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Have you ever been attacked by a goose?

crates.io Documentation Apache-2.0 licensed CI Docker Repository on Quay


Goose is a Rust load testing tool inspired by Locust. User behavior is defined with standard Rust code. Load tests are applications that have a dependency on the Goose library. Web requests are made with the Reqwest HTTP Client.

Getting Started

The in-line documentation offers much more detail about Goose specifics. For a general background to help you get started with Rust and Goose, read on.

Cargo is the Rust package manager. To create a new load test, use Cargo to create a new application (you can name your application anything, we've generically selected loadtest):

$ cargo new loadtest
     Created binary (application) `loadtest` package
$ cd loadtest/

This creates a new directory named loadtest/ containing loadtest/Cargo.toml and loadtest/src/main.rs. Start by editing Cargo.toml adding Goose under the dependencies heading:

goose = "^0.10"

At this point it's possible to compile all dependencies, though the resulting binary only displays "Hello, world!":

$ cargo run
    Updating crates.io index
  Downloaded goose v0.10.7
   Compiling goose v0.10.7
   Compiling loadtest v0.1.0 (/home/jandrews/devel/rust/loadtest)
    Finished dev [unoptimized + debuginfo] target(s) in 52.97s
     Running `target/debug/loadtest`
Hello, world!

To create an actual load test, you first have to add the following boilerplate to the top of src/main.rs to make Goose's functionality available to your code:

use goose::prelude::*;

Then create a new load testing function. For our example we're simply going to load the front page of the website we're load-testing. Goose passes all load testing functions a pointer to a GooseUser object, which is used to track metrics and make web requests. Thanks to the Reqwest library, the Goose client manages things like cookies, headers, and sessions for you. Load testing functions must be declared async, which helps ensure that your simulated users don't become CPU-locked.

In load test functions you typically do not set the host, and instead configure the host at run time, so you can easily run your load test against different environments without recompiling. The following loadtest_index function simply loads the front page of our web page:

async fn loadtest_index(user: &GooseUser) -> GooseTaskResult {
    let _goose_metrics = user.get("/").await?;


The function is declared async so that we don't block a CPU-core while loading web pages. All Goose load test functions are passed in a reference to a GooseUser object, and return a GooseTaskResult which is either an empty Ok(()) on success, or a GooseTaskError on failure. We use the GooseUser object to make requests, in this case we make a GET request for the front page, /. The .await frees up the CPU-core while we wait for the web page to respond, and the tailing ? passes up any unexpected errors that may be returned from this request. When the request completes, Goose returns metrics which we store in the _goose_metrics variable. The variable is prefixed with an underscore (_) to tell the compiler we are intentionally not using the results. Finally, after making a single successful request, we return Ok(()) to let Goose know this task function completed successfully.

We have to tell Goose about our new task function. Edit the main() function, setting a return type and replacing the hello world text as follows:

fn main() -> Result<(), GooseError> {

If you're new to Rust, main()'s return type of Result<(), GooseError> may look strange. It essentially says that main will return nothing (()) on success, and will return a GooseError on failure. This is helpful as several of GooseAttack's methods can fail, returning an error. In our example, initialize() and execute() each may fail. The ? that follows the method's name tells our program to exit and return an error on failure, otherwise continue on. The print() method consumes the GooseMetrics object returned by GooseAttack.execute() and prints a summary if metrics are enabled. The final line, Ok(()) returns the empty result expected on success.

And that's it, you've created your first load test! Let's run it and see what happens.

$ cargo run
   Compiling loadtest v0.1.0 (/home/jandrews/devel/rust/loadtest)
    Finished dev [unoptimized + debuginfo] target(s) in 3.56s
     Running `target/debug/loadtest`
Error: InvalidOption { option: "--host", value: "", detail: "A host must be defined via the --host option, the GooseAttack.set_default() function, or the GooseTaskSet.set_host() function (no host defined for LoadtestTasks)." }

Goose is unable to run, as it hasn't been told the host you want to load test. So, let's try again, this time passing in the --host flag. After running for a few seconds, we then press ctrl-c to stop the load test:

