated after the fact with anything unresolved escalated to a person.

Outcome

Documented outcome

Routine recovery dropped from 48-72 hours to under 30 minutes within the documented platform workflow.

The 48-72 hours to under 30 minutes improvement is bounded to the documented platform recovery workflow. It is not an organisation-wide availability, recovery, or uptime claim, and the former employer stays anonymized.

Controls

What kept it safe to operate

  • Post-recovery integrity validation, so a fast recovery is also a correct one.
  • Exceptions escalate to a human instead of being silently absorbed.
  • Recovery state is explicit and observable rather than inferred from logs.

Discovery

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