A background job needs to process a large dataset. How would you keep memory usage safe?

How would you design a memory-safe background batch job?

Covers chunking, bounded concurrency, scoped dependencies, progress, retries, and avoiding full-dataset memory spikes.

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I would process the data in chunks instead of loading everything into memory. Each chunk would use a fresh scope or unit of work, save progress, release references, and move to the next chunk. I would cap concurrency so multiple workers do not multiply memory usage beyond the process limit. I would also log progress and failures so the job can resume or retry without starting from zero.

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Batch processing design, bounded memory, scopes, concurrency limits, retries, and operational control.

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Batch jobs often fail differently from request code. The design needs a memory budget, not only a loop that eventually finishes on a developer machine.
I would process the data in chunks instead of loading everything into memory. Each chunk would use a fresh scope or unit of work, save progress, release references, and move to the next chunk. I would cap concurrency so multiple workers do not multiply memory usage beyond the process limit. I would also log progress and failures so the job can resume or retry without starting from zero.
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The main idea is bounded work. I would page through IDs or use a cursor, load only the records needed for the current chunk, process them, write results, and clear the scope. If the job calls external services, I would limit parallelism and use backoff so memory does not fill with pending work. For EF Core, I would avoid tracking huge graphs and avoid one DbContext for the whole job. The batch size becomes a tuning knob based on memory, throughput, and failure recovery.

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Loading the entire dataset before processing.
Starting unbounded tasks for every row.
Using one DbContext for a long-running batch.
Not recording progress or idempotent checkpoints.

A background job needs to process a large dataset. How would you keep memory usage safe?

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