$ cargo run -- --host http://local.dev/
    Finished dev [unoptimized + debuginfo] target(s) in 0.07s
     Running `target/debug/loadtest --host 'http://local.dev/'`

 Name                    | # times run    | # fails        | task/s | fail/s
 1: LoadtestTasks        |
   1:                    | 2,240          | 0 (0%)         | 280.0  | 0.000
 Name                    | Avg (ms)   | Min        | Max        | Median    
 1: LoadtestTasks        |
   1:                    | 15.54      | 6          | 136        | 14        

 Name                    | # reqs         | # fails        | req/s  | fail/s
 GET /                   | 2,240          | 0 (0%)         | 280.0  | 0.000
 Name                    | Avg (ms)   | Min        | Max        | Median    
 GET /                   | 15.30      | 6          | 135        | 14        

All 8 users hatched, resetting metrics (disable with --no-reset-metrics).

^C06:03:25 [ WARN] caught ctrl-c, stopping...

 Name                    | # times run    | # fails        | task/s | fail/s
 1: LoadtestTasks        |
   1:                    | 2,054          | 0 (0%)         | 410.8  | 0.000
 Name                    | Avg (ms)   | Min        | Max        | Median    
 1: LoadtestTasks        |
   1:                    | 20.86      | 7          | 254        | 19        

 Name                    | # reqs         | # fails        | req/s  | fail/s
 GET /                   | 2,054          | 0 (0%)         | 410.8  | 0.000
 Name                    | Avg (ms)   | Min        | Max        | Median    
 GET /                   | 20.68      | 7          | 254        | 19        
 Slowest page load within specified percentile of requests (in ms):
 Name                    | 50%    | 75%    | 98%    | 99%    | 99.9%  | 99.99%
 GET /                   | 19     | 21     | 53     | 69     | 250    | 250   

By default, Goose will hatch 1 GooseUser per second, up to the number of CPU cores available on the server used for load testing. In the above example, the server has 8 CPU cores, so it took 8 seconds to hatch all users. After all users are hatched, Goose flushes all metrics collected during the hatching process so all subsequent metrics are taken with all users running. Before flushing the metrics, they are displayed to the console so the data is not lost.

The same metrics are displayed per-task and per-request. In our simple example, our single task only makes one request, so in this case both metrics show the same results.

The per-task metrics are displayed first, starting with the name of our Task Set, LoadtestTasks. Individual tasks in the Task Set are then listed in the order they are defined in our load test. We did not name our task, so it simply shows up as 1: . All defined tasks will be listed here, even if they did not run, so this can be useful to confirm everything in your load test is running as expected.

Next comes the per-request metrics. Our single task makes a GET request for the / path, so it shows up in the metrics as GET /. Comparing the per-task metrics collected for 1: to the per-request metrics collected for GET /, you can see that they are the same.

There are two common tables found in each type of metrics. The first shows the total number of requests made (2,054), how many of those failed (0), the average number of requests per second (410.8), and the average number of failed requests per second (0).

The second table shows the average time required to load a page (20.68 milliseconds), the minimum time to load a page (7 ms), the maximum time to load a page (254 ms) and the median time to load a page (19 ms).

The per-request metrics include a third table, showing the slowest page load time for a range of percentiles. In our example, in the 50% fastest page loads, the slowest page loaded in 19 ms. In the 75% fastest page loads, the slowest page loaded in 21 ms, etc.

In real load tests, you'll most likely have multiple task sets each with multiple tasks, and Goose will show you metrics for each along with an aggregate of them all together.

Refer to the examples directory for more complicated and useful load test examples.


  • Avoid unwrap() in your task functions -- Goose generates a lot of load, and this tends to trigger errors. Embrace Rust's warnings and properly handle all possible errors, this will save you time debugging later.
  • When running your load test for real, use the cargo --release flag to generate optimized code. This can generate considerably more load test traffic.

Simple Example

The -h flag will show all run-time configuration options available to Goose load tests. For example, you can pass the -h flag to the simple example as follows, cargo run --example simple -- -h:

Usage: target/debug/examples/simple [OPTIONS]

Options available when launching a Goose load test.

