Cloud computing has revolutionized how we store, manage and access data. 2023 has arrived and digital transformation initiatives remain in the fast lane, and if 2023 cloud trends are any indication, there’s no slowing down. Moving to the cloud is no longer an option, as its benefits and new capabilities prove vital for moving forward, especially in an uncertain economy.
Gartner Inc. forecasts that in 2023, worldwide public cloud spending will grow 20.7% to total $591.8 billion, up from $490.3 billion in 2022. The cloud computing market is expected to reach over $1 trillion by 2028. Within a span of 10 years (between 2010 to 2020), the market grew by a massive 635 percent.
Several reasons, such as software bugs, human errors, etc., can lead to a security breach. Data breaches can occur as a result of misconfigurations or insecure cloud infrastructure. Exposed APIs can result in non-authorized personnel gaining access to the cloud data. Data security continues to be a major concern for large scale cloud deployments.
98% of organizations have experienced at least one cloud data breach in the last 18 months. More alarmingly, 67% reported over three cloud data breaches in the same period.
Robust cloud security will continue to be one of the top cloud trends as more and more organizations move their critical data to the cloud and more stringent regulations are put forth to protect it. In 2023, organization will continue to shift to a proactive approach to reduce the risk of costly data breaches, compliance failures and downtime. However, as more companies look to cut costs in the face of a predicted economic recession, the search for innovative and cost-efficient cybersecurity solutions will increase, highlighting the need for managed cloud security services.
Artificial Intelligence (AI) and Machine Learning (ML)
Most experts tout artificial intelligence and machine learning (AI and ML) as crucial technologies for the future of the business. Cloud computing will play a big role in this as most organizations don’t have the bandwidth or resources required to generate training data for machine learning platforms. Gathering data and training algorithms require vast amounts of storage space and computing power that is generally better to rent as-a-service to maximize ROI. It provides organizations with the necessary resources without a huge upfront investment and offers the flexibility to scale up or down, depending on your current needs.
A recent survey stated that the cloud AI market will be valued at $13.1 billion by 2026. This is a massive jump from the value of $5.2 billion in 2020. Companies can use AI and ML with cloud computing for various applications such as digital asset management, virtual assistants, reality-as-a-service, cloud-based security for applications, and much more. Compared to private data centers, public cloud infrastructure has the ample data storage and computing capability that are needed for AI and machine learning applications.
Businesses have come to understand the advantages of diversifying their services across a number of cloud providers. The multi-cloud approach offers a number of advantages, including improved flexibility and security. It also prevents organizations from becoming too tied in to one particular ecosystem. This helps to create redundancy that reduces the chance of system errors or downtime from causing a critical failure of business operations.
With the growing popularity of containerized applications, changes to service levels or more cost-efficient solutions becoming available from different providers, applications can be quickly ported across to new platforms. While back in 2020, most companies (70 percent) said they were still tied to one cloud service provider, reports have found that 84% of mid-to-large companies will have adopted a multi-cloud strategy by 2023, positioning it as one of the year’s defining trends in cloud computing.