The Art of Job Scheduling: A Comprehensive Guide

📅Job scheduling involves scheduling jobs to run on a dedicated cluster of compute units, with support for multiple scheduling types.

⏰Every job should be run at least once, ensuring no job is overlooked by the system.

💻Binary files of compiled code can be scheduled for execution and stored in S3 for scalability.

📝A database is used to store job metadata, including job ID, binary URL, status, and timestamps for scheduling.

⚙️A scheduler periodically fetches jobs from the database and enqueues them in an in-memory message broker for execution.

What are the functional requirements of a job scheduler?

—Functional requirements include the ability to schedule jobs, support multiple scheduling types, and ensure every job is run at least once.

How are binary files handled in job scheduling?

—Binary files are compiled code that can be scheduled for execution and stored in a scalable object store like S3.

What role does the database play in job scheduling?

—The database stores job metadata, such as job ID, binary URL, status, and timestamps for scheduling.

How does the scheduler fetch and execute jobs?

—The scheduler periodically fetches jobs from the database and enqueues them in an in-memory message broker for execution.

What is the importance of ensuring every job is run at least once?

—Ensuring every job is run at least once guarantees that no job is overlooked or missed by the system.

00:02Introduction to the topic of job scheduling and the importance of an efficient scheduler.

01:24Discussion of the functional requirements of a job scheduler, including types of scheduling and job execution.

03:21Overview of capacity estimates and the assumed characteristics of the jobs and compute units.

06:58Explanation of the database structure for storing job metadata and scheduling timestamps.

10:24Description of the architecture, including the use of an in-memory message broker and load balancer.