1648787768
Docker is a product that allows developers to create containers, which are self-contained areas on their computer for running applications. They can be used for databases, which is great if you can't install it normally (e.g. you use a Mac).
This video shows you how to set up a PostgreSQL database on Docker. It uses an existing PostgreSQL image on the Docker Hub website. You can use many different versions of PostgreSQL, not just the latest version.
You'll learn how to download and install Docker, find the right PostgreSQL image, download the image, run it, and connect to it in the DBeaver IDE. You can use any other IDE that works with PostgreSQL if you prefer.
Timestamps:
00:00 In this video
00:05 High-level steps
00:29 Download Docker
01:23 Run Docker
02:07 Create Docker Hub account
02:41 Search for PostgreSQL image on Docker Hub
03:15 Understand the docker run command
04:29 Adjust docker run command
05:19 Open Terminal and login to Docker
06:12 Download image using Docker Run
06:52 Check status using docker ps
07:19 Connect using DBeaver
07:47 Enter connection details
08:43 Run simple query
09:05 Docker Stop command
The connection details for this image mentioned in the video are below.
Host: localhost
Port: 5432
Username: postgres
Password: whatever you specify in the "docker run" command (default is mysecretpassword)
Subscribe: https://www.youtube.com/c/DatabaseStar/featured
1651383480
This serverless plugin is a wrapper for amplify-appsync-simulator made for testing AppSync APIs built with serverless-appsync-plugin.
Install
npm install serverless-appsync-simulator
# or
yarn add serverless-appsync-simulator
Usage
This plugin relies on your serverless yml file and on the serverless-offline
plugin.
plugins:
- serverless-dynamodb-local # only if you need dynamodb resolvers and you don't have an external dynamodb
- serverless-appsync-simulator
- serverless-offline
Note: Order is important serverless-appsync-simulator
must go before serverless-offline
To start the simulator, run the following command:
sls offline start
You should see in the logs something like:
...
Serverless: AppSync endpoint: http://localhost:20002/graphql
Serverless: GraphiQl: http://localhost:20002
...
Configuration
Put options under custom.appsync-simulator
in your serverless.yml
file
| option | default | description | | ------------------------ | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | apiKey | 0123456789
| When using API_KEY
as authentication type, the key to authenticate to the endpoint. | | port | 20002 | AppSync operations port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20002, 20012, 20022, etc.) | | wsPort | 20003 | AppSync subscriptions port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20003, 20013, 20023, etc.) | | location | . (base directory) | Location of the lambda functions handlers. | | refMap | {} | A mapping of resource resolutions for the Ref
function | | getAttMap | {} | A mapping of resource resolutions for the GetAtt
function | | importValueMap | {} | A mapping of resource resolutions for the ImportValue
function | | functions | {} | A mapping of external functions for providing invoke url for external fucntions | | dynamoDb.endpoint | http://localhost:8000 | Dynamodb endpoint. Specify it if you're not using serverless-dynamodb-local. Otherwise, port is taken from dynamodb-local conf | | dynamoDb.region | localhost | Dynamodb region. Specify it if you're connecting to a remote Dynamodb intance. | | dynamoDb.accessKeyId | DEFAULT_ACCESS_KEY | AWS Access Key ID to access DynamoDB | | dynamoDb.secretAccessKey | DEFAULT_SECRET | AWS Secret Key to access DynamoDB | | dynamoDb.sessionToken | DEFAULT_ACCESS_TOKEEN | AWS Session Token to access DynamoDB, only if you have temporary security credentials configured on AWS | | dynamoDb.* | | You can add every configuration accepted by DynamoDB SDK | | rds.dbName | | Name of the database | | rds.dbHost | | Database host | | rds.dbDialect | | Database dialect. Possible values (mysql | postgres) | | rds.dbUsername | | Database username | | rds.dbPassword | | Database password | | rds.dbPort | | Database port | | watch | - *.graphql
- *.vtl | Array of glob patterns to watch for hot-reloading. |
Example:
custom:
appsync-simulator:
location: '.webpack/service' # use webpack build directory
dynamoDb:
endpoint: 'http://my-custom-dynamo:8000'
Hot-reloading
By default, the simulator will hot-relad when changes to *.graphql
or *.vtl
files are detected. Changes to *.yml
files are not supported (yet? - this is a Serverless Framework limitation). You will need to restart the simulator each time you change yml files.
Hot-reloading relies on watchman. Make sure it is installed on your system.
You can change the files being watched with the watch
option, which is then passed to watchman as the match expression.
e.g.
custom:
appsync-simulator:
watch:
- ["match", "handlers/**/*.vtl", "wholename"] # => array is interpreted as the literal match expression
- "*.graphql" # => string like this is equivalent to `["match", "*.graphql"]`
Or you can opt-out by leaving an empty array or set the option to false
Note: Functions should not require hot-reloading, unless you are using a transpiler or a bundler (such as webpack, babel or typescript), un which case you should delegate hot-reloading to that instead.
