With the rise of serverless computing, many developers wonder if Java is still a viable option for building serverless applications. While there are some challenges to using Java in a serverless environment, there are also many benefits to using this popular programming language.

First, let’s take a look at the basics of serverless on AWS. Serverless computing allows you to run your code without having to provision or manage servers. Instead, your code is executed in response to events, such as an HTTP request or a message in a queue. This allows you to pay only for the compute resources you actually use, rather than having to pay for idle capacity.

When it comes to building serverless applications, there are several popular languages to choose from, including Node.js, Python, and Go. However, many developers are also considering using Java, which has a large ecosystem of libraries and frameworks, as well as a large and active community of developers.

One of the biggest challenges to using Java in a serverless environment is the increased memory usage and cost associated with running a JVM. Java applications tend to use more memory than other languages like Go and Node.js, which can result in higher costs when running on a serverless platform like AWS Lambda.

Since serverless functions are typically invoked in response to events, they may experience “cold starts” where the function must first be loaded into memory before it can begin executing. This can add additional latency to the function’s execution time.

There are several options available in AWS and in general that can help mitigate the cons of using Java in serverless environments:

  1. Reducing Memory Usage: One way to reduce the memory usage of a Java application is to use a smaller Java runtime, such as Amazon Corretto or OpenJDK. Another option is to use a Just-In-Time (JIT) compiler, such as GraalVM, which can help improve the performance of Java applications by reducing the amount of memory they use.
  2. Optimizing Function Execution Time: To minimize the cost of running Java functions in AWS Lambda, you can optimize the execution time by reducing the number of dependencies and libraries, and by using the latest version of the AWS Lambda runtime. Additionally, you can use the AWS Lambda Power Tuning feature to optimize the performance of your functions by adjusting the amount of memory allocated to them.
  3. Cold Start Optimization: To minimize the impact of cold starts on the performance of your Java functions, you can use the AWS Lambda Provisioned Concurrency feature, which keeps a pre-warmed instance of your function ready to respond to incoming requests. Additionally, you can use the AWS Lambda Layers feature to package and share common dependencies across multiple functions, reducing the time required for a function to initialize.
  4. Containerization: Another way to mitigate the cons of using Java in serverless environments is to containerize your applications. With containerization, you can package your application and its dependencies into a container, which can be deployed to a serverless platform like AWS Fargate or Amazon Elastic Container Service (ECS). This approach allows you to use Java with minimal cold-start latency and higher performance and memory control.
  5. Use of other serverless platforms: Alternately, you can use other serverless platforms like OpenFaaS, knative, etc which are designed to use containerization and support Java out of the box.

In conclusion, while there are certain cons of using Java in serverless environments, such as increased memory usage and longer cold start times, these can be mitigated by using the right tools and techniques. Java is a robust and scalable language that’s well-suited for enterprise-grade applications, making it a great choice for serverless development if you are willing to put in the effort to optimize the performance and cost. Additionally, its wide developer community and the vast collection of libraries and frameworks make it a great choice for those who are familiar with the language. However, it’s worth considering other languages like Go that have been specifically designed for cloud-native environments and have lower memory usage and faster cold start times out of the box.

It’s also worth noting that many large and well-known companies use Java in their serverless architectures, such as Netflix and Amazon Web Services (AWS). Netflix, for example, uses Java to power their serverless microservices and has reported that it has handled billions of requests per day with ease.

Ultimately, the choice of language will depend on your specific use case, requirements, and the expertise of your development team.