Hermann  Frami

Hermann Frami

1654345320

Serverless Fast Deploy Plugin: Lightening Fast Serverless Deployments

Serverless Fast Deploy Plugin  

Fast Serverless deployments for large packages

Requirements:

  • Serverless v1.12.x or higher.
  • AWS provider

How it works

I found that while working with Python libraries such Numpy and Pandas, my deploys became very slow and expensive (I work off a mobile data plan) due to the increased package size. This plugin deploys a specialized Lambda always you to only deploy the files that are most likely to change. It does this by merging the incoming files with the latest existing package on S3. So now when I deploy a change, I am sending a few KB across the wire each time, not 50 MB.

Caveats

A note about merging the update package with the base package

y first attempt was to just use the latest existing deployment package on S3, unpack that and create a new package with the update files. This was a bit "slow", so now I create a base package which is the full previous deployment package without the files described by the custom.fastDeploy.include property. This means that I can simply append the new files, resulting in an even faster deploy. The unfortunately side effect being that if you change the custom.fastDeploy.include property, you need to do a full deployment before doing your next FastDeploy.

The creation of the base deployment package also means that the first FastDeploy will be slightly slower than subsequent deployments.

Custom deployment bucket

At the moment this plugin bypasses all of the standard deployment lifecycle stages, so I am not yet able to get hold of the auto generated deployment bucket. As such this plugin only works if you have created a custom deployment bucket and configured it via the provider.deploymentBucket property.

IAM Role

The FastDeploy Lambda requires the following permissions on the deployment bucket. Either this can be added to the services default role, or you can create a new role and configure it via the custom.fastDeploy.role property.

Updates to CloudFormation configuration requires a full deployment

Much like Serverless's function deployment feature, any updates to the CloudFormation stack requires a full deployment.

- Effect: Allow
  Action:
    - s3:GetObject
    - s3:PutObject
  Resource: arn:aws:s3:::aronim-serverless/*
- Effect: Allow
  Action:
    - s3:ListBucket
  Resource: arn:aws:s3:::aronim-serverless     

Setup

Install via npm in the root of your Serverless service:

npm install serverless-plugin-fastdeploy --save-dev
  • Add the plugin to the plugins array in your Serverless serverless.yml:
plugins:
  - serverless-plugin-fastdeploy

Run

sls fastdeploy

Configuration

The custom.fastDeploy.include property describes which files to include in the update package, and exclude from the base package. This can be an array if you are just working in single module project, or an object if you are working with a multi-module project.

Available custom properties:


custom:
  fastDeploy:
    memorySize: 512    # Optional. Default: 512MB
    timeout: 30        # Optional. Default: 30sec
    include:           # Required. No Default
      - src/*.js       # Example
    role:              # Optional. Uses service default role if one is provided
      - FastDeployRole # Example
service: ServerlessFastDeployExample

plugins:
  - serverless-plugin-fastdeploy

provider:
  ...
  role: DefaultRole
  deploymentBucket: aronim-serverless

custom:
  fastDeploy:
    include:
      - package_one/**
      - package_two/**

######      
# OR #      
###### 
 
custom:
  fastDeploy:
    include:
      ".": service_one/**
      "../../modules/module-two": module_two/**     

resources:
  Resources:
    DefaultRole:
      Type: AWS::IAM::Role
      Properties:
        Path: /
        RoleName: ${self:service}-${self:provider.stage}
        AssumeRolePolicyDocument:
          Version: "2012-10-17"
          Statement:
            - Effect: Allow
              Principal:
                Service:
                  - lambda.amazonaws.com
              Action: sts:AssumeRole
        Policies:
          - PolicyName: ${self:service}-${self:provider.stage}
            PolicyDocument:
              Version: "2012-10-17"
              Statement:
                - Effect: Allow
                  Action:
                    - logs:CreateLogGroup
                    - logs:CreateLogStream
                    - logs:PutLogEvents
                  Resource: arn:aws:logs:${self:provider.region}:*:log-group:/aws/lambda/*:*:*
                - Effect: Allow
                  Action:
                    - s3:GetObject
                    - s3:PutObject
                  Resource: arn:aws:s3:::aronim-serverless/*
                - Effect: Allow
                  Action:
                    - s3:ListBucket
                  Resource: arn:aws:s3:::aronim-serverless     

Cost

Since we are deploying an additional Lambda, there are some neglible cost implications. The default memory allocated to the FastDeploy Lambda is 512MB, but this can be increased or decreased using the custom.fastDeploy.memory property.

