It is no secret that the cloud computing landscape is quite dynamic. With technological advancements in the cloud computing industry evolving at a breakneck speed along with the availability of new tools and services, Gartner forecasts worldwide public cloud spending to reach $600 billion in 2023.
This makes cloud computing a promising, exciting, and sometimes a little scary space to be in! But, what do you know about IT leaders and their strategies in the times of uncertainty? How are they evolving and adapting with the changing landscape? What are the trends they swear by for 2023?
To help the leaders keep up with the ever-evolving cloud computing trends and evaluate their predictions for the future, we are creating this blog with all the cloud computing trends in 2023. Let’s check it out!
Edge Computing
Edge computing is a distributed cloud computing model which brings data storage and computational power closer towards the edge of the network. With edge computing, the data is stored and processed near the edge servers and devices. This reduces the need of transferring large amounts of data, constantly, to a data centre or a centralised cloud system.
According to a report by MarketsandMarkets, the global edge computing market size was valued at $44.7 billion in 2022 and is expected to grow till $101 billion by the end of 2027.
Sam Altman, CEO of OpenAI and former president of Y Combinator said “The rise of edge computing signifies a fundamental shift in how we process and analyse data. By bringing computation closer to the source, we can unlock new opportunities for real-time interactions, autonomous systems, and immersive experiences.”
Now, the rise of edge computing in 2023 is driven by multiple factors, namely:
- Less Latency: With edge computing, data is processed closer to where it is generated which helps in significantly reducing the delay to a distant server and waiting for response. A good example where this is specifically useful can be gaming, augmented reality, or mission-critical systems.
- Bandwidth Optimization: Edge computing assists in reducing the amount of data needed to be transferred to the central cloud or distant server. This helps in optimising bandwidth and reducing network congestion. An example for the usefulness can be scenarios where network connectivity is unreliable, limited, or expensive.
- Data Security: Edge computing helps to level up your data privacy and security by localising data and minimising external threats or breaches associated with the transfer of data. Data security is a major concern in every industry but can be particularly necessary for government, healthcare, or financial industries.
Edge computing has many more advantages than the above-mentioned. Edge computing enables applications to run with limited connectivity or without an internet connection. It is also much more scalable and cost-efficient than other cloud computing methods.
Cloud Repatriation
The Cloud Repatriation movement refers to the trend where the organisations repatriate workloads or data from public cloud environments to on-premise or private cloud infrastructure. It is about migrating the data, applications or services that were previously hosted in public clouds back to private infrastructure. It is about moving on from large-scale hyperscalers like AWS, Azure, etc and moving to private or owned cloud infrastructure.
Here’s why cloud repatriation movement is on the go now:
- Cost Efficiency: A lot of organisations may agree that hosting their workloads in public cloud with hyperscalers is becoming a costly affair over the period of time. Especially when the usage of the said cloud scales up. Moving on from hyperscalers helps in reducing costs and utilising the most effective cloud infrastructure for their workload.
- Latency & Performance: Workloads with precise performance requirements like high-performance trading, real-time processing might benefit from being closer to the data source. Repatriation allows companies to reduce latency by hosting their cloud on local or owned premises.
- Security and Data Governance: Cloud computing organisations with strict data governance needs may prefer more autonomy over their data. Repatriation allows them the autonomy they need along with ensuring compliance, strengthening security measures to keep sensitive data on-premises and maintaining data sovereignty.
However, keep in mind that many workloads cannot be completely transitioned out of public clouds. Repatriation candidates, in other words, are often workloads that are more static and predictable in nature, i.e., workloads that do not require the ‘infinite flexibility’ that the hyperscalers claim.
Therefore, even if repatriation may aid in transferring data ownership to a “owned” configuration, it won’t completely render the data “independent” of the hyperscalers.
Kubernetes and Containerization
Kubernetes is an open-source-based container orchestration platform which automates the deployment, management, and scaling of containerized applications. However, containerization is a process which allows applications to be packaged into lightweight and isolated units called containers.
These containers encompassed the application along with its dependencies and consistent deployment across multiple computing environments.
This rising trend for Kubernetes and Containerization is driven by several factors:
- Resource Efficiency: Containers are lightweight and work by sharing the host’s operating system resources; this makes them resource-efficient as compared to traditional virtual machines (VMs). This allows for more deployments in an infrastructure which increases resource utilisation and helps in cost optimization.
- Portability and Scalability: Kubernetes simplifies the containerized application deployment and management process. It assists in easily scaling applications, up or down, based on the requirement, ensuring efficient resource utilisation. Containerization also provides portability which enables applications to run consistently across various cloud environments.
- DevOps and Agile Practices: Containerization and Kubernetes align seamlessly with DevOps principles which enables them to adopt agile development practices along with continuous integration and deployment. Containers provide a reproducible and consistent environment for developing, testing, and deploying applications seamlessly.
