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Deploying a Spring Cloud Function on AWS Lambda Platform using Serverless Framework

newray • January 31, 2023

If Java Is Your Choice Of Programming Language – Spring Cloud Function + Serverless Framework Makes A Great Technology Stack. It Boosts Developer Productivity By Decoupling From Vendor Specific FaaS API, And Deployment Activities.

Quick introduction to Spring Cloud Function

Spring Cloud Function provides an uniform programming model to develop functions which can be run on any Function-as-a-Service platforms like AWS Lambda. The same code can run as a web endpoint, a stream processor, or a task. Also, enables Spring Boot features. More information is availabe at Spring Cloud Function.


Quick introduction to Serverless Framework

I found the definition of Serverless Framework @ Serverless Inc. is precisely explained.

Serverless is your toolkit for deploying and operating serverless architectures. Focus on your application, not your infrastructure.

Example project (Source Code @ GitHub)


Use-case

This is a scenario in which when we provide a Member ID, the service should reply with the type of coverage that member has. In this fictional scenario it always returns a coverage type as MEDICAL for a given Member ID.


Function

@Bean

public Function<HealthFirstMemberRequest, HealthFirstMemberResponse> members() {

   return member -> {

      HealthFirstMemberResponse response = new HealthFirstMemberResponse();

      response.setMemberId(member.getMemberId());

      response.setCoverage(HealthFirstMemberResponse.Coverage.MEDICAL);

       return response;

       };

}


AWS Lambda Handler

A Handler class which just implements SpringBootRequestHandler is needed. This is what we are going to configure in serverless.yml file.


Maven POM file

The following dependencies in POM.xml file does all the magic of generating AWS specific Lambda code.

<dependency>

<groupId>org.springframework.cloud</groupId>

<artifactId>spring-cloud-function-adapter-aws</artifactId>

</dependency>

<dependency>

<groupId>com.amazonaws</groupId>

<artifactId>aws-lambda-java-core</artifactId>

<version>${aws-lambda-core.version}</version><scope>provided</scope>

</dependency>


Generating deployable Artifact

Run following command to generate deployable / uploadable .jar file.


$mvn clean package


This gnerates a JAR file ‘member-function-0.0.1-SNAPSHOT-aws.jar‘ under target folder. Serverless Framework uploads this JAR file to AWS Lambda.


Installing Serverless Framework

Run following command to install Serverless Framework from NPM

$npm install serverless -g

After installing you can run serverless or short form sis command to use Serverless Framework.

To check the command type

$serverless version

or

$sls version

Configuring serverless.yml file

We need to define serverless.yml file with all the settings needed.

service: sls-aws-java-spring-cloud-function-demo

provider:

  name: aws

  runtime: java8

  timeout: 10

package:

  artifact: target/aws-java-spring-cloud-function-demo-0.0.1-SNAPSHOT-aws.jar

functions:

  members:

    handler: com.healthfirst.memberfunction.AwsLambdaHandler

    environment:

      FUNCTION_NAME: members

Deploying on AWS Lambda Platform

Run following command to deploy the project on AWS Lambda

$sls deploy -v --aws-profile <your aws profile>

You would see something similar to this

Serverless: Packaging service...

Serverless: Creating Stack...

Serverless: Checking Stack create progress...

CloudFormation - CREATE_IN_PROGRESS - AWS::CloudFormation::Stack - sls-aws-java-spring-cloud-function-demo-dev

CloudFormation - CREATE_IN_PROGRESS - AWS::S3::Bucket - ServerlessDeploymentBucket

CloudFormation - CREATE_IN_PROGRESS - AWS::S3::Bucket - ServerlessDeploymentBucket

CloudFormation - CREATE_COMPLETE - AWS::S3::Bucket - ServerlessDeploymentBucket

CloudFormation - CREATE_COMPLETE - AWS::CloudFormation::Stack - sls-aws-java-spring-cloud-function-demo-dev

Serverless: Stack create finished...

Serverless: Uploading CloudFormation file to S3...

Serverless: Uploading artifacts...

Serverless: Uploading service .zip file to S3 (12.91 MB)...

Serverless: Validating template...

Serverless: Updating Stack...

Serverless: Checking Stack update progress...

CloudFormation - UPDATE_IN_PROGRESS - AWS::CloudFormation::Stack - sls-aws-java-spring-cloud-function-demo-dev

CloudFormation - CREATE_IN_PROGRESS - AWS::Logs::LogGroup - MembersLogGroup

CloudFormation - CREATE_IN_PROGRESS - AWS::IAM::Role - IamRoleLambdaExecution

CloudFormation - CREATE_IN_PROGRESS - AWS::Logs::LogGroup - MembersLogGroup

CloudFormation - CREATE_IN_PROGRESS - AWS::IAM::Role - IamRoleLambdaExecution

CloudFormation - CREATE_COMPLETE - AWS::Logs::LogGroup - MembersLogGroup

CloudFormation - CREATE_COMPLETE - AWS::IAM::Role - IamRoleLambdaExecution

CloudFormation - CREATE_IN_PROGRESS - AWS::Lambda::Function - MembersLambdaFunction

