Cloud computing has proven to be a key driver of several innovative technology trends, including Artificial Intelligence (AI), the Internet of Things (IoT), and more recently, powering work models like the remote and hybrid styles. According to the Thales Data Threat Report of 2022, more than 60% of corporate data is stored in the cloud. And as we go into 2023, we will see that it continues to push technologies such as virtual reality (VR) and augmented reality (AR). It will also play important roles in powering the Metaverse, in cloud-based gaming, and even in the field of quantum computing. With such a key role to play in the progress of technology, here’s a look at the important Cloud computing trends of 2023.
The Top 5 Cloud computing Trends In 2023
Cloud computing makes running computing-intensive applications easier on the finances of an organization because it eliminates the need for investing in complex and expensive infrastructure. Its availability ‘as-a-service’ ensures that companies do not have to invest in hiring and training specialized professionals for projects, but are still able to access the latest technologies.
In 2023, companies will continue to invest heavily in Cloud services to ensure they have unhindered access to innovative technologies that will help increase their efficiency in operations and multiple processes.
1. AI and Machine Learning (ML) Integration With Cloud computing
The integration of AI and ML in Cloud computing will increase in 2023. The Cloud AI Market was valued at USD 5.2 billion in 2020. This is poised to rise to USD 13.1 billion by 2026 which would clock a CAGR of 20.3% between 2021 and 2026. This is a sizable jump and companies will utilize AI and ML technologies for a range of applications. This can be digital asset management, powering virtual assistants, offering reality-as-a-service, enabling cloud-based security, and more. With AI and ML, companies will be able to:
- Increase the automation power of their Cloud computing capabilities.
- Improve on self-learning abilities.
- Advance their data security and privacy protocols.
- Personalize Cloud experiences.
There are several other advantages to using AI and ML in Cloud computing. Here is a look at how it can make a difference.
Decreased Expenses: When an enterprise adopts Cloud computing services, it pays for what it uses from a service provider. This means a company saves on the costs of setting up data centers, hiring and training professionals to manage them, and updating technology regularly. Instead, the funding can be invested in the strategic development and use of AI tools which will accelerate revenues and save on high expenses. Analysis of data becomes more focused as applications can evaluate without human aid and derive usable insights.
Advanced Data Management: In data-centric work, the management of data can be an onerous task. With AI and ML-based applications in the cloud, companies can manage their data better. These applications can help identify, upgrade, organize and provide data insights in real time. With AI tools, unusual activities or patterns can be recognized in advance, ensuring that any threats are well anticipated and addressed. Financial organizations are the largest users of such technologies considering the high-risk environments they operate in.
Intelligent Automation: AI-based Cloud computing allows companies to intelligently automate repetitive and/or complex tasks within a process. This not only increases productivity but also reduces the risk of any errors, all without any human intervention. IT-department workflows can also be managed and monitored with AI and ML. With AI handling all complicated tasks, IT teams are open to managing strategic operations more efficiently.
Access to Advanced Infrastructure: AI applications function at their best when they operate on servers that come with multiple Graphical Processing Units (GPUs). For companies, these GPUs and systems can be an expensive investment. However, when offered as a service, they become affordable, thus helping an enterprise access advanced infrastructure.
Team Integration: When AI combines with Cloud computing it makes an integration with DevOps simpler as it enables easy information sharing between multiple teams and sectors, enhancing efficiency.
2. Utilizing Kubernetes and Docker to Manage Cloud Deployment
The primary advantage of using Docker and Kubernetes is that they provide what is known as a packages software delivery platform called containers. With this, Docker and Kubernetes can handle large-scale Cloud deployment while offering:
- High levels of scalability
- High levels of efficiency
- Automation of Cloud deployment
- A flexible model of resource sharing
- Rapid and cost-effective deployment
The latest versions of Docker come with Kubernetes built-in, allowing it to automate and manage all applications that are in containers that are developed on the Docker platform. Here is what Docker and Kubernetes offer to help a business better understand which platform would work best for them:
- Docker is well known for its ease of scalability and its fast start-up times. Kubernetes offers flexibility and regulates all control applications.
- Docker runs on a single server and Kubernetes has been created to manage server clusters.
- Docker provides users with a client-server architecture. It also has its image format whereas Kubernetes makes use of a master-slave form of architecture and has several image formats.
- With Docker, you can execute a single instance of an application package, while Kubernetes can work multiple instances of an application package.
- Docker works on auto-deploy, running applications within a container. Kubernetes, on the other hand, auto-deploys while managing all containerized applications that are across nodes.
- With Docker, all packaged apps are shipped as portable containers along with all their dependencies. With Kubernetes, deployment is automated and containerized apps are scaled.
- Docker comes with its operating system whereas Kubernetes has the capability of handling several containers over a multitude of machines, in a parallel deployment system.
3. Heightened Focus on Data Security on Cloud computing
A key concern with the large-scale adoption of Cloud computing is data security. There are several causes for a possible data breach – from bugs in the software to human error and more. Here is a look at some of the major challenges that companies will have to deal with:
- Unauthorized persons can gain access to data in the Cloud if some APIs are exposed.
- Security breaches can take place when infrastructure is misconfigured or unsound.
- Data loss occurs for several reasons such as lack of data backup, corrupt software, natural disasters, or data deletion by accident, among other reasons.
Such breaches can be prevented if developers utilize tools like encryption, better access control, and monitoring of Cloud activity.
With the multi-Cloud model gaining popularity, enterprises are at a heightened security risk that only adds to the many complexities of managing several platforms and technologies. Going forward, organizations are going to increasingly focus on advanced and proactive data security strategies.
