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On the role of Distinguished Engineer and CTO Mindset Apr 27, 2025 The future is bright Mar 30, 2025 On luck and gumption Oct 8, 2023 Some thoughts on recent RTO announcements Jun 22, 2023 One size does not fit all: neither cloud nor on-prem Apr 10, 2023 Comparing AWS SQS, SNS, and Kinesis: A Technical Breakdown for Enterprise Developers Feb 11, 2023 Working from home works as well as any distributed team Nov 25, 2022 Things to be Thankful for Nov 24, 2022 Why you should question the “database per service” pattern Oct 5, 2022 Stop Shakespearizing Sep 16, 2022 Using GNU Make with JavaScript and Node.js to build AWS Lambda functions Sep 4, 2022 Why don’t they tell you that in the instructions? Aug 31, 2022 Monolithic repository vs a monolith Aug 23, 2022 Keep your caching simple and inexpensive Jun 12, 2022 Java is no longer relevant May 29, 2022 There is no such thing as one grand unified full-stack programming language May 27, 2022 Peloton could monetize these ideas if they only listen May 15, 2022 Best practices for building a microservice architecture Apr 25, 2022 True identity verification should require a human Mar 16, 2020 The passwords are no longer a necessity. Let’s find a good alternative. Mar 2, 2020 What programming language to use for a brand new project? Feb 18, 2020 TDWI 2019: Architecting Modern Big Data API Ecosystems May 30, 2019 Configuring Peloton Apple Health integration Feb 16, 2019 All emails are free -- except they are not Feb 9, 2019 Using Markov Chain Generator to create Donald Trump's state of union speech Jan 20, 2019 The religion of JavaScript Nov 26, 2018 Teleportation can corrupt your data Sep 29, 2018 Let’s talk cloud neutrality Sep 17, 2018 A conservative version of Facebook? Aug 30, 2018 On Facebook and Twitter censorship Aug 20, 2018 Facebook is the new Microsoft Apr 14, 2018 Node.js is a perfect enterprise application platform Jul 30, 2017 Design patterns in TypeScript: Factory Jul 30, 2017 Design patterns in TypeScript: Chain of Responsibility Jul 22, 2017 Singletons in TypeScript Jul 16, 2017 Architecting API ecosystems: my interview with Anthony Brovchenko of R. Culturi Jun 5, 2017 TDWI 2017, Chicago, IL: Architecting Modern Big Data API Ecosystems May 30, 2017 I tried an Apple Watch for two days and I hated it Mar 30, 2017 Emails, politics, and common sense Jan 14, 2017 Online grocers have an additional burden to be reliable Jan 5, 2017 Here is to a great 2017! Dec 26, 2016 Apple’s recent announcements have been underwhelming Oct 29, 2016 I am addicted to Medium, and I am tempted to move my entire blog to it Sep 9, 2016 What I learned from using Amazon Alexa for a month Sep 7, 2016 Praising Bank of America's automated phone-based customer service Aug 23, 2016 Amazon Alexa is eating the retailers alive Jun 22, 2016 In search for the mythical neutrality among top-tier public cloud providers Jun 18, 2016 In Support Of Gary Johnson Jun 13, 2016 Files and folders: apps vs documents May 26, 2016 Why it makes perfect sense for Dropbox to leave AWS May 7, 2016 JEE in the cloud era: building application servers Apr 22, 2016 Managed IT is not the future of the cloud Apr 9, 2016 LinkedIn needs a reset Feb 13, 2016 In memory of Ed Yourdon Jan 23, 2016 OAuth 2.0: the protocol at the center of the universe Jan 1, 2016 IT departments must transform in the face of the cloud revolution Nov 9, 2015 Banking Technology is in Dire Need of Standartization and Openness Sep 28, 2015 Top Ten Differences Between ActiveMQ and Amazon SQS Sep 5, 2015 We Live in a Mobile Device Notification Hell Aug 22, 2015 On Maintaining Personal Brand as a Software Engineer Aug 2, 2015 Book Review: "Shop Class As Soulcraft" By Matthew B. Crawford Jul 5, 2015 Attracting STEM Graduates to Traditional Enterprise IT Jul 4, 2015 The longer the chain of responsibility the less likely there is anyone in the hierarchy who can actually accept it Jun 7, 2015 Guaranteeing Delivery of Messages with AWS SQS May 9, 2015 The Clarkson School Class of 2015 Commencement speech May 5, 2015 Apple is (or was) the Biggest User of Apache Cassandra Apr 23, 2015 Ordered Sets and Logs in Cassandra vs SQL Apr 8, 2015 Exploration of the Software Engineering as a Profession Apr 8, 2015 What can Evernote Teach Us About Enterprise App Architecture Apr 2, 2015 Microsoft and Apple Have Everything to Lose if Chromebooks Succeed Mar 31, 2015 Where AWS Elastic BeanStalk Could be Better Mar 3, 2015 Configuring Master-Slave Replication With PostgreSQL Jan 31, 2015 Docker can fundamentally change how you think of server deployments Aug 26, 2014 Infrastructure in the cloud vs on-premise Aug 25, 2014 Things I wish Apache Cassandra was better at Feb 12, 2014 "Hello, World!" Using Apache Thrift Feb 24, 2013 Thoughts on Wall Street Technology Aug 11, 2012 Scripting News: After X years programming Jun 5, 2012 Java, Linux and UNIX: How much things have progressed Dec 7, 2010

Java is no longer relevant

May 29, 2022

Why I no longer use Java for backend services



I spent 18 years of my career advocating and using Java for all of my projects. However, in the past six years, my use of Java has dropped to practically zero.



