For many companies, adopting cloud computing technologies has become an excellent opportunity to keep a competitive edge in the market. With the help of cloud computing development services, businesses can significantly increase customer experience, cut down infrastructure costs, and much more. All this has resulted in the massive adoption and growth of cloud computing over the past several years.
According to Markets and Markets research, the global cloud computing market, estimated at $545.8 bln in 2022, is expected to increase further, reaching $1,240.9 bln by 2027 and growing at a CAGR of 17.9% in the forecasted period. Obviously, the popularity of cloud technology will only be expanding in 2023 with new innovations emerging in this field. Meanwhile, we will have a look at the most prominent cloud computing trends in 2023.
Deploying to the Edge
Latency, bandwidth, and security are becoming more dominant issues year by year. That’s because the number of IoT appliances and devices connected to the Internet are rapidly growing as well as the computing speeds for AI-based and robotics technologies. This encourages Internet providers to search for new ways and frameworks to offer their services. One of the effective solutions is to shift to edge computing technology. So, what is edge computing?
Edge computing is a new emerging cloud computing framework. It allows the processing and storing of data on the localized data centers that are located near their users’ networks, instead of sending it to remote data centers. Such a combination of cloud and edge computing results in a wide range of benefits for cloud users and cloud providers, including:
- Increased data processing speed
- Low to no latency in response times
- Lower bandwidth utilization
- Increased data security
- Enhanced storage capability
Hybrid and Multi-Cloud
Cloud computing can cover a wide range of business cases. Therefore, new cloud models appear on the market. The most popular are hybrid cloud and multi-cloud infrastructures.
Hybrid cloud is the use of several cloud environments at a time such as public, private, or dedicated clouds. By merging several models, companies can gain the best of each. For example, while public clouds provide more accessible services for various users, e.g. customers or business partners, private clouds ensure stronger protection of a company’s inner data.
Multi-cloud infrastructure presupposes the use of several cloud providers in order to better distribute the workload across multiple environments, increase security, improve risk management, and much more. The use of several clouds helps companies become more flexible, reduce system downtimes, and preserve more control over their digital solutions.
Low-Code and No-Code Cloud Services
Building a business application is a part of an effective business development strategy for many companies today. While not every company can afford to spend many resources and time on developing a solid digital solution, there are alternative ways like using low-code or no-code development platforms. The low-code or no-code services are offered via the cloud, meaning that their users don’t need to build any powerful development environments themselves or code.
Low-code and no-code applications are a good starting point for small and medium-sized companies, although they come with their own limitations. When creating low-code or no-code solutions, users can simply drag and drop the required pre-built components, composing them into a final application. Another great point about low-code or no-code solutions is that they don’t require any additional coding to deploy. It means that the cloud platforms handle the deployment process themselves, providing the users with the resulting solutions fast and easily.
AI and ML Intelligence
Artificial Intelligence and Machine Learning (AI/ML) are the two powerful technologies that help businesses better manage their data, reveal data insights, and optimize workflows. Therefore, they’re implemented for building various kinds of digital solutions. Meanwhile, AI/ML requires a lot of computational power, storage space, and high technical skills to utilize them. That’s where cloud computing services come as a great help.
Cloud computing services form the environment for effective AI/ML implementation. The cloud provides the necessary space to store complex code and the computational power to execute it. Moreover, by offering low-code and no-code software development models for AI/ML, cloud services democratize the use of AI/ML. They make the technology more accessible for the businesses that can’t afford to have their own AI/ML development teams or invest in the development of expensive infrastructure for building AI/ML-based solutions.
Clouds can facilitate software development, deployment, and hosting in so many ways. One of them is using serverless computing. Serverless cloud services are a cloud model where software developers don’t have to handle server provisioning or infrastructure management themselves, the cloud addresses all the server-related issues instead.
Many businesses already actively implement serverless computing for their digital solutions and gain multiple benefits from that:
- The services are provided in simple pay-as-you-go packages and businesses don’t have to consider the storage and bandwidth of each cloud to host their digital solutions.
- Server management is handled on the cloud side and software development teams don’t have to worry about the server infrastructure.
- Serverless platforms are simply scalable, they can adjust to increasing bandwidth or application requirements automatically.
- Serverless architectures handled by the clouds minimize the risks of lengthy downtimes or serious back-end failures.
Kubernetes and Blockchain
Cloud platforms work great for handling complex technologies such as AI/ML, IoT, or Blockchain. That’s why more and more companies prefer using clouds to on-premise hosting when it comes to working with sophisticated tech solutions.
It’s becoming more common when businesses start deploying Blockchain technology to the cloud as it’s much easier to store and scale it in the cloud infrastructure. For that, software developers often opt for Kubernetes systems that are offered as-a-service by many cloud providers. With these services, software specialists can simply scale, balance, and monitor Blockchain systems and manage them with a set of various tools from command-line interfaces, to web co