Acknowledgements

A big thank you to FidelLimited, I blatently plagiarized their WarmUp plugin for the basis of the FastDeploy Lambda :-) As they say "Mimicry is the highest form of flattery".

Contribute

Help us making this plugin better and future proof.

  • Clone the code
  • Install the dependencies with npm install
  • Create a feature branch git checkout -b new_feature
  • Lint with standard npm run lint

Author: Aronim
Source Code: https://github.com/aronim/serverless-plugin-fastdeploy 
License: MIT license

#serverless #plugin #deployment 

What is GEEK

Buddha Community

Serverless Fast Deploy Plugin: Lightening Fast Serverless Deployments
Hermann  Frami

Hermann Frami

1654345320

Serverless Fast Deploy Plugin: Lightening Fast Serverless Deployments

Serverless Fast Deploy Plugin  

Fast Serverless deployments for large packages

Requirements:

  • Serverless v1.12.x or higher.
  • AWS provider

How it works

I found that while working with Python libraries such Numpy and Pandas, my deploys became very slow and expensive (I work off a mobile data plan) due to the increased package size. This plugin deploys a specialized Lambda always you to only deploy the files that are most likely to change. It does this by merging the incoming files with the latest existing package on S3. So now when I deploy a change, I am sending a few KB across the wire each time, not 50 MB.

Caveats

A note about merging the update package with the base package

y first attempt was to just use the latest existing deployment package on S3, unpack that and create a new package with the update files. This was a bit "slow", so now I create a base package which is the full previous deployment package without the files described by the custom.fastDeploy.include property. This means that I can simply append the new files, resulting in an even faster deploy. The unfortunately side effect being that if you change the custom.fastDeploy.include property, you need to do a full deployment before doing your next FastDeploy.

The creation of the base deployment package also means that the first FastDeploy will be slightly slower than subsequent deployments.

Custom deployment bucket

At the moment this plugin bypasses all of the standard deployment lifecycle stages, so I am not yet able to get hold of the auto generated deployment bucket. As such this plugin only works if you have created a custom deployment bucket and configured it via the provider.deploymentBucket property.

IAM Role

The FastDeploy Lambda requires the following permissions on the deployment bucket. Either this can be added to the services default role, or you can create a new role and configure it via the custom.fastDeploy.role property.

Updates to CloudFormation configuration requires a full deployment

Much like Serverless's function deployment feature, any updates to the CloudFormation stack requires a full deployment.

- Effect: Allow
  Action:
    - s3:GetObject
    - s3:PutObject
  Resource: arn:aws:s3:::aronim-serverless/*
- Effect: Allow
  Action:
    - s3:ListBucket
  Resource: arn:aws:s3:::aronim-serverless     

Setup

Install via npm in the root of your Serverless service:

npm install serverless-plugin-fastdeploy --save-dev
  • Add the plugin to the plugins array in your Serverless serverless.yml:
plugins:
  - serverless-plugin-fastdeploy

Run

sls fastdeploy

Configuration

The custom.fastDeploy.include property describes which files to include in the update package, and exclude from the base package. This can be an array if you are just working in single module project, or an object if you are working with a multi-module project.

Available custom properties:


custom:
  fastDeploy:
    memorySize: 512    # Optional. Default: 512MB
    timeout: 30        # Optional. Default: 30sec
    include:           # Required. No Default
      - src/*.js       # Example
    role:              # Optional. Uses service default role if one is provided
      - FastDeployRole # Example
service: ServerlessFastDeployExample

plugins:
  - serverless-plugin-fastdeploy

provider:
  ...
  role: DefaultRole
  deploymentBucket: aronim-serverless

custom:
  fastDeploy:
    include:
      - package_one/**
      - package_two/**

######      
# OR #      
###### 
 
custom:
  fastDeploy:
    include:
      ".": service_one/**
      "../../modules/module-two": module_two/**     

resources:
  Resources:
    DefaultRole:
      Type: AWS::IAM::Role
      Properties:
        Path: /
        RoleName: ${self:service}-${self:provider.stage}
        AssumeRolePolicyDocument:
          Version: "2012-10-17"
          Statement:
            - Effect: Allow
              Principal:
                Service:
                  - lambda.amazonaws.com
              Action: sts:AssumeRole
        Policies:
          - PolicyName: ${self:service}-${self:provider.stage}
            PolicyDocument:
              Version: "2012-10-17"
              Statement:
                - Effect: Allow
                  Action:
                    - logs:CreateLogGroup
                    - logs:CreateLogStream
                    - logs:PutLogEvents
                  Resource: arn:aws:logs:${self:provider.region}:*:log-group:/aws/lambda/*:*:*
                - Effect: Allow
                  Action:
                    - s3:GetObject
                    - s3:PutObject
                  Resource: arn:aws:s3:::aronim-serverless/*
                - Effect: Allow
                  Action:
                    - s3:ListBucket
                  Resource: arn:aws:s3:::aronim-serverless     

