What are the most important software development trends to watch in the next five years?

I think that there will be a combination of traditionally generated applications and short-lived conversational applications that become almost like streaming services that are extremely personalized and low scale. These can find, link/integrate and act upon stimuli that are important to individuals with a very small footprint and subsequent low cost.

Below trends are strong contenders for shaping software development from now and beyond: 1) Cloud focus is solidifying, making cloud-native development a crucial skill. 2) AI/ML is on an upward trajectory, hence, their integration into software development will become a standard norm. 3) Low-code/no-code is gaining momentum and making software creation more approachable, and that trend is likely to continue. 4) Modern languages like Python, Kotlin, Go, etc. will be dominant forces and are unlikely to be dethroned soon. 5) Security remains paramount. DevSecOps practices will be essential as cyber threats evolve and secure development becomes even more critical. Prepare to empower the future!

As AI usage expands, there will be an escalating emphasis on guaranteeing the ethical development and deployment of AI systems, aiming to prevent biases and minimize potential harm to individuals and society.

Even now, everyone understands the benefits and uses AI systems. The following areas will be popular in the field of AI in the near future: 1. Explainable AI (XAI) and Interpretable ML (IML). Creating models with clear explanations for better transparency. 2. AI-powered chatbots and virtual assistants. Future development and improvement of conversational interfaces. 3. AI-driven Development (AIDD). Automation and assistance of SDLC 4. AI for DevOps and cloud infrastructure. Automation, predictive analytics, and streamlined development. 5. AI for security. Developing techniques to secure AI models against vulnerabilities and manipulation. 6. Quantum Computing. Exploring the integration of AI with quantum computing.

I think that Cloud Native Development will continue to grow and be a need. The needs of applications are changing rapidly and legacy monolithic models tend to bottleneck innovation. Cloud Native Development is more than just moving your workloads from your datacenter to a public cloud provider. It is actually refactoring your application to scale on the cloud based on needs. This will also integrate other concepts such as edge computing and AI. How do you ensure that your application can serve a device in someone's pocket? Apps need to be built to work on the cloud, not simply moved to the cloud.

The following areas are popular and most likely will be trends in the near future in the field of Cloud Native Development: 1. Serverless computing. More integrations with serverless technologies make code development simpler and faster. 2. Kubernetes and containers. Management and integration are expected to become clearer. 3. Microservices architecture. The use and integration are expected to continue growing. 4. DevOps and CI/CD. Automation and AI will speed up software delivery and teamwork. 5. Observability and monitoring. Smarter tools will be developed for spotting and fixing issues in complex systems.

Cloud native way of building and delivering softwares would definitely grow in multiple folds simply for the fact of its benefits. There is no better way than cloud native development to build top quality software product which are resilient, easy to scale, definitely more cost effective.

I agree with Inderpreet to an extent but obviously cloud computing companies will attempt to get you to lock into their services. I also understand the pros of multi-cloud but when they all offer the same services (with different names) it kind of makes sense to me for a company to specialize in one of the cloud environments and not be deployed across several.

I expect a huge change in the roles people will take in near future in every small, medium and large scale Industries. Dev, QA, DevOps, LiveOps will come to single team where everyone is accountable. It starts with being shipping app with Cloud Native architecture instead of migration.

As we embrace the rise of no-code and low-code development, the necessity for proficiency in specific programming languages is gradually diminishing. The trend is moving towards leveraging AI applications that can interpret instructions in natural language to generate code across various programming languages. Despite these advancements, the ability to conceptualize ideas, understand requirements, and integrate them into end-to-end (E2E) products or solutions remains an invaluable skill. This underscores a shifting focus in software development: while technical coding skills are becoming more accessible, strategic thinking, creativity, and the ability to envision comprehensive solutions are skills that will continue to be highly prized.

Anticipating a surge in adoption, I envision its widespread effectiveness across cloud services. Personally, I've been utilizing it extensively for serverless services, low-code ETL jobs, and enhanced infrastructure maintenance. The emphasis will be on prioritizing security and compliance, particularly with specialized offerings tailored for domains like healthcare. Seamless integration between existing solutions and low-code capabilities remains a key highlight.

Quick and Easy: It allows fast creation of basic apps, similar to using templates. Limited Flexibility: While user-friendly, they're not suitable for unique or complex projects. Developer's Role: Important for developers to recognize when to use these platforms and when traditional coding is necessary for more customized solutions.

No code platforms can leverage new ux paradigms that move away from interfaces that currently make more sense to coders that business users. I see no code as becoming more app based and less of a studio type of canvas.

Edge computing is a very promising area and will most likely be one of the main trends in software development in the near future. Areas of growth expected to include: 1. Integration with AI and ML. Increasing use of AI and ML directly on edge devices for faster decision-making. 2. 5G integration. The high-speed, low-latency capabilities of 5G will enhance the effectiveness of edge computing applications. 3. Security solutions. Focus on developing advanced security measures for edge devices and networks. 4. Decentralized cloud architectures. The continued shift to decentralized cloud setups for improved efficiency and responsiveness in data processing. 5. Edge frameworks. Huge improvements in edge frameworks to simplify development.

As IoT devices proliferate, edge computing will grow, processing data closer to where it is generated. This reduces latency and bandwidth use, enhancing real-time data processing and decision-making.

