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HTTP Load Tests and Keep-Alive: Why One Socket Can Look Fast

A high requests-per-second result does not reveal how many connections the test used. Check reuse and connection-count settings, then compare controlled runs against the workload you need to model.

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A load test can report strong throughput while reusing a single persistent HTTP connection. That result describes the configured test, but it does not by itself show how the same service will behave when clients open or use more concurrent connections. To interpret the result, check the load generator’s reuse and connection-count settings, then compare runs under controlled conditions.

Why one persistent connection can still produce high throughput

HTTP/1.1 allows a client to send successive requests over a persistent connection unless the client or server signals that the connection will close. Reusing a socket avoids establishing a new TCP connection for every request, so a generator can exercise request handling without reproducing the connection setup and churn of a workload that opens many connections. These are different workload patterns, not proof that one result is wrong. RFC 9112 describes HTTP/1.1 message framing and connection management.

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Reuse has conditions: each message needs a self-defined length, and the client must consume the complete response body before reusing the connection. Persistent does not mean permanent. Either endpoint or an intermediary can close a connection, and servers commonly apply idle timeouts.

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Requests per second and the number of concurrent TCP connections are separate properties. A throughput figure alone does not reveal how many sockets were open, how often connections were established, or whether requests queued behind a limited connection pool.

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What one socket does—and does not—tell you

If the test actually reused one socket, it measured a persistent-connection pattern for that run. It can still provide useful information about the configured request workload. It does not establish performance for a workload with more concurrent connections, frequent reconnects, or different client-side connection limits.

More connections are not automatically better or more representative. RFC 9112 notes that multiple connections can reduce head-of-line blocking, while also consuming server resources and contributing to network congestion. It advises clients to limit simultaneous open connections to a given server. Choose a connection pattern to match the workload you intend to model rather than maximizing the count by default.

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Check the generator settings that control reuse and connection count

In k6, distinguish the two reuse options

k6 documents noConnectionReuse as a boolean that disables keep-alive connections; its documented default is false. To explicitly disable connection reuse, an options block can include:

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export const options = { noConnectionReuse: true };

k6 also documents noVUConnectionReuse, which controls whether a virtual user (VU) reuses TCP connections between iterations. Its documented default is also false. These settings address different aspects of the workflow, so inspect the relevant option rather than treating them as interchangeable. Consult the k6 options reference for the documentation that matches your installed version.

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In wrk, inspect the total connection setting

wrk’s -c or --connections option sets the total number of HTTP connections to keep open; its threads handle shares of that total. The README’s example uses 12 threads and 400 connections. That is an example configuration, not a universal recommendation. Check both the connection count and thread count in the actual command. See the wrk README.

For other clients, verify the exact runtime and version

Connection pooling may be controlled by a runtime or HTTP client rather than a load-test option. Do not assume a setting’s name, default, or effect from another tool. Confirm the behavior in documentation for the exact client and version used, and record that version with the test results.

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Run a controlled comparison

A comparison is informative only if connection reuse is the intended variable. Keep the target, request mix, payloads, duration, concurrency model, and generator resources comparable; state which settings changed. If you change connection count, reuse policy, and virtual-user count together, you cannot attribute a difference to any one of them.

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  1. Record the setup. Note the load tool and version, HTTP protocol version, script or scenario, VUs or workers, configured connection count, and whether connections are reused between requests or iterations.
  2. Inspect the effective settings. For k6, check whether reuse-disabling options are set. For wrk, record -c and the thread count. Do not infer socket count from requests per second.
  3. Choose the connection patterns to compare. Configure each run explicitly for the intended reuse behavior. Keep other workload inputs comparable and report the settings that differ.
  4. Measure more than throughput. Compare latency distributions, errors, connection establishment and reconnect behavior, and signs of generator or target saturation.
  5. Check limits and closures. Account for server-side idle timeouts and connection closure. With wrk, also check ephemeral-port availability and whether the server listen backlog can handle the initial connection burst; these are possible constraints, not diagnoses of a particular test result.

Report each result narrowly: one run measured its configured persistent-connection pattern, and the comparison measured another pattern. Neither run alone establishes every aspect of production performance. Calling one pattern “more realistic” requires evidence that it matches the clients and connection behavior in the production workload.

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How to report the result accurately

Include the connection policy and count alongside the concurrency model, throughput, latency distribution, errors, connection setup or reconnect behavior, and relevant generator and target limits. This gives readers enough context to understand what the test exercised and what it did not. Do not turn a throughput result into a claim about concurrent connection capacity unless the test measured that dimension.

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