Optional arguments:
  -h, --help                 Displays this help
  -V, --version              Prints version information
  -l, --list                 Lists all tasks and exits

  -H, --host HOST            Defines host to load test (ie
  -u, --users USERS          Sets concurrent users (default: number of CPUs)
  -r, --hatch-rate RATE      Sets per-second user hatch rate (default: 1)
  -t, --run-time TIME        Stops after (30s, 20m, 3h, 1h30m, etc)
  -g, --log-level            Sets log level (-g, -gg, etc)
  -L, --log-file NAME        Enables log file and sets name
  -v, --verbose              Sets debug level (-v, -vv, etc)

  --running-metrics TIME     How often to optionally print running metrics
  --no-reset-metrics         Doesn't reset metrics after all users have started
  --no-metrics               Doesn't track metrics
  --no-task-metrics          Doesn't track task metrics
  -m, --requests-file NAME   Sets requests log file name
  --requests-format FORMAT   Sets requests log format (csv, json, raw)
  -d, --debug-file NAME      Sets debug log file name
  --debug-format FORMAT      Sets debug log format (json, raw)
  --no-debug-body            Do not include the response body in the debug log
  --status-codes             Tracks additional status code metrics

  --throttle-requests VALUE  Sets maximum requests per second
  --sticky-follow            Follows base_url redirect with subsequent requests

  --manager                  Enables distributed load test Manager mode
  --expect-workers VALUE     Sets number of Workers to expect
  --no-hash-check            Tells Manager to ignore load test checksum
  --manager-bind-host HOST   Sets host Manager listens on (default:
  --manager-bind-port PORT   Sets port Manager listens on (default: 5115)
  --worker                   Enables distributed load test Worker mode
  --manager-host HOST        Sets host Worker connects to (default:
  --manager-port PORT        Sets port Worker connects to (default: 5115)

The examples/simple.rs example copies the simple load test documented on the locust.io web page, rewritten in Rust for Goose. It uses minimal advanced functionality, but demonstrates how to GET and POST pages. It defines a single Task Set which has the user log in and then load a couple of pages.

Goose can make use of all available CPU cores. By default, it will launch 1 user per core, and it can be configured to launch many more. The following was configured instead to launch 1,024 users. Each user randomly pauses 5 to 15 seconds after each task is loaded, so it's possible to spin up a large number of users. Here is a snapshot of top when running this example on a 1-core VM with 10G of available RAM -- there were ample resources to launch considerably more "users", though ulimit had to be resized:

top - 06:56:06 up 15 days,  3:13,  2 users,  load average: 0.22, 0.10, 0.04
Tasks: 116 total,   3 running, 113 sleeping,   0 stopped,   0 zombie
%Cpu(s):  1.7 us,  0.7 sy,  0.0 ni, 96.7 id,  0.0 wa,  0.0 hi,  1.0 si,  0.0 st
MiB Mem :   9994.9 total,   7836.8 free,   1101.2 used,   1056.9 buff/cache
MiB Swap:  10237.0 total,  10237.0 free,      0.0 used.   8606.9 avail Mem 

  PID USER      PR  NI    VIRT    RES    SHR S  %CPU  %MEM     TIME+ COMMAND    
 1339 goose     20   0 1235480 758292   8984 R   3.0   7.4   0:06.56 simple     

Here's the output of running the loadtest. The -v flag sends INFO and more critical messages to stdout (in addition to the log file). The -u1024 tells Goose to spin up 1,024 users. The -r32 option tells Goose to hatch 32 users per second. The -t10m option tells Goose to run the load test for 10 minutes, or 600 seconds. The --status-codes flag tells Goose to track metrics about HTTP status codes returned by the server, in addition to the default per-task and per-request metrics. The --no-reset-metrics flag tells Goose to start tracking the 10m run-time from when the first user starts, instead of the default which is to flush all metrics and start timing after all users have started. And finally, the --only-summary flag tells Goose to only display the final metrics after the load test finishes, otherwise it would display running metrics every 15 seconds for the duration of the test.

