According to recent research, a staggering 99% of enterprises are planning to invest in generative AI over the next twelve months. While this investment will include the purchase of existing applications or the development of new ones, it will also require investment in the infrastructure on which these advanced applications are to run. Deploying AI successfully requires considerable computing power, high-speed data processing and scalable storage. Here, Name and Role at Hyperslice discusses the essential hosting requirements for running enterprise AI apps.
Computing power
AI algorithms need to analyse vast amounts of data very quickly, especially if you want to be able to interact with them in real time. This kind of processing requires huge computing resources. As a result, any enterprise wanting to host AI applications will need a solution that offers both processing power and speed. Consider using Intel Xeon processors with a high number of cores and lightning-fast storage, like NVMe SSDs. Depending on the needs of your application, you could also need between 8GB and 64GB of DDR RAM.
Importantly, to keep costs to a minimum and provide additional capacity when needed, it is vital to find a hosting solution that makes it quick and easy to scale up or down on demand. This can pose a dilemma for enterprises, as dedicated servers offer the best solution in terms of performance while the cloud is the better when it comes to easy scaling.
High-speed network
Processing large volumes of data, especially real-time data streams, requires a hosting solution that offers both a high-bandwidth network and low-latency data access. To prevent bottlenecks, it is important to have a high port speed, for example, 1Gbit, while having the application hosted at a data centre geographically near to its users can minimise latency. Just as crucial, is ensuring that data transfer limits are sufficient for the enterprise’s needs.
Scalable storage
According to Statista, the average enterprise data volume was expected to double from one to two petabytes (PB) between 2020 and 2022 and continue growing at over 40% year on year. Given that this post was written at the end of 2023, today’s enterprise storage requirements are significant, to say the least, and will accelerate over time. Scalable storage solutions are, therefore, essential. For this reason, enterprises should seek a solutions provider that offers not just ample and easily scalable storage space, but which also provides swift data retrieval and appropriate backup solutions. Putting this in place might require a combination of in-house, cloud or hybrid storage, depending on the specific needs of the organisation.
Security and compliance
As enterprises are likely to use their AI applications to process sensitive data, it is vital that robust security is put in place. When choosing a hosting provider, look for solutions that offer next-gen firewall protection, like FortiGate firewalls, together with intrusion and malware detection, and encryption in transit and at rest. Ideally, the provider should offer a holistic security solution, which encompasses compliance, governance, testing, auditing and offensive and defensive managed security services.
Reliability
Given that even everyday applications are now being given AI capabilities, it’s not a leap of faith to imagine that within a few years, most critical applications used by enterprises will be AI-based. For this reason, when finding a hosting solution, reliability and high availability are essential to ensure minimal disruption and to maintain consistent service to customers and staff. Cloud solutions are ideal for delivering high availability; however, enterprises should ensure that the provider backs these with service level agreements (SLAs).
Cost-effective pricing
With enormous data storage and huge processing requirements, enterprise-level AI applications can be costly to run. While this is undoubtedly an investment with, for most enterprises, a worthwhile return, that doesn’t mean pricing should be overlooked when choosing a hosting solution. Enterprises should look for a pricing model that is both flexible and transparent. A pay-per-use pricing policy should provide the flexibility to reduce costs when the AI application is less busy, while transparency will ensure there are no hidden costs that cause unexpected financial jitters.
Conclusion
The enormous potential of AI means that enterprises have little option but to make use of it if they are to remain competitive. However, this means ensuring that AI applications are given the right hosting solutions. Ideally, these should include significant computing power, fast data processing, scalable storage, robust security and flexible pricing. A reliable provider should also be able to offer 24/7 support, backup and business continuity solutions and enterprise-level expertise.
For more information about our enterprise-class Managed IT Solutions, visit Hyperslice.com
