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Surya Karmakar Portfolio

website·Indexed 29 days ago

https://suryakarmakar.com

Professional portfolio of Surya Karmakar, a specialist in engineering scalable systems and API performance optimization.

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What's inside Surya Karmakar

  1. Deploy zero-downtime mobile hotfixes using Microsoft CodePush

    Use Microsoft CodePush for CI/CD release engineering to deploy critical hotfixes directly to production mobile apps, allowing you to bypass the standard App Store and Google Play review cycles.

  2. Implement a fault-tolerant offline-first system with SQLite and Redux

    To build a fault-tolerant offline-first mobile system for zero-network environments, use a relational SQLite database for local storage and a Redux caching layer to reduce disk I/O operations. Implement a custom bi-directional sync engine utilizing timestamp-based conflict resolution to synchronize local data with the backend once connectivity is restored.
    Architecture: React Native + SQLite + Redux
Sync Strategy: Bi-directional sync with timestamp-based conflict resolution

  3. Handle bulk API payloads and deep dependency trees in mobile apps

    When dealing with high-volume data or complex structures in mobile interfaces:

    1. Bulk Payloads: Use payload chunking strategies to prevent API timeouts when processing bulk orders (e.g., 10,000+ items).
    2. Deep Hierarchies: Implement recursive search algorithms to render deep dependency trees (e.g., 24 levels deep) without causing UI lag.

  4. Optimize large-scale PostgreSQL datasets using partitioning and materialized views

    For managing massive datasets (e.g., 11.8M+ records) and reducing API latency, implement the following PostgreSQL strategies:

    1. Table Partitioning: Use date-based partitioning to manage large tables and efficiently route historical data requests.
    2. Pre-calculated Analytics: Use Materialized Views, triggers, and pg_cron to reduce reporting API response times to milliseconds.
    3. Migration: Transitioning from MongoDB to PostgreSQL can resolve severe latency and high compute costs for core aggregation logic.

  5. Architect an event-driven microservices ecosystem with AWS and Kafka

    Build a scalable distributed job processing system by combining AWS SNS/SQS for messaging, Kafka streams for real-time data pipelines, and automated retry mechanisms to ensure reliability across microservices.
    Stack: NestJS, Kafka, AWS SNS, AWS SQS, Docker