$ cargo run --release --example simple -- --host http://local.dev -v -u1024 -r32 -t10m --status-codes --no-reset-metrics --only-summary
    Finished release [optimized] target(s) in 0.09s
     Running `target/release/examples/simple --host 'http://local.dev' -v -u1024 -r32 -t10m --status-codes --no-reset-metrics --only-summary`
10:55:04 [ INFO] Output verbosity level: INFO
10:55:04 [ INFO] Logfile verbosity level: INFO
10:55:04 [ INFO] Writing to log file: goose.log
10:55:04 [ INFO] run_time = 600
10:55:04 [ INFO] global host configured: http://local.dev
10:55:04 [ INFO] initializing user states...
10:55:09 [ INFO] launching user 1 from WebsiteUser...
10:55:09 [ INFO] launching user 2 from WebsiteUser...
10:55:09 [ INFO] launching user 3 from WebsiteUser...


10:55:42 [ INFO] launching user 1022 from WebsiteUser...
10:55:42 [ INFO] launching user 1023 from WebsiteUser...
10:55:42 [ INFO] launching user 1024 from WebsiteUser...
10:55:42 [ INFO] launched 1024 users...
All 1024 users hatched.

11:05:09 [ INFO] stopping after 600 seconds...
11:05:09 [ INFO] waiting for users to exit
11:05:09 [ INFO] exiting user 879 from WebsiteUser...
11:05:09 [ INFO] exiting user 41 from WebsiteUser...
11:05:09 [ INFO] exiting user 438 from WebsiteUser...


11:05:10 [ INFO] exiting user 268 from WebsiteUser...
11:05:10 [ INFO] exiting user 864 from WebsiteUser...
11:05:10 [ INFO] exiting user 55 from WebsiteUser...
11:05:11 [ INFO] printing metrics after 601 seconds...

 Name                    | # times run    | # fails        | task/s | fail/s
 1: WebsiteUser          |
   1:                    | 1,024          | 0 (0%)         | 1.707  | 0.000
   2:                    | 28,746         | 0 (0%)         | 47.91  | 0.000
   3:                    | 28,748         | 0 (0%)         | 47.91  | 0.000
 Aggregated              | 58,518         | 0 (0%)         | 97.53  | 0.000
 Name                    | Avg (ms)   | Min        | Max        | Median    
 1: WebsiteUser          |
   1:                    | 5.995      | 5          | 37         | 6         
   2:                    | 0.428      | 0          | 17         | 0         
   3:                    | 0.360      | 0          | 37         | 0         
 Aggregated              | 0.492      | 5          | 37         | 5         

 Name                    | # reqs         | # fails        | req/s  | fail/s
 GET /                   | 28,746         | 0 (0%)         | 47.91  | 0.000
 GET /about/             | 28,748         | 0 (0%)         | 47.91  | 0.000
 POST /login             | 1,024          | 0 (0%)         | 1.707  | 0.000
 Aggregated              | 58,518         | 29,772 (50.9%) | 97.53  | 49.62
 Name                    | Avg (ms)   | Min        | Max        | Median    
 GET /                   | 0.412      | 0          | 17         | 0         
 GET /about/             | 0.348      | 0          | 37         | 0         
 POST /login             | 5.979      | 5          | 37         | 6         
 Aggregated              | 0.478      | 5          | 37         | 5         
 Slowest page load within specified percentile of requests (in ms):
 Name                    | 50%    | 75%    | 98%    | 99%    | 99.9%  | 99.99%
 GET /                   | 0      | 1      | 3      | 4      | 5      | 5     
 GET /about/             | 0      | 0      | 3      | 3      | 5      | 5     
 POST /login             | 6      | 6      | 7      | 7      | 28     | 28    
 Aggregated              | 5      | 5      | 5      | 6      | 7      | 17    
 Name                    | Status codes              
 GET /                   | 28,746 [200]             
 GET /about/             | 28,748 [200]             
 POST /login             | 1,024 [200]              
 Aggregated              | 58,518 [200]

Scheduling GooseTaskSets

When starting a load test, Goose assigns one GooseTaskSet to each GooseUser thread. By default, it assigns GooseTaskSets in a round robin order. As new GooseUser threads are launched, the first will be assigned the first defined GooseTaskSet, the next will be assigned the next defined GooseTaskSet, and so on, looping through all available GooseTaskSets. Weighting is respected during this process, so if one GooseTaskSet is weighted heavier than others, that GooseTaskSet will get assigned more at the end of the launching process.

