Level-Up Real-time Go Applications with Ringbuffers
summary
Shows how to turn an existing Go service into a low-latency stream processor using Hazelcast ringbuffers, with a GitHub demo and a Go client example. Explains ringbuffer semantics (tail/head, replicated but not partitioned), advises serializing complex structs, and demonstrates SQL access on top of the in-memory ring. Covers deployment: run in cloud, colocate microservices, and use failover between two clusters (blue/green) to avoid data loss while scaling toward millions or even billions of events/sec.
AI-written summary · about
chapters (11)
- 0:00Start
- 8:49Card Payment Go Fraud Detection: Behind the Scenes
- 19:48Ringbuffers
- 24:27Connect to Hazelcast
- 25:31Publisher
- 26:23Logger
- 26:43Alerter
- 28:00Cloud
- 29:59Failover
- 33:51Serializer: write
- 34:37Serializer: read/write
related talks
05mGo for Real Time Streaming Architectures
46mSimplifying Scalable Cloud Application Development with Go
59mDistributed applications using Hazelcast
25mWhen the “Go”ing Gets Tough: Relieving Pressure on a Budget
31mBuilding a microservices architecture with Go
43mBuild Your Own Distributed System Using Go
29mGolang and JavaScript: The Future of Cloud
28mManaging and Scaling Real Time Data Pipelines using Go