Kubernetes and containerization help organisations with agility, scalability, and efficiency. It also helps in the modernization of applications along with building native cloud architecture. Kubernetes also has a great amount of industry adoption which gives it a vibrant ecosystem and good vendor support.
Hybrid and Multi Cloud Adoption
Hybrid and multi cloud adoption is an ongoing trend in the cloud computing market in which organisations leverage private clouds, on-premises infrastructure, and multiple public cloud providers to meet all their computing needs.
Hybrid cloud is the process of using private and public clouds to meet your cloud computing requirements. Multi Cloud Adoption is basically utilising multiple public clouds for the same.
Here’s why this trend is on the rise:
- Flexibility & Vendor Independence: Hybrid and multi cloud architecture offer organisations the flexibility to choose the most suitable cloud environment for their requirements and workloads. The flexibility offered helps in avoiding vendor lock-in and the ability to leverage the strengths of different cloud platforms.
- Resilience and Risk Mitigation: By adopting multi cloud or hybrid cloud approach, organisations can distribute their workload across multiple cloud environments. This helps in risk mitigation like data breaches, regional disruptions, or service outages. A classic example can be – imagine if one cloud provider experiences an issue, the workload can be seamlessly shifted to another provider or brought back to on-premises infrastructure. This ensures the application keeps running, without any issues.
- Cost Optimization: Hybrid and multi cloud approach helps organisations to make their cloud computing process cost optimised by selecting the most cost-efficient option for different workloads. Some workloads might have predictable usage patterns and can be run on on-premises resources, reducing costs. Other workloads with bursty demand can make use of public clouds.
Artificial Intelligence & Machine Learning
With the submergence of AI & ML in every phase of running a business, the cloud leaders of the future need Cloud infrastructure that can support AI & ML workloads. To get this, they will not hesitate to turn to different cloud service providers, other than their primary, to fulfil this need.
According to research by the Enterprise Strategy Group, 39% of people cite Al/ML as their top workload priority leading to the use of other cloud service providers in addition to their primary ones.
Here are a few reasons why AI & ML trend is on the rise:
- Higher Data Processing: AI & ML algorithms look for substantial storage capabilities and computing power to process and analyse large amounts of data. Cloud Computing has the potential to provide the required infrastructure and resources to handle AI & ML workloads efficiently. This allows organisations to leverage advanced data processing capabilities without making any investments in expensive on-premises infrastructure.
- Flexibility and Scalability: AI & ML algorithms require scalability and flexibility that cloud platforms have to offer. As datasets and AI models grow or shrink, cloud computing allows organisations to scale up or down their resources to accommodate the changing demands. This agility enables inference, efficient training, and successful deployment of AI & ML models.
- Cost Efficiency: Cloud computing usually offers a pay-as-you-go model which helps in optimising the cost associated with those projects. It also assists in on-demand resource provisioning and eliminates any need for upfront investment in infrastructure and hardware.
Social Impact of Cloud Computing on Emerging Economies
Cloud computing has a higher level of social impact on emerging economies than you would think! It has brought about transformative change in their technological capabilities and a plethora of growth and transformation opportunities.
David Hansson, maker of Basecamp, and CTO of 37 Signals quoted “Cloud computing is not only about saving costs or increasing efficiency. It’s about enabling innovation, empowering businesses to focus on what they do best, and providing access to unlimited computing resources for everyone.”
That’s what cloud computing is about – enabling innovation in landscapes where it can bring substantial benefits and changes. That is the social impact of cloud computing on emerging economies
Here are a few reasons why this trend is important:
- Digital Inclusion & Transformation: Cloud computing helps in bridging the social divide by providing accessible and affordable computing resources to everyone in emerging economies. It enables them to access educational resources, information, and digital services and empowers them to unlock new opportunities in the global economy. Apiculus has been at the forefront of this mission, working with ISPs and Data Centers in emerging economies for over a decade now, and has helped a lot of economies with gaining better access to new technologies. You can read more about it here.
- Empowering Government Institutions: Governments in emerging economies can develop and modernise their services to ensure better public delivery. Cloud computing offers cost-effective solutions for different sectors like education, e-governance, healthcare, citizen services, and other important sectors.
- Economic Growth: Cloud computing serves as a catalyst for economic growth and job creation in emerging economies. It enables small businesses, individuals, and businesses to leverage technology without investing large amounts of money in computing resources, levelling the playing field.
Wrapping Up
In conclusion, there are a few trends that are going to shape the cloud computing industry in 2023. Change is inevitable and evolution is the key – especially with technology. 2023 will see a lot of attention focused on evaluating data security gaps and strengthening it. With AI and ML in full swing, the cloud industry is going to see multiple changes in the coming years and service providers will need to adapt and adjust accordingly.