Using Amazon ElastiCache for Redis To Optimize Your Spring Boot Application

Brandon Klimek AWS, Development Technologies, Java, Spring, Spring Boot 13 Comments

Has your project gotten to the point when big data sets and/or time-consuming calculations have begun to affect performance? Or are you struggling to optimize your queries and need to cache some information to avoid continually hitting your database? Then caching could be your solution.

For this article, I will demonstrate how to utilize Amazon ElastiCache for Redis to speed up areas of your application. The example application we will build uses Spring Boot 2.x and is available on Github.

AWS AppSync with Lambda Data Sources

Mat Warger AWS, Cloud, Development Technologies, GraphQL, JavaScript, Tutorial Leave a Comment

The power of GraphQL lies in its flexibility. That is especially the case regarding resolvers, where any local or remote data can be used to fulfill a GraphQL query or mutation.

In this post, I’m going to demo a quick example of what this looks like, and a couple gotchas that were apparent in working with Lambdas as a data source for AppSync. Let’s gooooo!

Go Forth and AppSync!

Mat Warger AWS, Development Technologies, GraphQL, JavaScript 1 Comment

In a previous post, we discussed the basics of GraphQL and how it can be a great REST API alternative. In this one, we’ll see how AppSync can be more than just a great API alternative — it gives you a soft landing into the world of GraphQL.

Recall our Game API example? Let’s start with the basic type of a game. Follow along and we can implement a simple schema in AppSync together….

AWS Lambda with Spring Boot

Greg Emerick AWS, Cloud, Development Technologies, Java, Spring, Spring Boot 12 Comments

The typical deployment scenario for a Spring Boot application in AWS involves running the Java application on an EC2 instance 24 hours a day. Of course, the application could be deployed in AWS ECS as a Docker container, but it still runs continuously on an EC2 instance. In each case, the EC2 instances need to be monitored and you pay for compute capacity used by that EC2 instance.

AWS Lambda provides low cost compute with zero maintenance. Lambda runs your code on demand, without provisioned and managed servers. Lambda automatically runs and scales your code. You are charged for every 100ms your code executes and the number of times your code is triggered. If the code isn’t running, you pay nothing.

Lambda has clear cost and maintenance benefits. But what does it take to run the standard Spring Boot application as a Lambda? How does it work? What are the drawbacks? These are the questions that will be answered in this blog through a tangible example…

Using Docker + AWS to Build, Deploy and Scale your App

Brandon Klimek AWS, Cloud, DevOps, Docker, Spring, Spring Boot, Tutorial 8 Comments

I recently worked to develop a software platform that relied on Spring Boot and Docker to prop up an API. Being the only developer on the project, I needed to find a way to quickly and efficiently deploy new releases. However, I found many solutions overwhelming to set up.

That was until I discovered AWS has tools that allow any developer to quickly build and deploy their application.

In this 30 minute tutorial, you will discover how to utilize the following technologies:
– AWS CodeCommit – source control (git)
– AWS Code Build – source code compiler, rest runner
– AWS Codepipeline – builds, tests, and deploys code every time the repo changes
-AWS Elastic Beanstalk – service to manage EC2 instances handling deployments, provisioning, load balancing, and health monitoring
-Docker + Spring Boot – Our containerized Spring Boot application for the demo

Once finished, you will have a Docker application running that automatically builds your software on commit, and deploys it to the Elastic beanstalk sitting behind a load balancer for scalability. This continuous integration pipeline will allow you to worry less about your deployments and get back to focusing on feature development within your application.