Cost

Since we are deploying an additional Lambda, there are some neglible cost implications. The default memory allocated to the FastDeploy Lambda is 512MB, but this can be increased or decreased using the custom.fastDeploy.memory property.

Acknowledgements

A big thank you to FidelLimited, I blatently plagiarized their WarmUp plugin for the basis of the FastDeploy Lambda :-) As they say "Mimicry is the highest form of flattery".

Contribute

Help us making this plugin better and future proof.

  • Clone the code
  • Install the dependencies with npm install
  • Create a feature branch git checkout -b new_feature
  • Lint with standard npm run lint

Author: Aronim
Source Code: https://github.com/aronim/serverless-plugin-fastdeploy 
License: MIT license

#serverless #plugin #deployment 

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 

Hermann  Frami

Hermann Frami

1656577200

Serverless S3 Deploy

serverless-s3-deploy

Plugin for serverless to deploy files to a variety of S3 Buckets

Note: This project is currently not maintained.

Installation

 npm install --save-dev serverless-s3-deploy

Usage

Add to your serverless.yml:

  plugins:
    - serverless-s3-deploy

  custom:
    assets:
      targets:
       - bucket: my-bucket
         files:
          - source: ../assets/
            globs: '**/*.css'
          - source: ../app/
            globs:
              - '**/*.js'
              - '**/*.map'
       - bucket: my-other-bucket
         empty: true
         prefix: subdir
         files:
          - source: ../email-templates/
            globs: '**/*.html'

You can specify any number of targets that you want. Each target has a bucket and a prefix.

bucket is either the name of your S3 bucket or a reference to a CloudFormation resources created in the same serverless configuration file. See below for additional details.

You can specify source relative to the current directory.

Each source has its own list of globs, which can be either a single glob, or a list of globs.

Setting empty to true will delete all files inside the bucket before uploading the new content to S3 bucket. The prefix value is respected and files outside will not be deleted.

Now you can upload all of these assets to your bucket by running:

$ sls s3deploy

If you have defined multiple buckets, you can limit your deployment to a single bucket with the --bucket option:

$ sls s3deploy --bucket my-bucket

ACL

You can optionally specificy an ACL for the files uploaded on a per target basis:

  custom:
    assets:
      targets:
        - bucket: my-bucket
          acl: private
          files:

The default value is private. Options are defined here.

Content Type

The appropriate Content Type for each file will attempt to be determined using mime-types. If one can't be determined, a default fallback of 'application/octet-stream' will be used.

You can override this fallback per-source by setting defaultContentType.

  custom:
    assets:
      targets:
        - bucket: my-bucket
          files:
            - source: html/
              defaultContentType: text/html
              ...

Other Headers

Additional headers can be included per target by providing a headers object.

See http://docs.aws.amazon.com/AmazonS3/latest/API/RESTObjectPUT.html for more details.

  custom:
    assets:
      targets:
        - bucket: my-bucket
          files:
            - source: html/
              headers:
                CacheControl: max-age=31104000 # 1 year

Resolving References

A common use case is to create the S3 buckets in the resources section of your serverless configuration and then reference it in your S3 plugin settings:

  custom:
    assets:
      targets:
        - bucket:
            Ref: MyBucket
          files:
            - source: html/

  resources:
    # AWS CloudFormation Template
    Resources:
      MyBucket:
        Type: AWS::S3::Bucket
        Properties:
          AccessControl: PublicRead
          WebsiteConfiguration:
            IndexDocument: index.html
            ErrorDocument: index.html

