Design a Scheduler and Metrics Platform
Company: Palo Alto Networks
Role: Software Engineer
Category: System Design
Difficulty: medium
Interview Round: Onsite
Design a cloud-native job scheduling and metrics monitoring platform for a Kubernetes-like environment.
The platform should allow internal users to submit containerized jobs, schedule them onto a pool of compute nodes, track job execution, retry failed jobs, and expose operational metrics for jobs and infrastructure.
Your design should cover:
- Job submission and scheduling APIs
- How jobs are represented and persisted
- Scheduling decisions, including resource constraints such as CPU, memory, and node availability
- Handling job failures, retries, cancellations, and timeouts
- Metrics collection for job status, latency, resource usage, and node health
- Alerting and dashboard support
- Scalability, reliability, and fault tolerance
- Security and multi-tenant isolation considerations
Overview: This question evaluates a candidate's ability to design cloud-native distributed systems, covering job scheduling, lifecycle management, observability, persistence, resource-aware placement, retry semantics, and multi-tenant security for containerized workloads.
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