Hermann  Frami

Hermann Frami

1656636720

Serverless Framework: Deploy on Scaleway Functions

Serverless Framework: Deploy on Scaleway Functions

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.

Requirements

  • Install node.js
  • Install Serverless CLI (npm install serverless -g)

Let's work into ~/my-srvless-projects

# mkdir ~/my-srvless-projects
# cd ~/my-srvless-projects

Create a Project

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

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.

Configure your functions

Your functions are defined in the serverless.yml file created:

service: scaleway-python3
configValidationMode: off

useDotenv: true

provider:
  name: scaleway
  runtime: python310
  # Global Environment variables - used in every functions
  env:
    test: test
  # Storing credentials in this file is strongly not recommanded for security concerns, please refer to README.md about best practices
  scwToken: <scw-token>
  scwProject: <scw-project-id>
  # region in which the deployment will happen (default: fr-par)
  scwRegion: <scw-region>

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

Note: provider.name and 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 python3)

The different parameters are:

  • service: your namespace name
  • useDotenv: Load environment variables from .env files (default: false), read Security and secret management
  • configValidationMode: Configuration validation: 'error' (fatal error), 'warn' (logged to the output) or 'off' (default: warn)
  • 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
  • provider.secret: secret environment variables attached to your namespace are injected to all your namespace functions, see this example project
  • scwToken: Scaleway token you got in prerequisites
  • scwProject: Scaleway org id you got in prerequisites
  • scwRegion: Scaleway region in which the deployment will take place (default: fr-par)
  • 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 specific for the current function
    • secret (Optional): secret environment variables specific for the current function, see this example project
    • 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
    • timeout: is the maximum duration in seconds that the request will wait to be served before it times out (default: 300 seconds)
    • runtime: (Optional) runtime of the function, if you need to deploy multiple functions with different runtimes in your Serverless Project. If absent, provider.runtime will 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 CRONJobs). See events section below
    • custom_domains (Optional): List of custom domains, refer to Custom Domain Documentation

Security and secret management

You configuration file may contains sensitive data, your project ID and your Token must not be shared and must not be commited in VCS.

To keep your informations safe and be able to share or commit your serverles.yml file you should remove your credentials from the file. Then you can :

  • use global environment variables
  • use .env file and keep it secret

To use .env file you can modify your serverless.yml file as following :

# This will alow the plugin to read your .env file
useDotenv: true

provider:
  name: scaleway
  runtime: node16

  scwToken: ${env:SCW_SECRET_KEY}
  scwProject: ${env:SCW_DEFAULT_PROJECT_ID}
  scwRegion: ${env:SCW_REGION}

And then create a .env file next to your serverless.yml file, containing following values :

SCW_SECRET_KEY=XXX
SCW_DEFAULT_PROJECT_ID=XXX
SCW_REGION=fr-par

You can use this pattern to hide your secrets (for example a connexion string to a database or a S3 bucket).

Functions Handler

Based on the chosen runtime, the handler variable on function might vary.

Using ES Modules

Node has two module systems: CommonJS modules and ECMAScript (ES) modules. By default, Node treats your code files as CommonJS modules, however ES modules have also been available since the release of node16 runtime on Scaleway Serverless Functions. ES modules give you a more modern way to re-use your code.

According to the official documentation, to use ES modules you can specify the module type in package.json, as in the following example:

  ...
  "type": "module",
  ...

This then enables you to write your code for ES modules:

export {handle};

function handle (event, context, cb) {
    return {
        body: process.version,
        statusCode: 200,
    };
};

The use of ES modules is encouraged, since they are more efficient and make setup and debugging much easier.

Note that using "type": "module" or "type": "commonjs" in your package.json will enable/disable some features in Node runtime. For a comprehensive list of differences, please refer to the official documentation, the following is a summary only:

  • commonjs is used as default value
  • commonjs allows you to use require/module.exports (synchronous code loading, it basically copies all file contents)
  • module allows you to use import/export ES6 instructions (asynchronous loading, more optimized as it imports only the pieces of code you need)

Node

Path to your handler file (from serverless.yml), omit ./, ../, and add the exported function to use as a handler :

- src
  - handlers
    - firstHandler.js  => module.exports.myFirstHandler = ...
    - secondHandler.js => module.exports.mySecondHandler = ...
- serverless.yml

In serverless.yml:

provider:
  # ...
  runtime: node16
functions:
  first:
    handler: src/handlers/firstHandler.myFirstHandler
  second:
    handler: src/handlers/secondHandler.mySecondHandler

Python

Similar to node, path to handler file src/testing/handler.py:

