Design a job scheduler with SLA and logs
Design a Distributed Job Scheduler with SLA and Logs
Problem Description
Design a distributed system capable of scheduling and executing time-based jobs (e.g., cron-like schedules or fixed intervals). The system must enforce a Service Level Agreement (SLA) for each job execution, marking runs as timed out and raising an error or alert if they exceed the defined SLA window. Furthermore, users must be able to inspect the execution logs for each job run.
Core Requirements
- Job Management: Provide functionality to create, update, and delete scheduled jobs.
- Scheduling: Accurately trigger job runs according to their defined schedules (cron expressions or fixed intervals).
- Execution: Distribute and execute jobs across a fleet of worker machines.
- State Tracking: Maintain and track the state of each job run, including
PENDING,RUNNING,SUCCEEDED,FAILED,TIMED_OUT, andCANCELED. - SLA Enforcement: Implement mechanisms to detect when a job run exceeds its allocated SLA, automatically marking it as
TIMED_OUTand triggering an appropriate error or alert. - Log Viewing: Enable users to view and access execution logs for individual job runs.
Non-Functional Requirements (Discuss in Detail)
- Scalability: The system should be able to handle a potentially large number of jobs and a high rate of job executions.
- Reliability: The design must be resilient to various failures, including worker crashes, scheduler crashes, and network partitions.
- Correctness: Ensure that scheduled jobs are not missed. Minimize duplicate job runs, clearly defining acceptable semantics for such occurrences.
- Observability: Incorporate metrics, tracing, and auditing capabilities for monitoring and debugging.
Key Follow-up Considerations
- Strategies for handling failures at various stages (e.g., scheduler failure, worker failure, log pipeline failure, database outages).
- Implementation of retry mechanisms, exponential backoff, dead-letter queues, and ensuring idempotency for job executions.
- Approaches for managing long-running jobs, including graceful cancellation.
- Addressing complexities related to clock skew, time zones, and daylight saving changes.
AI interview prep
Core dilemma
Balancing the precision and reliability of time-based scheduling (avoiding missed jobs, handling clock skew) with the robustness and scalability of distributed execution (worker failures, network partitions, high throughput, strict SLA enforcement).
3 tradeoffs and 3 stress tests locked
Interview prep
Unlock the interviewer X-Ray rubric, tradeoff matrix, stress tests, clarifying questions, and key concepts.
Design a job scheduler with SLA and logs
Design a Distributed Job Scheduler with SLA and Logs
Problem Description
Design a distributed system capable of scheduling and executing time-based jobs (e.g., cron-like schedules or fixed intervals). The system must enforce a Service Level Agreement (SLA) for each job execution, marking runs as timed out and raising an error or alert if they exceed the defined SLA window. Furthermore, users must be able to inspect the execution logs for each job run.
Core Requirements
- Job Management: Provide functionality to create, update, and delete scheduled jobs.
- Scheduling: Accurately trigger job runs according to their defined schedules (cron expressions or fixed intervals).
- Execution: Distribute and execute jobs across a fleet of worker machines.
- State Tracking: Maintain and track the state of each job run, including
PENDING,RUNNING,SUCCEEDED,FAILED,TIMED_OUT, andCANCELED. - SLA Enforcement: Implement mechanisms to detect when a job run exceeds its allocated SLA, automatically marking it as
TIMED_OUTand triggering an appropriate error or alert. - Log Viewing: Enable users to view and access execution logs for individual job runs.
Non-Functional Requirements (Discuss in Detail)
- Scalability: The system should be able to handle a potentially large number of jobs and a high rate of job executions.
- Reliability: The design must be resilient to various failures, including worker crashes, scheduler crashes, and network partitions.
- Correctness: Ensure that scheduled jobs are not missed. Minimize duplicate job runs, clearly defining acceptable semantics for such occurrences.
- Observability: Incorporate metrics, tracing, and auditing capabilities for monitoring and debugging.
Key Follow-up Considerations
- Strategies for handling failures at various stages (e.g., scheduler failure, worker failure, log pipeline failure, database outages).
- Implementation of retry mechanisms, exponential backoff, dead-letter queues, and ensuring idempotency for job executions.
- Approaches for managing long-running jobs, including graceful cancellation.
- Addressing complexities related to clock skew, time zones, and daylight saving changes.