Tag archive
How we architected the AirAsia Move platform for massive scale — circuit breakers, distributed tracing, Kafka event flows, and hard lessons from production.
Hi everyone, I recently ran into a problem with our microservices architecture: the data is spread...
When services fail, standard exponential backoff causes retries to sync up, creating a "thundering...
Your trace shows api-gateway calling orders, then stops. orders definitely called inventory, but...
When traces are absent or incomplete, structured logs become your only forensic layer. Here's how to close the gap in Go microservices.
Watermill makes event-driven Go feel almost as ergonomic as an HTTP router. That is exactly why it is...
Architect resilient, low-latency systems by combining Kafka's partition-based log streaming with RabbitMQ's smart-routing quorum queues under heavy re
Service discovery without honest health checks is just a fancy phone book of corpses. Consul can give...
Inside our system no service ever receives the caller's token. The edge parses the input once and passes on a claim about who arrived; the service has no keys and no reason to verify anything. What holds that in place is not an agreement - it is a test stand that fails the moment a token header arrives.
Quick Answer CAP Theorem Trade-Offs in .NET Microservices: Balance consistency and latency...
Descubre cómo estas interfaces astutas acceden y optimizan tus datos sin necesidad de una configuración GraphQL explícita.
Temporal Workflow for Microservices: Why We Replaced 40 CronJobs With One Engine We...