How Hybrid Cloud is Key to Enterprise AI Infrastructure Strategies

by | Mar 3, 2021 | Artificial Intelligence, Cloud Computing, Data, DevOps & Engineering | 0 comments

Artificial Intelligence is both loved and feared for its unending possibilities. AI is reshaping everyday life, from simple tasks to the complex, and if your organisation isn’t trying to apply AI in one way or another, it’ll be left behind the competition.

AI does have its own unique requirements, including strategic planning to ensure data scientists and researchers work efficiently to delivery projects on time and successfully.

AI Excels in the Cloud

The cloud is second to none when it comes to resource availability. This easy-access infrastructure also extends to AI workloads. With GPU-accelerated instances available from cloud service providers, cloud is an ideal resource for testing AI projects and prototypes.

Cloud provides scalability when training new models. The cloud can serve to:

  • Enterprises as infrastructure for AI inference workloads
  • Deployment of computer vision, conversational AI, speech, language and translation, and recommendation systems

Data governance and cloud costs can complicate the adoption of AI in the cloud space, posing roadblocks to developments. As AI projects expand, data hosting can result in unexpected costs. In most cases, AI applications that are deployed require multiple apps to respond in real-time to improve automation and the overall user experience. 

Hybrid Clouds Deliver on AI Objectives

To overcome these kinds of challenges, enterprises should build AI centres of excellence with on-premises systems for AI computing and prototyping at scale.

A few things to consider to avoid these challenges are:

  • Plan for data gravity and putting computing closer to the source of data. This will ensure your costs are balanced and resources ready
  • Your projects will scale, so make sure your cloud service providers offer hybrid accelerated computing solutions to ease the resource availability;

It’s important to make sure your internal team (particularly data scientists) have resources available to stay productive. Training AI, building new models, and evaluating a deployed model are more efficient and accurate when a hybrid approach is adopted.

Remember your costs will scale with the amount of applications you create, so be sure to optimise your cloud environment for cost savings and efficiency. Take advantage of our cloud optimisation assessment at no cost.

Software is Central to AI Success

Software is the cornerstone of every AI project delivered. Unique applications rely on specialised software to excel, so naturally it’s important for an enterprise to update their tech stack. Fossil systems are the biggest challenge for enterprise organisations looking to adapt to the AI world, this is particularly true for banking & financial institutes.

Adopting a hybrid cloud strategy assists IT teams to accelerate and deliver AI on demand and within budget. 

By keeping AI software in mind and developing a strategy to keep pace with software innovation, enterprises will be ready to scale easily from the data centre, to the cloud, to the edge.

We pride ourselves on cloud optimisation and find passion in supporting our customers to reduce cost and optimise performance efficiently and effectively. Contact us today to begin your cloud migration journey. Crystal Delta is a global software engineering practice specialising in banking & finance, manufacturing, and education.