SVC-02 · Backend & Distributed Systems
Distributed systems that behave predictably under real load.
APIs, event-driven architectures and high-throughput services, built and operated by an engineer who has run them at 16 million concurrent users and 80K writes per second.
Capabilities
Backend engineering for systems with real traffic.
- 01
APIs & services
Java, Kotlin and Scala services on Spring, WebFlux, Quarkus and Akka. Contracts, versioning, backpressure and idempotency handled deliberately.
- 02
Event-driven architecture
Kafka topics, partitions, ordering guarantees, consumer groups, exactly-once semantics where they are worth their cost.
- 03
Data stores under load
Cassandra, Redis, PostgreSQL, Couchbase and DynamoDB — data modelling for the access pattern, not the ORM.
- 04
Concurrency & throughput
Thread and connection pools, queue depth, timeouts, circuit breakers and retry budgets sized from measurements.
- 05
Failure domains
Bulkheads, graceful degradation, multi-region behaviour and recovery paths tested before an incident tests them for you.
- 06
Performance engineering
Load tests, profiling, GC tuning and capacity models, with results your team can rerun.
Working stack
What we reach for, day to day.
Model calls increasingly live inside these systems. That is why the AI Systems Audit looks at queues, state and concurrency alongside prompts and models.
- LANGUAGES
- Java · Kotlin · Scala · Python · TypeScript
- FRAMEWORKS
- Spring Boot · WebFlux · Quarkus · Akka · FastAPI
- MESSAGING
- Kafka · RabbitMQ · REST · WebSocket
- DATA
- Cassandra · Couchbase · PostgreSQL · Redis · DynamoDB · Elasticsearch
Have a service that behaves differently at 10× load?
Short engagements, written proposals, real code in your repository.