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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

There is no such thing as one grand unified full-stack programming language

May 27, 2022

I was thinking recently about Mel Conway's two lessons regarding programming tools:




Lesson 1. The developer's productivity is best served by a tool set whose behavior throughout the development cycle is strictly consistent with the principle that the program being executed is available without delay after every change and is identical to the source program entered by the developer. (That is, there should be no hint of the existence of a translator.)

Lesson 2. Application languages and algorithm languages are different creatures. The job of a productive application language is not to describe algorithms, but to hide them.




Conway discovered these lessons based on his experience in early computing. Nevertheless, they still hold today.



They say that software architects gravitate towards a particular specialization or a specific flavor of architecture they tend to implement, and the patterns they learn early on trend well into their late careers. In my case, be it trading systems, cloud-based CRM, ERP, or HCM, my work revolves around building one kind of SaaS or another. As a result, the architecture I gravitate to can best be described as a microkernel.



In microkernel architecture, the application is split into two general areas. One is what Conway describes as the algorithms, though I prefer to call it platform. The other is application implemented as plugins for the platform.



The role of the platform is to meet architecture requirements, such as security, scalability, deliverability, testability, reliability, and various other "-ilities". Aside from the primary goal of meeting business requirements, the plugins for the platform support developer productivity needed to evolve business processes rapidly.



In a modern SaaS, the microkernel platform provides the APIs to perform tasks in the application. The plugins are a glue that ties the APIs into meaningful and rapidly evolving business processes. 



A trading system may be implemented as a microkernel that provides the basic functionality to execute trades -- and plugins implement customizable trading algorithms. An HCM microkernel may offer a set of APIs required to manipulate HR workflows and run payroll, with pluggable components describing business processes. Amazon's Alexa architecture can be viewed as a platform offering basic functionality needed to implement and run plugins called skills.



The toolchains, including the programming languages required to build the platform vs. the plugins, do not have to be the same. The developer skillsets needed to work on the platform vs. the plugins don't need to overlap.



As Conway would say, a productive application language must offer a quick turnaround. Developers should be able to execute their work without delay after every change, and the code being performed should be identical to what they've written. Conceptually, this idea tends to favor interpreted languages with REPL such as Python or JavaScript and rules out the use of any transpiler such as TypeScript1



In the past, I implemented two styles of the mechanisms for plugins. One was for a trading system implemented as a Groovy-based DSL to describe trading algorithms. Another was an ERP SaaS platform that supported JavaScript plugins, deployed as AWS Lambda functions behind the scenes. The AWS Lambda-based approach checks many architecture requirements boxes for projects I am working on these days, and it is my preferred approach.



The platform language must meet a different set of goals. Though developer productivity is essential, it must also meet architecture requirements. The platform language must be capable of expressing modern systems concepts such as networking, object serialization, and multi-core processing. In the past, my preference was Java. These days, I love Go.



Meeting the architecture requirements of the platform and developer productivity does not have to be mutually exclusive. However, one should not discount the difference between application developer productivity and platform developer productivity. Whereas the goal of a platform developer is to build reliable infrastructure code, the goal of an application developer is to develop and update business process logic quickly.




Some final thoughts




There is no such thing as one grand unified full-stack programming language or a full-stack developer using a single tool. As a SaaS software architect, I certainly do not see some holy grail from my vantage point. We need to use tools that best meet the needs of the task -- and the needs and the skills of developers who use them. 









  1. When I talk about my distaste for transpilers, I do not generally include web application front-ends. Front-end development nuances are outside of the scope of this article. ↩︎