We are living in the fast paced technology age where new trends are emerging every year. To stay informed and not to be behind, the software professionals must keep up to date with the technology trends. Some of the key technologies to watch are: 1. Containerization and Microservices Architecture 2. Cybersecurity will always be in demand 3. Smart contracts and decentralized applications (DApps) are areas where blockchain will make an impact. 4. Serverless computing is gaining popularity for its scalability and cost-effectiveness. 5. Augmented Reality (AR)and Virtual Reality (VR) technologies 6. Low-code/no-code platforms enable business users to participate in application development, reducing the reliance on professional programmers.

Edge computing is like giving your devices superpowers to handle tasks locally, speeding things up and reducing delays. It's great for real-time actions like gaming or smart cars. As a developer, you're the tech wizard, creating applications that work on these local devices and ensuring they connect well with the cloud. But remember, with great power comes great responsibility: you've got to ensure these superhero gadgets are reliable, can handle lots of action (scalability), and are secure against villains (security threats). So, get ready to innovate and secure the edge!

Edge Computing is like putting small, smart computers right where the action is, like in your game console or your home's smart speakers, instead of relying on big, distant servers. This makes things go more quickly and smoothly, which is great for cool tech that needs to make quick choices, like VR games or smart cars. It's like having a smart assistant right next to you instead of having to wait for someone far away to give you advise. As a developer, your job would be to make apps for these smart assistants that make sure they can do their jobs fast and connect to the main servers when they need to. You have to keep all the balls in the air at the same time, like when you juggle.

As AI/ML are in trend. We will soon get the need to get those training set computation/evaluation in real time. Then we will definitely looking at Quantum computing for solutions. Data is getting generated in Zettabytes/day. As we will have more AI/ML and more devices this data will see exponential growth and in order to deal with growing data, we will need to look way to faster computing , hence Quantum Computing.

Quantum computing is the most revolutionary area that can turn everything upside down in many areas of human life. The most important aspects to keep an eye on for the near future are: 1. Quantum hardware. Achieving computational boundaries and implementing robust error-correction techniques for stable qubit operations. 2. Quantum software tools. Development of efficient algorithm, error identification, and correction in quantum code. 3. Quantum cloud computing. Providing quantum resources through cloud platforms (QaaS). 4. Hybrid quantum-classical systems. Solving optimization challenges through a combination of quantum and classical approaches. 5. Quantum machine learning (QML). Enhancing neural networks with quantum capabilities.

Quantum computing, while a revolutionary and promising field, is likely to remain largely within academic circles for the next decade or so. Similar to the concept of nuclear fusion, it's an area brimming with potential but also facing many unresolved fundamental issues. While we can expect some notable breakthroughs in the years to come, the prospect of using quantum computers in our homes or accessing quantum computing power through services like AWS or Google Cloud seems distant. This technology, intriguing as it is, still has a long journey ahead before it becomes a common tool in our everyday lives.

In my experience, it's beneficial to start with quantum algorithms like Shor's or Grover's to grasp the potential of quantum computing. An example of a quantum breakthrough is the development of quantum key distribution for cybersecurity, showcasing how quantum principles can enhance security. I agree that there's a steep learning curve, but engaging with quantum computing communities and contributing to open-source quantum projects can be an excellent way to build expertise and stay ahead of the curve."

Quantum Computing is the most underrated technology of our time, this can break unimaginable boundaries and I think we need to focus on it more. Though, it will come with a cost or reorganize various sectors eg. Data encryption and security, storage, hardware. There will be reforms in our world since we need better and improved technology to work with quantum computing. But as it always happens, with new technology coming new changes and we human live on changes and we have mastered it. Waiting for new breakthroughs in coming time.

Slightly different topic: AI is getting better every day. But there's a funny thing that might happen. People might start to depend too much on AI and stop using their brains as much. This could make it hard to find really talented people who are good at solving problems. If AI takes over a lot of jobs, people who don't have special skills might become more common in the job market. The skill everyone will want? Problem Solving. If AI does all the work, what will happen to our brains? It's just a thought to consider with a smile. 😄 If you are reading this, here are three most demanding skills of the future: - Problem Solving - Writing - Prompt Engineering (Not everyone can guide the AI very well)

What I would like to see is a normalization in the trends. Everything is hyped and pushed to the limits and then thrown out of the window in a few years. Which technology, method, process, etc. does really make us faster and more efficient? Start using tools and technology where they make sense and not because you need them on your CV. And please make Agile great again. What I am currently observing in various companies, is very far away from the original idea of Agile and Extreme Programming.

- AI Augmented Development: AI integration in development tools will significantly enhance coding efficiency and error detection, revolutionizing the traditional development lifecycle. - Platform Engineering: Emphasis on creating internal development platforms to streamline workflows, improve productivity, and maintain consistency across software products. - Cloud Development Environments: Shift towards fully cloud-based development environments, offering scalability, collaboration, and reduced infrastructure overhead. - LLMOps (Large Language Model Operations): The rise of operations focusing on the deployment, maintenance, and scaling of large language models, catering to the growing AI-driven development landscape.

With the rapid rise of AI/ML, Low Code No Code should get smarter and make application development even faster and easier. Secondly, building on top of the micro services architecture and platforms, interoperability between platforms like ONDC, banking, payments etc across countries and continents will increase leading to a more connected ecosystem.