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Batch Processing

Azure Batch · Spot vs dedicated nodes · HPC

Practice questions for this topic →

Spot vs dedicated nodes

FactorFavor SpotFavor dedicated
Task recoveryShort, restartable or checkpointed tasksInterruption loses costly work
Completion timeFlexible deadlineStrict deadline or predictable capacity
Workload shapeMany independent tasksLong-running, tightly coupled multi-node MPI jobs
CapacityPool can run at reduced capacityPool must keep its full target capacity

Facts to know

Exam Tips

Tick each tip once you can answer it without looking.

“Large-scale parallel or HPC jobs scheduled across a pool of VMs, no cluster to manage” → Azure Batch.

“Cut Batch cost; tasks are restartable and the deadline is flexible” → Batch pool with Spot nodes. Trap: Spot has no SLA and can be preempted immediately after creation.

“Tightly coupled MPI job with a strict deadline” → Dedicated nodes using RDMA/InfiniBand-capable HPC VM sizes.

“Balance low cost with guaranteed progress” → Mix dedicated baseline nodes + Spot nodes in the pool.

“Low-priority VMs in Batch” → Retired Sep 30, 2025: the answer is now Spot VMs.

“What happens to a task when a Spot node is preempted?” → It's requeued automatically; checkpointing to durable storage is your responsibility.

“Short event-driven background jobs (not HPC)” → Functions or Container Apps jobs. Trap: Don't over-engineer with Batch.

“Preempted Spot node in Batch” → Azure tries to restore the VM only during the first 48 hours, with no guarantee. Trap: Interrupted tasks are requeued; work not checkpointed is lost.

“Before setting Spot node targets” → Plan capacity: quota, regional capacity, VM availability and fallback options. Trap: Spot has no SLA and can be preempted immediately.

“Pool must hold its full capacity or meet a strict deadline” → Dedicated nodes (mix in Spot only for extra cost-savings). Trap: Tightly coupled MPI jobs also favor dedicated nodes.

Sources

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