The Tool Desk
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This guide explains what each setting does, how to test GET, HEAD, and POST endpoints, and how to turn ApacheBench output into a repeatable capacity signal rather than a misleading headline number.
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What ApacheBench is and what it measures
ApacheBench is the ab command-line client. Ubuntu distributes it in the apache2-utils package, and Apache HTTP Server documentation describes it as a tool for benchmarking an HTTP server. It sends requests to an HTTP or HTTPS URL and summarizes timing, throughput, and error information for that run.
The client is deliberately focused: it exercises the request you specify, not an entire browser session. A test can therefore answer a precise question such as “How many requests per second can this endpoint serve at 20 concurrent requests?” It cannot, by itself, represent every browser feature, user think time, cache pattern, or multi-step application journey.
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That distinction determines how to use the results. Treat an ab run as a controlled endpoint test. If you need realistic user capacity, define a workload model that includes the sequence of requests and pauses users actually make, then use a tool or test design capable of reproducing that model.
Install ApacheBench on Ubuntu and verify it
The package name and executable are separate: you install apache2-utils, then invoke the installed program as ab.
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Refresh Ubuntu’s package metadata:
sudo apt update -
Install the package that supplies ApacheBench:
sudo apt install apache2-utils -
Confirm that the command is available and inspect its version:
ab -V -
Display the command synopsis and available switches:
ab -h
Run these commands on the machine that will generate the traffic, which may be different from the server under test. Keeping the load generator separate prevents the generator’s CPU, memory, network, or connection limits from being mistaken for server capacity.
Before you load test: authorization, scope, and a safe baseline
Send load only to infrastructure you own or are explicitly authorized to exercise. A benchmark creates real connections and requests; against an unrelated host it can be disruptive or interpreted as hostile traffic.
Write down the test scope before starting. Record the exact URL, HTTP method, protocol, headers, cookies, authentication method, request body, request count or duration, concurrency, keep-alive setting, and socket timeout. Also record the server revision, application configuration, cache state, and the machine and network used to generate traffic. Without this information, two apparently similar runs may not be comparable.
Begin with a modest, finite test. The following command is a useful GET baseline:
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ab -n 1000 -c 20 https://example.com/Here, -n 1000 asks for 1,000 total requests and -c 20 permits 20 requests to be in flight at once. Replace the URL with an endpoint you control. The example numbers are a starting workload, not a universal benchmark or a promised capacity target.
While the command runs, observe server-side CPU and memory, access and error logs, connection limits, and application metrics. Stop the run if the service becomes unhealthy. After the baseline completes, increase concurrency in measured steps rather than jumping directly to an extreme value. Record every step and its outcome.
What -n and -c mean in ApacheBench
| Option | Meaning | Why you should set it explicitly |
|---|---|---|
-n number |
Total number of requests sent during the run. | The default is one request, which is normally too small to represent sustained service. |
-c number |
Number of multiple requests made at the same time, or requests in flight. | It defines the pressure placed on the endpoint and makes runs comparable. |
Concurrency is not the same as total volume. A run can send many requests with a low concurrency, or a smaller total with a high concurrency. Both dimensions affect what you learn: -n controls how long the sample lasts, while -c controls how many simultaneous operations the server must handle.
Always specify both values. Leaving the default single request in place can produce a number dominated by connection setup or transient timing instead of normal service behavior. Keep the endpoint, method, payload, and protocol identical when comparing different concurrency levels.
Run a time-bounded or persistent-connection test
Use a duration instead of a fixed request count
Use -t when the test should run for a defined duration rather than stop after a fixed number of requests:
ab -t 60 -c 20 https://example.com/The duration is supplied by your test plan. A time-bounded run is useful when you want to observe a steady interval, but it does not remove the need to monitor the server or record the exact command.
Enable HTTP persistent connections
Add -k to request keep-alive behavior:
ab -n 1000 -c 20 -k https://example.com/Keep-alive changes connection reuse and therefore changes the workload. Compare a keep-alive run only with another run using the same setting. If your production clients use persistent connections, include a matching test; if you are measuring connection setup behavior, omit it deliberately and label the run accordingly.
