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[GSK-1698] Remove legacy ML worker info and properties (#1390)
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* Remove TCP port exposing in ngrok

Format `cli_server.py` by git pre-commit

* Remove legacy worker related properties

* Cleanup legacy ML worker port description in doc

* Remove 40051 port in backend and ngrok configs

* Try to remove all legacy ML worker related info

* Clean up legacy port in legacy Docker compose file

---------

Co-authored-by: Andrey Avtomonov <andreybavt@gmail.com>
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@Inokinoki @andreybavt
Inokinoki and andreybavt authored Sep 15, 2023
1 parent 1f8fb76 commit dd16b80
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Showing 16 changed files with 24 additions and 120 deletions.
5 changes: 0 additions & 5 deletions backend/src/main/java/ai/giskard/config/ApplicationProperties.java
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Expand Up @@ -16,11 +16,6 @@
@Getter
@ConfigurationProperties(prefix = "giskard", ignoreUnknownFields = false)
public class ApplicationProperties {
private String mlWorkerHost;
private int mlWorkerPort;
private int externalMlWorkerEntrypointPort;
private String externalMlWorkerEntrypointHost;
private boolean externalMlWorkerEnabled;
private int apiTokenValidityInDays;
private int invitationTokenValidityInDays;
private int maxInboundMLWorkerMessageMB = 1024;
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2 changes: 0 additions & 2 deletions backend/src/main/java/ai/giskard/web/dto/config/AppConfigDTO.java
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Expand Up @@ -42,8 +42,6 @@ public static class AppInfoDTO {
private String buildCommitId;
private Instant buildCommitTime;
private GeneralSettings generalSettings;
private int externalMlWorkerEntrypointPort;
private String externalMlWorkerEntrypointHost;
private String hfSpaceId;
@JsonProperty(value = "isRunningOnHfSpaces")
private boolean isRunningOnHfSpaces;
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5 changes: 0 additions & 5 deletions backend/src/main/java/ai/giskard/web/dto/config/MLWorkerConnectionInfoDTO.java
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Expand Up @@ -8,11 +8,6 @@
@NoArgsConstructor
@AllArgsConstructor
public class MLWorkerConnectionInfoDTO {
private int externalMlWorkerEntrypointPort;
private String externalMlWorkerEntrypointHost;

private String encryptionKey;
private String keyId;
private String instanceId;
private String serverVersion;
private String user;
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4 changes: 0 additions & 4 deletions backend/src/main/java/ai/giskard/web/rest/controllers/SettingsController.java
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Expand Up @@ -96,8 +96,6 @@ public AppConfigDTO getApplicationSettings(@AuthenticationPrincipal final UserDe
.buildCommitTime(buildCommitTime)
.planCode(currentLicense.getPlanCode())
.planName(currentLicense.getPlanName())
.externalMlWorkerEntrypointPort(applicationProperties.getExternalMlWorkerEntrypointPort())
.externalMlWorkerEntrypointHost(applicationProperties.getExternalMlWorkerEntrypointHost())
.hfSpaceId(GeneralSettingsService.hfSpaceId)
.isRunningOnHfSpaces(GeneralSettingsService.isRunningInHFSpaces)
.roles(roles)
Expand All @@ -111,8 +109,6 @@ public MLWorkerConnectionInfoDTO getMLWorkerConnectionInfo() {
String currentUser = SecurityUtils.getCurrentAuthenticatedUserLogin();

return MLWorkerConnectionInfoDTO.builder()
.externalMlWorkerEntrypointHost(applicationProperties.getExternalMlWorkerEntrypointHost())
.externalMlWorkerEntrypointPort(applicationProperties.getExternalMlWorkerEntrypointPort())
.instanceId(settingsService.getSettings().getInstanceId())
.serverVersion(buildVersion)
.user(currentUser)
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4 changes: 0 additions & 4 deletions backend/src/main/resources/config/application.yml
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Expand Up @@ -162,10 +162,6 @@ info:
display-ribbon-on-profiles: 'dev'

giskard:
ml-worker-host: localhost
ml-worker-port: 50051
external-ml-worker-entrypoint-port: 40051
external-ml-worker-enabled: true
api-token-validity-in-days: 90
invitation-token-validity-in-days: 3
borderLineThreshold: 0.1
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2 changes: 0 additions & 2 deletions backend/src/test/resources/config/application.yml
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Expand Up @@ -80,8 +80,6 @@ server:
giskard:
api-token-validity-in-days: 90
invitation-token-validity-in-days: 3
ml-worker-host: localhost
ml-worker-port: 50051
home: ${user.home}/giskard-home
auth: true
email-from: giskard@localhost
2 changes: 0 additions & 2 deletions docker-compose.dev.yml
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Expand Up @@ -6,8 +6,6 @@ services:
- "5432:5432"

ml-worker:
ports:
- "50051:50051"

backend:
ports:
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4 changes: 0 additions & 4 deletions docker-compose.yml
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Expand Up @@ -34,8 +34,6 @@ services:
- db
env_file:
- .env
ports:
- "${GISKARD_EXTERNAL_ML_WORKER_PORT-40051}:40051"
environment:
- _JAVA_OPTIONS=-Xmx4048m -Xms512m
- SPRING_PROFILES_ACTIVE=prod
Expand All @@ -45,8 +43,6 @@ services:
- SPRING_DATASOURCE_PASSWORD=y1QYbF2BtFUC
- SPRING_DATASOURCE_URL=jdbc:postgresql://db:5432/app
- SPRING_LIQUIBASE_URL=jdbc:postgresql://db:5432/app
- GISKARD_ML_WORKER_HOST=${GISKARD_ML_WORKER_HOST-ml-worker}
- GISKARD_ML_WORKER_PORT=50051
- SPRING_MAIL_HOST
- SPRING_MAIL_PORT
- SPRING_MAIL_USERNAME
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2 changes: 0 additions & 2 deletions python-client/docs/cli/ngrok/index.rst
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Expand Up @@ -33,7 +33,5 @@ Now you can run :code:`giskard server expose --token <ngrok_API_key>` which shou

# To run your model with the Giskard Server, execute these three lines on Google Colab:

%env GSK_EXTERNAL_ML_WORKER_HOST=<host>
%env GSK_EXTERNAL_ML_WORKER_PORT=<port>
%env GSK_API_KEY=...
!giskard worker start -d -u <ngrok_external_server_link>
4 changes: 1 addition & 3 deletions python-client/docs/guides/installation_app/index.rst
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Expand Up @@ -62,7 +62,7 @@ You can either install and run the server **locally** or on an **external server

Installing Giskard in the cloud is preferable if you want to use the **collaborative** features of Giskard: collect feedback on your model from your team, share your Quality Assurance results, save and provide all your custom tests to your team, etc.

Since Giskard uses 2 TCP ports: ``19000`` and ``40051``, **make sure that these two ports are open** on the cloud instances where Giskard is installed. For step-by-step installation steps in the cloud, please go to the `AWS <install_aws/index/index.md>`_, `GCP <install_gcp/index.md>`_, and `Azure <install_azure/index.md>`_ installation pages.
Since Giskard uses a TCP ports: ``19000``, **make sure that the port is open** on the cloud instances where Giskard is installed. For step-by-step installation steps in the cloud, please go to the `AWS <install_aws/index/index.md>`_, `GCP <install_gcp/index.md>`_, and `Azure <install_azure/index.md>`_ installation pages.

.. toctree::
:maxdepth: 1
Expand Down Expand Up @@ -123,8 +123,6 @@ Giskard executes your model using an worker that runs directly the model in your

.. code-block:: sh
%env GSK_EXTERNAL_ML_WORKER_HOST=4.tcp.ngrok.io
%env GSK_EXTERNAL_ML_WORKER_PORT=10853
%env GSK_API_KEY=YOUR_API_KEY
!giskard worker start -d -k YOUR_TOKEN -u https://e840-93-23-184-184.ngrok-free.app
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2 changes: 1 addition & 1 deletion python-client/docs/guides/installation_app/install_aws/index.md
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Expand Up @@ -10,7 +10,7 @@
* **Application and OS image**: Select the default Ubuntu server 22.04 LTS 64-bit (x86)
* **Instance type**: We recommend you to choose at least a `t2.large` instance type (2vCPU, 8GB memory)
* **Key pair**: Choose your usual key pair. If you don't have one, go to the [Amazon document](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/create-key-pairs.html) to create the right one
* **Network settings**: You need to **open the ports `19000` and `40051` (TCP connection)** to access the Giskard frontend (port `19000`) and upload your model (port `40051`). To do so, click on `Edit` and add the following security groups:
* **Network settings**: You need to **open the port `19000` to access the Giskard frontend and upload your model. To do so, click on `Edit` and add the following security groups:

![](<../../../assets/image_(1)_(1)_(2).png>)

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4 changes: 1 addition & 3 deletions python-client/docs/guides/installation_app/install_gcp/index.md
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Expand Up @@ -10,11 +10,10 @@ Installing Giskard in GCP enables you to inspect & test models that you created
2. Choose `Allow full access to all Cloud APIs`
3. In the firewall section, allow **HTTP** and **HTTPS** traffic
3. Connect to your VM in SSH by opening a browser window
4. Create a firewall rule to open ports `19000` and `40051` port of the Giskard instance. Here is the command line that you can execute in the terminal opened by your SSH connection:
4. Create a firewall rule to open the `19000` port of the Giskard instance. Here is the command line that you can execute in the terminal opened by your SSH connection:

```bash
gcloud compute firewall-rules create giskard-main --allow tcp:19000
gcloud compute firewall-rules create giskard-worker --allow tcp:40051
```

