# How to execute scenarios

**Note:** you can provide file with all environment variables (system env variables overrides env from file) using
`-e ENV_FILE=.env` (relative path to that file must start from working directory):
```shell
$ ./k6 run -e ENV_FILE=.env some-scenario.js
```

## Common options for all scenarios:

Scenarios `grpc.js`, `local.js`, `http.js` and `s3.js` support the following options:
  * `DURATION` - duration of scenario in seconds.
  * `READERS` - number of VUs performing read operations.
  * `WRITERS` - number of VUs performing write operations.
  * `REGISTRY_FILE` - if set, all produced objects will be stored in database for subsequent verification. Database file name will be set to the value of `REGISTRY_FILE`.
  * `WRITE_OBJ_SIZE` - object size in kb for write(PUT) operations.
  * `PREGEN_JSON` - path to json file with pre-generated containers and objects (in case of http scenario we use json pre-generated for grpc scenario).
  * `SLEEP_WRITE` - time interval (in seconds) between writing VU iterations.
  * `SLEEP_READ` - time interval (in seconds) between reading VU iterations.
  * `SELECTION_SIZE` - size of batch to select for deletion (default: 1000).
  * `PAYLOAD_TYPE` - type of an object payload ("random" or "text", default: "random").
  * `STREAMING` - if set, the payload is generated on the fly and is not read into memory fully.
  * `METRIC_TAGS` - `instance` tag value.

Additionally, the profiling extension can be enabled to generate CPU and memory profiles which can be inspected with `go tool pprof file.prof`:
```shell
$ ./k6 run --out profile (...)
```
The profiles are saved in the current directory as `cpu.prof` and `mem.prof`, respectively.

## Common options for the local scenarios:

  * `DEBUG_LOGGER` - uses a development logger for the local storage engine to aid debugging (default: false).

Examples of how to use these options are provided below for each scenario.

## gRPC

1. Create pre-generated containers or objects:

The tests will use all pre-created containers for PUT operations and all pre-created objects for READ operations.

```shell
$ ./scenarios/preset/preset_grpc.py --size 1024 --containers 1 --out grpc.json --endpoint host1:8080 --preload_obj 500 --policy "REP 2 IN X CBF 1 SELECT 2 FROM * AS X" 
```
  * `--policy` - container policy. If parameter is omitted, the default value is "REP 1 IN X CBF 1 SELECT 1 FROM * AS X".
  * `--update` - container id. Specify the existing container id, if parameter is omitted the new container will be created.
2. Execute scenario with options:

```shell
$ ./k6 run -e DURATION=60 -e WRITE_OBJ_SIZE=8192 -e READERS=20 -e WRITERS=20 -e DELETERS=30 -e DELETE_AGE=10 -e REGISTRY_FILE=registry.bolt -e GRPC_ENDPOINTS=host1:8080,host2:8080 -e PREGEN_JSON=./grpc.json scenarios/grpc.js
```

Options (in addition to the common options):
  * `GRPC_ENDPOINTS` - GRPC endpoints of FrostFS storage in format `host:port`. To specify multiple endpoints separate them by comma.
  * `DELETERS` - number of VUs performing delete operations (using deleters requires that options `DELETE_AGE` and `REGISTRY_FILE` are specified as well).
  * `DELETE_AGE` - age of object in seconds before which it can not be deleted. This parameter can be used to control how many objects we have in the system under load.
  * `SLEEP_DELETE` - time interval (in seconds) between deleting VU iterations.
  * `DIAL_TIMEOUT` - timeout to connect to a node (in seconds).
  * `STREAM_TIMEOUT` - timeout for a single stream message for `PUT`/`GET` operations (in seconds).