You can disable the resolving with the following flag:

  custom:
    assets:
      resolveReferences: false

Auto-deploy

If you want s3deploy to run automatically after a deploy, set the auto flag:

  custom:
    assets:
      auto: true

IAM Configuration

You're going to need an IAM policy that supports this deployment. This might be a good starting point:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::${bucket}"
            ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "s3:PutObject",
                "s3:PutObjectAcl",
                "s3:GetObject",
                "s3:DeleteObject"
            ],
            "Resource": [
                "arn:aws:s3:::${bucket}/*"
            ]
        }
    ]
}

Upload concurrency

If you want to tweak the upload concurrency, change uploadConcurrency config:

config:
  assets:
    # defaults to 3
    uploadConcurrency: 1

Verbosity

Verbosity cloud be enabled using either of these methods:

Configuration:

  custom:
    assets:
      verbose: true

Cli:

  sls s3deploy -v

Author: Funkybob
Source Code: https://github.com/funkybob/serverless-s3-deploy 
License: MIT license

#serverless #deploy #s3 #plugin 

Hermann  Frami

Hermann Frami

1653578100

Serverless Plugin Datadog

Datadog recommends the Serverless Framework Plugin for developers using the Serverless Framework to deploy their serverless applications. The plugin automatically enables instrumentation for applications to collect metrics, traces, and logs by:

  • Installing the Datadog Lambda library to your Lambda functions as a Lambda layer.
  • Installing the Datadog Lambda Extension to your Lambda functions as a Lambda layer (addExtension) or subscribing the Datadog Forwarder to your Lambda functions' log groups (forwarderArn).
  • Making the required configuration changes, such as adding environment variables or additional tracing layers, to your Lambda functions.

Getting started

To quickly get started, follow the installation instructions for Python, Node.js, Ruby, Java, Go, or .NET and view your function's enhanced metrics, traces, and logs in Datadog.

After installation is complete, configure the advanced options to suit your monitoring needs.

Upgrade

Each version of the plugin is published with a specific set of versions of the Datadog Lambda layers. To pick up new features and bug fixes provided by the latest versions of Datadog Lambda layers, upgrade the serverless framework plugin. Test the new version before applying it on your production applications.

Configuration parameters

To further configure your plugin, use the following custom parameters in your serverless.yml:

ParameterDescription
siteSet which Datadog site to send data to, such as datadoghq.com (default), datadoghq.eu, us3.datadoghq.com, us5.datadoghq.com, or ddog-gov.com. This parameter is required when collecting telemtry using the Datadog Lambda Extension.
apiKey[Datadog API key][7]. This parameter is required when collecting telemetry using the Datadog Lambda Extension. Alternatively, you can also set the DATADOG_API_KEY environment variable in your deployment environment.
appKeyDatadog app key. Only needed when the monitors field is defined. Alternatively, you can also set the DATADOG_APP_KEY environment variable in your deployment environment.
apiKeySecretArnAn alternative to using the apiKey field. The ARN of the secret that is storing the Datadog API key in AWS Secrets Manager. Remember to add the secretsmanager:GetSecretValue permission to the Lambda execution role.
apiKMSKeyAn alternative to using the apiKey field. Datadog API key encrypted using KMS. Remember to add the kms:Decrypt permission to the Lambda execution role.
envWhen set along with addExtension, a DD_ENV environment variable is added to all Lambda functions with the provided value. Otherwise, an env tag is added to all Lambda functions with the provided value. Defaults to the stage value of the serverless deployment.
serviceWhen set along with addExtension, a DD_SERVICE environment variable is added to all Lambda functions with the provided value. Otherwise, a service tag is added to all Lambda functions with the provided value. Defaults to the service value of the serverless project.
versionWhen set along with addExtension, a DD_VERSION environment variable is added to all Lambda functions with the provided value. When set along with forwarderArn, a version tag is added to all Lambda functions with the provided value.
tagsA comma separated list of key:value pairs as a single string. When set along with extensionLayerVersion, a DD_TAGS environment variable is added to all Lambda functions with the provided value. When set along with forwarderArn, the plugin parses the string and sets each key:value pair as a tag on all Lambda functions.
enableXrayTracingSet true to enable X-Ray tracing on the Lambda functions and API Gateway integrations. Defaults to false.
enableDDTracingEnable Datadog tracing on the Lambda function. Defaults to true.
enableDDLogsEnable Datadog log collection using the Lambda Extension. Defaults to true. Note: This setting has no effect on logs sent by the Datadog Forwarder.
monitorsWhen defined, the Datadog plugin configures monitors for the deployed function. Requires setting DATADOG_API_KEY and DATADOG_APP_KEY in your environment. To learn how to define monitors, see To Enable and Configure a Recommended Serverless Monitor.
captureLambdaPayload[Captures incoming and outgoing AWS Lambda payloads][17] in the Datadog APM spans for Lambda invocations. Defaults to false.
enableSourceCodeIntegrationEnable [Datadog source code integration][18] for the function. Defaults to true.
subscribeToApiGatewayLogsEnable automatic subscription of the Datadog Forwarder to API Gateway log groups. Requires setting forwarderArn. Defaults to true.
subscribeToHttpApiLogsEnable automatic subscription of the Datadog Forwarder to HTTP API log groups. Requires setting forwarderArn. Defaults to true.
subscribeToWebsocketLogsEnable automatic subscription of the Datadog Forwarder to WebSocket log groups. Requires setting forwarderArn. Defaults to true.
forwarderArnThe ARN of the Datadog Forwarder to be subscribed to the Lambda or API Gateway log groups.
addLayersWhether to install the Datadog Lambda library as a layer. Defaults to true. Set to false when you plan to package the Datadog Lambda library to your function's deployment package on your own so that you can install a specific version of the Datadog Lambda library ([Python][8] or [Node.js][9]).
addExtensionWhether to install the Datadog Lambda Extension as a layer. Defaults to true. When enabled, it's required to set the apiKey and site.
excludeWhen set, this plugin ignores all specified functions. Use this parameter if you have any functions that should not include Datadog functionality. Defaults to [].
enabledWhen set to false, the Datadog plugin stays inactive. Defaults to true. You can control this option using an environment variable. For example, use enabled: ${strToBool(${env:DD_PLUGIN_ENABLED, true})} to activate/deactivate the plugin during deployment. Alternatively, you can also use the value passed in through --stage to control this option—see example.
customHandlerWhen set, the specified handler is set as the handler for all the functions.
failOnErrorWhen set, this plugin throws an error if any custom Datadog monitors fail to create or update. This occurs after deploy, but will cause the result of serverless deploy to return a nonzero exit code (to fail user CI). Defaults to false.
integrationTestingSet true when running integration tests. This bypasses the validation of the Forwarder ARN and the addition of Datadog Monitor output links. Defaults to false.
logLevelThe log level, set to DEBUG for extended logging.

To use any of these parameters, add a custom > datadog section to your serverless.yml similar to this example:

custom:
  datadog:
    apiKeySecretArn: "{Datadog_API_Key_Secret_ARN}"
    enableXrayTracing: false
    enableDDTracing: true
    enableDDLogs: true
    subscribeToAccessLogs: true
    forwarderArn: arn:aws:lambda:us-east-1:000000000000:function:datadog-forwarder
    exclude:
      - dd-excluded-function

Webpack

If you are using a bundler, such as webpack, see Serverless Tracing and Webpack.

TypeScript

You may encounter the error of missing type definitions. To resolve the error, add datadog-lambda-js and dd-trace to the devDependencies list of your project's package.json.

If you are using serverless-typescript, make sure that serverless-datadog is above the serverless-typescript entry in your serverless.yml. The plugin will automatically detect .ts files.

plugins:
  - serverless-plugin-datadog
  - serverless-typescript

Disable Plugin for Particular Environment

If you'd like to turn off the plugin based on the environment (passed via --stage), you can use something similar to the example below.

provider:
  stage: ${self:opt.stage, 'dev'}

custom:
  staged: ${self:custom.stageVars.${self:provider.stage}, {}}

  stageVars:
    dev:
      dd_enabled: false

  datadog:
    enabled: ${self:custom.staged.dd_enabled, true}

Serverless Monitors

There are seven recommended monitors with default values pre-configured.

MonitorMetricsThresholdServerless Monitor ID
High Error Rateaws.lambda.errors/aws.lambda.invocations>= 10%high_error_rate
Timeoutaws.lambda.duration.max/aws.lambda.timeout>= 1timeout
Out of Memoryaws.lambda.enhanced.out_of_memory> 0out_of_memory
High Iterator Ageaws.lambda.iterator_age.maximum>= 24 hrshigh_iterator_age
High Cold Start Rateaws.lambda.enhanced.invocations(cold_start:true)/
aws.lambda.enhanced.invocations
>= 20%high_cold_start_rate
High Throttlesaws.lambda.throttles/aws.lambda.invocations>= 20%high_throttles
Increased Costaws.lambda.enhanced.estimated_cost↑20%increased_cost

To Enable and Configure a Recommended Serverless Monitor

To create a recommended monitor, you must use its respective serverless monitor ID. Note that you must also set the DATADOG_API_KEY and DATADOG_APP_KEY in your environment.

If you’d like to further configure the parameters for a recommended monitor, you can directly define the parameter values below the serverless monitor ID. Parameters not specified under a recommended monitor will use the default recommended value. The query parameter for recommended monitors cannot be directly modified and will default to using the query valued as defined above; however, you may change the threshold value in query by re-defining it within the options parameter. To delete a monitor, remove the monitor from the serverless.yml template. For further documentation on how to define monitor parameters, see the Datadog Monitors API.

Monitor creation occurs after the function is deployed. In the event that a monitor is unsuccessfully created, the function will still be successfully deployed.

To create a recommended monitor with the default values

Define the appropriate serverless monitor ID without specifying any parameter values

custom:
  datadog:
    addLayers: true
    monitors:
      - high_error_rate:

To configure a recommended monitor

custom:
  datadog:
    addLayers: true
    monitors:
      - high_error_rate:
          name: "High Error Rate with Modified Warning Threshold"
          message: "More than 10% of the function’s invocations were errors in the selected time range. Notify @data.dog@datadoghq.com @slack-serverless-monitors"
          tags: ["modified_error_rate", "serverless", "error_rate"]
          require_full_window: true
          priority: 2
          options:
            include_tags: true
            notify_audit: true
            thresholds:
              ok: 0.025
              warning: 0.05

To delete a monitor

Removing the serverless monitor ID and its parameters will delete the monitor.

To Enable and Configure a Custom Monitor

To define a custom monitor, you must define a unique serverless monitor ID string in addition to passing in the API key and Application key, DATADOG_API_KEY and DATADOG_APP_KEY, in your environment. The query parameter is required but every other parameter is optional. Define a unique serverless monitor ID string and specify the necessary parameters below. For further documentation on monitor parameters, see the Datadog Monitors API.

custom:
  datadog:
    addLayers: true
    monitors:
      - custom_monitor_id:
          name: "Custom Monitor"
          query: "max(next_1w):forecast(avg:system.load.1{*}, 'linear', 1, interval='60m', history='1w', model='default') >= 3"
          message: "Custom message for custom monitor. Notify @data.dog@datadoghq.com @slack-serverless-monitors"
          tags: ["custom_monitor", "serverless"]
          priority: 3
          options:
            enable_logs_sample: true
            require_full_window: true
            include_tags: false
            notify_audit: true
            notify_no_data: false
            thresholds:
              ok: 1
              warning: 2

Breaking Changes

v5.0.0

  • When used in conjunction with the Datadog Extension, this plugin sets service and env tags through environment variables instead of Lambda resource tags.
  • The enableTags parameter was replaced by the new service, env parameters.

v4.0.0

  • The Datadog Lambda Extension is now the default mechanism for transmitting telemetry to Datadog.

Opening Issues

If you encounter a bug with this package, let us know by filing an issue! Before opening a new issue, please search the existing issues to avoid duplicates.

When opening an issue, include your Serverless Framework version, Python/Node.js version, and stack trace if available. Also, please include the steps to reproduce when appropriate.

You can also open an issue for a feature request.

Contributing

If you find an issue with this package and have a fix, open a pull request following the procedures.

Community

For product feedback and questions, join the #serverless channel in the Datadog community on Slack.

Author: DataDog
Source Code: https://github.com/DataDog/serverless-plugin-datadog 
License: View license

#serverless #datadog #plugin 

How To Customize WordPress Plugins? (4 Easy Ways To Do)

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WordPress needs no introduction. It has been in the world for quite a long time. And up till now, it has given a tough fight to leading web development technology. The main reason behind its remarkable success is, it is highly customizable and also SEO-friendly. Other benefits include open-source technology, security, user-friendliness, and the thousands of free plugins it offers.

Talking of WordPress plugins, are a piece of software that enables you to add more features to the website. They are easy to integrate into your website and don’t hamper the performance of the site. WordPress, as a leading technology, has to offer many out-of-the-box plugins.

However, not always the WordPress would be able to meet your all needs. Hence you have to customize the WordPress plugin to provide you the functionality you wished. WordPress Plugins are easy to install and customize. You don’t have to build the solution from scratch and that’s one of the reasons why small and medium-sized businesses love it. It doesn’t need a hefty investment or the hiring of an in-house development team. You can use the core functionality of the plugin and expand it as your like.

In this blog, we would be talking in-depth about plugins and how to customize WordPress plugins to improve the functionality of your web applications.

What Is The Working Of The WordPress Plugins?

Developing your own plugin requires you to have some knowledge of the way they work. It ensures the better functioning of the customized plugins and avoids any mistakes that can hamper the experience on your site.

1. Hooks

Plugins operate primarily using hooks. As a hook attaches you to something, the same way a feature or functionality is hooked to your website. The piece of code interacts with the other components present on the website. There are two types of hooks: a. Action and b. Filter.

A. Action

If you want something to happen at a particular time, you need to use a WordPress “action” hook. With actions, you can add, change and improve the functionality of your plugin. It allows you to attach a new action that can be triggered by your users on the website.

There are several predefined actions available on WordPress, custom WordPress plugin development also allows you to develop your own action. This way you can make your plugin function as your want. It also allows you to set values for which the hook function. The add_ action function will then connect that function to a specific action.

B. Filters

They are the type of hooks that are accepted to a single variable or a series of variables. It sends them back after they have modified it. It allows you to change the content displayed to the user.

You can add the filter on your website with the apply_filter function, then you can define the filter under the function. To add a filter hook on the website, you have to add the $tag (the filter name) and $value (the filtered value or variable), this allows the hook to work. Also, you can add extra function values under $var.

Once you have made your filter, you can execute it with the add_filter function. This will activate your filter and would work when a specific function is triggered. You can also manipulate the variable and return it.

2. Shortcodes

Shortcodes are a good way to create and display the custom functionality of your website to visitors. They are client-side bits of code. They can be placed in the posts and pages like in the menu and widgets, etc.

There are many plugins that use shortcodes. By creating your very own shortcode, you too can customize the WordPress plugin. You can create your own shortcode with the add_shortcode function. The name of the shortcode that you use would be the first variable and the second variable would be the output of it when it is triggered. The output can be – attributes, content, and name.

3. Widgets

Other than the hooks and shortcodes, you can use the widgets to add functionality to the site. WordPress Widgets are a good way to create a widget by extending the WP_Widget class. They render a user-friendly experience, as they have an object-oriented design approach and the functions and values are stored in a single entity.

How To Customize WordPress Plugins?

There are various methods to customize the WordPress plugins. Depending on your need, and the degree of customization you wish to make in the plugin, choose the right option for you. Also, don’t forget to keep in mind that it requires a little bit of technical knowledge too. So find an expert WordPress plugin development company in case you lack the knowledge to do it by yourself.

1. Hire A Plugin Developer3
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One of the best ways to customize a WordPress plugin is by hiring a plugin developer. There are many plugin developers listed in the WordPress directory. You can contact them and collaborate with world-class WordPress developers. It is quite easy to find a WordPress plugin developer.

Since it is not much work and doesn’t pay well or for the long term a lot of developers would be unwilling to collaborate but, you will eventually find people.

2. Creating A Supporting Plugin

If you are looking for added functionality in an already existing plugin go for this option. It is a cheap way to meet your needs and creating a supporting plugin takes very little time as it has very limited needs. Furthermore, you can extend a plugin to a current feature set without altering its base code.

However, to do so, you have to hire a WordPress developer as it also requires some technical knowledge.

3. Use Custom Hooks

Use the WordPress hooks to integrate some other feature into an existing plugin. You can add an action or a filter as per your need and improve the functionality of the website.

If the plugin you want to customize has the hook, you don’t have to do much to customize it. You can write your own plugin that works with these hooks. This way you don’t have to build a WordPress plugin right from scratch. If the hook is not present in the plugin code, you can contact a WordPress developer or write the code yourself. It may take some time, but it works.

Once the hook is added, you just have to manually patch each one upon the release of the new plugin update.

4. Override Callbacks

The last way to customize WordPress plugins is by override callbacks. You can alter the core functionality of the WordPress plugin with this method. You can completely change the way it functions with your website. It is a way to completely transform the plugin. By adding your own custom callbacks, you can create the exact functionality you desire.

We suggest you go for a web developer proficient in WordPress as this requires a good amount of technical knowledge and the working of a plugin.

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#customize wordpress plugins #how to customize plugins in wordpress #how to customize wordpress plugins #how to edit plugins in wordpress #how to edit wordpress plugins #wordpress plugin customization