In high-scale distributed systems, failures are not a possibility—they are a certainty. Whether it’s an unexpected traffic surge, cascading micro-service timeouts, or downstream database contention, resilience must be architected from day one.
Drawing from hands-on production experience building and scaling high-throughput backend services across fintech and travel-tech, this talk deconstructs real-world outages and how to engineer deterministic recovery. We will examine practical architectural blueprints for fault isolation, graceful degradation, and self-healing systems natively on GCP.

Key Takeaways for Attendees:
Root-Cause Deconstruction: How cascading failure loops and thundering herds propagate across microservices—and how to stop them at the network boundary.
Observability in Action: Leveraging Google Cloud Operations Suite (formerly Stackdriver)—using Cloud Trace, distributed telemetry, and structured Cloud Logging to identify tail-latency degradation before users notice.
Resilience & Backpressure Patterns: Implementing distributed circuit breakers, exponential backoff with jitter, and dead-letter queue (DLQ) triage using Cloud Pub/Sub, Eventarc, and Cloud Run / Cloud Functions.
Automated Self-Healing & Traffic Management: Utilizing Google Cloud Load Balancing (GCLB) and serverless traffic splitting/canaries to shed load, trigger automated rollbacks, and maintain sub-second response times during partial zone or dependency degradation.