## Local

1. Create pre-generated containers or objects:

The tests will use all pre-created containers for PUT operations and all pre-created objects for READ operations. There is no dedicated script to preset HTTP scenario, so we use the same script as for gRPC:
```shell
$ ./scenarios/preset/preset_grpc.py --size 1024 --containers 1 --out grpc.json --endpoint host1:8080 --preload_obj 500
```

2. Execute scenario with options:

```shell
$ ./k6 run -e DURATION=60 -e WRITE_OBJ_SIZE=8192 -e READERS=20 -e WRITERS=20 -e DELETERS=30 -e DELETE_AGE=10 -e REGISTRY_FILE=registry.bolt -e CONFIG_FILE=/path/to/config.yaml -e PREGEN_JSON=./grpc.json scenarios/local.js
```

Options (in addition to the common options):
  * `CONFIG_FILE` - path to the local configuration file used for the storage node. Only the storage configuration section is used.
  * `DELETERS` - number of VUs performing delete operations (using deleters requires that options `DELETE_AGE` and `REGISTRY_FILE` are specified as well).
  * `DELETE_AGE` - age of object in seconds before which it can not be deleted. This parameter can be used to control how many objects we have in the system under load.
  * `MAX_TOTAL_SIZE_GB` - if specified, max payload size in GB of the storage engine. If the storage engine is already full, no new objects will be saved.

## HTTP

1. Create pre-generated containers or objects:

There is no dedicated script to preset HTTP scenario, so we use the same script as for gRPC:
```shell
$ ./scenarios/preset/preset_grpc.py --size 1024 --containers 1 --out grpc.json --endpoint host1:8080 --preload_obj 500
```

2. Execute scenario with options:

```shell
$ ./k6 run -e DURATION=60 -e WRITE_OBJ_SIZE=8192 -e READERS=10 -e WRITERS=20 -e REGISTRY_FILE=registry.bolt -e HTTP_ENDPOINTS=host1:8888,host2:8888 -e PREGEN_JSON=./grpc.json scenarios/http.js
```

Options (in addition to the common options):
  * `HTTP_ENDPOINTS` - endpoints of HTTP gateways in format `host:port`. To specify multiple endpoints separate them by comma.

## S3

1. Create s3 credentials:

```shell
$ frostfs-s3-authmate issue-secret --wallet wallet.json --peer host1:8080 --gate-public-key 03d33a2cc7b8daaa5a3df3fccf065f7cf1fc6a3279efc161fcec512dcc0c1b2277 --gate-public-key 03ff0ad212e10683234442530bfd71d0bb18c3fbd6459aba768eacf158b0c359a2 --gate-public-key 033ae03ff30ed3b6665af69955562cfc0eae18d50e798ab31f054ee22e32fee993 --gate-public-key 02127c7498de0765d2461577c9d4f13f916eefd1884896183e6de0d9a85d17f2fb --bearer-rules rules.json  --container-placement-policy "REP 1 IN X CBF 1 SELECT 1 FROM * AS X" --container-policy ./scenarios/files/policy.json

Enter password for wallet.json > 
{
  "access_key_id": "38xRsCTb2LTeCWNK1x5dPYeWC1X22Lq4ahKkj1NV6tPk0Dack8FteJHQaW4jkGWoQBGQ8R8UW6CdoAr7oiwS7fFQb",
  "secret_access_key": "e671e353375030da3fbf521028cb43810280b814f97c35672484e303037ea1ab",
  "owner_private_key": "48e83ab313ca45fe73c7489565d55652a822ef659c75eaba2d912449713f8e58",
  "container_id": "38xRsCTb2LTeCWNK1x5dPYeWC1X22Lq4ahKkj1NV6tPk"
}
```

Run `aws configure`.

2. Create pre-generated buckets or objects:

The tests will use all pre-created buckets for PUT operations and all pre-created objects for READ operations.

```shell
$ ./scenarios/preset/preset_s3.py --size 1024 --buckets 1 --out s3_1024kb.json --endpoint host1:8084 --preload_obj 500 --location load-1-4
```
  * '--location' - specify the name of container policy (from policy.json file). It's important to run 'aws configure' each time when the policy file has been changed to pick up the latest policies.