:::{warning}
Expand All @@ -32,7 +31,6 @@ Creating the firewall rules can also be done **through UI** in the `VPC Network`
* In `source IPv4 ranges,` select `0.0.0.0/0`
* In `Protocols and ports`, select `Specified protocols and ports`
* Then select `TCP`, and type `19000`
* `Repeat the same steps to open port 40051`
:::

### 2. Install Giskard in the GCP VM
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82 changes: 18 additions & 64 deletions python-client/giskard/commands/cli_server.py
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Expand Up @@ -3,7 +3,6 @@
import time
from pathlib import Path
from typing import Optional
from urllib.parse import urlparse

import click
import docker
Expand Down Expand Up @@ -41,9 +40,7 @@ def create_docker_client() -> DockerClient:
exit(1)


@click.group(
"server", help="Giskard UI management", context_settings={"show_default": True}
)
@click.group("server", help="Giskard UI management", context_settings={"show_default": True})
def server() -> None:
"""
Giskard UI management
Expand Down Expand Up @@ -88,9 +85,7 @@ def get_container(version=None, quit_if_not_exists=True) -> Optional[Container]:
return create_docker_client().containers.get(name)
except NotFound:
if quit_if_not_exists:
logger.error(
f"Container {name} could not be found. Run `giskard server start` to create the container"
)
logger.error(f"Container {name} could not be found. Run `giskard server start` to create the container")
raise click.Abort()
else:
return None
Expand Down Expand Up @@ -128,7 +123,6 @@ def _start(attached=False, version=None):

settings = _get_settings() or {}
port = settings.get("port", 19000)
ml_worker_port = settings.get("ml_worker_port", 40051)

version = get_version(version)

Expand All @@ -143,17 +137,15 @@ def _start(attached=False, version=None):
get_image_name(version),
detach=not attached,
name=get_container_name(version),
ports={7860: port, 40051: ml_worker_port},
ports={7860: port},
volumes={home_volume.name: {"bind": "/home/giskard/datadir", "mode": "rw"}},
)
container.start()

up = _wait_backend_ready(port)

if up:
logger.info(
f"Giskard Server {version} started. You can access it at http://localhost:{port}"
)
logger.info(f"Giskard Server {version} started. You can access it at http://localhost:{port}")
else:
logger.warning(
"Giskard backend takes unusually long time to start, "
Expand Down Expand Up @@ -190,17 +182,13 @@ def _fetch_latest_tag() -> str:
"""
Returns: the latest tag from the Docker Hub API. Format: vX.Y.Z
"""
response = requests.get(
"https://hub.docker.com/v2/namespaces/giskardai/repositories/giskard/tags?page_size=10"
)
response = requests.get("https://hub.docker.com/v2/namespaces/giskardai/repositories/giskard/tags?page_size=10")
response.raise_for_status()
json_response = response.json()
latest_tag = "latest"
latest = next(i for i in json_response["results"] if i["name"] == latest_tag)
latest_version_image = next(
i
for i in json_response["results"]
if ((i["name"] != latest_tag) and (i["digest"] == latest["digest"]))
i for i in json_response["results"] if ((i["name"] != latest_tag) and (i["digest"] == latest["digest"]))
)

tag = latest_version_image["name"]
Expand Down Expand Up @@ -236,9 +224,7 @@ def _expose(token):
container = get_container()
if container:
if container.status != "running":
print(
"Error: Giskard server is not running. Please start it using `giskard server start`"
)
print("Error: Giskard server is not running. Please start it using `giskard server start`")
raise click.Abort()
else:
raise click.Abort()
Expand All @@ -249,29 +235,17 @@ def _expose(token):
if token:
ngrok.set_auth_token(token)

http_tunnel = ngrok.connect(
19000, "http", pyngrok_config=None if token else PyngrokConfig(region="us")
)
tcp_tunnel = ngrok.connect(
40051, "tcp", pyngrok_config=None if token else PyngrokConfig(region="eu")
)

# Only split the last ':' in case the URL contains a port
tcp_addr = urlparse(tcp_tunnel.public_url)
http_tunnel = ngrok.connect(19000, "http", pyngrok_config=None if token else PyngrokConfig(region="us"))

print("Giskard Server is now exposed to the internet.")
print(
"You can now upload objects to the Giskard Server using the following client: \n"
)
print("You can now upload objects to the Giskard Server using the following client: \n")

print(
f"""token=...
client = giskard.GiskardClient(\"{http_tunnel.public_url}\", token)
# To run your model with the Giskard Server, execute these three lines on Google Colab:
%env GSK_EXTERNAL_ML_WORKER_HOST={tcp_addr.hostname}
%env GSK_EXTERNAL_ML_WORKER_PORT={tcp_addr.port}
%env GSK_API_KEY=...
!giskard worker start -d -u {http_tunnel.public_url}"""
)
Expand All @@ -294,9 +268,7 @@ def _expose(token):
default=False,
help="Starts the server and attaches to it, displaying logs in console.",
)
@click.option(
"--version", "version", required=False, help="Version of Giskard server to start"
)
@click.option("--version", "version", required=False, help="Version of Giskard server to start")
@common_options
def start(attached, version):
"""\b
Expand Down Expand Up @@ -373,12 +345,8 @@ def restart(service, hard):
logger.info(f"Container {container.name} restarted")
else:
if service:
logger.info(
f"Restarting service {service} in {container.name} container"
)
command = (
f"supervisorctl -c /opt/giskard/supervisord.conf restart {service}"
)
logger.info(f"Restarting service {service} in {container.name} container")
command = f"supervisorctl -c /opt/giskard/supervisord.conf restart {service}"
else:
logger.info(f"Restarting all services in {container.name} container")
command = "supervisorctl -c /opt/giskard/supervisord.conf restart all"
Expand Down Expand Up @@ -455,15 +423,11 @@ def diagnose(local_dir):
analytics.track("giskard-server:diagnose")
out_dir = Path(local_dir)
assert out_dir.is_dir(), "'output' should be an existing directory"
bits, _ = get_container().get_archive(
"/home/giskard/datadir/run", encode_stream=True
)
bits, _ = get_container().get_archive("/home/giskard/datadir/run", encode_stream=True)
from datetime import datetime

now = datetime.now().strftime("%Y%m%d_%H%M%S_%f")
out_file = (
out_dir / f"giskard-diagnose-{get_version().replace('.', '_')}-{now}.tar.gz"
)
out_file = out_dir / f"giskard-diagnose-{get_version().replace('.', '_')}-{now}.tar.gz"
with open(out_file, "wb") as f:
for chunk in bits:
f.write(chunk)
Expand Down Expand Up @@ -514,9 +478,7 @@ def status():
analytics.track("giskard-server:status")
app_settings = _get_settings()
if not app_settings:
logger.info(
"Giskard Server is not installed. Install using `giskard server start`"
)
logger.info("Giskard Server is not installed. Install using `giskard server start`")
return
else:
version = app_settings["version"]
Expand All @@ -532,21 +494,13 @@ def status():
if container:
if container.status == "running":
logger.info(f"Container {container.name} status:")
print(
get_container()
.exec_run("supervisorctl -c /opt/giskard/supervisord.conf")
.output.decode()
)
print(get_container().exec_run("supervisorctl -c /opt/giskard/supervisord.conf").output.decode())
else:
logger.info(
f"Container {container.name} isn't running ({container.status})"
)
logger.info(f"Container {container.name} isn't running ({container.status})")


@server.command("clean")
@click.option(
"--data", "delete_data", is_flag=True, help="Delete user data (giskard-home volume)"
)
@click.option("--data", "delete_data", is_flag=True, help="Delete user data (giskard-home volume)")
@common_options
def clean(delete_data):
"""\b
Expand Down
3 changes: 0 additions & 3 deletions python-client/giskard/settings.py
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Expand Up @@ -18,13 +18,10 @@ def expand_env_var(env_var: Optional[str]) -> Optional[str]:

class Settings(BaseSettings):
home: str = "~/giskard-home"
port: int = 50051
ws_port: int = 9000
ws_path: str = "/ml-worker"
host: str = "localhost"
max_workers: int = 10
max_send_message_length_mb: int = 1024
max_receive_message_length_mb: int = 1024
loglevel = "INFO"
cache_dir: str = "cache"
disable_analytics = False
Expand Down
14 changes: 2 additions & 12 deletions python-client/tests/utils.py
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Expand Up @@ -63,12 +63,7 @@ def __enter__(self):
self.mocked_requests.register_uri(
requests_mock.GET,
self.ml_worker_connect_url_pattern,
json={
"externalMlWorkerEntrypointPort": 40051,
"externalMlWorkerEntrypointHost": None,
"encryptionKey": "7J2oBM4si/GciQScXjjs6w==",
"keyId": "fh1sjr7h",
},
json={},
)

url = "http://giskard-host:12345"
Expand All @@ -95,12 +90,7 @@ def verify_model_upload(my_model, my_data):
m.register_uri(
requests_mock.GET,
ml_worker_connect_url_pattern,
json={
"externalMlWorkerEntrypointPort": 40051,
"externalMlWorkerEntrypointHost": None,
"encryptionKey": "7J2oBM4si/GciQScXjjs6w==",
"keyId": "fh1sjr7h",
},
json={},
)

url = "http://giskard-host:12345"
Expand Down
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