Case StudyAutomation & APIs

9 APIs in parallel. Zero human input.

How I built a self-healing automation platform that orchestrates multiple third-party APIs across 9 parallel sessions — with automatic recovery, intelligent rate limiting, and 24/7 uptime.

Parallel sessions

24/7

Self-healing uptime

Manual intervention

API integrations

The Problem

Before: Manual workflows

Managing data across multiple APIs manually. Constant copy-pasting, lagging updates, missed events, records out of sync. Scaling beyond a few hundred operations was physically impossible.

After: Fully automated

Automated platform handling the entire data lifecycle: ingestion, transformation, synchronization, and downstream actions. 9 concurrent API sessions — all self-healing, zero intervention.

Architecture

✓

Multi-API orchestration — Concurrent connections to multiple APIs via REST. Each session manages its own authentication, rate limits, and retry logic independently.

✓

OAuth token management — Automatic token refresh across 9 sessions. Tokens rotate before expiry, failed refreshes trigger backup flows.

✓

Intelligent rate limiting — Custom rate limiter adapting to each API. Exponential backoff on 429s, request queuing during throttle, automatic recovery.

✓

Self-healing pipelines — Every pipeline stage has automatic error recovery. Network failures, timeouts, invalid responses — each has a defined recovery path.

✓

Batch processing — Optimized batch processing with deduplication, conflict resolution, and checkpoint recovery if a batch fails mid-way.

✓

Health monitoring — Real-time monitoring of all sessions, response times, error rates. Automatic alerts when metrics deviate from baseline.

Tech Stack

Python

Core language

REST APIs

Data layer

OAuth 2.0

Authentication

PostgreSQL

State management

Rate Limiting

Throughput control

Health Monitoring

Observability

Results

Concurrent sessions

Nine parallel API sessions with independent auth, rate limiting, and error recovery.

24/7

Autonomous operation

Runs continuously without human intervention. Self-healing pipelines handle failures.

Manual steps

Every workflow runs end-to-end automatically. Alerts only on truly novel failures.