For businesses and developers alike, staying abreast of these trends is not just beneficial-it’s essential for remaining competitive and successful. In this article, we explore the key software development trends expected to make a significant impact in 2024.
General principles of software engineering in 2024
Artificial intelligence and machine learning integration
AI and machine learning are not buzzwords anymore; they’re integral components of modern software development, setting new standards for functionality and performance.
Blockchain beyond cryptocurrencies
Blockchain is finding its footing beyond cryptocurrencies. The surge in mobile applications prioritizing enhanced security and superior quality has led to an increased adoption of blockchain-based apps.
The essential characteristics of Blockchain-Oriented Software (BOS) systems include:
- Sequential transaction logging: BOS records transactions in a chronologically arranged log consisting of interconnected blocks set up through a consensus algorithm.
- Public-key cryptography: The transaction process in BOS is based on public-key cryptography, ensuring secure and verifiable transactions.
Multi-runtime microservices
Microservices architecture is a method of developing software applications as a suite of small, independently deployable, and modular services, each running in its process and communicating with lightweight mechanisms, often an HTTP-based API.
The primary advantage of a multi-runtime microservices architecture is its ability to leverage the strengths of various technologies and platforms.
Cybersecurity at the forefront of 2024
The increasing sophistication of cyber threats has made security a critical aspect of software development for 2024. Integrating advanced security protocols and utilizing AI for threat detection are becoming standard practices. The focus is shifting from reactive to proactive security measures:
- Emphasis on DevSecOps: Companies are integrating security into their DevOps processes, creating a culture where security is a shared responsibility among all stakeholders. This approach ensures that security considerations are an integral part of the entire software development lifecycle.
- Focus on secure code practices: There’s an increasing emphasis on training developers in secure coding practices.
Sustainable software development
Green computing and sustainable software practices are gaining attention as environmental concerns grow.
Key aspects of sustainable software development include:
- Software optimization: Streamlining code to reduce energy use and improve performance.
- Deployment: Using resources only as needed, like lazy functions and cloud-based applications, to minimize energy waste.
- Integrations: Reducing data processing between systems to avoid unnecessary data usage.
- Data size: Using smaller-sized media where possible to reduce storage and processing needs.
- Refactoring: Regularly updating software to remove outdated or unused features.
- Avoiding third-party components: Reducing reliance on large external components that consume more resources.
Computing
In the coming year, we anticipate advancements in key computing areas: Function-as-a-Service, cloud and edge computing, and most notably, quantum computing.
Serverless computing (FaaS)
Serverless computing, or Function as a Service (FaaS), is on the rise, with AWS Lambda, Azure Functions, and Google Cloud Functions leading the field. FaaS allows developers to build and run applications and services without managing infrastructure, leading to more efficient and cost-effective development processes.
- One notable example is Netflix utilizing AWS Lambda for various purposes within its streaming platform. Netflix leverages Lambda for tasks like encoding videos, handling user authentication, and managing backend processes.
- Spotify utilizes Google Cloud Functions to handle various backend tasks within its music streaming platform.
- IBM’s subsidiary, The Weather Company, uses IBM Cloud Functions to process and analyze large volumes of weather data. Serverless functions enabled them to perform real-time data processing, generate forecasts, and deliver personalized weather alerts to users based on their locations without the need to manage the underlying infrastructure.
These FaaS solutions, characterized by event-driven architecture, automatically trigger execution in response to requests and adjust resource use as needed.
Expansion of cloud computing
Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform expand their services, providing more advanced analytics, machine learning capabilities, and better security features.
This motivates companies to migrate to the cloud for better data management, enhanced collaboration, and improved security.
Surge of edge computing
Edge computing is an IT architecture that processes client data at the network’s edge, as close to the source of the data as possible. By bringing computation closer to data sources, edge computing reduces latency and enhances real-time data processing capabilities.
In healthcare, edge computing ensures data privacy and enables AI-based real-time monitoring and analysis of the patient’s condition. Edge computing is crucial for the adoption of smart grids, helping enterprises manage energy consumption efficiently.
Python dominance
Python remains a dominant programming language, favored for its simplicity, versatility, and robust library support.
Application development
In the world of applications, significant trends include the broader adoption of low-code and no-code platforms, advancements in cross-platform development, and the increasing use of progressive web applications.
Rise of low-code and no-code platforms
A key factor in the rising popularity of PWAs (Progressive Web Apps) among developers is their platform independence. This eliminates the need for creating separate apps for mobile, tablet, and desktop.
Cross-platform applications offer multiple advantages:
- Consistent user experience: Cross-platform applications have a uniform look and feel across different platforms, enhancing user familiarity.
- Shared codebase: Code reusability and efficiency in development
- Resource efficiency: Requires fewer resources and a smaller development team.
