About the service
I am a backend developer and work only in Go, because I'm interested in the part of the product that must be correct, fast and always available. Over the past several years I've launched microservices, internal platforms and public APIs to production, through which real traffic flows, and I'm convinced that Go's value is not in clever tricks, but in boring reliability: predictable memory management, honest error handling and code that the whole team reads without translation. By hiring me, you get someone who thinks about delay percentiles, graceful shutdown and what will happen at three in the morning when an external dependency starts timing out, not just about making the happy path work.
My daily work is designing and building services with clean REST or gRPC contracts backed by PostgreSQL, Redis, Kafka or NATS. I deliberately rely on Go's concurrency model: goroutines and channels for pipelines, context for cancellation and deadlines, worker pools and rate limiting, so traffic spikes degrade gracefully instead of crashing the service. I embed observability from the first commit: structured logs, metrics and tracing are built in right away, and every service comes with tests, health-checks and a container ready for Docker and Kubernetes. I write migrations, document endpoints and keep code idiomatic so the next developer moves fast.
I'm equally comfortable diving into an existing system to untangle a slow endpoint or memory leak, and starting a new service from an empty repository and bringing it to production. I estimate timelines honestly, communicate to the point and prefer small verifiable changes to large risky deployments. Describe the task and constraints — I'll return a plan, realistic timeline and working code.
— Microservices on Go with REST and gRPC APIs
— Concurrency: goroutines, channels, context, worker pools
— Data integration and modeling: PostgreSQL, Redis, Kafka, NATS
— Docker, Kubernetes and CI/CD pipelines
— Observability: structured logs, Prometheus metrics, tracing
— Testing, profiling and performance tuning under load
My daily work is designing and building services with clean REST or gRPC contracts backed by PostgreSQL, Redis, Kafka or NATS. I deliberately rely on Go's concurrency model: goroutines and channels for pipelines, context for cancellation and deadlines, worker pools and rate limiting, so traffic spikes degrade gracefully instead of crashing the service. I embed observability from the first commit: structured logs, metrics and tracing are built in right away, and every service comes with tests, health-checks and a container ready for Docker and Kubernetes. I write migrations, document endpoints and keep code idiomatic so the next developer moves fast.
I'm equally comfortable diving into an existing system to untangle a slow endpoint or memory leak, and starting a new service from an empty repository and bringing it to production. I estimate timelines honestly, communicate to the point and prefer small verifiable changes to large risky deployments. Describe the task and constraints — I'll return a plan, realistic timeline and working code.
— Microservices on Go with REST and gRPC APIs
— Concurrency: goroutines, channels, context, worker pools
— Data integration and modeling: PostgreSQL, Redis, Kafka, NATS
— Docker, Kubernetes and CI/CD pipelines
— Observability: structured logs, Prometheus metrics, tracing
— Testing, profiling and performance tuning under load
