Data pipelines, API integrations, and system connectivity
Partial API failures corrupt more pipelines than outages do. Here's how to isolate bad records and keep bad batches from spreading downstream.
Most integration outages trace back to an API change nobody flagged. Here's how a real data contract stops that from happening again.
When a vendor renames a field or restructures a response, a well-built mapping layer contains the damage. Here is how to design one that actually holds.
Naive two-way sync creates infinite update loops. Here is how to design origin tagging, debouncing, and idempotent writes that actually hold.
Passing tests do not catch data drift. Here is how silent sync failures happen and how to build reconciliation that actually catches them.
A practical guide to designing idempotency keys so retried API calls never double process orders, payments, or webhook events.
Polling and nightly batch jobs both fall apart at scale. Here is how log based change data capture keeps downstream systems fresh without locking anything.
The bad records reaching your production tables are a design failure, not a source failure. Here is how to build a quality gate that catches them at ingest.
A practical guide to building a replay mechanism for a data integration that survives outages without duplicating processed events or losing genuinely failed ones.