CloudFormation - CREATE_IN_PROGRESS - AWS::Lambda::Function - MembersLambdaFunction

CloudFormation - CREATE_COMPLETE - AWS::Lambda::Function - MembersLambdaFunction

CloudFormation - CREATE_IN_PROGRESS - AWS::Lambda::Version - MembersLambdaVersionN8TC7eR31v5vRUjauJUxtjhrj6n1C123yUgLKetxebM

CloudFormation - CREATE_IN_PROGRESS - AWS::Lambda::Version - MembersLambdaVersionN8TC7eR31v5vRUjauJUxtjhrj6n1C123yUgLKetxebM

CloudFormation - CREATE_COMPLETE - AWS::Lambda::Version - MembersLambdaVersionN8TC7eR31v5vRUjauJUxtjhrj6n1C123yUgLKetxebM

CloudFormation - UPDATE_COMPLETE_CLEANUP_IN_PROGRESS - AWS::CloudFormation::Stack - sls-aws-java-spring-cloud-function-demo-dev

CloudFormation - UPDATE_COMPLETE - AWS::CloudFormation::Stack - sls-aws-java-spring-cloud-function-demo-dev

Serverless: Stack update finished...

Service Information

service: sls-aws-java-spring-cloud-function-demo

stage: dev

region: us-east-1

stack: sls-aws-java-spring-cloud-function-demo-dev

api keys:

  None

endpoints:

  None

functions:members: sls-aws-java-spring-cloud-function-demo-dev-members


Stack Outputs

MembersLambdaFunctionQualifiedArn: arn:aws:lambda:us-east-1:899022498951:function:sls-aws-java-spring-cloud-function-demo-dev-members:1

ServerlessDeploymentBucketName: sls-aws-java-spring-clou-serverlessdeploymentbuck-1qadcge7s5r27

Run following command to invoke the function

$ sls invoke -f members -l --aws-profile <your AWS profile name> --data '{"memberId":"1234567890"}'

This will invoke the function by passing the Member ID. You would see console output with response MEDICAL as below.

{

    "memberId": "1234567890",

    "coverage": "MEDICAL"

}

--------------------------------------------------------------------

START RequestId: ae39247a-7c6d-11e8-b022-eb1234c7df4f Version: $LATEST

13:58:36.347 [main] INFO org.springframework.cloud.function.adapter.aws.SpringFunctionInitializer - Initializing: class com.healthfirst.memberfunction.MemberFunctionApplication


  .   ____          _            __ _ _

 /\\ / ___'_ __ _ _(_)_ __  __ _ \ \ \ \

( ( )\___ | '_ | '_| | '_ \/ _` | \ \ \ \

 \\/  ___)   _)             (_     ) ) ) )

  '   ____  .__|_   _|_   _\__,   / / / /

 =========|_|==============|___/=/_/_/_/

 :: Spring Boot ::                       


2018-06-30 13:58:39.013  INFO 1 --- [           main] lambdainternal.LambdaRTEntry             : Starting LambdaRTEntry on ip-10-22-39-231.ec2.internal with PID 1 (/var/runtime/lib/LambdaJavaRTEntry-1.0.jar started by sbx_user1060 in /)

2018-06-30 13:58:39.016  INFO 1 --- [           main] lambdainternal.LambdaRTEntry             : No active profile set, falling back to default profiles: default

2018-06-30 13:58:39.297  INFO 1 --- [           main] s.c.a.AnnotationConfigApplicationContext : Refreshing org.springframework.context.annotation.AnnotationConfigApplicationContext@23fe1d71: startup date [Sat Jun 30 13:58:39 UTC 2018]; root of context hierarchy

2018-06-30 13:58:44.069  INFO 1 --- [           main] o.s.j.e.a.AnnotationMBeanExporter        : Registering beans for JMX exposure on startup

2018-06-30 13:58:44.152  INFO 1 --- [           main] lambdainternal.LambdaRTEntry             : Started LambdaRTEntry in 7.536 seconds (JVM running for 8.879)

END RequestId: ae39247a-7c6d-11e8-b022-eb1234c7df4f

REPORT RequestId: ae39247a-7c6d-11e8-b022-eb1234c7df4f  Duration: 8002.57 ms    Billed Duration: 8100 ms        Memory Size: 1024 MB    Max Memory Used: 142 MB

Run the following command to uninstall the project from AWS

$sls remove --aws-profile <your aws profile>

This one command will uninstall the stack on AWS cloud so that you may not be charged for any more usage.

Serverless: Getting all objects in S3 bucket...

Serverless: Removing objects in S3 bucket...

Serverless: Removing Stack...

Serverless: Checking Stack removal progress...

........

Serverless: Stack removal finished...

Summary

If Java is your choice of programming language – Spring Cloud Function + Serverless Framework makes a great technology stack. It boosts developer productivity by decoupling from Vendor specific FaaS API, and deployment activities.