It is also possible to allocate GooseTaskSets in a serial or random order. When allocating GooseTaskSets serially, they are launched in the exact order and weighting as they are defined in the load test. When allocating randomly, running the same load test multiple times can generate different amounts of load.

Prior to Goose 0.10.6 GooseTaskSets were allocated in a serial order. To restore this behavior, you can use the .set_scheduler() function as follows:


Or, to randomize the order GooseTaskSets are allocated to newly launched users, you can instead configure your GooseAttack as follows:


The following configuration is possible but superfluous because it is the scheduling default:



All run-time options can be configured with custom defaults. For example, you may want to default to the the host name of your local development environment, only requiring that --host be set when running against a production environment. Assuming your local development environment is at "http://local.dev/" you can do this as follows:

        .set_default(GooseDefault::Host, "http://local.dev/")?

The following defaults can be configured with a &str:

  • host: GooseDefault::Host
  • log file name: GooseDefault::LogFile
  • requests log file name: GooseDefault::RequestsFile
  • requests log file format: GooseDefault::RequestsFormat
  • debug log file name: GooseDefault::DebugFile
  • debug log file format: GooseDefault::DebugFormat
  • host to bind Manager to: GooseDefault::ManagerBindHost
  • host for Worker to connect to: GooseDefault::ManagerHost

The following defaults can be configured with a usize integer:

  • total users to start: GooseDefault::Users
  • users to start per second: GooseDefault::HatchRate
  • how often to print running statistics: GooseDefault::RunningStatistics
  • number of seconds for test to run: GooseDefault::RunTime
  • log level: GooseDefault::LogLevel
  • verbosity: GooseDefault::Verbose
  • maximum requests per second: GooseDefault::ThrottleRequests
  • number of Workers to expect: GooseDefault::ExpectWorkers
  • port to bind Manager to: GooseDefault::ManagerBindPort
  • port for Worker to connect to: GooseDefault::ManagerPort

The following defaults can be configured with a bool:

  • do not reset metrics after all users start: GooseDefault::NoResetMetrics
  • do not track metrics: GooseDefault::NoMetrics
  • do not track task metrics: GooseDefault::NoTaskMetrics
  • track status codes: GooseDefault::StatusCodes
  • follow redirect of base_url: GooseDefault::StickyFollow
  • enable Manager mode: GooseDefault::Manager
  • ignore load test checksum: GooseDefault::NoHashCheck
  • enable Worker mode: GooseDefault::Worker

For example, without any run-time options the following load test would automatically run against local.dev, logging metrics to goose-metrics.log and debug to goose-debug.log. It will automatically launch 20 users in 4 seconds, and run the load test for 15 minutes. Metrics will be displayed every minute during the test and will include additional status code metrics. The order the defaults are set is not important.

        .set_default(GooseDefault::Host, "local.dev")?
        .set_default(GooseDefault::RequestsFile, "goose-requests.log")?
        .set_default(GooseDefault::DebugFile, "goose-debug.log")?
        .set_default(GooseDefault::Users, 20)?
        .set_default(GooseDefault::HatchRate, 4)?
        .set_default(GooseDefault::RunTime, 900)?
        .set_default(GooseDefault::RunningStatistics, 60)?
        .set_default(GooseDefault::StatusCodes, true)?

Throttling Requests

By default, Goose will generate as much load as it can. If this is not desirable, the throttle allows optionally limiting the maximum number of requests per second made during a load test. This can be helpful to ensure consistency when running a load test from multiple different servers with different available resources.

The throttle is specified as an integer. For example:

$ cargo run --example simple -- --host http://local.dev/ -u100 -r20 -v --throttle-requests 5

In this example, Goose will launch 100 GooseUser threads, but the throttle will prevent them from generating a combined total of more than 5 requests per second. The --throttle-requests command line option imposes a maximum number of requests, not a minimum number of requests.