- src
  - handlers
    - firstHandler.py  => def my_first_handler
    - secondHandler.py => def my_second_handler
- serverless.yml

In serverless.yml:

provider:
  # ...
  runtime: python310 # or python37, python38, python39
functions:
  first:
    handler: src/handlers/firstHandler.my_first_handler
  second:
    handler: src/handlers/secondHandler.my_second_handler

Golang

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

Your serverless.yml functions should look something like this:

provider:
  # ...
  runtime: go118
functions:
  main:
    handler: "."
  testing:
    handler: src/testing
  second:
    handler: src/second

Events

With 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:

  • schedule: Trigger your function based on CRON schedules
    • 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:

Custom domains

Custom domains allows users to use their own domains.

For domain configuration please Refer to Scaleway Documentation

Integration with serverless framework example :

functions:
  first:
    handler: handler.handle
    # Local environment variables - used only in given function
    env:
      local: local
    custom_domains:
      - func1.scaleway.com
      - func2.scaleway.com

Note As your domain must have a record to your function hostname, you should deploy your function once to read its hostname. Custom Domains configurations will be available after the first deploy.

Note: Serverless Framework will consider the configuration file as the source of truth.

If you create a domain with other tools (Scaleway's Console, CLI or API) you must refer created domain into your serverless configuration file. Otherwise it will be deleted as Serverless Framework will give the priority to its configuration.

Managing containers

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.

.
├── 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 serverless.yml.

You may use the container example to getting started.

Logs

The 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 --function:

serverless logs --function <function_or_container_name>

Info

serverless info command gives you informations your current deployement state in JSON format.

Documentation and useful Links

Contributing

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.

Author: Scaleway
Source Code: https://github.com/scaleway/serverless-scaleway-functions 
License: MIT license

#serverless #function #aws #lambda 

What is GEEK

Buddha Community

Serverless Framework: Deploy on Scaleway Functions
Hermann  Frami

Hermann Frami

1656636720

Serverless Framework: Deploy on Scaleway Functions

Serverless Framework: Deploy on Scaleway Functions

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.

Requirements

  • Install node.js
  • Install Serverless CLI (npm install serverless -g)

Let's work into ~/my-srvless-projects

# mkdir ~/my-srvless-projects
# cd ~/my-srvless-projects

Create a Project

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

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.

Configure your functions

Your functions are defined in the serverless.yml file created:

service: scaleway-python3
configValidationMode: off

useDotenv: true

provider:
  name: scaleway
  runtime: python310
  # Global Environment variables - used in every functions
  env:
    test: test
  # Storing credentials in this file is strongly not recommanded for security concerns, please refer to README.md about best practices
  scwToken: <scw-token>
  scwProject: <scw-project-id>
  # region in which the deployment will happen (default: fr-par)
  scwRegion: <scw-region>

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

Note: provider.name and 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 python3)

The different parameters are:

  • service: your namespace name
  • useDotenv: Load environment variables from .env files (default: false), read Security and secret management
  • configValidationMode: Configuration validation: 'error' (fatal error), 'warn' (logged to the output) or 'off' (default: warn)
  • 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
  • provider.secret: secret environment variables attached to your namespace are injected to all your namespace functions, see this example project
  • scwToken: Scaleway token you got in prerequisites
  • scwProject: Scaleway org id you got in prerequisites
  • scwRegion: Scaleway region in which the deployment will take place (default: fr-par)
  • 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 specific for the current function
    • secret (Optional): secret environment variables specific for the current function, see this example project
    • 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
    • timeout: is the maximum duration in seconds that the request will wait to be served before it times out (default: 300 seconds)
    • runtime: (Optional) runtime of the function, if you need to deploy multiple functions with different runtimes in your Serverless Project. If absent, provider.runtime will 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 CRONJobs). See events section below
    • custom_domains (Optional): List of custom domains, refer to Custom Domain Documentation

Security and secret management

You configuration file may contains sensitive data, your project ID and your Token must not be shared and must not be commited in VCS.

To keep your informations safe and be able to share or commit your serverles.yml file you should remove your credentials from the file. Then you can :

  • use global environment variables
  • use .env file and keep it secret

To use .env file you can modify your serverless.yml file as following :

# This will alow the plugin to read your .env file
useDotenv: true

provider:
  name: scaleway
  runtime: node16

  scwToken: ${env:SCW_SECRET_KEY}
  scwProject: ${env:SCW_DEFAULT_PROJECT_ID}
  scwRegion: ${env:SCW_REGION}

And then create a .env file next to your serverless.yml file, containing following values :

SCW_SECRET_KEY=XXX
SCW_DEFAULT_PROJECT_ID=XXX
SCW_REGION=fr-par

You can use this pattern to hide your secrets (for example a connexion string to a database or a S3 bucket).

