Autumn Stanish, Senior Principal Analyst, Gartner, shares predictions that shed light on the dynamic landscape of infrastructure platforms and operations. The shift towards infrastructure platforms promises not only increased efficiency and sustainability but also a more holistic and outcome-driven approach to technology management, and as organisations adapt to these changes, they will be better positioned to thrive in the digital era.
In the ever-evolving landscape of technology and business, infrastructure and operations leaders are on the cusp of a transformative shift. Traditional, siloed approaches to managing infrastructure are giving way to platform-based strategies that promise scalability, agility and improved business outcomes.
Gartner predicts four pivotal predictions that are outlined below that offer a glimpse into the future of infrastructure and operations, providing a roadmap for organisations looking to navigate this landscape.
- Balancing globalism and data sovereignty
There is a growing trend among nations to reduce their dependence on service providers located outside their borders. This shift is and will continue to significantly impact how organisations approach their infrastructure platform strategies. Due to growing concerns over data sovereignty and international conflicts, countries are taking a proactive stance to ensure their digital sovereignty.
Initiatives such as China’s Belt and Road, the US Biden Administration’s strategy and the European Cybersecurity Certification Scheme are emblematic of this trend. These initiatives hold both potential benefits and risks: on the positive side, a focus on domestic sourcing can create new opportunities and bolster economies. However, it can also stifle innovation and place resource-constrained countries at a disadvantage.
Look to initially identify the dependencies on infrastructure delivery, talent, services and intellectual property that exist outside the home country. Understanding the potential risks associated with changes in international relationships, laws and regulations will be crucial. Additionally, developing contingency plans that can swiftly shift dependencies to domestic sources, if necessary, is a prudent approach in this evolving landscape.
- Sustainable modernisation through infrastructure platforms
Infrastructure platforms play a critical role in driving sustainable modernisation. These platforms are essential in ensuring energy-efficient virtualisation and containerisation, ultimately leading to resource optimisation. With enterprises increasingly focusing on environmental sustainability, energy-efficient solutions will become a cornerstone of infrastructure strategies.
Furthermore, regulations and requirements surrounding sustainability are expected to intensify in the coming years, reinforcing the need for a focus on sustainability performance metrics. As organisations grapple with these challenges, selecting infrastructure platforms that optimise energy-intensive workloads and facilitate energy optimisation becomes imperative.
Organisations are entering the early stages of a platform shift that seeks to integrate AI seamlessly into infrastructure, middleware and applications. This transformation promises to equip organisations with the capability to support advanced, AI-infused business applications.
Cloud service providers and hyperscalers are driving the transformation by enabling access to a diverse range of AI adoption pathways. While most Generative AI model training is currently cloud-based, certain government organisations and enterprises may need to consider on-premises, Edge, or colocation strategies for AI applications. This necessitates the adoption of specialised infrastructures, incorporating GPUs, AI ASICs and customised networking stacks.
With this in mind, take a cloud-based approach to Generative AI stacks, considering the uncertainty, cost and integration challenges associated with on-premises solutions. As the landscape becomes clearer, a strategic evaluation of the total cost of ownership (TCO) will guide the decision on whether to replicate cloud-native capabilities on-premises.
- The revirtualisation and cloud-native transition
The impact of increasing prices and the shift towards subscription-based licensing for on-premises private cloud and virtualisation software are now established norms. This transformation is driving organisations to invest more heavily in cloud-native infrastructure and reconsider the revirtualisation of workloads ill-suited for cloud migration.
With the disruption in the server virtualisation market, more than 60% of enterprises are projected to accelerate their public cloud migrations and explore the revirtualisation of existing virtual workloads. Private cloud footprints will decrease, but costs will rise due to increased audits, pricing, bundling and a shift to consumption models.
Therefore, prioritise revirtualisation and private cloud alternatives with a focus on business cases and application modernisation directives. Separating lift-and-shift cloud migration, workload transitions driven by modernisation and application transformation will be key to optimising the implementation of things like XaaS cloud delivery.
- The shift from siloed to holistic infrastructure teams
Infrastructure and operations organisations are increasingly focusing on enterprise and business outcomes rather than purely tactical goals – a shift from siloed infrastructure teams to infrastructure platform teams. This shift is driven by the need to operate more holistically. In the face of hybrid infrastructure and increasing complexity, I&O teams are challenged to manage siloed infrastructures effectively, which requires a combination of automation, engineering and operations skills.
Focus on improving performance and business outcomes by aligning infrastructure platform groups with enterprise-related metrics. Treating hybrid infrastructure in a more integrated manner, leveraging platforms to evolve from siloed infrastructure management and driving agility and scale through automation and skill development is crucial.
