Case Study
API Backend for Automation Tool
Real-time data processing with scalable architecture.
API
Microservices
DevOps
Overview
A robust backend for an automation product that orchestrates workflows and synchronizes data across external APIs.
Goals
- Process events in near real time.
- Improve reliability of external API integrations.
- Provide clear workflow status and retry visibility.
Challenge
Unreliable integrations led to workflow failures and missing status visibility for end users.
Constraints
- Multiple third-party APIs with inconsistent rate limits.
- High volume event bursts at peak times.
- Need for fast incident triage.
Solution
We delivered a modular API platform with resilient processing, audit trails, and observability for every workflow step.
Architecture
- Queue-first event processing with worker pools.
- Service boundaries for integrations and orchestration.
- Centralized logging and metrics for workflow traces.
Implementation
- Built FastAPI services with validated schemas.
- Added retry policies, dead-letter queues, and alerts.
- Created status APIs and dashboards for operations.
Tech Stack
FastAPI
PostgreSQL
Kafka
Docker
AWS
Timeline
- Week 1: Workflow mapping and API contract design.
- Weeks 2-3: Services, queues, and integration adapters.
- Week 4: Observability, QA, and deployment.
Results
- Reduced integration failures with retries and audit logs.
- Enabled real-time workflow status tracking.
- Improved deployment speed with automated pipelines.
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