Each new programming language and platform is meant to solve a particular set of problems. The prolonged use of tools that no longer solve relevant problems makes solving contemporary issues harder. When Java first came out in 1995, it set out to solve specific problems that are no longer relevant 27 years later.



Platform independence in 1995 was strategically crucial to any company trying to compete with Microsoft, whose Windows operating system was dominant. By convincing developers to use a toolchain that could produce executable artifacts that could be distributed to many platforms, competing operating systems could gain new applications.



The way Java achieved platform independence was by using the concept of byte-code. The Java compiler never produced the final binary executable for any particular hardware and operating system combination. Instead, it produced byte-code, a higher-level binary code than machine code. This byte-code would then execute in a Java Virtual Machine (JVM) in its final deployment environment. The JVM, in turn, would dynamically translate byte-code into native code at runtime.



The JVM itself had to be installed on the operating system to run Java applications. Initially, all major operating systems enthusiastically embraced it. In theory, if all new applications were built in Java, all operating systems that could run a JVM would automatically be able to run them.



Sun Microsystems (the original company behind Java) built out what they called Abstract Windowing Toolkit (AWT) and later Swing to support platform-independent user interfaces. They built abstractions over most common UI artifacts such as lists, buttons, windows, frames, tabs, dialogs, and pop-ups.



The cracks in the Java-on-the-desktop idea began to form early on. The problem was that Java prevented developers from taking advantage of native operating system capabilities by abstracting GUI artifacts. Desktop Java applications would never look as polished as native, and they would never perform as well either.



Microsoft built their proprietary JVM. When Apple launched macOS X, they initially included support for Java as one of the primary languages and runtime environments for MacOS X applications. Though AWT was part of the JVMs, by promoting their native UI frameworks, both Apple and Microsoft sabotaged the idea of a platform-independent UI.



The growth of Java on the desktop was therefore stunted from the beginning. Today, except for a few niche products such as Integrated Development Environments (IDEs) and legacy enterprise applications still eking out their daily survival, Java on the desktop is effectively dead. IDEs, by their very nature, must be platform-independent and allow developers to use whatever development environment they find appropriate for their productivity. Enterprise desktop applications written in Java could be implemented as full-stack, at least theoretically



Over time, the mistakes made by Oracle, legal battles over JVM distribution, security incidents, and the rise of smartphones and modern web browsers destroyed the idea that platform-independent UIs can be built in Java. As of today, the only user-facing platform still running Java natively is Android, and platform independence means running Java apps on various Android devices — if such a thing is even possible.



Java’s prospects on the servers looked much better. Platform independent networking, concurrency, and distributed computing capabilities proved valuable. As is typical in most situations, a developer could write and test backend code in a platform-independent manner on their computer. They could then deploy their work to the server, which could be a UNIX server. 



Typically a Java server would run a JEE (Java Enterprise Edition) application server. A single application server would run multiple applications at a time. The application components would take the form of servlets and Enterprise Java Beans. The application itself would be packaged as an Enterprise Application Archive (EAR) and deployed to the application server utilizing its command line. It made sense in the late 1990s and the first decade of the 2000s when there was no such thing as a public cloud, on-premise servers were expensive shared resources, and application server licenses were sold by CPU.



JEE application servers were expensive, bloated, and resource-intensive. They also had proprietary features. Rather than being tied to an operating system, Java server components would get linked to an application server. One of the projects I worked on was porting a trading system backend out of WebLogic to run as a simple Java process.



The rise of containers such as Docker put an end to the idea that JVM was the only way to run platform-independent backend code. One of the problems with JVM was that over time, different versions of JVMs became incompatible with one another. So, developers used Docker to control the version of JVM. However, Docker itself raised some questions about the need for the use of Java and JVM at all — if I can run Docker on my development machine, use whatever language I want, and then deploy this Docker container on the server, why do I need a JVM at all?



The decline of on-premise servers and the rise of server-less public cloud put the final nail in the coffin of JEE application servers. If I can deploy my docker containers in the form of AWS Lambda functions or AWS ECS services, I need neither Java nor JEE servers. I can pick whatever language works best for my productivity and my application’s performance. I can write my code once, build a container, and deploy it anywhere I want.



Platform independence was not the only problem Java solved. Java addressed many of the complexities of C and C++. Java streamlined object-oriented programming. Though relevant in 1995 and the first decade of the 2000s, today very few applications have more than 2 levels of class hierarchy and modern languages like Swift, Go, and Rust address complexities of C, C++, and now Java in much better ways.




Final thoughts




Though Java was my primary way of earning a living from about 1997 to 2015, it has long outlived the problems it solved. Java’s issues are being solved now by modern tools like Docker. Except for a few niche use cases, I no longer use Java for my projects.