3. Execute scenario with options:

```shell
$ ./k6 run -e DURATION=60 -e WRITE_OBJ_SIZE=8192 -e READERS=20 -e WRITERS=20 -e DELETERS=30 -e DELETE_AGE=10 -e S3_ENDPOINTS=host1:8084,host2:8084 -e PREGEN_JSON=s3.json scenarios/s3.js
```

Options (in addition to the common options):
  * `S3_ENDPOINTS` - endpoints of S3 gateways in format `host:port`. To specify multiple endpoints separate them by comma.
  * `DELETERS` - number of VUs performing delete operations (using deleters requires that options `DELETE_AGE` and `REGISTRY_FILE` are specified as well).
  * `DELETE_AGE` - age of object in seconds before which it can not be deleted. This parameter can be used to control how many objects we have in the system under load.
  * `SLEEP_DELETE` - time interval (in seconds) between deleting VU iterations.
  * `OBJ_NAME` - if specified, this name will be used for all write operations instead of random generation.

## S3 Multipart

Perform multipart upload operation, break up large objects, so they can be transferred in multiple parts, in parallel

```shell
$ ./k6 run -e DURATION=600 \
-e WRITERS=400 -e WRITERS_MULTIPART=10 \
-e WRITE_OBJ_SIZE=524288 -e WRITE_OBJ_PART_SIZE=10240  \
-e S3_ENDPOINTS=10.78.70.142:8084,10.78.70.143:8084,10.78.70.144:8084,10.78.70.145:8084 \
-e PREGEN_JSON=/home/service/s3_4kb.json \
scenarios/s3_multipart.js
```

Options:
* `DURATION` - duration of scenario in seconds.
* `REGISTRY_FILE` - if set, all produced objects will be stored in database for subsequent verification. Database file name will be set to the value of `REGISTRY_FILE`.
* `PREGEN_JSON` - path to json file with pre-generated containers.
* `SLEEP_WRITE` - time interval (in seconds) between writing VU iterations.
* `PAYLOAD_TYPE` - type of an object payload ("random" or "text", default: "random").
* `S3_ENDPOINTS` - - endpoints of S3 gateways in format `host:port`. To specify multiple endpoints separate them by comma.
* `WRITERS` - number of VUs performing upload payload operation
* `WRITERS_MULTIPART` - number of goroutines that will upload parts in parallel
* `WRITE_OBJ_SIZE` - object size in kb for write(PUT) operations.
* `WRITE_OBJ_PART_SIZE` - part size in kb for multipart upload operations (must be greater or equal 5mb).

## S3 Local

1. Follow steps 1. and 2. from the normal S3 scenario in order to obtain credentials and a preset file with the information about the buckets and objects that were pre-created.
2. Assuming the preset file was named `pregen.json`, we need to populate the bucket-to-container mapping before running the local S3 scenario:

**WARNING**: Be aware that this command will overwrite the `containers` list field in `pregen.json` file. Make a backup if needed beforehand.

```shell
$ ./scenarios/preset/resolve_containers_in_preset.py --endpoint s3host:8080 --preset_file pregen.json
```

After this, the `pregen.json` file will contain a `containers` list field the same length as `buckets`, which is the mapping of bucket name to container ID in the order they appear.

3. Execute the scenario with the desired options. For example:
```shell
$ ./k6 run -e DURATION=60 -e WRITE_OBJ_SIZE=8192 -e READERS=20 -e WRITERS=20 -e CONFIG_FILE=/path/to/node/config.yml -e PREGEN_JSON=pregen.json scenarios/s3local.js
```

Note that the `s3local` scenario currently does not support deleters.

Options (in addition to the common options):
  * `OBJ_NAME` - if specified, this name will be used for all write operations instead of random generation.
  * `MAX_TOTAL_SIZE_GB` - if specified, max payload size in GB of the storage engine. If the storage engine is already full, no new objects will be saved.

## Export metrics

To export metrics to Prometheus (also Grafana and Victoria Metrics support Prometheus format), you need to run `k6` with an option `-o experimental-prometheus-rw` and
an environment variable `K6_PROMETHEUS_RW_SERVER_URL` whose value corresponds to the URL for the remote write endpoint.
To specify percentiles for trend metrics, use an environment variable `K6_PROMETHEUS_RW_TREND_STATS`.
See [k6 docs](https://k6.io/docs/results-output/real-time/prometheus-remote-write/) for a list of all possible options.
To distinct metrics from different loaders, use an option `METRIC_TAGS`. These tags does not apply to builtin `k6` metrics.

