Analytics and cost optimization were the central themes of today’s AWS Startup Showcase event, with specific emphasis on topics such as policy as code, infrastructure automation, governance and database caching.

With operational efficiency now a board-level concern that significantly affects enterprise bottom lines, companies such as Sedai Inc. are attacking that cost optimization pain point so that organizations can carve out new thresholds in revenue generation and profitability.

“Sedai is an autonomous cloud management platform that helps you run your applications with the lowest cost, the highest availability and the best performance for modern applications,” said Suresh Mathew (pictured), founder and chief executive officer of Sedai. “It includes ECS, EKS and Lambda too. We have seen customers like Freshworks, Fabric and KnowBe4 saving 30 to 50% with absolutely zero manual intervention. And, of course, we are a Gartner Cool Vendor and an AWS GSP partner.”

Mathew spoke with theCUBE industry analyst Lisa Martin at the “Analytics and Cost Optimization” AWS Startup Showcase event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the need for enterprise cost optimization given the constantly changing tech and macroeconomic landscapes. (* Disclosure below.)

Between optimization and overkill: The thin line in cloud spending strategies

Digital and cloud transformation has meant that companies rely on a myriad of cloud-powered solutions across several areas, such as software development, security, supply chain management, marketing and point of sale. If unchecked, spending could balloon to a point where an organization’s earnings could be affected, according to Mathew.

“There is a direct cost to the bottom line for companies with significant cloud spend,” he explained. “When you save that money, that could impact your earnings itself. We have seen a 10% impact in a positive way when they report to Wall Street.”

On the other hand, companies can also harm their bottom line when they over-optimize, Matthew added. This could be because certain services aren’t allocated a sufficient amount of resources, leading them to run below required levels; thus, negatively affecting critical objectives such as customer experience.

“The second aspect is if you get it wrong, for example, if you over-optimize, it might hurt your revenue itself, because your peak could probably suffer because of your optimization,” Mathew explained. “And peak is gold for any company. They care about it, so you have to do it neat and clean so your peak doesn’t suffer.”

Complex modern apps requirements present new challenges

The modern application landscape is worlds apart from where it was just a few years ago. However, while today’s apps are enabling corporate innovation and value delivery, they run on exponentially more services and have more dependencies than ever before, creating a more intricate ecosystem to control, according to Mathew.

“The one challenge there is, like 10 years ago, you used to have tens or hundreds of services,” he said. “Now you have like hundreds of thousands of services, so that makes it complex. There are a lot of dependencies out there. When you modify something here, you may be really impacting something in the sixth layer. Now, this is a complex ecosystem.”

Another factor that makes modern applications so hard to manage is the higher frequency of updates and new feature releases, Mathew added.

“On top of it, you frequently release; it used to be once a month or once a week,” he noted. “Now it is once every minute, once every five minutes. Now it’s impossible for people to manage their production optimized, so that’s why modern systems, it’s hard to manage with just automation.”

Artificial intelligence lies at the heart of Sedai’s autonomous approach to cloud management and optimization. By learning and adapting itself to changing states within an infrastructure, the AI learns over time and becomes more versatile in responding to new operating parameters, according to Mathew.

“For us, the learning aspect defines the rule itself. Initially, with the automated system, you say, ‘If CPU goes above 50%, do this.’ And this 50% could change, it goes stale quickly,” he said. “What an autonomous system does is it removes that rule 100%. So there is no rule, there is nothing to go stale; the system learns what that number is, and when it learns, it updates. And the action that has to be taken is always reinforced with learning. That’s how it is different and why it makes it more effective.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the “Analytics and Cost Optimization” AWS Startup Showcase event:

(* Disclosure: Sedai Inc. sponsored this segment of theCUBE. Neither Sedai nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE