xk6-frostfs/scenarios/run_scenarios.md

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How to execute scenarios

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.

./scenarios/preset/preset_grpc.py --size 1024 --containers 1 --out grpc.json --endpoint node4.intra:8080 --preload_obj 500

2. Execute scenario with options:

$ ./k6 run -e PROFILE=50:60 -e WRITE_OBJ_SIZE=8192 -e CLIENTS=400 -e GRPC_ENDPOINTS=node1.data:8080,node4.data:8080 -e PREGEN_JSON=./grpc.json scenarios/grpc.js

Options:

• PROFILE - format write:duration
  • write - percent of VUs performing write operations (the rest will be read VUs)
  • duration - time in sec
• CLIENTS - number of VUs for all operations
• WRITE_OBJ_SIZE - object size in kb for write(PUT) operations
• PREGEN_JSON - path to json file with pre-generated containers and objects
• REGISTRY - if set to "enabled", all produced objects will be stored in database for subsequent verification.

S3

1. Create s3 credentials:

$ neofs-s3-authmate issue-secret --wallet wallet.json --peer node1.intra: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"

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.

./scenarios/preset/preset_s3.py --size 1024 --buckets 1 --out s3.json --endpoint node4.intra:8084 --preload_obj 500

3. Execute scenario with options:

$ ./k6 run -e PROFILE=50:60 -e WRITE_OBJ_SIZE=8192 -e CLIENTS=400 -e S3_ENDPOINTS=node1.data:8084,node4.data:8084 -e PREGEN_JSON=s3.json scenarios/s3.js

Options are identical to gRPC scenario, plus:

• OBJ_NAME - if specified, this name will be used for all write operations instead of random generation.

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 and/or S3 scenario with option REGISTRY=enabled.

To verify stored objects execute scenario with options:

./k6 run -e CLIENTS=200 -e TIME_LIMIT=120 -e GRPC_ENDPOINTS=node1.data:8080,node2.data:8080 -e S3_ENDPOINTS=node1.data:8084,node2.data:8084 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 (return code will be 108).

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.