Functions Handler

Based on the chosen runtime, the handler variable on function might vary.

Using ES Modules

Node has two module systems: CommonJS modules and ECMAScript (ES) modules. By default, Node treats your code files as CommonJS modules, however ES modules have also been available since the release of node16 runtime on Scaleway Serverless Functions. ES modules give you a more modern way to re-use your code.

According to the official documentation, to use ES modules you can specify the module type in package.json, as in the following example:

  ...
  "type": "module",
  ...

This then enables you to write your code for ES modules:

export {handle};

function handle (event, context, cb) {
    return {
        body: process.version,
        statusCode: 200,
    };
};

The use of ES modules is encouraged, since they are more efficient and make setup and debugging much easier.

Note that using "type": "module" or "type": "commonjs" in your package.json will enable/disable some features in Node runtime. For a comprehensive list of differences, please refer to the official documentation, the following is a summary only:

  • commonjs is used as default value
  • commonjs allows you to use require/module.exports (synchronous code loading, it basically copies all file contents)
  • module allows you to use import/export ES6 instructions (asynchronous loading, more optimized as it imports only the pieces of code you need)

Node

Path to your handler file (from serverless.yml), omit ./, ../, and add the exported function to use as a handler :

- src
  - handlers
    - firstHandler.js  => module.exports.myFirstHandler = ...
    - secondHandler.js => module.exports.mySecondHandler = ...
- serverless.yml

In serverless.yml:

provider:
  # ...
  runtime: node16
functions:
  first:
    handler: src/handlers/firstHandler.myFirstHandler
  second:
    handler: src/handlers/secondHandler.mySecondHandler

Python

Similar to node, path to handler file src/testing/handler.py:

- src
  - handlers
    - firstHandler.py  => def my_first_handler
    - secondHandler.py => def my_second_handler
- serverless.yml

In serverless.yml:

provider:
  # ...
  runtime: python310 # or python37, python38, python39
functions:
  first:
    handler: src/handlers/firstHandler.my_first_handler
  second:
    handler: src/handlers/secondHandler.my_second_handler

Golang

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

Your serverless.yml functions should look something like this:

provider:
  # ...
  runtime: go118
functions:
  main:
    handler: "."
  testing:
    handler: src/testing
  second:
    handler: src/second

Events

With 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:

  • schedule: Trigger your function based on CRON schedules
    • 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:

Custom domains

Custom domains allows users to use their own domains.

For domain configuration please Refer to Scaleway Documentation

Integration with serverless framework example :

functions:
  first:
    handler: handler.handle
    # Local environment variables - used only in given function
    env:
      local: local
    custom_domains:
      - func1.scaleway.com
      - func2.scaleway.com

Note As your domain must have a record to your function hostname, you should deploy your function once to read its hostname. Custom Domains configurations will be available after the first deploy.

Note: Serverless Framework will consider the configuration file as the source of truth.

If you create a domain with other tools (Scaleway's Console, CLI or API) you must refer created domain into your serverless configuration file. Otherwise it will be deleted as Serverless Framework will give the priority to its configuration.

Managing containers

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.

.
├── 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 serverless.yml.

You may use the container example to getting started.

Logs

The 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 --function:

serverless logs --function <function_or_container_name>

Info

serverless info command gives you informations your current deployement state in JSON format.

Documentation and useful Links

Contributing

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.

Author: Scaleway
Source Code: https://github.com/scaleway/serverless-scaleway-functions 
License: MIT license

#serverless #function #aws #lambda 

Noah  Rowe

Noah Rowe

1596645960

Cloud Function on GCP (Jakarta Region) & Serverless Framework

Hi everyone, I just heard from fellow Google Customer Engineer that Cloud Function now available in my region Jakarta! It is exciting news as now we can utilize the Cloud Function within the Region itself!

Cloud Functions Locations | Cloud Functions Documentation

Image for post

So with that kind of news, I am interested to actually test it out for a small experience of serverless in this new availability in the Jakarta region. (If you have any further or more elaborated experience please do share it with me!)

Now the idea is just to test the basic functionality of the Cloud Function to just do the most famous code ever (Hello World — who did not know this code?) and tested it with the HTTP trigger (the most basic one) and also tested the Serverless Framework to deploy the code.

Shall we test?

