A parallel loop uses one EF Core DbContext and starts failing or returning inconsistent tracking results. What is wrong, and how would you redesign it?

Do not share DbContext across parallel work

Diagnoses thread-unsafe scoped dependencies inside parallel execution and redesigns the data boundary without exhausting shared resources.

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DbContext is not thread-safe, so I would not run concurrent queries or saves through the same instance. Its change tracker and database operations assume one logical unit of work at a time. I would first ask whether the work can become one set-based query or update, because that is often faster and simpler than many parallel contexts. If operations are truly independent, each worker needs its own context created through an appropriate factory and the overall concurrency must remain bounded.

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DbContext thread safety, scoped dependency lifetime, independent units of work, factories, set-based alternatives, connection pools, transactions, and bounded concurrency.

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Parallelizing a loop does not make the objects captured by its delegate safe. Scoped data-access and client dependencies often carry mutable state or limited resources that define the real concurrency boundary.
DbContext is not thread-safe, so I would not run concurrent queries or saves through the same instance. Its change tracker and database operations assume one logical unit of work at a time. I would first ask whether the work can become one set-based query or update, because that is often faster and simpler than many parallel contexts. If operations are truly independent, each worker needs its own context created through an appropriate factory and the overall concurrency must remain bounded.
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For example, processing independent tenant batches can use IDbContextFactory<TContext> inside a bounded worker so each batch gets a fresh context, completes, and disposes it. I would not resolve one scoped repository before the loop if that repository holds the original context. One context per item can still be wasteful, so I may partition items into sensible units and use database-side joins, projections, , or bulk operations where possible. Parallel contexts also consume connections and may contend on the same tables, indexes, or rows.

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Putting a lock around one shared DbContext and keeping all database calls serialized inside a parallel loop.
Creating an unbounded number of contexts and exhausting the connection pool.
Assuming separate contexts still share one atomic transaction.
Parallelizing row-by-row work that one set-based database operation can perform.

A parallel loop uses one EF Core DbContext and starts failing or returning inconsistent tracking results. What is wrong, and how would you redesign it?

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