Example:
```bash
K6_PROMETHEUS_RW_SERVER_URL=http://host:8428/api/v1/write \
K6_PROMETHEUS_RW_TREND_STATS="p(95),p(99),min,max" \
./k6 run ... -o experimental-prometheus-rw -e METRIC_TAGS="instance:server1;run:run1" scenario.js
```

## Grafana annotations

There is no option to export Grafana annotaions, but it can be easily done with `curl` and Grafana's annotations API.
Example:
```shell
curl --request POST \
  --url https://user:password@grafana.host/api/annotations \
  --header 'Content-Type: application/json' \
  --data '{
    "dashboardUID": "YsVWNpMIk",
    "time": 1706533045014,
    "timeEnd": 1706533085100,
    "tags": [
        "tag1",
        "tag2"
    ],
    "text": "Test annotation"
}'
```
See [Grafana docs](https://grafana.com/docs/grafana/latest/developers/http_api/annotations/) for details.

## Verify

This scenario allows to verify that objects created by a previous run are really stored in the system and their data is not corrupted. Running this scenario assumes that you've already run gRPC or HTTP or S3 scenario with option `REGISTRY_FILE`.

To verify stored objects execute scenario with options:

```
./k6 run -e CLIENTS=200 -e TIME_LIMIT=120 -e GRPC_ENDPOINTS=host1:8080,host2:8080 -e S3_ENDPOINTS=host1:8084,host2:8084 -e REGISTRY_FILE=registry.bolt scenarios/verify.js
```

Scenario picks up all objects in `created` status. If object is stored correctly, its' status will be changed into `verified`. If object does not exist or its' data is corrupted, then the status will be changed into `invalid`.
Scenario ends as soon as all objects are checked or time limit is exceeded.

Running `VERIFY` scenario modifies status of objects in `REGISTRY_FILE`. Objects that have been verified once won't be verified again. If you would like to verify the same set of objects multiple times, you can create a copy of `REGISTRY_FILE` produced by the `LOAD` scenario and run `VERIFY` against the copy of the file.

Objects produced by HTTP scenario will be verified via gRPC endpoints.

Options:
  * `CLIENTS` - number of VUs for verifying objects (VU can handle both GRPC and S3 objects)
  * `TIME_LIMIT` - amount of time in seconds that is sufficient to verify all objects. If this time interval ends, then verification process will be interrupted and objects that have not been checked will stay in the `created` state.
  * `REGISTRY_FILE` - database file from which objects for verification should be read.
  * `SLEEP` - time interval (in seconds) between VU iterations.
  * `SELECTION_SIZE` - size of batch to select for deletion (default: 1000).
  * `DIAL_TIMEOUT` - timeout to connect to a node (in seconds).
  * `STREAM_TIMEOUT` - timeout for a single stream message for `PUT`/`GET` operations (in seconds).

## Verify preset 

Check what all preset objects is in cluster and can be got:
```
./scenarios/preset/check_objects_in_preset.py --endpoint az:8080 --preset_file ./scenarios/presets/grpc_1Mb_c1_o100.json 
```

Options: 
  * `--endpoint` - endpoint to get objects
  * `--preset_file` - path to preset file

Check what all objects in preset is compliance with container policy and get distribution of keys:
```
./scenarios/preset/check_policy_compliance.py --endpoints "az:8080,buky:8080,vedi:8080,glagoli:8080" --expected_copies 2 --preset_file "./scenarios/presets/grpc_10Mb_c100_o400.json"  
```

Options:
  * `--endpoints` - list of all live endpoints in cluster (comma separated)
  * `--preset_file` - path to preset file
  * `--expected_copies` - amount of expected copies for each object
  * `--max_workers` - amount of workers for check in parallel
  * `--print_failed` - print failed objects to console