Logging Load Test Requests

Goose can optionally log details about all load test requests to a file. To enable, add the --requests-file=foo command line option, where foo is either a relative or absolute path of the log file to create. Any existing file that may already exist will be overwritten.

When operating in Gaggle-mode, the --requests--file option can only be enabled on the Worker processes, configuring Goose to spread out the overhead of writing logs.

By default, logs are written in JSON Lines format. For example:


Logs include the entire GooseRawRequest object as defined in src/goose.rs, which are created on all requests. This object includes the following fields:

  • elapsed: total milliseconds between when the GooseUser thread started and this request was made;
  • method: the type of HTTP request made;
  • name: the name of the request;
  • url: the URL that was requested;
  • final_url: the URL that was returned (may be different if the request was redirected);
  • redirected: true or false if the request was redirected;
  • response_time: how many milliseconds the request took;
  • status_code: the HTTP response code returned for this request;
  • success: true or false if this was a successful request;
  • update: true or false if this is a recurrence of a previous log entry, but with success toggling between true and false. This happens when a load test calls set_success() on a request that Goose previously interpreted as a failure, or set_failure() on a request previously interpreted as a success;
  • user: an integer value indicating which GooseUser thread made this request.

In the first line of the above example, GooseUser thread 0 made a POST request to /login and was successfully redirected to /user/42 in 220 milliseconds. The second line is the same GooseUser thread which then made a GET request to / in 3 milliseconds. The third and fourth lines are a second GooseUser thread doing the same thing, first logging in and then loading the front page.

By default Goose logs requests in JSON Lines format. The --metrics-log-format option can be used to log in csv, json or raw format. The raw format is Rust's debug output of the entire GooseRawRequest object.

For example, csv output of the same requests logged above would look like:


Load Test Debug Logging

Goose can optionally log details about requests and responses for debug purposes. When writing a load test you must invoke client.log_debug(tag, Option<request>, Option<headers>, Option<body>) where tag is an arbitrary string to identify where in the load test and/or why debug is being written, request is an optional reference to a GooseRawRequest object, headers are an optional reference to the HTTP headers returned by the server, and body is an optionial reference to the web page body returned by the server.

For an example on how to correctly use client.log_debug(), including how to obtain the response headers and body, see examples/drupal_loadtest.

If the load test is run with the --debug-log-file=foo command line option, where foo is either a relative or an absolute path, Goose will log all debug generated by calls to client.log_debug() to this file. For example:

{"body":"<!DOCTYPE html>\n<html>\n  <head>\n    <title>503 Backend fetch failed</title>\n  </head>\n  <body>\n    <h1>Error 503 Backend fetch failed</h1>\n    <p>Backend fetch failed</p>\n    <h3>Guru Meditation:</h3>\n    <p>XID: 923425</p>\n    <hr>\n    <p>Varnish cache server</p>\n  </body>\n</html>\n","header":"{\"date\": \"Wed, 01 Jul 2020 10:27:31 GMT\", \"server\": \"Varnish\", \"content-type\": \"text/html; charset=utf-8\", \"retry-after\": \"5\", \"x-varnish\": \"923424\", \"age\": \"0\", \"via\": \"1.1 varnish (Varnish/6.1)\", \"x-varnish-cache\": \"MISS\", \"x-varnish-cookie\": \"SESSd7e04cba6a8ba148c966860632ef3636=hejsW1mQnnsHlua0AicCjEpUjnCRTkOLubwL33UJXRU\", \"content-length\": \"283\", \"connection\": \"keep-alive\"}","request":{"elapsed":4192,"final_url":"http://local.dev/node/3247","method":"GET","name":"(Auth) comment form","redirected":false,"response_time":8,"status_code":503,"success":false,"update":false,"url":"http://local.dev/node/3247","user":4},"tag":"post_comment: no form_build_id found on node/3247"}

If --debug-log-file=foo is not specified at run time, nothing will be logged.

By default Goose writes debug logs in JSON Lines format. The --debug-log-format option can be used to log in json or raw format. The raw format is Rust's debug output of the entire GooseDebug object.

