Case Studies 🏆
Real-world examples of technical challenges and their solutions.
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UkraineAlarm (Ajax Systems)
Context:
Needed a nationwide air-strike alarm system rapidly deployed during wartime. (Stack: Kotlin, Java, Spring Framework, MySQL, NATS, Kafka, AWS, Terraform)
Action:
- Architected and launched the nationwide air strike alarm system in response to the war.
- Led the engineering team to rapidly develop and release the critical application.
Result:
Shipped a life-saving system in 3 days, credited with saving lives across Ukraine.
Context:
Continuous Delivery platform needed hardening to support growing number of applications and ensure safe deployments across multiple AWS accounts. (Stack: Java, Kotlin, Go, Python, AWS, Spinnaker, Terraform, Kubernetes, MySQL, Docker)
Action:
- Designed and implemented AWS multi-account support for the CD platform, enhancing security, observability, and maintainability.
- Implemented MySQL database optimizations for Spinnaker Keel.
Result:
Resulted in a 4x increase in supported applications, significantly improving platform scalability.
Form3
Context:
Real-time payments platform required enhanced stability and throughput under heavy load. (Stack: Go, NATS, Kubernetes, CockroachDB, Docker, AWS, GCP, DevOps)
Action:
- Led initiatives to improve system stability.
- Proposed and implemented solutions that increased observability, prevented data loss, and optimized processing times.
Result:
Enhanced system stability, observability, and processing times for the high-load payments platform.
Ajax Systems
Context:
Deliver software for installers across mobile and desktop platforms (iOS, Android, Windows, macOS) enabling equipment control and adjustment. (Stack: Kotlin, Java, Spring, NATS, Kafka, AWS, Terraform)
Action:
- Led a cross-platform team of 20 engineers.
- Delivered new features enhancing user experience and system functionality.
- Proposed and implemented isolated AWS developer environments, reducing time-to-market.
Result:
Successfully launched new features and improved developer velocity by optimizing testing infrastructure.
Revolut
Context:
Needed improvements to the internal ML Ops platform for managing machine learning model features. (Stack: Java, GCP, Kubernetes, Postgres)
Action:
- Improved the ML Ops platform to manage features for Machine Learning Models.
Result:
Contributed to improving the ML Ops platform for managing ML model features.
Cowbell Cyber
Context:
Required enhanced system architecture, including integration tests, zero-downtime migration, and knowledge sharing, to improve stability and maintainability. (Stack: Java, Kafka, Spring Framework, Kubernetes, Docker, AWS, Postgres, Elasticsearch)
Action:
- Enhanced system architecture by introducing integration tests.
- Performed a zero-downtime database migration (PostgreSQL).
- Developed a team knowledge-sharing plan.
Result:
Led to significant improvements in service stability and maintainability.
OfferAI
Context:
Develop the initial architecture and MVP for a new startup as the sole engineer. (Stack: Java, JavaScript, Apache Wicket, Google Guice, OrientDB, Orienteer)
Action:
- Created the initial product architecture.
- Implemented core features, collaborating with CEO/CTO.
- Successfully navigated startup launch challenges.
Result:
Successfully launched the MVP, enabling the startup to generate its first revenue.
Orienteer BAP
Context:
Enhance a Business Application Platform (BAP) by adding graphical modeling and plugin capabilities. (Stack: Java, JavaScript, Apache Wicket, Google Guice, OrientDB)
Action:
- Built an in-platform graphical editor for OrientDB data models.
- Developed a hot-plugin module system allowing platform customization without server restarts.
Result:
Enabled clients to design data models visually and customize the platform without code.
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