Portfolio — Frost River Inc.

DevOpsObservabilityDatadogKubernetesAWSLog AggregationAlerting

Observability Platform — Venture Capital Portfolio System

A venture capital firm managing a portfolio of investments had no meaningful visibility into how their production system behaved under load. Incidents surfaced through partner complaints, not internal detection. We deployed Datadog across their Kubernetes cluster — structured log aggregation, metric collection, and alert policies covering all backend services — then integrated the observability stack with their existing AWS data pipeline to surface latency patterns and performance bottlenecks. The team moved from reactive firefighting to proactive operations, with the visibility and tooling to detect and resolve issues before they reached partners.

BackendPythonDjangoDjango REST FrameworkFastAPIPostgreSQLAPI Design

Backend Re-architecture — Healthcare Platform

A healthcare platform had accumulated significant maintenance debt in their backend: ad-hoc query patterns, inconsistent data handling, and an API layer that had grown without structure. The goal wasn't a rewrite — it was a structural migration the team could live with. We led the migration from FastAPI to Django REST Framework, introducing Django ORM to enforce data consistency at the model layer and ViewSets and serializers to standardise the API. The migration was executed with no disruption to the production system, and the team came out with a codebase they could build on without continuing to accumulate debt.

BackendData EngineeringPythonDjangoAirflowKubernetes

Marketing Platform — Hyperlocal Social Network

The marketing org of a hyperlocal social platform with millions of daily active users needed data infrastructure to run campaigns at scale. They had the data science talent and product reach — what they lacked was the infrastructure to move from raw event data to actionable insights. We designed and built pipelines to power campaign analytics, audience targeting, and performance reporting, and worked alongside data scientists to establish the DevOps workflows that supported the full marketing function. The platform moved from ad-hoc data access to a structured infrastructure that scaled with the business without creating engineering bottlenecks.