Gaggle: Distributed Load Test

Goose also supports distributed load testing. A Gaggle is one Goose process running in Manager mode, and 1 or more Goose processes running in Worker mode. The Manager coordinates starting and stopping the Workers, and collects aggregated metrics. Gaggle support is a cargo feature that must be enabled at compile-time as documented below. To launch a Gaggle, you must copy your load test application to all servers from which you wish to generate load.

It is strongly recommended that the same load test application be copied to all servers involved in a Gaggle. By default, Goose will verify that the load test is identical by comparing a hash of all load test rules. Telling it to skip this check can cause the load test to panic (for example, if a Worker defines a different number of tasks or task sets than the Manager).

Gaggle Compile-time Feature

Gaggle support is a compile-time Cargo feature that must be enabled. Goose uses the nng library to manage network connections, and compiling nng requires that cmake be available.

The gaggle feature can be enabled from the command line by adding --features gaggle to your cargo command.

When writing load test applications, you can default to compiling in the Gaggle feature in the dependencies section of your Cargo.toml, for example:

goose = { version = "^0.10", features = ["gaggle"] }

Gaggle Manager

To launch a Gaggle, you first must start a Goose application in Manager mode. All configuration happens in the Manager. To start, add the --manager flag and the --expect-workers flag, the latter necessary to tell the Manager process how many Worker processes it will be coordinating. For example:

cargo run --features gaggle --example simple -- --manager --expect-workers 2 --host http://local.dev/ -v

This configures a Goose Manager to listen on all interfaces on the default port ( for 2 Goose Worker processes.

Gaggle Worker

At this time, a Goose process can be either a Manager or a Worker, not both. Therefor, it usually makes sense to launch your first Worker on the same server that the Manager is running on. If not otherwise configured, a Goose Worker will try to connect to the Manager on the localhost. This can be done as follows:

cargo run --features gaggle --example simple -- --worker -v

In our above example, we expected 2 Workers. The second Goose process should be started on a different server. This will require telling it the host where the Goose Manager process is running. For example:

cargo run --example simple -- --worker --manager-host -v

Once all expected Workers are running, the distributed load test will automatically start. We set the -v flag so Goose provides verbose output indicating what is happening. In our example, the load test will run until it is canceled. You can cancel the Manager or either of the Worker processes, and the test will stop on all servers.

Gaggle Run-time Flags

  • --manager: starts a Goose process in Manager mode. There currently can only be one Manager per Gaggle.
  • --worker: starts a Goose process in Worker mode. How many Workers are in a given Gaggle is defined by the --expect-workers option, documented below.
  • --no-hash-check: tells Goose to ignore if the load test application doesn't match between Worker(s) and the Manager. This is not recommended, and can cause the application to panic.

The --no-metrics, --only-summary, --no-reset-metrics, --status-codes, and --no-hash-check flags must be set on the Manager. Workers inherit these flags from the Manager

Gaggle Run-time Options

  • --manager-bind-host <manager-bind-host>: configures the host that the Manager listens on. By default Goose will listen on all interfaces, or
  • --manager-bind-port <manager-bind-port>: configures the port that the Manager listens on. By default Goose will listen on port 5115.
  • --manager-host <manager-host>: configures the host that the Worker will talk to the Manager on. By default, a Goose Worker will connect to the localhost, or In a distributed load test, this must be set to the IP of the Goose Manager.
  • --manager-port <manager-port>: configures the port that a Worker will talk to the Manager on. By default, a Goose Worker will connect to port 5115.

The --users, --hatch-rate, --host, and --run-time options must be set on the Manager. Workers inherit these options from the Manager.

The --throttle-requests option must be configured on each Worker, and can be set to a different value on each Worker if desired.

Technical Details

Goose uses nng to send network messages between the Manager and all Workers. Serde and Serde CBOR are used to serialize messages into Concise Binary Object Representation.

Workers initiate all network connections, and push metrics to the Manager process.


By default Reqwest (and therefore Goose) uses the system-native transport layer security to make HTTPS requests. This means schannel on Windows, Security-Framework on macOS, and OpenSSL on Linux. If you'd prefer to use a pure Rust TLS implementation, disable default features and enable rustls in Cargo.toml as follows:

goose = { version = "^0.10", default-features = false, features = ["rustls"] }


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