Jina AI Cloud Hosting#
After building a Jina project, the next step is to deploy and host it on the cloud. Jina AI Cloud is Jina’s reliable, scalable and production-ready cloud-hosting solution that manages your project lifecycle without surprises or hidden development costs.
Tip
At present, Jina AI Cloud hosts all your Jina projects and offers computational/storage resources for free!
Basics#
Jina AI Cloud provides a CLI that you can use via jina cloud
from the terminal (or jcloud
or simply jc
for minimalists.)
Hint
You can also install just the JCloud CLI without installing the Jina package.
pip install jcloud
jc -h
If you installed the JCloud CLI individually, all of its commands fall under the jc
or jcloud
executable.
In case the command jc
is already occupied by another tool, use jcloud
instead. If your pip install doesn’t register bash commands for you, you can run python -m jcloud -h
.
For the rest of this section, we use jc
or jcloud
. But again they are interchangable with jina cloud
.
Deploy#
In Jina’s idiom, a project is a Flow, which represents an end-to-end task such as indexing, searching or recommending. In this document, we use “project” and “Flow” interchangeably.
Caution
Flows have a maximum lifetime after which they are automatically deleted.
A Flow can have two types of file structure: a single YAML file or a project folder.
Single YAML file#
A self-contained YAML file, consisting of all configuration at the Flow-level and Executor-level.
All Executors’
uses
must follow the formatjinaai+docker://<username>/MyExecutor
(from Executor Hub) to avoid any local file dependencies:
# flow.yml
jtype: Flow
executors:
- name: sentencizer
uses: jinaai+docker://jina-ai/Sentencizer
To deploy:
jc deploy flow.yml
Tip
We recommend testing locally before deployment:
jina flow --uses flow.yml
Project folder#
Tip
The best practice of creating a JCloud project is to use:
jc new
This ensures the correct project structure accepted by JCloud.
Just like a regular Python project, you can have sub-folders of Executor implementations and a flow.yml
on the top-level to connect all Executors together.
You can create an example local project using jc new hello
. The default structure looks like:
hello/
├── .env
├── executor1
│ ├── config.yml
│ ├── executor.py
│ └── requirements.txt
└── flow.yml
Where:
hello/
is your top-level project folder.executor1
directory has all Executor related code/configuration. You can read the best practices for file structures. Multiple Executor directories can be created.flow.yml
Your Flow YAML..env
All environment variables used during deployment.
To deploy:
jc deploy hello
The Flow is successfully deployed when you see:
You will get a Flow ID, say merry-magpie-82b9c0897f
. This ID is required to manage, view logs and remove the Flow.
As this Flow is deployed with the default gRPC gateway (feel free to change it to http
or websocket
), you can use jina.Client
to access it:
from jina import Client, Document
print(
Client(host='grpcs://merry-magpie-82b9c0897f.wolf.jina.ai').post(
on='/', inputs=Document(text='hello')
)
)
Get status#
To get the status of a Flow:
jc status merry-magpie-82b9c0897f
Monitoring#
Basic monitoring is provided to Flows deployed on Jina AI Cloud.
To access the Grafana-powered dashboard, first get the status of the Flow. The Grafana Dashboard
link is displayed at the bottom of the pane. Visit the URL to find basic metrics like ‘Number of Request Gateway Received’ and ‘Time elapsed between receiving a request and sending back the response’:
List Flows#
To list all of your “Serving” Flows:
jc list
You can also filter your Flows by passing a phase:
jc list --phase Deleted
Or see all Flows:
jc list --phase all
Remove Flows#
You can remove a single Flow, multiple Flows or even all Flows by passing different identifiers.
To remove a single Flow:
jc remove merry-magpie-82b9c0897f
To remove multiple Flows:
jc remove merry-magpie-82b9c0897f wondrous-kiwi-b02db6a066
To remove all Flows:
jc remove all
By default, removing multiple or all Flows is an interactive process where you must give confirmation before each Flow is deleted. To make it non-interactive, set the below environment variable before running the command:
export JCLOUD_NO_INTERACTIVE=1
Restrictions#
JCloud scales according to your needs. You can demand different resources (GPU/RAM/CPU/storage/instance-capacity) based on the needs of your Flows and Executors. If you have specific resource requirements, please contact us on Slack or raise a GitHub issue.
Restrictions
Deployments are only supported in the
us-east
region.Each Executor is allocated a maximum of 4GB RAM, 2 CPU cores & 10GB of block storage.
Three Flows can be deployed at a time, out of which one Flow can use a GPU.
A maximum of two GPUs are allocated per Flow.
Flows with Executors using GPU are removed after 12 hours, whereas other Flows are removed after 72 hours.