#bytebytego

ByteByteGo nails another "a picture is worth a thousand words" infographic. This one highlights some key differences between traditional SDLC, DevOps and emerging NoOps.

In a traditional software development, code, build, test, release and monitoring are siloed functions. Each stage works independently and hands over to the next stage.

DevOps, on the other hand, encourages continuous development and collaboration between developers and operations. This shortens the overall life cycle and provides continuous software delivery.

NoOps is a newer concept with the development of serverless computing. Since we can architect the system using FaaS (Function-as-a-Service) and BaaS (Backend-as-a-Service), the cloud service providers can take care of most operations tasks. The developers can focus on feature development and automate operations tasks.

NoOps is a pragmatic and effective methodology for startups or smaller-scale applications, which moves shortens the SDLC even more than DevOps.

ByteByteGo | Newsletter/Blog

From the newsletter:

Imperative Programming Imperative programming describes a sequence of steps that change the program’s state. Languages like C, C++, Java, Python (to an extent), and many others support imperative programming styles.

Declarative Programming Declarative programming emphasizes expressing logic and functionalities without describing the control flow explicitly. Functional programming is a popular form of declarative programming.

Object-Oriented Programming (OOP) Object-oriented programming (OOP) revolves around the concept of objects, which encapsulate data (attributes) and behavior (methods or functions). Common object-oriented programming languages include Java, C++, Python, Ruby, and C#.

Aspect-Oriented Programming (AOP) Aspect-oriented programming (AOP) aims to modularize concerns that cut across multiple parts of a software system. AspectJ is one of the most well-known AOP frameworks that extends Java with AOP capabilities.

Functional Programming Functional Programming (FP) treats computation as the evaluation of mathematical functions and emphasizes the use of immutable data and declarative expressions. Languages like Haskell, Lisp, Erlang, and some features in languages like JavaScript, Python, and Scala support functional programming paradigms.

Reactive Programming Reactive Programming deals with asynchronous data streams and the propagation of changes. Event-driven applications, and streaming data processing applications benefit from reactive programming.

Generic Programming Generic Programming aims at creating reusable, flexible, and type-independent code by allowing algorithms and data structures to be written without specifying the types they will operate on. Generic programming is extensively used in libraries and frameworks to create data structures like lists, stacks, queues, and algorithms like sorting, searching.