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The future is bright Mar 30, 2025 On Amazon Prime Video’s move to a monolith May 14, 2023 One size does not fit all: neither cloud nor on-prem Apr 10, 2023 Some thoughts on the latest LastPass fiasco Mar 5, 2023 Comparing AWS SQS, SNS, and Kinesis: A Technical Breakdown for Enterprise Developers Feb 11, 2023 There is no such thing as one grand unified full-stack programming language May 27, 2022 Which AWS messaging and queuing service to use? Jan 25, 2019 Using Markov Chain Generator to create Donald Trump's state of union speech Jan 20, 2019 Adobe Creative Cloud is an example of iPad replacing a laptop Jan 3, 2019 Facebook is the new Microsoft Apr 14, 2018 Leaving Facebook and Twitter: here are the alternatives Mar 25, 2018 Rather than innovating Walmart bullies their tech vendors to leave AWS Jun 27, 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 Online grocers have an additional burden to be reliable Jan 5, 2017 Windows 10: a confession from an iOS traitor Jan 4, 2017 What I learned from using Amazon Alexa for a month Sep 7, 2016 Why I switched to Android and Google Project Fi and why should you Aug 28, 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 What can we learn from the last week's salesforce.com outage ? May 15, 2016 Why it makes perfect sense for Dropbox to leave AWS May 7, 2016 Our civilization has a single point of failure Dec 16, 2015 IT departments must transform in the face of the cloud revolution Nov 9, 2015 Setting Up Cross-Region Replication of AWS RDS for PostgreSQL Sep 12, 2015 Top Ten Differences Between ActiveMQ and Amazon SQS Sep 5, 2015 What Every College Computer Science Freshman Should Know Aug 14, 2015 Ten Questions to Consider Before Choosing Cassandra Aug 8, 2015 Big Data Should Be Used To Make Ads More Relevant Jul 29, 2015 Book Review: "Shop Class As Soulcraft" By Matthew B. Crawford Jul 5, 2015 Attracting STEM Graduates to Traditional Enterprise IT Jul 4, 2015 Smart IT Departments Own Their Business API and Take Ownership of Data Governance May 13, 2015 Guaranteeing Delivery of Messages with AWS SQS May 9, 2015 We Need a Cloud Version of Cassandra May 7, 2015 The Clarkson School Class of 2015 Commencement speech May 5, 2015 Building a Supercomputer in AWS: Is it even worth it ? Apr 13, 2015 Ordered Sets and Logs in Cassandra vs SQL Apr 8, 2015 Microsoft and Apple Have Everything to Lose if Chromebooks Succeed Mar 31, 2015 Where AWS Elastic BeanStalk Could be Better Mar 3, 2015 Trying to Replace Cassandra with DynamoDB ? Not so fast Feb 2, 2015 Why I am Tempted to Replace Cassandra With DynamoDB Nov 13, 2014 Infrastructure in the cloud vs on-premise Aug 25, 2014 Cassandra: a key puzzle piece in a design for failure Aug 18, 2014 Cassandra: Lessons Learned Jun 6, 2014 Things I wish Apache Cassandra was better at Feb 12, 2014

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. ↩︎