Tens of thousands
Events handled under peak load
Architected a fault-tolerant Go/GCP event-processing platform with stable throughput across distributed backend services.
Distributed systems · Go · GCP
Anna Sbrodova
Distributed Systems Engineer and Technical Lead
I design and build backend systems in Go and GCP, with a focus on distributed processing, reliability, data-intensive workloads, and cloud efficiency.
I have 12+ years of software engineering experience and work across the full lifecycle: understanding the problem, designing the architecture, implementing critical parts, and supporting systems in production.
Current focus
- 01Distributed and event-driven systems
- 02Production Go backend services
- 03GCP architecture and data processing
- 04Reliability, performance, and cost
- 05Developer and open-source products
12+years engineering
30k+peak concurrent users
~18%BigQuery cost reduction
Millionsof rows per execution
Featured open-source work
Aura Tracker GCP
The open-source intelligence layer for Google Cloud.
Ask a question in plain language. Aura investigates live GCP inventory, metrics, logs, IAM, topology, recommendations, and billing data—then returns a prioritised answer grounded in inspectable evidence.
I designed and built Aura independently in Go as a self-hosted, model-agnostic system for incident investigation, security, architecture, environment drift, and cost optimisation.
Investigation
“Why did the scheduled Cloud Run jobs fail?”
- 01ObserveExecutions, logs, metrics, configuration
- 02CorrelateFailures, dependencies, recent changes
- 03ExplainPrioritised findings with evidence
Evidence attached to every conclusion
Selected outcomes
Examples of production work
A few concrete results from systems I have designed, built, or improved.
Hundreds
Parallel compute jobs
Designed Cloud Run pipelines where each execution processes millions of BigQuery rows for high-volume transformations.
15k–30k+
Peak concurrent users
Helped keep large-scale e-commerce systems stable through Black Friday traffic and unpredictable demand surges.
~18%
Lower BigQuery cost
Reduced operational expenditure through query optimisation, schema redesign, and execution-flow improvements.
Experience
Professional experience
I work across the full system lifecycle: clarifying the problem, defining boundaries, building critical paths, and making systems observable and operable.
Download the full CVHands-on Technical Lead
Leading architecture and delivery across Go/GCP distributed systems spanning Kafka, Pub/Sub, BigQuery, Cloud Run, GKE, and multi-service production environments.
Senior Backend Engineer / Technical Lead
Built high-throughput Go services and event-driven workflows, introduced structured observability, and translated complex business requirements into scalable system designs.
Senior Software Engineer
Improved and scaled distributed Go services supporting approximately 50 million monthly visits and extreme seasonal traffic.
Backend, automation, and enterprise systems
Progressed through Java, integration, banking automation, and distributed enterprise backend engineering.
Technical writing
Architecture deep dives
Practical articles about design decisions, failure modes, and implementation patterns in Go and distributed systems.
The Complete (But Not Boring) Book of Go Auth
Authentication foundations including memory-hard password hashing, stateful and stateless sessions, token safety, and hybrid authentication patterns for distributed services.
Read on MediumThe Redelivery Trap: A Safe Transactional Inbox
An idempotent consumer architecture for handling Google Pub/Sub retries and redelivery safely with Go, GKE, and PostgreSQL.
Read on MediumThe Dual-Write Problem: A Scalable Transactional Outbox
A source-agnostic delivery design using Go, PostgreSQL, GKE, and Pub/Sub to avoid lost messages, scale dispatchers, and keep polling costs under control.
Read on MediumExpertise
Technical focus
My strongest areas are distributed systems, Go backend engineering, GCP, reliability, and data-intensive applications.
Distributed systems
Event-driven architecture, service boundaries, consistency, idempotency, fault tolerance, and high-load system design.
Go backend engineering
Production Go services, concurrency, performance profiling, APIs, asynchronous workflows, and maintainable architecture.
Cloud-native systems
GCP, GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL, Kubernetes, Terraform, and delivery automation.
Reliability & observability
Metrics, logs, tracing, SLO-minded operations, production diagnosis, proactive alerting, and safe change design.
Data & cloud economics
Large-scale data processing, query design, cloud billing models, cost optimisation, and execution efficiency.
Developer products
Internal platforms, open-source tooling, AI-assisted workflows, technical product discovery, and end-to-end ownership.
Contact
Get in touch
I’m open to senior engineering and technical leadership roles, founding-engineer opportunities, consulting, partnerships, and other interesting projects.
If you think my experience could be useful, feel free to contact me.