Resource CloudFormation functions resolution
This plugin supports some resources resolution from the Ref
, Fn::GetAtt
and Fn::ImportValue
functions in your yaml file. It also supports some other Cfn functions such as Fn::Join
, Fb::Sub
, etc.
Note: Under the hood, this features relies on the cfn-resolver-lib package. For more info on supported cfn functions, refer to the documentation
You can reference resources in your functions' environment variables (that will be accessible from your lambda functions) or datasource definitions. The plugin will automatically resolve them for you.
provider:
environment:
BUCKET_NAME:
Ref: MyBucket # resolves to `my-bucket-name`
resources:
Resources:
MyDbTable:
Type: AWS::DynamoDB::Table
Properties:
TableName: myTable
...
MyBucket:
Type: AWS::S3::Bucket
Properties:
BucketName: my-bucket-name
...
# in your appsync config
dataSources:
- type: AMAZON_DYNAMODB
name: dynamosource
config:
tableName:
Ref: MyDbTable # resolves to `myTable`
Sometimes, some references cannot be resolved, as they come from an Output from Cloudformation; or you might want to use mocked values in your local environment.
In those cases, you can define (or override) those values using the refMap
, getAttMap
and importValueMap
options.
refMap
takes a mapping of resource name to value pairsgetAttMap
takes a mapping of resource name to attribute/values pairsimportValueMap
takes a mapping of import name to values pairsExample:
custom:
appsync-simulator:
refMap:
# Override `MyDbTable` resolution from the previous example.
MyDbTable: 'mock-myTable'
getAttMap:
# define ElasticSearchInstance DomainName
ElasticSearchInstance:
DomainEndpoint: 'localhost:9200'
importValueMap:
other-service-api-url: 'https://other.api.url.com/graphql'
# in your appsync config
dataSources:
- type: AMAZON_ELASTICSEARCH
name: elasticsource
config:
# endpoint resolves as 'http://localhost:9200'
endpoint:
Fn::Join:
- ''
- - https://
- Fn::GetAtt:
- ElasticSearchInstance
- DomainEndpoint
In some special cases you will need to use key-value mock nottation. Good example can be case when you need to include serverless stage value (${self:provider.stage}
) in the import name.
This notation can be used with all mocks - refMap
, getAttMap
and importValueMap
provider:
environment:
FINISH_ACTIVITY_FUNCTION_ARN:
Fn::ImportValue: other-service-api-${self:provider.stage}-url
custom:
serverless-appsync-simulator:
importValueMap:
- key: other-service-api-${self:provider.stage}-url
value: 'https://other.api.url.com/graphql'
This plugin only tries to resolve the following parts of the yml tree:
provider.environment
functions[*].environment
custom.appSync
If you have the need of resolving others, feel free to open an issue and explain your use case.
For now, the supported resources to be automatically resovled by Ref:
are:
Feel free to open a PR or an issue to extend them as well.
External functions
When a function is not defined withing the current serverless file you can still call it by providing an invoke url which should point to a REST method. Make sure you specify "get" or "post" for the method. Default is "get", but you probably want "post".
custom:
appsync-simulator:
functions:
addUser:
url: http://localhost:3016/2015-03-31/functions/addUser/invocations
method: post
addPost:
url: https://jsonplaceholder.typicode.com/posts
method: post
Supported Resolver types
This plugin supports resolvers implemented by amplify-appsync-simulator
, as well as custom resolvers.
From Aws Amplify:
Implemented by this plugin
#set( $cols = [] )
#set( $vals = [] )
#foreach( $entry in $ctx.args.input.keySet() )
#set( $regex = "([a-z])([A-Z]+)")
#set( $replacement = "$1_$2")
#set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
#set( $discard = $cols.add("$toSnake") )
#if( $util.isBoolean($ctx.args.input[$entry]) )
#if( $ctx.args.input[$entry] )
#set( $discard = $vals.add("1") )
#else
#set( $discard = $vals.add("0") )
#end
#else
#set( $discard = $vals.add("'$ctx.args.input[$entry]'") )
#end
#end
#set( $valStr = $vals.toString().replace("[","(").replace("]",")") )
#set( $colStr = $cols.toString().replace("[","(").replace("]",")") )
#if ( $valStr.substring(0, 1) != '(' )
#set( $valStr = "($valStr)" )
#end
#if ( $colStr.substring(0, 1) != '(' )
#set( $colStr = "($colStr)" )
#end
{
"version": "2018-05-29",
"statements": ["INSERT INTO <name-of-table> $colStr VALUES $valStr", "SELECT * FROM <name-of-table> ORDER BY id DESC LIMIT 1"]
}
#set( $update = "" )
#set( $equals = "=" )
#foreach( $entry in $ctx.args.input.keySet() )
#set( $cur = $ctx.args.input[$entry] )
#set( $regex = "([a-z])([A-Z]+)")
#set( $replacement = "$1_$2")
#set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
#if( $util.isBoolean($cur) )
#if( $cur )
#set ( $cur = "1" )
#else
#set ( $cur = "0" )
#end
#end
#if ( $util.isNullOrEmpty($update) )
#set($update = "$toSnake$equals'$cur'" )
#else
#set($update = "$update,$toSnake$equals'$cur'" )
#end
#end
{
"version": "2018-05-29",
"statements": ["UPDATE <name-of-table> SET $update WHERE id=$ctx.args.input.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.input.id"]
}
{
"version": "2018-05-29",
"statements": ["UPDATE <name-of-table> set deleted_at=NOW() WHERE id=$ctx.args.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.id"]
}
#set ( $index = -1)
#set ( $result = $util.parseJson($ctx.result) )
#set ( $meta = $result.sqlStatementResults[1].columnMetadata)
#foreach ($column in $meta)
#set ($index = $index + 1)
#if ( $column["typeName"] == "timestamptz" )
#set ($time = $result["sqlStatementResults"][1]["records"][0][$index]["stringValue"] )
#set ( $nowEpochMillis = $util.time.parseFormattedToEpochMilliSeconds("$time.substring(0,19)+0000", "yyyy-MM-dd HH:mm:ssZ") )
#set ( $isoDateTime = $util.time.epochMilliSecondsToISO8601($nowEpochMillis) )
$util.qr( $result["sqlStatementResults"][1]["records"][0][$index].put("stringValue", "$isoDateTime") )
#end
#end
#set ( $res = $util.parseJson($util.rds.toJsonString($util.toJson($result)))[1][0] )
#set ( $response = {} )
#foreach($mapKey in $res.keySet())
#set ( $s = $mapKey.split("_") )
#set ( $camelCase="" )
#set ( $isFirst=true )
#foreach($entry in $s)
#if ( $isFirst )
#set ( $first = $entry.substring(0,1) )
#else
#set ( $first = $entry.substring(0,1).toUpperCase() )
#end
#set ( $isFirst=false )
#set ( $stringLength = $entry.length() )
#set ( $remaining = $entry.substring(1, $stringLength) )
#set ( $camelCase = "$camelCase$first$remaining" )
#end
$util.qr( $response.put("$camelCase", $res[$mapKey]) )
#end
$utils.toJson($response)
Variable map support is limited and does not differentiate numbers and strings data types, please inject them directly if needed.
Will be escaped properly: null
, true
, and false
values.
{
"version": "2018-05-29",
"statements": [
"UPDATE <name-of-table> set deleted_at=NOW() WHERE id=:ID",
"SELECT * FROM <name-of-table> WHERE id=:ID and unix_timestamp > $ctx.args.newerThan"
],
variableMap: {
":ID": $ctx.args.id,
## ":TIMESTAMP": $ctx.args.newerThan -- This will be handled as a string!!!
}
}
Requires
Author: Serverless-appsync
Source Code: https://github.com/serverless-appsync/serverless-appsync-simulator
License: MIT License
1599914520
Hello, in this post I will show you how to set up official Apache/Airflow with PostgreSQL and LocalExecutor using docker and docker-compose. In this post, I won’t be going through Airflow, what it is, and how it is used. Please checktheofficial documentation for more information about that.
Before setting up and running Apache Airflow, please install Docker and Docker Compose.
In this chapter, I will show you files and directories which are needed to run airflow and in the next chapter, I will go file by file, line by line explaining what is going on.
Firstly, in the root directory create three more directories: dags, logs, and scripts. Further, create following files: **.env, docker-compose.yml, entrypoint.sh **and **dummy_dag.py. **Please make sure those files and directories follow the structure below.
#project structure
root/
├── dags/
│ └── dummy_dag.py
├── scripts/
│ └── entrypoint.sh
├── logs/
├── .env
└── docker-compose.yml
Created files should contain the following:
#docker-compose.yml
version: '3.8'
services:
postgres:
image: postgres
environment:
- POSTGRES_USER=airflow
- POSTGRES_PASSWORD=airflow
- POSTGRES_DB=airflow
scheduler:
image: apache/airflow
command: scheduler
restart_policy:
condition: on-failure
depends_on:
- postgres
env_file:
- .env
volumes:
- ./dags:/opt/airflow/dags
- ./logs:/opt/airflow/logs
webserver:
image: apache/airflow
entrypoint: ./scripts/entrypoint.sh
restart_policy:
condition: on-failure
depends_on:
- postgres
- scheduler
env_file:
- .env
volumes:
- ./dags:/opt/airflow/dags
- ./logs:/opt/airflow/logs
- ./scripts:/opt/airflow/scripts
ports:
- "8080:8080"
#entrypoint.sh
#!/usr/bin/env bash
airflow initdb
airflow webserver
#.env
AIRFLOW__CORE__SQL_ALCHEMY_CONN=postgresql+psycopg2://airflow:airflow@postgres/airflow
AIRFLOW__CORE__EXECUTOR=LocalExecutor
#dummy_dag.py
from airflow import DAG
from airflow.operators.dummy_operator import DummyOperator
from datetime import datetime
with DAG('example_dag', start_date=datetime(2016, 1, 1)) as dag:
op = DummyOperator(task_id='op')
Positioning in the root directory and executing “docker-compose up” in the terminal should make airflow accessible on localhost:8080. Image bellow shows the final result.
If you encounter permission errors, please run “chmod -R 777” on all subdirectories, e.g. “chmod -R 777 logs/”
For the curious ones...
In Leyman’s terms, docker is used when managing individual containers and docker-compose can be used to manage multi-container applications. It also moves many of the options you would enter on the docker run into the docker-compose.yml file for easier reuse. It works as a front end "script" on top of the same docker API used by docker. You can do everything docker-compose does with docker commands and a lot of shell scripting.
Before running our multi-container docker applications, docker-compose.yml must be configured. With that file, we define services that will be run on docker-compose up.
The first attribute of docker-compose.yml is version, which is the compose file format version. For the most recent version of file format and all configuration options click here.
Second attribute is services and all attributes one level bellow services denote containers used in our multi-container application. These are postgres, scheduler and webserver. Each container has image attribute which points to base image used for that service.
For each service, we define environment variables used inside service containers. For postgres it is defined by environment attribute, but for scheduler and webserver it is defined by .env file. Because .env is an external file we must point to it with env_file attribute.
By opening .env file we can see two variables defined. One defines executor which will be used and the other denotes connection string. Each connection string must be defined in the following manner:
dialect+driver://username:password@host:port/database
Dialect names include the identifying name of the SQLAlchemy dialect, a name such as sqlite
, mysql
, postgresql
, oracle
, or mssql
. Driver is the name of the DBAPI to be used to connect to the database using all lowercase letters. In our case, connection string is defined by:
postgresql+psycopg2://airflow:airflow@postgres/airflow
Omitting port after host part denotes that we will be using default postgres port defined in its own Dockerfile.
Every service can define command which will be run inside Docker container. If one service needs to execute multiple commands it can be done by defining an optional .sh file and pointing to it with entrypoint attribute. In our case we have entrypoint.sh inside the scripts folder which once executed, runs airflow initdb and airflow webserver. Both are mandatory for airflow to run properly.
Defining depends_on attribute, we can express dependency between services. In our example, webserver starts only if both scheduler and postgres have started, also the scheduler only starts after postgres have started.
In case our container crashes, we can restart it by restart_policy. The restart_policy configures if and how to restart containers when they exit. Additional options are condition, delay, max_attempts, and window.
Once service is running, it is being served on containers defined port. To access that service we need to expose the containers port to the host's port. That is being done by ports attribute. In our case, we are exposing port 8080 of the container to TCP port 8080 on 127.0.0.1 (localhost) of the host machine. Left side of :
defines host machines port and the right-hand side defines containers port.
Lastly, the volumes attribute defines shared volumes (directories) between host file system and docker container. Because airflows default working directory is /opt/airflow/ we need to point our designated volumes from the root folder to the airflow containers working directory. Such is done by the following command:
#general case for airflow
- ./<our-root-subdir>:/opt/airflow/<our-root-subdir>
#our case
- ./dags:/opt/airflow/dags
- ./logs:/opt/airflow/logs
- ./scripts:/opt/airflow/scripts
...
This way, when the scheduler or webserver writes logs to its logs directory we can access it from our file system within the logs directory. When we add a new dag to the dags folder it will automatically be added in the containers dag bag and so on.
Originally published by Ivan Rezic at Towardsdatascience
#docker #how-to #apache-airflow #docker-compose #postgresql
1617889740
Open terminal and execute the following commands.
In the above line, the required version is specified as “postgres:10”. Refer the documentation for a list of supported versions.
#database-backup #postgres #postgresql #docker-image #docker
1651319520
Serverless APIGateway Service Proxy
This Serverless Framework plugin supports the AWS service proxy integration feature of API Gateway. You can directly connect API Gateway to AWS services without Lambda.
Run serverless plugin install
in your Serverless project.
serverless plugin install -n serverless-apigateway-service-proxy
Here is a services list which this plugin supports for now. But will expand to other services in the feature. Please pull request if you are intersted in it.
Define settings of the AWS services you want to integrate under custom > apiGatewayServiceProxies
and run serverless deploy
.
Sample syntax for Kinesis proxy in serverless.yml
.
custom:
apiGatewayServiceProxies:
- kinesis: # partitionkey is set apigateway requestid by default
path: /kinesis
method: post
streamName: { Ref: 'YourStream' }
cors: true
- kinesis:
path: /kinesis
method: post
partitionKey: 'hardcordedkey' # use static partitionkey
streamName: { Ref: 'YourStream' }
cors: true
- kinesis:
path: /kinesis/{myKey} # use path parameter
method: post
partitionKey:
pathParam: myKey
streamName: { Ref: 'YourStream' }
cors: true
- kinesis:
path: /kinesis
method: post
partitionKey:
bodyParam: data.myKey # use body parameter
streamName: { Ref: 'YourStream' }
cors: true
- kinesis:
path: /kinesis
method: post
partitionKey:
queryStringParam: myKey # use query string param
streamName: { Ref: 'YourStream' }
cors: true
- kinesis: # PutRecords
path: /kinesis
method: post
action: PutRecords
streamName: { Ref: 'YourStream' }
cors: true
resources:
Resources:
YourStream:
Type: AWS::Kinesis::Stream
Properties:
ShardCount: 1
Sample request after deploying.
curl https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/kinesis -d '{"message": "some data"}' -H 'Content-Type:application/json'
Sample syntax for SQS proxy in serverless.yml
.
custom:
apiGatewayServiceProxies:
- sqs:
path: /sqs
method: post
queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
cors: true
resources:
Resources:
SQSQueue:
Type: 'AWS::SQS::Queue'
Sample request after deploying.
curl https://xxxxxx.execute-api.us-east-1.amazonaws.com/dev/sqs -d '{"message": "testtest"}' -H 'Content-Type:application/json'
If you'd like to pass additional data to the integration request, you can do so by including your custom API Gateway request parameters in serverless.yml
like so:
custom:
apiGatewayServiceProxies:
- sqs:
path: /queue
method: post
queueName: !GetAtt MyQueue.QueueName
cors: true
requestParameters:
'integration.request.querystring.MessageAttribute.1.Name': "'cognitoIdentityId'"
'integration.request.querystring.MessageAttribute.1.Value.StringValue': 'context.identity.cognitoIdentityId'
'integration.request.querystring.MessageAttribute.1.Value.DataType': "'String'"
'integration.request.querystring.MessageAttribute.2.Name': "'cognitoAuthenticationProvider'"
'integration.request.querystring.MessageAttribute.2.Value.StringValue': 'context.identity.cognitoAuthenticationProvider'
'integration.request.querystring.MessageAttribute.2.Value.DataType': "'String'"
The alternative way to pass MessageAttribute
parameters is via a request body mapping template.
See the SQS section under Customizing request body mapping templates
Simplified response template customization
You can get a simple customization of the responses by providing a template for the possible responses. The template is assumed to be application/json
.
custom:
apiGatewayServiceProxies:
- sqs:
path: /queue
method: post
queueName: !GetAtt MyQueue.QueueName
cors: true
response:
template:
# `success` is used when the integration response is 200
success: |-
{ "message: "accepted" }
# `clientError` is used when the integration response is 400
clientError: |-
{ "message": "there is an error in your request" }
# `serverError` is used when the integration response is 500
serverError: |-
{ "message": "there was an error handling your request" }
Full response customization
If you want more control over the integration response, you can provide an array of objects for the response
value:
custom:
apiGatewayServiceProxies:
- sqs:
path: /queue
method: post
queueName: !GetAtt MyQueue.QueueName
cors: true
response:
- statusCode: 200
selectionPattern: '2\\d{2}'
responseParameters: {}
responseTemplates:
application/json: |-
{ "message": "accepted" }
The object keys correspond to the API Gateway integration response object.
Sample syntax for S3 proxy in serverless.yml
.
custom:
apiGatewayServiceProxies:
- s3:
path: /s3
method: post
action: PutObject
bucket:
Ref: S3Bucket
key: static-key.json # use static key
cors: true
- s3:
path: /s3/{myKey} # use path param
method: get
action: GetObject
bucket:
Ref: S3Bucket
key:
pathParam: myKey
cors: true
- s3:
path: /s3
method: delete
action: DeleteObject
bucket:
Ref: S3Bucket
key:
queryStringParam: key # use query string param
cors: true
resources:
Resources:
S3Bucket:
Type: 'AWS::S3::Bucket'
Sample request after deploying.
curl https://xxxxxx.execute-api.us-east-1.amazonaws.com/dev/s3 -d '{"message": "testtest"}' -H 'Content-Type:application/json'
Similar to the SQS support, you can customize the default request parameters serverless.yml
like so:
custom:
apiGatewayServiceProxies:
- s3:
path: /s3
method: post
action: PutObject
bucket:
Ref: S3Bucket
cors: true
requestParameters:
# if requestParameters has a 'integration.request.path.object' property you should remove the key setting
'integration.request.path.object': 'context.requestId'
'integration.request.header.cache-control': "'public, max-age=31536000, immutable'"
If you'd like use custom API Gateway request templates, you can do so like so:
custom:
apiGatewayServiceProxies:
- s3:
path: /s3
method: get
action: GetObject
bucket:
Ref: S3Bucket
request:
template:
application/json: |
#set ($specialStuff = $context.request.header.x-special)
#set ($context.requestOverride.path.object = $specialStuff.replaceAll('_', '-'))
{}
Note that if the client does not provide a Content-Type
header in the request, ApiGateway defaults to application/json
.
Added the new customization parameter that lets the user set a custom Path Override in API Gateway other than the {bucket}/{object}
This parameter is optional and if not set, will fall back to {bucket}/{object}
The Path Override will add {bucket}/
automatically in front
Please keep in mind, that key or path.object still needs to be set at the moment (maybe this will be made optional later on with this)
Usage (With 2 Path Parameters (folder and file and a fixed file extension)):
custom:
apiGatewayServiceProxies:
- s3:
path: /s3/{folder}/{file}
method: get
action: GetObject
pathOverride: '{folder}/{file}.xml'
bucket:
Ref: S3Bucket
cors: true
requestParameters:
# if requestParameters has a 'integration.request.path.object' property you should remove the key setting
'integration.request.path.folder': 'method.request.path.folder'
'integration.request.path.file': 'method.request.path.file'
'integration.request.path.object': 'context.requestId'
'integration.request.header.cache-control': "'public, max-age=31536000, immutable'"
This will result in API Gateway setting the Path Override attribute to {bucket}/{folder}/{file}.xml
So for example if you navigate to the API Gatway endpoint /language/en
it will fetch the file in S3 from {bucket}/language/en.xml
Can use greedy, for deeper Folders
The forementioned example can also be shortened by a greedy approach. Thanks to @taylorreece for mentioning this.
custom:
apiGatewayServiceProxies:
- s3:
path: /s3/{myPath+}
method: get
action: GetObject
pathOverride: '{myPath}.xml'
bucket:
Ref: S3Bucket
cors: true
requestParameters:
# if requestParameters has a 'integration.request.path.object' property you should remove the key setting
'integration.request.path.myPath': 'method.request.path.myPath'
'integration.request.path.object': 'context.requestId'
'integration.request.header.cache-control': "'public, max-age=31536000, immutable'"
This will translate for example /s3/a/b/c
to a/b/c.xml
You can get a simple customization of the responses by providing a template for the possible responses. The template is assumed to be application/json
.
custom:
apiGatewayServiceProxies:
- s3:
path: /s3
method: post
action: PutObject
bucket:
Ref: S3Bucket
key: static-key.json
response:
template:
# `success` is used when the integration response is 200
success: |-
{ "message: "accepted" }
# `clientError` is used when the integration response is 400
clientError: |-
{ "message": "there is an error in your request" }
# `serverError` is used when the integration response is 500
serverError: |-
{ "message": "there was an error handling your request" }
Sample syntax for SNS proxy in serverless.yml
.
custom:
apiGatewayServiceProxies:
- sns:
path: /sns
method: post
topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
cors: true
resources:
Resources:
SNSTopic:
Type: AWS::SNS::Topic
Sample request after deploying.
curl https://xxxxxx.execute-api.us-east-1.amazonaws.com/dev/sns -d '{"message": "testtest"}' -H 'Content-Type:application/json'
Simplified response template customization
You can get a simple customization of the responses by providing a template for the possible responses. The template is assumed to be application/json
.
custom:
apiGatewayServiceProxies:
- sns:
path: /sns
method: post
topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
cors: true
response:
template:
# `success` is used when the integration response is 200
success: |-
{ "message: "accepted" }
# `clientError` is used when the integration response is 400
clientError: |-
{ "message": "there is an error in your request" }
# `serverError` is used when the integration response is 500
serverError: |-
{ "message": "there was an error handling your request" }
Full response customization
If you want more control over the integration response, you can provide an array of objects for the response
value:
custom:
apiGatewayServiceProxies:
- sns:
path: /sns
method: post
topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
cors: true
response:
- statusCode: 200
selectionPattern: '2\d{2}'
responseParameters: {}
responseTemplates:
application/json: |-
{ "message": "accepted" }
The object keys correspond to the API Gateway integration response object.
Content Handling and Pass Through Behaviour customization
If you want to work with binary fata, you can not specify contentHandling
and PassThrough
inside the request
object.
custom:
apiGatewayServiceProxies:
- sns:
path: /sns
method: post
topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
request:
contentHandling: CONVERT_TO_TEXT
passThrough: WHEN_NO_TEMPLATES
The allowed values correspond with the API Gateway Method integration for ContentHandling and PassthroughBehavior
Sample syntax for DynamoDB proxy in serverless.yml
. Currently, the supported DynamoDB Operations are PutItem
, GetItem
and DeleteItem
.
custom:
apiGatewayServiceProxies:
- dynamodb:
path: /dynamodb/{id}/{sort}
method: put
tableName: { Ref: 'YourTable' }
hashKey: # set pathParam or queryStringParam as a partitionkey.
pathParam: id
attributeType: S
rangeKey: # required if also using sort key. set pathParam or queryStringParam.
pathParam: sort
attributeType: S
action: PutItem # specify action to the table what you want
condition: attribute_not_exists(Id) # optional Condition Expressions parameter for the table
cors: true
- dynamodb:
path: /dynamodb
method: get
tableName: { Ref: 'YourTable' }
hashKey:
queryStringParam: id # use query string parameter
attributeType: S
rangeKey:
queryStringParam: sort
attributeType: S
action: GetItem
cors: true
- dynamodb:
path: /dynamodb/{id}
method: delete
tableName: { Ref: 'YourTable' }
hashKey:
pathParam: id
attributeType: S
action: DeleteItem
cors: true
resources:
Resources:
YourTable:
Type: AWS::DynamoDB::Table
Properties:
TableName: YourTable
AttributeDefinitions:
- AttributeName: id
AttributeType: S
- AttributeName: sort
AttributeType: S
KeySchema:
- AttributeName: id
KeyType: HASH
- AttributeName: sort
KeyType: RANGE
ProvisionedThroughput:
ReadCapacityUnits: 1
WriteCapacityUnits: 1
Sample request after deploying.
curl -XPUT https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/dynamodb/<hashKey>/<sortkey> \
-d '{"name":{"S":"john"},"address":{"S":"xxxxx"}}' \
-H 'Content-Type:application/json'
Sample syntax for EventBridge proxy in serverless.yml
.
custom:
apiGatewayServiceProxies:
- eventbridge: # source and detailType are hardcoded; detail defaults to POST body
path: /eventbridge
method: post
source: 'hardcoded_source'
detailType: 'hardcoded_detailType'
eventBusName: { Ref: 'YourBusName' }
cors: true
- eventbridge: # source and detailType as path parameters
path: /eventbridge/{detailTypeKey}/{sourceKey}
method: post
detailType:
pathParam: detailTypeKey
source:
pathParam: sourceKey
eventBusName: { Ref: 'YourBusName' }
cors: true
- eventbridge: # source, detail, and detailType as body parameters
path: /eventbridge/{detailTypeKey}/{sourceKey}
method: post
detailType:
bodyParam: data.detailType
source:
bodyParam: data.source
detail:
bodyParam: data.detail
eventBusName: { Ref: 'YourBusName' }
cors: true
resources:
Resources:
YourBus:
Type: AWS::Events::EventBus
Properties:
Name: YourEventBus
Sample request after deploying.
curl https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/eventbridge -d '{"message": "some data"}' -H 'Content-Type:application/json'
To set CORS configurations for your HTTP endpoints, simply modify your event configurations as follows:
custom:
apiGatewayServiceProxies:
- kinesis:
path: /kinesis
method: post
streamName: { Ref: 'YourStream' }
cors: true
Setting cors to true assumes a default configuration which is equivalent to:
custom:
apiGatewayServiceProxies:
- kinesis:
path: /kinesis
method: post
streamName: { Ref: 'YourStream' }
cors:
origin: '*'
headers:
- Content-Type
- X-Amz-Date
- Authorization
- X-Api-Key
- X-Amz-Security-Token
- X-Amz-User-Agent
allowCredentials: false
Configuring the cors property sets Access-Control-Allow-Origin, Access-Control-Allow-Headers, Access-Control-Allow-Methods,Access-Control-Allow-Credentials headers in the CORS preflight response. To enable the Access-Control-Max-Age preflight response header, set the maxAge property in the cors object:
custom:
apiGatewayServiceProxies:
- kinesis:
path: /kinesis
method: post
streamName: { Ref: 'YourStream' }
cors:
origin: '*'
maxAge: 86400
If you are using CloudFront or another CDN for your API Gateway, you may want to setup a Cache-Control header to allow for OPTIONS request to be cached to avoid the additional hop.
To enable the Cache-Control header on preflight response, set the cacheControl property in the cors object:
custom:
apiGatewayServiceProxies:
- kinesis:
path: /kinesis
method: post
streamName: { Ref: 'YourStream' }
cors:
origin: '*'
headers:
- Content-Type
- X-Amz-Date
- Authorization
- X-Api-Key
- X-Amz-Security-Token
- X-Amz-User-Agent
allowCredentials: false
cacheControl: 'max-age=600, s-maxage=600, proxy-revalidate' # Caches on browser and proxy for 10 minutes and doesnt allow proxy to serve out of date content
You can pass in any supported authorization type:
custom:
apiGatewayServiceProxies:
- sqs:
path: /sqs
method: post
queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
cors: true
# optional - defaults to 'NONE'
authorizationType: 'AWS_IAM' # can be one of ['NONE', 'AWS_IAM', 'CUSTOM', 'COGNITO_USER_POOLS']
# when using 'CUSTOM' authorization type, one should specify authorizerId
# authorizerId: { Ref: 'AuthorizerLogicalId' }
# when using 'COGNITO_USER_POOLS' authorization type, one can specify a list of authorization scopes
# authorizationScopes: ['scope1','scope2']
resources:
Resources:
SQSQueue:
Type: 'AWS::SQS::Queue'
Source: AWS::ApiGateway::Method docs
You can indicate whether the method requires clients to submit a valid API key using private
flag:
custom:
apiGatewayServiceProxies:
- sqs:
path: /sqs
method: post
queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
cors: true
private: true
resources:
Resources:
SQSQueue:
Type: 'AWS::SQS::Queue'
which is the same syntax used in Serverless framework.
Source: Serverless: Setting API keys for your Rest API
Source: AWS::ApiGateway::Method docs
By default, the plugin will generate a role with the required permissions for each service type that is configured.
You can configure your own role by setting the roleArn
attribute:
custom:
apiGatewayServiceProxies:
- sqs:
path: /sqs
method: post
queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
cors: true
roleArn: # Optional. A default role is created when not configured
Fn::GetAtt: [CustomS3Role, Arn]
resources:
Resources:
SQSQueue:
Type: 'AWS::SQS::Queue'
CustomS3Role:
# Custom Role definition
Type: 'AWS::IAM::Role'
The plugin allows one to specify which parameters the API Gateway method accepts.
A common use case is to pass custom data to the integration request:
custom:
apiGatewayServiceProxies:
- sqs:
path: /sqs
method: post
queueName: { 'Fn::GetAtt': ['SqsQueue', 'QueueName'] }
cors: true
acceptParameters:
'method.request.header.Custom-Header': true
requestParameters:
'integration.request.querystring.MessageAttribute.1.Name': "'custom-Header'"
'integration.request.querystring.MessageAttribute.1.Value.StringValue': 'method.request.header.Custom-Header'
'integration.request.querystring.MessageAttribute.1.Value.DataType': "'String'"
resources:
Resources:
SqsQueue:
Type: 'AWS::SQS::Queue'
Any published SQS message will have the Custom-Header
value added as a message attribute.
If you'd like to add content types or customize the default templates, you can do so by including your custom API Gateway request mapping template in serverless.yml
like so:
# Required for using Fn::Sub
plugins:
- serverless-cloudformation-sub-variables
custom:
apiGatewayServiceProxies:
- kinesis:
path: /kinesis
method: post
streamName: { Ref: 'MyStream' }
request:
template:
text/plain:
Fn::Sub:
- |
#set($msgBody = $util.parseJson($input.body))
#set($msgId = $msgBody.MessageId)
{
"Data": "$util.base64Encode($input.body)",
"PartitionKey": "$msgId",
"StreamName": "#{MyStreamArn}"
}
- MyStreamArn:
Fn::GetAtt: [MyStream, Arn]
It is important that the mapping template will return a valid
application/json
string
Source: How to connect SNS to Kinesis for cross-account delivery via API Gateway
Customizing SQS request templates requires us to force all requests to use an application/x-www-form-urlencoded
style body. The plugin sets the Content-Type
header to application/x-www-form-urlencoded
for you, but API Gateway will still look for the template under the application/json
request template type, so that is where you need to configure you request body in serverless.yml
:
custom:
apiGatewayServiceProxies:
- sqs:
path: /{version}/event/receiver
method: post
queueName: { 'Fn::GetAtt': ['SqsQueue', 'QueueName'] }
request:
template:
application/json: |-
#set ($body = $util.parseJson($input.body))
Action=SendMessage##
&MessageGroupId=$util.urlEncode($body.event_type)##
&MessageDeduplicationId=$util.urlEncode($body.event_id)##
&MessageAttribute.1.Name=$util.urlEncode("X-Custom-Signature")##
&MessageAttribute.1.Value.DataType=String##
&MessageAttribute.1.Value.StringValue=$util.urlEncode($input.params("X-Custom-Signature"))##
&MessageBody=$util.urlEncode($input.body)
Note that the ##
at the end of each line is an empty comment. In VTL this has the effect of stripping the newline from the end of the line (as it is commented out), which makes API Gateway read all the lines in the template as one line.
Be careful when mixing additional requestParameters
into your SQS endpoint as you may overwrite the integration.request.header.Content-Type
and stop the request template from being parsed correctly. You may also unintentionally create conflicts between parameters passed using requestParameters
and those in your request template. Typically you should only use the request template if you need to manipulate the incoming request body in some way.
Your custom template must also set the Action
and MessageBody
parameters, as these will not be added for you by the plugin.
When using a custom request body, headers sent by a client will no longer be passed through to the SQS queue (PassthroughBehavior
is automatically set to NEVER
). You will need to pass through headers sent by the client explicitly in the request body. Also, any custom querystring parameters in the requestParameters
array will be ignored. These also need to be added via the custom request body.
Similar to the Kinesis support, you can customize the default request mapping templates in serverless.yml
like so:
# Required for using Fn::Sub
plugins:
- serverless-cloudformation-sub-variables
custom:
apiGatewayServiceProxies:
- kinesis:
path: /sns
method: post
topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
request:
template:
application/json:
Fn::Sub:
- "Action=Publish&Message=$util.urlEncode('This is a fixed message')&TopicArn=$util.urlEncode('#{MyTopicArn}')"
- MyTopicArn: { Ref: MyTopic }
It is important that the mapping template will return a valid
application/x-www-form-urlencoded
string
Source: Connect AWS API Gateway directly to SNS using a service integration
You can customize the response body by providing mapping templates for success, server errors (5xx) and client errors (4xx).
Templates must be in JSON format. If a template isn't provided, the integration response will be returned as-is to the client.
custom:
apiGatewayServiceProxies:
- kinesis:
path: /kinesis
method: post
streamName: { Ref: 'MyStream' }
response:
template:
success: |
{
"success": true
}
serverError: |
{
"success": false,
"errorMessage": "Server Error"
}
clientError: |
{
"success": false,
"errorMessage": "Client Error"
}
Author: Serverless-operations
Source Code: https://github.com/serverless-operations/serverless-apigateway-service-proxy
License:
1595249460
Following the second video about Docker basics, in this video, I explain Docker architecture and explain the different building blocks of the docker engine; docker client, API, Docker Daemon. I also explain what a docker registry is and I finish the video with a demo explaining and illustrating how to use Docker hub
In this video lesson you will learn:
#docker #docker hub #docker host #docker engine #docker architecture #api