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This article is part of our Opinions section, where we invite industry professionals to share their views on the most pressing technology questions of our time.
As AI capabilities continue to grow exponentially, so will investment in the technologies supporting it. Generative AI in particular requires (and creates) overwhelming amounts of data that needs processing and storing in the cloud. Gartner predicts worldwide public cloud end-user spending will reach a whopping $679 billion this year alone – a statistic primarily driven by GenAI advancements.
With an influx of organizations adopting GenAI at pace and scale, many are looking to move their operations to the cloud or scale their cloud infrastructure for the first time, leading to questions about finding the right cloud environment. A number of those are finding that a multi-cloud approach allows organizations to pick and choose from providers to find the cloud services that meet their specific needs, enabling them to pick the best of the bunch for individual purposes, rather than settling for a ‘one-size fits all’ approach.
Crucially, a multi-cloud approach helps organizations to avoid vendor lock-in. Much like the rest of us with phone contracts, companies can get stuck in cloud contracts that they can’t escape without incurring significant costs, legal headaches, and often technological incompatibility. The multi-cloud approach eliminates dependencies on any single vendor, allowing organizations to operate largely on their own terms. Some cloud providers even offer pay-as-you-go pricing, allowing companies the flexibility to walk away when needed. Beyond that, the mix-and-match nature of the multi-cloud approach also boosts organisational reliability and resilience. Even if one cloud provider goes down, organizations will still have additional providers to fall back on.
But building a multi-cloud system requires diligence, careful planning and organisational buy-in. So, with that in mind, let’s consider the best practices organizations can implement to set them up for multi-cloud success.
The first step for any organisation looking to implement a multi-cloud approach is to create a comprehensive strategy. When adopting multi-cloud, organizational alignment behind the business objectives is crucial to capture the full ROI.
Organizations should carefully consider their data workloads to ensure that company data is distributed across multiple clouds most efficiently. For example, a business working with AI and machine learning might choose to leverage various cloud platforms to access specific high-performance computing resources to support the training and running of AI/ML models.
If organizations consider the strategy carefully before implementation, they can accurately match their workloads to the most appropriate and advanced technology available. Not only will this allow them to minimise costs in the long term, but it will also help them realise the full benefits a multi-cloud approach offers.
Once organizations have selected a multi-cloud model, data security is the second major aspect to consider. This typically means securing access to workloads across multiple providers with the ‘usual’ methods such as encryption and identity management tools. Addressing this at the very start of the process ensures that the final model is compliant with regulatory standards from the offset, allowing organizations to avoid any hiccups later down the line.
It’s also worth highlighting that the very nature of the multi-cloud model also provides a significant boost to organizational reliability, ensuring that systems can remain online even during critical incidents. Having workloads spread across multiple cloud providers means that the impact of downtime can be vastly minimized, securing business continuity as even if one provider experiences an outage, the others will still be available to work from.
While this does increase potential attack surfaces, organizations can minimize the risk of damage by using consistent security policies and compliance measures across all cloud environments. In a way, it also mitigates itself by the very design of the model, as even if one cloud provider does suffer a data breach, it would only affect a fraction of the data and applications, with the rest safely secured at other providers.
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Of course, once organizations have completed all of the preparatory work, they actually have to implement multi-cloud. While this will look vastly different in each individual case, the best approach is to do so with continuous monitoring to keep a close eye on the resources and spending going into the process. This also gives a degree of flexibility, allowing us to make any adjustments as and when they inevitably surface during the process.
The other lynchpin for a successful implementation stage is the team itself. Ensuring that those involved in the process have been trained and upskilled on the relevant cloud platforms is essential. It’s key that they are educated on the value of multi-cloud and understand why this approach is being introduced. It will be a big change, but getting them fully engaged is invaluable and will produce a better end result.
When it comes to implementing a multi-cloud approach, the key really is in the preparation. Having a thorough understanding of how the proposed cloud support aligns with business objectives is essential to ensuring successful adoption. Any security considerations can be largely mitigated by encryption and identity management tools, not to mention the improved organisation reliability that can be gained from the multi-cloud model. Combine this all with an engaged team and you’re set for multi-cloud success!
