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The Scaleway functions plugin for Serverless Framework allows users to deploy their functions and containers to Scaleway Functions with a simple serverless deploy.
Serverless Framework handles everything from creating namespaces to function/code deployment by calling APIs endpoint under the hood.
npm install serverless -g)
Let’s work into ~/my-srvless-projects
# mkdir ~/my-srvless-projects # cd ~/my-srvless-projects
The easiest way to create a project is to use one of our templates. The list of templates is here)
Let’s use python3
serverless create --template-url https://github.com/scaleway/serverless-scaleway-functions/tree/master/examples/python3 --path myService
Important: template-path MUST be absolute
Once it’s done, we can install mandatory node packages used by serverless
cd mypython3functions npm i
Note: these packages are only used by serverless, they are not shipped with your functions.
Your functions are defined in the
serverless.yml file created:
service: scaleway-python3 configValidationMode: off provider: name: scaleway runtime: python3 # Global Environment variables - used in every functions env: test: test scwToken: <scw-token> scwProject: <scw-project-id> plugins: - serverless-scaleway-functions package: patterns: - '!node_modules/**' - '!.gitignore' - '!.git/**' functions: first: handler: handler.py # Local environment variables - used only in given function env: local: local
plugins MUST NOT be changed, they enable us to use the scaleway provider
This file contains the configuration of one namespace containing one or more functions (in this example, only one) of the same runtime (here
The different parameters are:
service: your namespace name
provider.runtime: the runtime of your functions (check the supported runtimes above)
provider.env: environment variables attached to your namespace are injected to all your namespace functions
scwToken: Scaleway token you got in prerequisites
scwProject: Scaleway org id you got in prerequisites
package.patterns: usually, you don’t need to configure it. Enable to include/exclude directories to/from the deployment
functions: Configure of your fonctions. It’s a yml dictionary, with the key being the function name
handler(Required): file or function which will be executed. See the next section for runtime specific handlers
env(Optional): environment variables specifics for the current function
minScale(Optional): how many function instances we keep running (default: 0)
maxScale(Optional): maximum number of instances this function can scale to (default: 20)
memoryLimit: ram allocated to the function instances. See the introduction for the list of supported values
runtime: (Optional) runtime of the function, if you need to deploy multiple functions with different runtimes in your Serverless Project. If absent,
provider.runtimewill be used to deploy the function, see this example project.
events(Optional): List of events to trigger your functions (e.g, trigger a function based on a schedule with
Based on the chosen runtime, the
handler variable on function might vary.
Path to your handler file (from serverless.yml), omit
../, and add the exported function to use as a handler:
# ls - src - handlers - firstHandler.js => module.exports.myFirstHandler = ... - secondHandler.js => module.exports.mySecondHandler = ... - serverless.yml
provider: # ... runtime: node8 # or node10 or node14 functions: first: handler: src/handlers/firstHandler.myFirstHandler second: handler: src/handlers/secondHandler.mySecondHandler
node, path to handler file
- src - handlers - firstHandler.py => def my_first_handler - secondHandler.py => def my_second_handler - serverless.yml
provider: # ... runtime: python3 # or python for python 2.7 functions: first: handler: src/handlers/firstHandler.my_first_handler second: handler: src/handlers/secondHandler.my_second_handler
Path to your handler’s package, for example if I have the following structure:
- src - testing - handler.go -> package main in src/testing subdirectory - second - handler.go -> package main in src/second subdirectory - serverless.yml - handler.go -> package main at the root of project
functions should look something like this:
provider: # ... runtime: golang functions: main: handler: "." testing: handler: src/testing second: handler: src/second
events, you may link your functions with specific triggers, which might include
CRON Schedule (Time based),
MQTT Queues (Publish on a topic will trigger the function),
S3 Object update (Upload an object will trigger the function).
Note that we do not include HTTP triggers in our event types, as a HTTP endpoint is created for every function. Triggers are just a new way to trigger your Function, but you will always be able to execute your code via HTTP.
Here is a list of supported triggers on Scaleway Serverless, and the configuration parameters required to deploy them:
rate: CRON Schedule (UNIX Format) on which your function will be executed
input: key-value mapping to define arguments that will be passed into your function’s event object during execution.
To link a Trigger to your function, you may define a key
events in your function:
functions: handler: myHandler.handle events: # "events" is a list of triggers, the first key being the type of trigger. - schedule: # CRON Job Schedule (UNIX Format) rate: '1 * * * *' # Input variable are passed in your function's event during execution input: key: value key2: value2
You may link Events to your Containers too (See section
Managing containers below for more informations on how to deploy containers):
custom: containers: mycontainer: directory: my-directory # Events key events: - schedule: rate: '1 * * * *' input: key: value key2: value2
You may refer to the follow examples:
Requirements: You need to have Docker installed to be able to build and push your image to your Scaleway registry.
You must define your containers inside the
custom.containers field in your serverless.yml manifest. Each container must specify the relative path of its application directory (containing the Dockerfile, and all files related to the application to deploy):
custom: containers: mycontainer: directory: my-container-directory # port: 8080 # Environment only available in this container env: MY_VARIABLE: "my-value"
Here is an example of the files you should have, the
directory containing your Dockerfile and scripts is
. ├── my-container-directory │ ├── Dockerfile │ ├── requirements.txt │ ├── server.py │ └── (...) ├── node_modules │ ├── serverless-scaleway-functions │ └── (...) ├── package-lock.json ├── package.json └── serverless.yml
Scaleway’s platform will automatically inject a PORT environment variable on which your server should be listening for incoming traffic. By default, this PORT is 8080. You may change the
port in your
You may use the container example to getting started.
serverless logs command lets you watch the logs of a specific function or container.
Pass the function or container name you want to fetch the logs for with
serverless logs --function <function_or_container_name>
MUSTuse this library if you plan to develop with Golang).
This plugin is mainly developed and maintained by
Scaleway Serverless Team but you are free to open issues or discuss with us on our Community Slack Channels #serverless-containers and #serverless-functions.
This project is MIT licensed.