POSHub Self Healing
Built a system that detects integration failures before merchants notice them.
Problem
POSHub reliably transmits changes from POS systems to marketplaces and other platforms. But there was no way to know if those changes actually arrived correctly on the other side. Menu mismatches, price discrepancies, and store status failures were only discovered when merchants called to complain.
What I built
A self-healing and automated verification framework that continuously samples and validates integration state.
Instead of verifying every event (which would overwhelm the system at 1000 plus events per minute per location), the system samples a configurable number of events, compares expected state in POSHub against live state on the destination platform, and triggers automated retries with exponential backoff when mismatches are found.
Failed authentications are healed automatically via token refresh. Alerts are deduplicated within a 10-minute window to prevent notification flooding. Severity is classified as INFO, WARNING, or CRITICAL with different routing per level.
Each integration exposes a confidence score, for example Uber 98 percent, POS connectivity 72 percent, so support teams can act before merchants escalate.
Key decisions
Sampling over full verification for scalability. Confidence scoring for proactive support. Alert deduplication to prevent noise.
Outcome
Target: detect 95 percent of propagation failures within 5 minutes. Target: 90 percent auto-recovery rate for transient failures. Target: reduce menu mismatch support tickets by 50 percent.