2022 has been a remarkably successful year for cloud consumption worldwide. According to Flexera’s State of the Cloud report, presently 53% of small to mid-sized businesses are spending more than $1.2 million annually on the cloud. It’s a sign of good things to come and that we’re well on our way to widespread adoption of cloud technologies. The rising popularity of the cloud has already led to significant developments in key areas, including cloud migration, data analytics, self-driving cars, smart appliances, Cloud of Things (CoT) and more. Let's look at some of the more exciting cloud developments we can expect in the coming months.
1. Growing adoption of serverless computing
Serverless computing is a development model for cloud-native applications where you can provision backend services and infrastructure as per your usage. The service can scale automatically, eliminating the need to reserve any bandwidth, servers or storage capacity. The developers simply write and deploy the code in containers which are then managed by the cloud service providers (CSPs); this includes scaling and management of the infrastructure, security, monitoring, maintenance and more.
So, how is it different from traditional cloud computing models?
For most cloud computing setups under the infrastructure-as-a-service (IaaS) model, developers must pre-provision the server components remotely. Even with automatic scaling of resource utilization, the users must account for spikes in traffic when renting server space. That’s exactly what serverless infrastructure is trying to change; you only pay for the resources you use. The CSPs will dynamically allocate resources for your application when an event triggers the application code to execute. Once the execution stops, the resource usage scales back to zero; in other words, the developers never have to pay for idle capacity.
It’s ‘serverless’ from the developers’ point of view because the responsibility can be completely offloaded to the CSPs. It's a significant functional and quality of life upgrade and we expect it to pick up more steam heading into 2023.
2. Edge computing as a parallel to cloud computing
Edge computing is an emerging computational technique that processes data closer to the source. Because edge computing takes place closer to where the data is being generated, there is little to no latency, allowing users to process and respond to greater volumes of data in real time. Gartner predicts 75% of enterprise-generated data will be created and processed outside traditional data centers or the cloud by 2025. In fact, we can already see the effects of edge computing in various real-life use cases like self-driving cars, healthcare systems, and automated retail and manufacturing equipment. Because edge computing quite literally lives on edge devices like PoS (Point of Sale) systems, IoT (Internet of Things) devices and sensors, and doesn’t need a separate network, it can respond to more immediate and proactive situations.
What does this mean for cloud computing?
It means we can slowly shift from to a hybrid computational model where the workload is shared between edge computing and cloud computing. With 5G networks bringing even more speed and stability to edge devices, we can task edge computing to reduce data complexity by moving processing closer to the network edge. In exchange, cloud computing and AI/ML can continue analyzing colossal amounts of enterprise data to deliver actionable insights.
3. Large-scale deployment of containerized applications
More and more organizations are waking up to the benefits of containerized applications when it comes to reducing migration complexity, promoting reusability and increasing efficiency. As standalone and decoupled packages of application code, containers are irreplaceable drivers of innovation in the cloud. A report by Red Hat revealed 39% of respondents were using containers in the public cloud, with another 25% and 36% using containerization in on-premises and hybrid cloud environments, respectively.
Container technology allows code to run on any infrastructure, leading to greater resilience, portability and storage orchestration than traditional virtual machines. It combines effortlessly with DevOps, AIOps and edge computing to enable real-time computation of large volumes of data without congesting the cloud architecture. Containerization is the future, and as the leading platform and engine for container orchestration, Kubernetes will feature more prominently in managing cloud deployments going forward.
Ultimately, deploying containers requires considerable technical expertise. But with businesses developing a deeper understanding of containerization, we are expecting to see a rapid growth in deployment of containerized applications.
4. 5G as a catalyst for cloud gaming
5G’s extremely fast networking speed might be the push that cloud gaming needs to finally take off in 2023. Based on research done by Omdia and ABI Research, inCode Consulting expects cloud gaming to reach 99 million subscribers over the next decade, with 67% of them using 5G-enabled devices. This opens up a tremendous opportunity for service providers, with the primary obstacles to large-scale adoption being latency and network stability.
As we inch closer to widespread availability of 5G networks, service providers can use the 5G network slicing framework to reduce latency by delivering a minimum guaranteed bitrate, spectrum allocation and consistent bandwidth. With 5G-enabled edge computing, service providers can also reduce any input lag between the user’s commands and the game’s response time, significantly improving the cloud gaming experience. Triggered by a new wave of 5G-led digital enablement, we expect cloud gaming to unlock unique revenue streams for service providers.
5. Artificial intelligence and machine learning to further empower cloud computing capabilities
Building and maintaining individual AI infrastructure is a complex and cost-intensive task requiring high computing power, bandwidth, and storage. However, cloud access has made it easier for businesses to experiment with AI/ML functionalities by lowering the technical complexity and overhead costs. Hyperscale cloud providers are continuously innovating their artificial intelligence and machine learning capabilities, and we are already seeing the effects in key areas like automation, data security and privacy, personalized cloud management and predictive analytics. According to a report by OECD, global spending on AI infrastructure will increase to $110 billion by 2024.
What is the relationship between AI/ML and the cloud?
The cloud infrastructure, with access to scalable computing and massive data storage, plays a pivotal role in machine learning training and inference at a reasonable cost. It's a low-commitment and low-cost opportunity for businesses to process tremendous volumes of data and create AI models without investing in their own datacenters. With cloud vendors supplying the necessary hardware and software, businesses are building their own AI algorithms and machine learning models, powering diverse use cases like shipping automation, text analysis, speech recognition, self-driving cars, and more.
And the best part is that any win for the AI/ML department is also a massive win for the cloud. Growth in AI adoption will further trigger an increase in demand for cloud services; as AI/ML becomes more important to business workloads, we expect this mutually beneficial relationship to rapidly accelerate demand in 2023.
6. Symbiotic relationship between blockchain and cloud of things (CoT)
Blockchain technology is finally making its way into the mainstream and businesses in various industry verticals are using it to record and store transactions and digital assets. Blockchain is a distributed ledger technology (DLT) which electronically stores data in the form of blocks. Each block has a timestamp of when it was added, along with a cryptographic hash of the previous block and all the stored data.
Blockchain is decentralized and immune to manipulation which fulfills a particularly important requirement for multiple industries. Traditional IoT infrastructure setups use centralized communication models, resulting in scalability issues and latency. Also, once the data has been uploaded to the cloud, it's vulnerable to attack from external threats. Because blockchain technology is decentralized, multiple copies of the same data exist on several nodes. In a centralized framework, failure of the central server can threaten the entire system, but a decentralized architecture can significantly limit the fallout. In addition, blockchain solves several cloud security challenges by segmenting and encrypting user data through hashtag functions. Only users with the encryption key can read the transaction data, making it more resilient to corruption or tampering.
With cloud service providers (CSPs) offering managed blockchain cloud services, we expect a sharp increase in adoption of blockchain technology to manage cloud workloads. Key areas to look out for are healthcare, home automation, transportation and manufacturing. Businesses in these industries employ a vast network of IoT devices and sensors to gather and process data in near real-time and perform specific functions. A secure and decentralized blockchain architecture can be the missing piece of the puzzle.
Next Steps
We are entering a new era of cloud supremacy where cloud computing is going to have the majority stake in most industry workloads. The cloud's accessibility and convenience make it the go-to choice for businesses irrespective of industry vectors, and new developments in adjacent areas quickly get assimilated into cloud services. We think 2023 will be a year of collaboration for cloud computing, with applications in key areas bringing the cloud closer to us than ever before.
