"AI may be both the driver and the remedy for multi-cloud adoption," says Dmitry Panenkov, Founder & CEO of emma, alluding to the vast potential and possibilities Artificial Intelligence (AI) and multi-cloud strategies offer.
In this episode of the Tech Transformed podcast, Tom Croll, a Cybersecurity Industry Analyst and Tech Advisor at Lionfish, speaks to Panenkov. They talk about the intricacies of powering multi-cloud systems with AI, offering valuable insights for businesses aiming to tap into the full potential of both.
They also discuss data fragmentation, interoperability issues, and security concerns.
Addressing the key challenges of AI adoption in multi-cloud environments, Panenkov spotlights one of the most prominent issues – data fragmentation.
“AI thrives on unified data sets. But multi-cloud setups often lead to data silos across the different platforms,” the founder of emma, the cloud management platform, explained.
Data silos creates a disconnect which makes it increasingly challenging for AI models. It makes it harder for AI models to access and process the huge amounts of data needed to function efficiently.
Instead, Panenkov stresses the potential of AI to drive multi-cloud adoption by optimising workloads and automating policies.
In addition to data fragmentation, the lack of interoperability and tooling presents another challenge when integrating AI with multi-cloud. This is where Inconsistent APIs, a lack of standardisation, and variations in cloud-native tools create major friction. The difference is evident when building AI pipelines across diverse environments.
Panenkov also pointed out the impact of latency and performance. He says, "Even Kubernetes is sensitive to latency. When we talk about AI and inference, and I'm not even talking about the training, I'm saying that inference is also sensitive."
Without proper networking solutions, running AI workloads effectively in multi-cloud environments becomes next to impossible.
Of course, security and compliance are a looming challenge for all enterprises across varying industries. Managing data protection in different jurisdictions and environments adds layers of legal and operational complexity.
Despite these challenges, AI has significant advantages in multi-cloud systems that well surpass any challenges.
The main topic of the conversation was how AI can actually help overcome the complexities of multi-cloud adoption. As the...