Set a socket timeout
Use -s to set the socket timeout in seconds:
ab -n 1000 -c 20 -s 10 https://example.com/A timeout is part of the test definition. A shorter value can classify slow responses as failures sooner, while a longer value allows more time for a delayed response. State the chosen value when you report results.
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Send the request your application actually needs
A plain GET of the home page is only one workload. ApacheBench provides switches for common request variations; use them to make the benchmark match the endpoint under examination.
Add a request header
Supply a header with -H:
ab -n 1000 -c 20 -H 'Accept: application/json' https://example.com/api/itemsHeaders can select a representation, identify a client, or provide another application input. Preserve the exact spelling and value used in your comparison runs.
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Send a cookie
Use -C for a cookie:
ab -n 1000 -c 20 -C 'session=example-value' https://example.com/accountA cookie can move an endpoint from an anonymous code path to a session-specific one. Use only test credentials and test session data, and do not paste production secrets into a command that may be saved in shell history.
Supply Basic Authentication
Use -A with a username and password:
ab -n 1000 -c 20 -A 'username:password' https://example.com/privateOnly authenticate to systems you are authorized to test. Credentials written directly in a command can be exposed through shell history, process listings, terminal logs, or copied test records. Prefer a controlled test account and remove sensitive command output from shared logs.
POST a request body
Use -p to read a body from a file and -T to declare its content type:
ab -n 500 -c 10 -p body.json -T application/json https://example.com/api/itemsThe file must contain the body you intend to send. A POST benchmark can trigger writes, jobs, messages, or other side effects, so use an endpoint and data set designed for testing. Keep the body file, content type, and request count in the run record.
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Issue HEAD requests
Add -i to issue HEAD requests when you need headers without downloading a response body:
ab -n 1000 -c 20 -i https://example.com/assets/app.jsHEAD and GET exercise different application and transfer paths. Do not compare their requests-per-second values as if they were the same workload.
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How to read ApacheBench output
ApacheBench prints a group of measurements. Read them together rather than selecting the largest requests-per-second figure.
| Output field | What it tells you | How to use it |
|---|---|---|
| Concurrency Level | The concurrency configured for the run. | Confirm that the run used the intended -c value before comparing it with another run. |
| Time taken for tests | Elapsed time for the benchmark. | Use it to understand the interval over which the totals and averages were calculated. |
| Complete requests | Requests completed by the run. | Check that the completed count matches the workload you intended to send. |
| Failed requests | Requests ApacheBench considered failures because of connection, read, content-length, or exception problems. | Investigate failures before treating throughput as acceptable. |
| Non-2xx responses | Responses outside the successful 200 range. | Check application behavior, routing, authentication, and server logs; a fast error is not successful capacity. |
| Keep-Alive requests | Requests handled using persistent connections. | Verify that the result reflects the intended -k setting. |
| Total transferred | Total data transferred during the run. | Use it to see how much traffic the test generated and whether response size is a factor. |
| HTML transferred | Transferred response content counted as HTML data. | Compare runs with the same response and payload characteristics. |
| Requests per second | Total requests divided by elapsed test time. | Use as a throughput measure only alongside errors, latency, protocol, and concurrency. |
| Time per request | ApacheBench’s reported average request timing. | Compare it only across otherwise identical runs. |
| Transfer rate | Rate at which response data was received. | Consider it when response size, bandwidth, or network capacity may limit the run. |
A higher requests-per-second value is not an improvement if failed requests or non-2xx responses rise. For each run, preserve the complete output and pair it with server-side logs and metrics. A valid comparison keeps the URL, protocol, method, payload, authentication, headers, cookies, keep-alive setting, timeout, and concurrency controlled.
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A single concurrency value tells you what happened at one pressure level. A ramp shows where behavior changes. Start with a modest value, run the same endpoint and request definition, then increase concurrency in steps. At every step, capture the command, elapsed time, complete requests, failed requests, non-2xx responses, requests per second, time per request, and transfer rate.
Keep the total request count or duration sufficient for a meaningful sample, but do not let an early successful run justify an unlimited increase. Watch for a point where latency grows, failures appear, non-2xx responses increase, or the application and connection limits become saturated. That transition is more useful than a maximum number obtained after the service is already returning errors.
Repeat each important step with the same conditions. If the first run warms a cache or initializes application resources, label that run and decide whether your capacity question concerns a cold or warm state. Do not mix those states in one comparison.
Use acceptance criteria that include errors and latency
Define success before running the test. A practical acceptance record includes:
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- The HTTP method, body, content type, headers, cookies, and authentication state.
- The requested total or duration and the concurrency.
- Whether keep-alive was enabled and which socket timeout was used.
- Zero or an explicitly reviewed number of failed requests.
- Zero or an explicitly reviewed number of non-2xx responses.
- A requests-per-second result interpreted with its time per request and transfer rate.
- Server-side CPU, memory, connection, access-log, error-log, and application observations.
These criteria prevent a fast stream of error responses from being reported as healthy capacity. They also make it possible to explain why two runs with similar throughput may have very different operational value.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Common failure signals and what to investigate
Failed requests are nonzero
ApacheBench counts connection, read, content-length, and exception problems as failed requests. Separate those categories in your investigation using the command output and the server’s access and error logs. Check whether the failures begin only after a concurrency increase, whether the socket timeout is too short for the endpoint, and whether the server or an intermediary is rejecting connections.
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Non-2xx responses appear
Non-2xx responses are not necessarily transport failures, but they are outside the successful 200 range. Inspect the response behavior and application logs for routing, authentication, validation, rate limiting, or other endpoint conditions. Decide whether the response is expected for the test; do not silently count it as successful service.
Throughput rises while timing worsens
Requests per second is an aggregate throughput value. As concurrency increases, throughput may rise while average time per request also rises. Compare both fields and look at server resource usage. A run that processes more requests but produces unacceptable latency is not automatically a better operating point.
Transfer rate changes unexpectedly
Transfer rate depends on the amount of response data and how quickly it is received. Confirm that the endpoint, response representation, compression behavior, protocol, and request headers are unchanged before attributing a transfer-rate difference to server processing.
Compare HTTP, HTTPS, and connection behavior deliberately
ApacheBench accepts HTTP and HTTPS URLs. Protocol choice is part of the workload: use the same protocol when comparing application changes, and test each protocol separately when the deployment serves both. Do not combine an HTTP run and an HTTPS run into one throughput claim.
Likewise, persistent and non-persistent connections answer different questions. A command with -k measures behavior with keep-alive requested; a command without it measures a different connection pattern. Record this switch alongside concurrency and request count so the result remains interpretable.
What ApacheBench cannot tell you
ab does not reproduce every browser behavior, user think time, cache pattern, or multi-step application journey. It is therefore unsuitable as the sole basis for a claim about the capacity of an entire site or a complete user experience. A homepage GET, an authenticated POST, and a sequence involving several pages are different workloads even when they target the same server.
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Use ApacheBench when the question is narrow and controlled: for example, comparing one endpoint before and after a configuration change under the same request conditions. When the question is realistic user capacity, define the user journey, request mix, pauses, cache state, authentication, and acceptance criteria, then choose a workload model or another load-testing approach that can represent those conditions.
Quick Recap
A compact runbook
- Confirm ownership or written authorization for the target.
- Install and verify
apache2-utils,ab -V, andab -h. - Choose one endpoint and document its method, protocol, payload, headers, cookies, and authentication.
- Start with explicit
-nand-cvalues, such asab -n 1000 -c 20 https://example.com/. - Set
-k,-s,-t, or request-specific switches only when they match the question you are testing. - Monitor CPU, memory, logs, connection limits, and application metrics while the run executes.
- Increase concurrency gradually, recording the full command and output for every step.
- Evaluate complete and failed requests, non-2xx responses, requests per second, time per request, and transfer rate together.
- Repeat identical runs before drawing a conclusion, and report the workload conditions with the result.
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