An ASP.NET Core endpoint is hot and allocates heavily. How would you reduce allocations safely?

How would you reduce allocations in a hot .NET API path?

Frames allocation reduction as measurement-driven API work rather than premature micro-optimization.

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I would first measure where the allocations happen, because guessing can waste time. If the endpoint is truly hot, I would look for repeated string creation, unnecessary ToList calls, large DTO graphs, LINQ chains in tight loops, and buffering that can be streamed. Then I would make small changes and compare before and after. The goal is lower allocation rate without making the code hard to maintain.

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Profiling, request hot paths, practical allocation reduction, trade-offs, and regression safety.

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Why this question matters
Allocation optimization begins with a measured hot path and a user-facing latency or capacity cost. Data shape, unnecessary materialization, repeated strings, serialization, and buffering usually deserve attention before low-level memory APIs.
I would first measure where the allocations happen, because guessing can waste time. If the endpoint is truly hot, I would look for repeated string creation, unnecessary ToList calls, large DTO graphs, LINQ chains in tight loops, and buffering that can be streamed. Then I would make small changes and compare before and after. The goal is lower allocation rate without making the code hard to maintain.
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My first pass would be profiling under realistic traffic. I would check allocation rate, top allocating methods, request latency, and whether GC time is meaningful. Then I would remove obvious waste: avoid building intermediate collections, select only needed columns, use pagination or streaming, reuse serializers or options where appropriate, and simplify mapping in tight loops. I would be cautious with Span or ArrayPool until ordinary fixes are exhausted, because they can add complexity and bugs if the team is not comfortable with them.

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Optimizing code without profiling first.
Making low-level changes that obscure business logic.
Ignoring database and serialization allocations.
Measuring only a synthetic loop that does not match API traffic.

An ASP.NET Core endpoint is hot and allocates heavily. How would you reduce allocations safely?

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