TDD of Microservice-Nanoservice Combination with a Contract (In other words, SpringBoot-SpringFunction Combo with a Spring RestDocs-Contract)

By newray • January 31, 2023
This Article Attempts To Demonstrate How Powerful Is Test Driven Development & Consumer-Driven-Contract When There Is A Dependency On An Internal/External Service. If There Is A Mix Of Microservices And Nanoservices This Approach Really Boosts Developer Productivity To Produce Quality Testable Code.

Application Logging & Log Draining in Cloud Foundry

By newray • January 31, 2023
Introduction The main goal of this blog post is to provide necessary information to get started on using Cloud Foundry Logging Component. A little introduction to concepts like Cloud-Native Apps, 12 Factor Apps is needed to understand System and Application logging on Cloud. Here is the breakdown of this blog post. The purpose of aggregating logs from all running instances of an application on cloud. How the aggregation of logs is handled on Open-Source PaaS - Cloud Foundry. How easy it is to route the log streams to a specialized log management system - Papertrail. Prerequisite This article assumes you are familiar with Cloud foundry A brief understanding of Cloud Native Applications. A high-level understanding of 12 Factor Apps concepts. I have provided links to various resources at the end of this article to get an understanding of these concepts before you go on and read this blog post. Why do we need to aggregate logs? Cloud Native Apps Applications designed and developed to take advantage of cloud features are supposed to be called cloud native apps. Following constraints makes cloud native applications difficult to troubleshoot. Distributed applications like microservices hard to maintain, and debug. Applications on cloud run on Virtual machines and(or) Containers which are ephemeral. Container Instances are immutable. Because of these constraints storing, analyzing application and system log information is difficult. 12 factor Apps 12 factor apps is like a benchmarking to make sure your application is built for cloud (like microservices) and following certain recommendations. Among the 12 factors following four factors are pertinent to topic of this post. Processes - 12 factor apps are supposed to be state-less so that scaling is easy. Concurrency - For high availability multiple instances of an App are run and load is distributed across. Disposability - To scale-out and scale-in, Apps should be quick to boot-up and easy to be disposable. Logs - 12 factor apps recommends treating logs from all app instances as event streams, never store them inside containers or virtual machines. Logs should be streamed out and stored somewhere else and should be aggregated not to loose them. What component of Cloud Foundry handles logging? Cloud Foundry Loggregator Component A brief introduction to Cloud foundry Cloud Foundry is an open-source Platform-As-A-Service (Paas) to run applications on any cloud. Instead of focusing on Cloud infrastructure CF abstracts all the operational activities and provides a platform to speedup application development and deployment. Various components of CF address certain factors of 12 factor operations. Loggregator component of CF takes care of aggregation of logs from all running instances of an application. Following diagram explains various sub components within PCF Loggragator Component.

Flutter- Bottom Navigation Bar- Navigation using Dart Streams & BLoC Pattern

By newray • January 31, 2023
Dart’s StreamController and Flutter’s StreamBuilder are powerful tools to achieve a better design and intra-app communication. Prerequisites Basic understanding of Flutter SDK and Scaffold Material Widget. Dart Programming Language. (Basic idea of Streams). BLoC Pattern — (Writing logic separate from UI in a Dart class and sharing it among Widgets). Main focus is Scaffold Widget’s body and bottomNavigationBar sections. “The Scaffold widget takes a number of different widgets as named arguments, each of which are placed in the Scaffold layout in the appropriate place.” The most significant among those named arguments are appBar: (The top section) body: (Main body section) bottomNavigationBar: (Bottom section) Navigating between screens using Scaffold’s bottomNavigationBar can be achieved in many different ways. Most common way is Hold the current BottomNavigationBarItem index value inside the State of a StatefulWidget every time a BottomNavigationBarItem was tapped, and Call that State’s setState() to repaint the whole widget tree to reflect those changes. A slightly better approach can be using a combination of BLoC — to separate business logic from UI Dart’s StreamController — to communicate the UI intents. Flutter’s StreamBuilder — to trigger UI updates. Advantages Using BLoC we can achieve clear separation of business logic from UI. No need to store current BottomNavigationBarItem index inside the State. No need to call setState() every time which re-creates the entire widget tree. Use StreamBuilder to re-create only a sub-tree or widget(s) instead of entire widget tree. So, how can it be achieved? Two key things Communication between the Scaffold’s bottomNavigationBar and body sections is done using Dart’s StreamController. Use Flutter’s StreamBuilder to re-paint just the body section and the BottomNavigationBar. First thing we need a BLoC Let’s create a BLoC. This BLoC holds an enum to represent various BottomNavigationBarItems. a dart StreamController object. a default Navigation Bar Item enum for initial state. a function which can be attached to onTap() gesture of BottomNavigationBar on UI side. a method to close the stream. Lets go over each piece of BLoC in detail… an enum to represent various BottomNavigationBarItems.
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