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On the role of Distinguished Engineer and CTO Mindset Apr 27, 2025 The future is bright Mar 30, 2025 My giant follows me wherever I go Sep 20, 2024 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 Why you should question the “database per service” pattern Oct 5, 2022 Stop Shakespearizing Sep 16, 2022 Monolithic repository vs a monolith Aug 23, 2022 All developers should know UNIX Jun 30, 2022 Scripting languages are tools for tying APIs together, not building complex systems Jun 8, 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 Best practices for building a microservice architecture Apr 25, 2022 In most cases, there is no need for NoSQL Apr 18, 2022 What programming language to use for a brand new project? Feb 18, 2020 TDWI 2019: Architecting Modern Big Data API Ecosystems May 30, 2019 Returning security back to the user Feb 2, 2019 Microsoft acquires Citus Data Jan 26, 2019 Adobe Creative Cloud is an example of iPad replacing a laptop Jan 3, 2019 The religion of JavaScript Nov 26, 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 What does a Chief Software Architect do? Jun 23, 2018 Facebook is the new Microsoft Apr 14, 2018 Quick guide to Internet privacy for families Apr 7, 2018 Node.js is a perfect enterprise application platform Jul 30, 2017 Design patterns in TypeScript: Chain of Responsibility Jul 22, 2017 I built an ultimate development environment for iPad Pro. Here is how. Jul 21, 2017 Singletons in TypeScript Jul 16, 2017 The technology publishing industry needs to transform in order to survive Jun 30, 2017 Rather than innovating Walmart bullies their tech vendors to leave AWS Jun 27, 2017 Copyright in the 21st century or how "IT Gurus of Atlanta" plagiarized my and other's articles Mar 21, 2017 Emails, politics, and common sense Jan 14, 2017 Windows 10: a confession from an iOS traitor Jan 4, 2017 Collaborative work in the cloud: what I learned teaching my daughter how to code Dec 10, 2016 Don't trust your cloud service until you've read the terms Sep 27, 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 Why I switched to Android and Google Project Fi and why should you Aug 28, 2016 In search for the mythical neutrality among top-tier public cloud providers Jun 18, 2016 Files and folders: apps vs documents May 26, 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 JEE in the cloud era: building application servers Apr 22, 2016 Managed IT is not the future of the cloud Apr 9, 2016 JavaScript as the language of the cloud Feb 20, 2016 OAuth 2.0: the protocol at the center of the universe Jan 1, 2016 Operations costs are the Achille's heel of NoSQL Nov 23, 2015 IT departments must transform in the face of the cloud revolution Nov 9, 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 Your IT Department's Kodak Moment Jun 17, 2015 Smart IT Departments Own Their Business API and Take Ownership of Data Governance May 13, 2015 We Need a Cloud Version of Cassandra May 7, 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 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 Docker can fundamentally change how you think of server deployments Aug 26, 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

Scripting languages are tools for tying APIs together, not building complex systems

June 8, 2022

There are two general categories of programming languages: compiled, and interpreted.



A program written in a compiled language must first be converted into native machine code to run. This step is called compilation.



A program written in an interpreted language does not need to be converted into native code. The interpreter parses the program and executes it in real-time. It is possible to use the interpreter interactively as a calculator or debugger.



In some cases, the interpreter may store the program in the form of intermediate code in memory and compile parts of it into native code in-real-time in a process called Just-in-time Compilation.



The interpreter may save the intermediate bytecode for faster loading times during future execution as an optimization. Python, for example, saves *.pyc files with compiled bytecode of the imported modules. 



Similarly, though technically a compiled language, Java produces *.class files with bytecode. Java is not a strictly interpreted language and is outside of this post's scope.



An interpreted language is typically a higher-level language. It may explicitly represent data structures, such as lists, tuples, and dictionaries (maps). It may also have higher-level abstractions over algorithms. It does not have to be loosely typed, though most interpreted languages are.



Under most circumstances, a program written in an interpreted language is slower than compiled. However, program performance needs to be balanced against developer productivity. The very purpose of an interpreted language is to hide complex algorithms from the developer and make programs available to run immediately after every change. A program being executed is in the same language that it is written in.



To paraphrase Mel Conway, an interpreted language is an application language, not algorithm (aka platform ) language. Interpreted languages are best used as a "glue" that ties algorithms and APIs together — not to implement algorithms.



There is a reason why many modern interpreted languages are also referred to as "scripting." Scripting is automating existing APIs and algorithms and combining them into new APIs and algorithms. Scripting is about controlling or orchestrating existing tools, APIs, and algorithms.








A reader may rightfully ask, "Oleg, what are you getting at?"



What makes me think of these things early in the mornings is the proliferation of JavaScript as an enterprise application language. I believe using JS as a hammer to solve every problem will hound enterprise IT for decades.



JavaScript is an interpreted scripting language. It's a tool for tying things together — DOM objects on a web page and APIs.



I love JavaScript as a tool for quickly building simple apps that tie cloud APIs together.



I'm not too fond of JavaScript for the religion it cultivates among its fans who are in denial about its limitations and feel the need to use it to solve every problem, however inappropriate it might be for the task.