AI and cloud-native technologies could help the UK public sector to brace itself for the recession, as well as support growth in times of uncertainty
The UK’s public sector is feeling the squeeze of inflationary pressures. Globally, IT leaders are calling for reduced cloud spending, but in reality, AI and cloud-native technologies might be the very thing that braces organisations for hard times.
Research firm Gartner showed that despite economic headwinds, end-user public cloud spending is expected to increase in 2023 by 20.7%. The forecast cited cloud computing as a “bastion of safety and innovation, supporting growth during uncertain times due to its agile, elastic, and scalable nature.”
End-user public cloud spending is expected to increase in 2023 by 20.7%
In 2023, every company must modernise to survive, chiefly by adopting container orchestration platforms in conjunction with the cloud. As organisations look to improve efficiency and cost savings for their IT infrastructure, Kubernetes and the cloud will play a big part in realising this goal, with AI offering further differentiation and advancement.
It’s the pairing of cloud, Kubernetes, and AI that poses the most exciting advantages
Companies exploiting this combination are poised to gain not only an advantage in innovation and the ability to outcompete rivals, but also have an opportunity to become greener and cut costs in economically austere times.
As an entrepreneur and practitioner in the cloud-native sphere, I’ve seen first-hand the transformative power of AI and cloud native technologies when it comes to business digitalisation as a solution, and as a foundation for modernisation across the board.
Facing the recession is a daunting task for any business or government, but both government and CIOs must implement technology solutions that improve and reinforce agility, speed to market, and innovation.
Just as AI and cloud native technologies have assisted businesses through the pandemic, so too will they bolster business resilience amidst the recession, which should put them at the top of any CIO’s shopping list.
AI for digital transformation
Today, AI powers a host of solutions that enrich and improve our lives. AI is being built into almost every product and service we use, from mobile phones to sensors that monitor environments and physical systems that alter environments, to houses, cars, factories, and entire cities. AI can monitor weather patterns, traffic patterns, and patient health to improve routes and outcomes. It accelerates innovation and scientific discovery every day and is enabling new art forms and modes of search.
AI can monitor weather patterns, traffic patterns, and patient health to improve routes and outcomes
In the business world, AI can aid decision-making to help organisations improve business operations and the bottom line. It can help banks determine creditworthiness and detect fraud, help retailers optimise inventory and sales, and help marketers identify prospects and personalise messaging.
AI-based chatbots can provide detailed customer service round-the-clock, gathering data to improve quality of service and generate potential new revenue streams.
There are numerous other benefits, some of which include:
- Accelerating discovery of new chemical compounds for better materials, fuels, pesticides, and other products that are better for the environment.
- Making buildings more energy-efficient. For example, Bearing.AI reduces fuel consumption and plans safer routes for maritime shipping, a large emitter of greenhouse gases.
- AI might even help make nuclear fusion a reliable, carbon-neutral, cheap, and abundant source of energy, which could aid in combating climate change.
But AI is also an expensive and resource-heavy technology. To intelligently leverage AI and reduce compute resources when unneeded, you need automation by way of cloud-native platforms like Kubernetes, which already streamlines the deployment and management of containerized cloud-native applications at scale to reduce operational costs.
Enter cloud native and Kubernetes
Like a conductor or helmsman, Kubernetes orchestrates containerized applications in the cloud, ensuring the right compute, network, storage, and configuration. It manages an organisation’s entire portfolio of applications on any infrastructure, including cloud, data centre, and edge.
The reason 96% of organisations are already using or evaluating Kubernetes, according to the Cloud Native Computing Foundation, is because it gains them agility, speed-to-market, and more efficient operations. They can spin up, terminate, update, and scale up applications with better resilience, governance, security, and visibility, while reducing operational costs.
‘Speed up development and lower costs’
Similarly, Kubernetes is a natural fit for supporting AI/ML workloads by scaling to meet the resource needs of AI/ML training and production workloads, enabling continuous development of models. Developers can share expensive and limited resources like graphic processing units between themselves to speed up development and lower costs.
Empower AI, for example, which provides automation solutions to the U.S government, has significantly reduced operational costs using Kubernetes, freeing up resources to accelerate new AI initiatives and embark on a new journey of innovation.
The fact that Kubernetes is an open-source, the cloud-native platform makes it easy to apply cloud-native best practices and take advantage of continuous open-source innovation. Many modern AI/ML technologies are open source as well and come with native Kubernetes integration.
The skills gap is the fly in the cloud’s ointment
Despite the benefits of AI and cloud-native, surveys show that businesses are overspending on cloud implementations and that Kubernetes costs are surging, significantly impacting IT professionals.
Because Kubernetes is complex and unlike traditional IT environments, most organisations lack the DevOps skills needed for Kubernetes management. Likewise, most AI projects fail because of complexity and skills issues.
As the number of cloud platforms within organisations grows, so too will the number of tools they must juggle for cloud cost optimization, Enterprises are already expending some level of manual effort to consolidate data from them, which can create discrepancies in reporting.
Risks of overspending are furthered as developers and IT teams overprovision resources to ensure their applications maintain availability, which can lead to abandoned or orphaned cloud resources.
As more companies hire IT generalists over specialists, this challenge will likely be compounded, forcing many to partner with vendors that provide centralised governance and cost optimisation insights. They’re also going to have to devote time and resources to upskill DevOps teams internally on cloud-native rather than hiring new ones.
Training in combination with platform automation and simplified user interfaces can help DevOps teams master Kubernetes management. Feature-complete Kubernetes platforms that provide “instant platform engineering” are another way to ease the DevOps burden.
Cutting corners can have long-term repercussions
No organisation can avoid cost increases ahead. But even in a downturn, CIOs should weigh technology investment against improved business outcomes, competitive demands, and profitability from adopting cloud-native, Kubernetes, AI, and edge technologies.
Cutting back on cloud-native IT modernization initiatives might save money in the short term, but could seriously hurt long-term capabilities for innovation, growth, and profitability.
This piece was written and provided by Tobi Knaup, CEO at D2iQ