There’s no doubt that the Coronavirus mutation and high-tech-enabled vaccine development will be in an evolutionary arms race in 2022. The present digitalization trends in the software development business will continue, with numerous modifications, breakthroughs, and new applications of existing technology. The challenge of foreseeing the future is difficult, but here we have tried to predict the most important Software Development trends for 2022.
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- Cloud-First is the new norm
The public Cloud will continue to replace regional Data Centers in the same way a few large supermarkets have replaced small businesses in the Western world. Enterprises, government, and startups will all use the public Cloud in the next years. The public Cloud is currently the epicenter of digital innovation, and this trend is expected to continue until 2022. The public cloud is also helping to democratize technology.
- Everyone will be concerned about cyber security.
For startups and mid-sized businesses, cyber security is more important than ever. They recognize the need for cyber security, but because of a lack of resources, they are unable to fully execute it. A dedicated security crew can only be afforded by huge corporations. The fact that public cloud suppliers have democratized Cyber Security is one of their most significant advantages. Startups and mid-sized businesses can now easily create highly secure apps by utilizing Public Cloud services.
- Finally, Blockchain expands beyond cryptocurrency
The terms “blockchain” and “cryptocurrency” are frequently used interchangeably. Every time there is a Cryptocurrency counterfeit, Blockchain Technology is chastised. The Distributed Ledger or Blockchain is one of the most revolutionary technologies of the twenty-first century. Although cryptocurrency is the most well-known use of Blockchain, it is much more than that. Blockchain has the potential to transform many aspects of our industry and our daily lives.
- AutoML and No-Code AI will make machine learning more accessible.
Machine Learning (ML) is another disruptive technology that has exploded in popularity in recent years. However, there is a severe scarcity of Machine Learning professionals, corresponding to demand. Furthermore, many businesses desire to use machine learning in a restricted capacity rather than hiring a full-time, high-cost machine learning specialist. AutoML (Automatic Machine Learning) is a new endeavor that aims to automate Machine Learning usage in a restricted fashion without the need for machine learning expertise. You’ll need a machine learning professional for the majority of application cases. However, you may utilize AutoML to supplement machine learning expertise or use AutoML without a machine learning expert in some circumstances.
- Artificial Intelligence: Narrow artificial intelligence will be widely adopted.
Deep Learning (AI), like Machine Learning, is a revolutionary technology that has seen tremendous acceptance and quick growth in the last decade. In 2022 and beyond, AI will witness more use, financing, and innovation. The hunt for “General Intelligence,” in which AI can be as clever (or smarter) than humans, is one of AI’s holy grails. We’re still a long way from universal intelligence. However, “Narrow Artificial Intelligence,” in which AI bots assist/augment humans in a certain (Narrow) field, will be more prevalent. Many non-critical use cases (e.g., Call Center, IT) will witness increased Narrow AI adoption in 2022 when AI agents will aid humans utilizing Narrow AI.
- The Tensor Flow will continue to reign supreme.
There are several AI libraries available, but two stand out: Google’s TensorFlow and Facebook’s PyTorch. In its 2.0 version, TensorFlow rebuilt itself, adding dynamic Graph, Python friendliness, and a slew of other improvements. It also includes Tensorflow.js, which allows users to utilize the AI library in the browser. Tensorflow Lite, another Tensorflow invention, allows users to install Tensorflow on mobile and the web. Tensorflow Extended (TFX) is an end-to-end framework for delivering production machine learning pipelines. Another popular AI package is PyTorch. PyTorch Mobile is also available, allowing users to utilize PyTorch on Android and iOS devices.
- Spark vs. Public Cloud Services for Data-Intensive Computation
As the default Data-Intensive Computation Framework, Apache Spark has almost completely superseded the Hadoop ecosystem. Using the same API, Spark also provides near-real-time Stream processing. Apache Beam has gained a lot of attention in recent years because it provides a unified programming paradigm for defining and executing a data processing pipeline: Batch and Stream. The Apache Beam is implemented by Google’s Cloud Dataflow. Batch processing is also available via Azure and AWS.
- Modern DevOps: Intelligent Observability
Only a few years ago, huge businesses needed to be observable. Observability is critical for modern software development, especially with the rapid emergence of Cloud Native programming and Microservice Architecture. We’ll require telemetry and topology data from our Kubernetes cluster in addition to standard Observability (logging, monitoring, and tracing). We’ll also see a rise in the use of AI in conjunction with a time-series database to create an intelligent Observability platform. In 2022 and beyond, intelligent, Cloud Native observability will continue to increase.
- Python will take the lead
Python’s popularity as a general-purpose programming language has skyrocketed in recent years. Python has finally taken the lead and is now the number one programming language, according to the prominent programming language rating website TIOBE. Python will continue to be the most popular programming language in 2022 since many new developers will likely begin with Python. Before deciding on a programming language.
Conclusions
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