<ul><li>The blog post covers the design of a Distributed Job Scheduler, focusing on functional and non-functional requirements, storage choices, idempotency, and integration with tools like AWS SQS and Kafka.</li><li>Functional requirements include support for scheduling, manual triggering, Python scripts for jobs, at-least-once execution, recurring jobs, and job sequencing.</li><li>Non-functional requirements emphasize high availability, on-time job execution, durability, scalability, and throughput estimations.</li><li>The design includes API endpoints, database considerations favoring NoSQL stores, scheduling and execution flow, handling duplicate events with idempotency, and using FIFO SQS, with Java and Kafka implementations discussed.</li></ul>

Building a Distributed Job Scheduler: End2End Design

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