4. Hybrid Cloud Solutions
- There is going to be an increase in the use of hybrid Cloud solutions. With a private cloud, there is an assurance of higher processing power making it a popular solution. The global hybrid Cloud market was valued at USD 85.3 billion in 2021. This is expected to touch USD 262.4 billion by 2027, with a CAGR of 20.6% during 2021-2027. For a client, the benefits are:
- Access to the best of both private and public clouds
- Increased flexibility
- Improved cost-effectiveness
- Ability to perform critical data processing
Working with multi-Cloud and hybrid Cloud solutions offers an enterprise the ability to customize to suit their specific needs.
- Cloud-based ML-focused AI is a point that we discussed earlier as being a strong trend going forward. Technologies such as AIOps, MLOps, and APM will work towards the optimization of IT performance. Through automation, these tools reduce operational costs and increase efficiency while providing insights in real time about ongoing operations. AI/ML models need to be trained and deployed using the right resources to make the most use of the vast amounts of data they handle.
- Blockchain security measures can easily be integrated into existing Cloud environments. These measures improve data security and provide seamless services. It helps make the storage of data, transactions, and processes safer and increasingly more reliable. When blockchain combines with the cloud, it provides enhanced security and a level of decentralization where authorization and privacy are handled well.
- Advancements in serverless computing and sustainability help with energy conservation protocols, ensuring better cost management. The serverless Cloud is still nascent but is exciting. It is a form of Cloud that is a pay-as-you-use model and scales where necessary, invisibly. It helps with quicker deployment and scaling.
5. Cloud Cost Optimization
With companies eager to use Cloud computing, there is a constant demand for the optimization of expenses on such services. Cloud service providers are going to work harder on creating cost-effective solutions for enterprises that offer not just enhanced efficiency, but also better availability of resources. These improved resources for clients will help with the optimization of cloud-based workloads and ensure a good return on investment. These are the major cloud-cost optimization solutions that will be seen in 2023.
- Better visibility into Cloud spending: The inability to effectively track the use of Cloud resources can add up to bad cost-related decisions. When a company is unable to see its Cloud spend-related data over time or is unable to monitor and manage its Cloud resources, it can lead to an undisciplined use of Cloud capabilities or what is known as a Cloud sprawl. This problem can be resolved by investing in an optimization partner where you can receive incisive views into Cloud expenses across all cost centres. This way all hidden costs related to the Cloud will be transparent and accounted for.
- Better provisioning of Cloud resources: In an ideal situation, an enterprise should be able to predict its usage of Cloud resources. Not doing so can result in unnecessary costs and inefficiency. Over-provisioning is where a company acquires more resources than it needs to run the business. In such cases, resources remain unused despite having been paid for. Investing in customized monitoring of Cloud costs, automatic scaling solutions and right-sizing tools can help prevent over-provisioning of Cloud resources.
- Simplification of billing systems: Bills related to the Cloud can be complex and riddled with unnecessary jargon. These complexities increase where hybrid and multi-Cloud models are used. A Gartner report says that 95% of business and IT leaders find Cloud billing the most confusing element of using public Cloud services. The lack of standardization of billing processes also adds to the confusion. What can help is the use of a Cloud cost optimization partner who will review batches of Cloud bills regularly. This will help in identifying any Cloud usage wastage and can optimize Cloud spending.
- Improvement in Cloud architecture: AWS users are often not aware that AWS Well-Architected Frameworks can help in the creation of secure and scalable workloads for Cloud infrastructure. Not utilizing this leaves applications open to attacks, weak data security, and data loss. A developer’s lack of skill is also exposed to with a badly designed Cloud application which leads to high costs. This happens because applications can be developed using a range of architectures and components from different price ranges. Using a tool like AWS Well-Architected Framework helps in dealing with such issues effectively.
- Collaboration and alignment of Cloud budgeting: When multiple teams using the Cloud are not aligned in their cost optimization approaches, it can lead to a lot of unwarranted costs. Teams often develop and follow their approaches to Cloud resources and costing, and the result is less than optimal situation for the company as a whole. An effective Cloud cost management system that is uniformly applicable across teams in an organization is going to be the way forward.
- Using Cloud automation: Users of cloud-native technologies often adopt Kubernetes or DevOps as methodologies. Automating these aspects of infrastructure is going to be a key trend in 2023, a continuation of the same from this year. Cloud automation reduces human efforts in configuring virtual machines, choosing accurate resources, creating clusters, etc. It brings down infrastructure costs and enhances both security and backup systems. There are several tangible benefits to Cloud automation, particularly for the IT department, freeing up valuable human resources for crucial work.
- Better utilization of spot instances: AWS, Azure, and GCP, among several other Cloud service providers, often sell unused capacity they have on hand at highly discounted prices. These are known as spot instances. An Amazon EC2 spot instance sometimes becomes available for as much as a 90% discount in pricing. AWS can offer a spot instance that gives you up to 6 uninterrupted hours. The only problem is that one can never be too sure how long these offers will last. They can be pulled with as short a notice as a few minutes. Having an automated Cloud helps in such cases, where you can make the best use of a spot instance for as long as the offer lasts and reset seamlessly.
These are the five major trends that the world of Cloud computing is going to witness in 2023. The dynamic nature of markets was seen during the pandemic and the quick adoption of various technologies by organizations worldwide to ensure optimal use of their resources has been evident. Moving to the Cloud is no longer a trend but a necessity. Ensuring that the move is seamless and fruitful in the long term is essential.