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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