From product development to Open Beta and post-launch operations — connecting infrastructure, integration, performance, and release readiness.
2025 – present · Ongoing developmentCash Management helps small and medium businesses consolidate cash inflows/outflows, balances, and funding needs from their operations. The product combines invoicing and related data sources with manual entry, CSV, dashboards, reports, and alerts.
I built the production deployment and operations foundation, optimized application performance, and led cross-team integration coordination to bring CAM to Open Beta and support stable development after launch.
Officially joined in October 2025 after POC phase 1, when only staging existed; established development workflows and a full production environment.
Open Beta launched on the revised schedule after the original May 2026 target; responsible for readiness, performance, and operations.
Monitoring detected two business-impacting cases that the team quickly resolved; continued the technical roadmap for late 2026–2027.
When I joined, the initial targets were Closed Beta in November 2025 and Open Beta in May 2026. Closed Beta launched on January 23. Based on remaining features and progress, Open Beta was rescheduled to September 16, 2026 and successfully released on that date.
Led Kafka / CDC integration coordination, separating database, messaging, and application dependencies into clear release steps. For newly activated tenants, initial synchronization required historical data backfill alongside continuous updates.
Built production Kubernetes namespaces, release / maintenance pipelines, and branch-to-namespace deployment with GitHub Actions and operations guides. Contributed to PostgreSQL migration in development and staging.
Analyzed and proposed separate database roles, preserving row-level security for user workflows while supporting system operations with clear permission boundaries. Combined Datadog dashboards, fault tolerance testing, and k6 tooling to prepare for production operations.
Aligned idev — an AWS EKS environment for microservice development acting as a cloud localhost — with Gitflow. Unified CI/CD from local → idev → staging, integrated SonarQube, Datadog, Rollbar, and Slack notifications, and standardized logging/error handling. Built Kubernetes manifests and provisioned/configured RDS, S3, Valkey, and production operations components.
Used Datadog to guide architecture and caching improvements. Redesigned Kafka-related services around business domains; restructured background processing and consumers to remove bottlenecks caused by using downstream services as intermediaries for data access.
Implemented Expand–Contract, addressed database migration backlog, and improved CI/CD with internal tools and Argo Workflows. Integrated Cloudflare, internal domains, and maintenance applications; coordinated security scanning and remediation with the security team.
Automated deployment of branches into selected namespaces using GitHub Actions, with operating instructions. Enabled the team to validate changes in isolated environments.
Coordinated CAM integration so activation events triggered backfill in source services. Data flowed through outbox, Debezium, and Kafka before CAM applied business rules.
Implemented sharing of in-flight authentication between loaders / actions using the same Request, reducing repeated Redis lookups and RPCs. Used request-scoped caching to preserve authentication isolation and correctness.
Developed k6 tooling and capacity estimates; coordinated evidence, rollback readiness, and launch monitoring. Combined test results and sizing to select appropriate launch capacity.
Improved the onboarding state machine and redirects after launch. Ran Datadog / monitoring sessions to help the team observe systems and respond to operational issues independently.
Recovery and observability for Kafka / CDC pipelines, deployment guardrails, cost optimization, and AI-assisted SDLC. Translate the technical roadmap into a prioritized backlog while developing context and workflows for AI in engineering.
Partnered with QA to integrate k6 and make tests available through Argo Workflows. Led improvements to caching, duplicate requests, load-amplifying layers, database connections, and slow queries. Fault tolerance testing informed error handler and retry improvements; stress testing included 500 RPS.
Designed Datadog dashboards and SLIs/SLOs aligned with business value. After Open Beta, monitoring provided early warnings and detected two business-impacting cases that the team quickly resolved; the system ran stably during the observed post-launch period.
Completed deployment and operations procedures, documented incident handling, and ran incident drills. The Observe & React → Understand & Improve → Respond & Recover program combines monitoring, Datadog, SLIs/SLOs, labs, and tabletop exercises to help members take operational shifts, investigate, and coordinate incident response.
Designed FFP principles for audiences/segments, shadow and user-facing flags, ownership, audits, canary rollout, and kill switches. Integrated AI for monitoring support, information synthesis, and an SDLC knowledge base. The late 2026–2027 roadmap covers technical debt, AI-assisted SDLC, and improvements; implementation is ongoing.