[One] let’s just try to create the function from the UI and go to Cloud Function — ensure that the API is already enabled — and create a new function.

Image for post

Sorry for the mistake caused by the dual monitor, I am kinda lazy to redo the capture. I created the function in Asia-southeast2 (Jakarta!) and allow unauthorized invocation.

Image for post

just use the default hello world function using the Node.js 12 and deploy

So after the deployment, we can test it through several ways which the easiest is through the UI

Image for post

Run!

These are the triggers that actually Cloud Function is able to use, so it is more than just meet the eyes. Well, I will keep the other for some future stories.

Image for post

For other kinds of test, we can use the gcloud cli call

gcloud functions call <function name> --region <region> --data {<any data>}

Image for post

It runs!

Or we can just use the plain old curl

curl -X POST "https://<region>-<project name>.cloudfunctions.net/<function name>" -H "Content-type:application/json" --data '{}'

#gcp #serverless #cloud-functions #serverless-framework #jakarta-region #function

Hermann  Frami

Hermann Frami

1655426640

Serverless Plugin for Microservice Code Management and Deployment

Serverless M

Serverless M (or Serverless Modular) is a plugin for the serverless framework. This plugins helps you in managing multiple serverless projects with a single serverless.yml file. This plugin gives you a super charged CLI options that you can use to create new features, build them in a single file and deploy them all in parallel

splash.gif

Currently this plugin is tested for the below stack only

  • AWS
  • NodeJS λ
  • Rest API (You can use other events as well)

Prerequisites

Make sure you have the serverless CLI installed

# Install serverless globally
$ npm install serverless -g

Getting Started

To start the serverless modular project locally you can either start with es5 or es6 templates or add it as a plugin

ES6 Template install

# Step 1. Download the template
$ sls create --template-url https://github.com/aa2kb/serverless-modular/tree/master/template/modular-es6 --path myModularService

# Step 2. Change directory
$ cd myModularService

# Step 3. Create a package.json file
$ npm init

# Step 3. Install dependencies
$ npm i serverless-modular serverless-webpack webpack --save-dev

ES5 Template install

# Step 1. Download the template
$ sls create --template-url https://github.com/aa2kb/serverless-modular/tree/master/template/modular-es5 --path myModularService

# Step 2. Change directory
$ cd myModularService

# Step 3. Create a package.json file
$ npm init

# Step 3. Install dependencies
$ npm i serverless-modular --save-dev

If you dont want to use the templates above you can just add in your existing project

Adding it as plugin

plugins:
  - serverless-modular

Now you are all done to start building your serverless modular functions

API Reference

The serverless CLI can be accessed by

# Serverless Modular CLI
$ serverless modular

# shorthand
$ sls m

Serverless Modular CLI is based on 4 main commands

  • sls m init
  • sls m feature
  • sls m function
  • sls m build
  • sls m deploy

init command

sls m init

The serverless init command helps in creating a basic .gitignore that is useful for serverless modular.

The basic .gitignore for serverless modular looks like this

#node_modules
node_modules

#sm main functions
sm.functions.yml

#serverless file generated by build
src/**/serverless.yml

#main serverless directories generated for sls deploy
.serverless

#feature serverless directories generated sls deploy
src/**/.serverless

#serverless logs file generated for main sls deploy
.sm.log

#serverless logs file generated for feature sls deploy
src/**/.sm.log

#Webpack config copied in each feature
src/**/webpack.config.js

feature command

The feature command helps in building new features for your project

options (feature Command)

This command comes with three options

--name: Specify the name you want for your feature

--remove: set value to true if you want to remove the feature

--basePath: Specify the basepath you want for your feature, this base path should be unique for all features. helps in running offline with offline plugin and for API Gateway

optionsshortcutrequiredvaluesdefault value
--name-nstringN/A
--remove-rtrue, falsefalse
--basePath-pstringsame as name

Examples (feature Command)

Creating a basic feature

# Creating a jedi feature
$ sls m feature -n jedi

Creating a feature with different base path

# A feature with different base path
$ sls m feature -n jedi -p tatooine

Deleting a feature

# Anakin is going to delete the jedi feature
$ sls m feature -n jedi -r true

function command

The function command helps in adding new function to a feature

options (function Command)

This command comes with four options

--name: Specify the name you want for your function

--feature: Specify the name of the existing feature

--path: Specify the path for HTTP endpoint helps in running offline with offline plugin and for API Gateway

--method: Specify the path for HTTP method helps in running offline with offline plugin and for API Gateway

optionsshortcutrequiredvaluesdefault value
--name-nstringN/A
--feature-fstringN/A
--path-pstringsame as name
--method-mstring'GET'

Examples (function Command)

Creating a basic function

# Creating a cloak function for jedi feature
$ sls m function -n cloak -f jedi

Creating a basic function with different path and method

# Creating a cloak function for jedi feature with custom path and HTTP method
$ sls m function -n cloak -f jedi -p powers -m POST

build command

The build command helps in building the project for local or global scope

options (build Command)

This command comes with four options

--scope: Specify the scope of the build, use this with "--feature" tag

--feature: Specify the name of the existing feature you want to build

optionsshortcutrequiredvaluesdefault value
--scope-sstringlocal
--feature-fstringN/A

Saving build Config in serverless.yml

You can also save config in serverless.yml file

custom:
  smConfig:
    build:
      scope: local

Examples (build Command)

all feature build (local scope)

# Building all local features
$ sls m build

Single feature build (local scope)

# Building a single feature
$ sls m build -f jedi -s local

All features build global scope

# Building all features with global scope
$ sls m build -s global

deploy command

The deploy command helps in deploying serverless projects to AWS (it uses sls deploy command)

options (deploy Command)

This command comes with four options

--sm-parallel: Specify if you want to deploy parallel (will only run in parallel when doing multiple deployments)

--sm-scope: Specify if you want to deploy local features or global

--sm-features: Specify the local features you want to deploy (comma separated if multiple)

optionsshortcutrequiredvaluesdefault value
--sm-paralleltrue, falsetrue
--sm-scopelocal, globallocal
--sm-featuresstringN/A
--sm-ignore-buildstringfalse

Saving deploy Config in serverless.yml

You can also save config in serverless.yml file

custom:
  smConfig:
    deploy:
      scope: local
      parallel: true
      ignoreBuild: true

Examples (deploy Command)

Deploy all features locally

# deploy all local features
$ sls m deploy

Deploy all features globally

# deploy all global features
$ sls m deploy --sm-scope global

Deploy single feature

# deploy all global features
$ sls m deploy --sm-features jedi

Deploy Multiple features

# deploy all global features
$ sls m deploy --sm-features jedi,sith,dark_side

Deploy Multiple features in sequence

# deploy all global features
$ sls m deploy  --sm-features jedi,sith,dark_side --sm-parallel false

Author: aa2kb
Source Code: https://github.com/aa2kb/serverless-modular 
License: MIT license

#serverless #aws #node #lambda 

Deploying Serverless Framework Applications with Altostra

Many of the dev teams we work with have an arsenal of existing projects built with the Serverless Framework. These projects are large and complex, so the developers prefer to use them as-is and migrate them later on.

Here at Altostra, our goal is to help developers and to make their work easier. So, we are happy to announce that Altostra now supports importing and deploying Serverless Framework projects!

Welcome home

Import your Serverless Framework projects into Altostra directly from you Git hosting service:

#serverless #infrastructure #deployment #cloud #serverless-framework

Christa  Stehr

Christa Stehr

1602681082

Overcoming Common Serverless Challenges with Mainframe CICS Programs

By this point most enterprises, including those running on legacy infrastructures, are familiar with the benefits of serverless computing:

  • Greater scalability
  • Faster development
  • More efficient deployment
  • Lower cost

The benefits of agility and cost reduction are especially relevant in the current macroeconomic environment when customer behavior is changing, end-user needs are difficult to predict, and development teams are under pressure to do more with less.

So serverless is a no-brainer, right?

Not exactly. Serverless might be relatively painless for a new generation of cloud-native software companies that grew up in a world of APIs and microservices, but it creates headaches for the many organizations that still rely heavily on legacy infrastructure.

In particular, enterprises running mainframe CICS programs are likely to encounter frustrating stumbling blocks on the path to launching Functions as a Service (FaaS). This population includes global enterprises that depend on CICS applications to effectively manage high-volume transactional processing requirements – particularly in the banking, financial services, and insurance industries.

These organizations stand to achieve time and cost savings through a modern approach to managing legacy infrastructure, as opposed to launching serverless applications on a brittle foundation. Here are three of the biggest obstacles they face and how to overcome them.

Challenge #1

Middleware that introduces complexity, technical debt, and latency. Many organizations looking to integrate CICS applications into a microservices or serverless architecture rely on middleware (e.g., an ESB or SOA) to access data from the underlying applications. This strategy introduces significant runtime performance challenges and creates what one bank’s chief architect referred to as a “lasagna architecture,” making DevOps impossible.

#serverless architecture #serverless functions #serverless benefits #mainframes #serverless api #serverless integration