The KubeCon + CloudNativeCon gathering in Amsterdam provided an opportunity for engineers and developers to hear the latest on container, cloud-native and open-source innovation. The rise of artificial intelligence and its impact on the evolution of DevOps, as well as data governance, were prime topics of discussion during the weeklong event.

TheCUBE, SiliconANGLE Media’s livestreaming studio, was on the ground, providing daily coverage from the KubeCon show floor. This included interviews with industry executives and analysts who provided their unique insights into key cloud-native developments and future trends. (* Disclosure below.)

Here are three insights you might have missed from theCUBE’s extensive coverage:

1. Cloud-native is enabling the edge and use cases are growing.

The edge is starting to get crowded. Storage data is there and so is AI. In theCUBE’s interview with Murli Thirumale (pictured), vice president and general manager of the Cloud-Native Business Unit at Pure Storage Inc., it’s becoming more apparent there is room for Kubernetes at the edge as well.

“There’s a lot of things that enable the edge,” Thirumale said. “One of them is the very concept of microservices. By having microservices now, everything doesn’t need to be really one big heavy monolithic application. You can kind of structure them. One app can be four to five microservices, and you can run different microservices at the edge versus the core.”

Kubernetes is used as a platform for complex applications made up of multiple microservices, and Thirumale noted that the food services vertical is where the IT community is seeing growing use of slimmer Kubernetes for microservices deployment.

One example of this can be seen in how the AgTech company Tevel Inc. is now using Kubernetes to power fruit-picking robots at the edge. The technology relies on large images that makes the programming a challenge. Implementation of a microservices architecture run by Kubernetes resulted in slimmer, more manageable images, making the robots easier to operate.

Here’s theCUBE’s complete video interview with Murli Thirumale:

2. WebAssembly could put a turbo charge into the serverless space.

The WebAssembly, or Wasm, project is beginning to generate its own momentum in the cloud-native world. The technology was initially focused on providing an ability to run portable code in the browser with near-native performance. Last fall, a Cloud Native Computing Foundation survey found that 30% of respondents were using Wasm and another 37% were planning to do so within the next year.

As Wasm evolves, there are some in the cloud-native world who are intrigued with its potential application in the serverless space. One company that has explored options in this area is Fermyon Technologies Inc., which aims to deliver a frictionless developer experience using Wasm and Spin, a WebAssembly framework.

CNCF reported that adoption of serverless architecture appeared to have stalled last year, hindered by challenges around the lack of standards for interoperability and integration. The chief executive officer of Fermyon believes that this situation will change.

“When we think about serverless, a couple years ago, it was all hype, but it didn’t quite live up to the hype,” said Matt Butcher, CEO of Fermyon, in an interview with theCUBE. “Some of the problems we were seeing are there’s a mismatch between the architecture underneath and the kinds of applications we’re trying to write. WebAssembly is a better architecture to sit underneath that and be able to start things with supersonic speed and just pick up very quickly.”

Here’s theCUBE’s complete video interview with Matt Butcher, along with Justin Cormack, chief technology officer of Docker Inc.:

3. Recent breakthroughs in AI have bridged the chasm between humans and machines.

If there is a simple way to cut through the current hype surrounding OpenAI’s ChatGPT, it may be by simply looking at the bigger picture. By creating a conversational interface where a seemingly unlimited number of tasks can be handled through basic communication, AI technology has brought humans closer to the machines they use.

This has effectively opened up a new world, one formerly inhabited only by programmers. Since ChatGPT was officially launched late last year, there has been a steady stream of announcements from companies aimed at democratizing use of large language models.

Meta Platform Inc. publicly released Large Language Model Meta AI with a goal to democratize access. Big data analytics firm Databricks Inc. open-sourced an AI model so that it could become available to millions of smaller firms, rather than only the largest tech players.

“What have large language models actually done for us?” asked Amit Eyal Govrin, CEO of Kubiya Inc., during an interview at KubeCon. “Beyond all the buzz and all the cool little demos you are seeing, it’s bridged a gap between human to machine interaction. Humans and machines can understand each other and rather than having the human need to know code or low code to interact with the machine, the machine is now smart enough to interact in natural language and convert that into code.”

Here’s theCUBE’s complete video interview with Amit Eyal Govrin:

To watch more of theCUBE’s coverage of KubeCon + CloudNativeCon, here’s our complete event video playlist:

(* Disclosure: TheCUBE is a paid media partner for KubeCon + CloudNativeCon. Neither Red Hat Inc. nor other sponsors of theCUBE’s event coverage have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE