By Enterprises deploying AI agents and stateful applications are running into a hard infrastructure ceiling. Vanilla Kubernetes provides no data service orchestration layer, and without one, AI workloads that carry state have no reliable foundation to run on across multi-cluster environments.
In this interview on TFiR, Julian Fischer, CEO at anynines, covers how the anynines platform and a9s Hub address data service orchestration across Cloud Foundry and Kubernetes, and why this integration forms the runtime foundation AI workloads require.
Guest: Julian Fischer, CEO at anynines
Show: TFiR
Here is what every platform engineer and AI infrastructure team needs to know.
Technical Deep Dive
Q: Where is the anynines platform headed as enterprises scale AI workloads and deal with increasing cloud complexity?
Julian Fischer, CEO at anynines, describes the anynines platform as becoming a complete set. Cloud Foundry remains a strong and growing part of the business, Kubernetes is treated as unavoidable and valuable, and a9s Hub ties them together into a modular platform that teams can adopt fully or in part depending on their environment. The roadmap is shaped directly by the emerging requirements of AI workloads, data sovereignty, and AI sovereignty.
“We are building the foundation that is necessary for AI to thrive.” — Julian Fischer, CEO, anynines
Q: Is Cloud Foundry still relevant for running AI agents and modern cloud-native applications?
Fischer is direct: Cloud Foundry is still strong and anynines continues to grow its Cloud Foundry business. For teams running large numbers of AI agents and 12-factor compliant applications, Cloud Foundry delivers economy of scale that no other runtime matches. It is not being replaced. It is being extended.
“If you want to run a large number of AI agents and 12-factor compliant apps, there is no better way to run them than running them in Cloud Foundry. The economy of scale is just awesome.” — Julian Fischer, CEO, anynines
Q: What does vanilla Kubernetes lack that makes it insufficient for enterprise AI platforms?
Fischer acknowledges Kubernetes as a valuable and unavoidable technology, but flags a core problem: with vanilla Kubernetes, teams are left to figure out data service orchestration on their own. There is no native layer to manage stateful services across clusters, which means AI workloads that carry state have no managed foundation without additional tooling.
“With vanilla Kubernetes, you’re basically just left alone in the dark.” — Julian Fischer, CEO, anynines
Q: What problem does a9s Hub solve and how does it work across Cloud Foundry and Kubernetes?
a9s Hub solves the data service orchestration problem across Cloud Foundry and Kubernetes environments. It integrates with a single Klutch to expose any service to both runtimes across many Kubernetes clusters. This gives platform teams the tooling they need to build a real application developer platform regardless of whether they run both Cloud Foundry and Kubernetes, or only one of the two.
“With a9s Hub, you solve the data service orchestration problem seamlessly between Cloud Foundry and Kubernetes.” — Julian Fischer, CEO, anynines
Q: How modular is the anynines platform for teams that do not want to run both Cloud Foundry and Kubernetes?
Fischer is explicit that the platform is modular. Teams can run it with both Cloud Foundry and Kubernetes, with Kubernetes only, or with Cloud Foundry only. The architecture is designed to be used flexibly depending on the organization’s existing infrastructure and migration stage.
“It’s modular and it can be just used in a flexible way.” — Julian Fischer, CEO, anynines
Q: Why do AI workloads specifically require orchestrated data services rather than just a runtime?
Fischer frames it as a chain of dependencies. AI code running in the cloud needs a runtime, either Cloud Foundry or Kubernetes. If that code carries state, it needs data services. And if data services are present across multiple clusters and environments, they need to be orchestrated. Skipping any step in that chain leaves AI workloads without a stable foundation.
“If it carries state, it needs data services. And if you have data services, they need to be orchestrated.” — Julian Fischer, CEO, anynines
Resources & Documentation
- anynines Platform, enterprise platform combining Cloud Foundry and Kubernetes with data service orchestration via a9s Hub
***
👇 Click to Read Full Raw Transcript
Swapnil Bhartiya: Looking ahead, where do you see the anynines platform evolving? Especially as enterprises deal with AI workloads and increasing cloud complexity? You mentioned data sovereignty and AI sovereignty becoming critical. How does that shape your roadmap?
Julian Fischer: Well, first of all, I think it’s becoming a complete set. Any 9’s Cloud Foundry is still strong, which means if you want to run a large number of AI agents and 12 factor compliant apps, there is no better way to run them as running them in a Cloud Foundry. The economy of scale is just awesome. Cloud Foundry is a thing. It remains a thing. We’re still growing with our Cloud Foundry business. Cloud Foundry is important, but it’s not everything. It doesn’t cover all of it. Kubernetes is unavoidable. And why would you. It’s a wonderful technology. However, you’re basically with vanilla Kubernetes, you’re just left alone in the dark. So with a9s Hub, you solve the data service orchestration problem seamlessly between Cloud Foundry and Kubernetes. You integrate with Clutch One and you expose any service to both Cloud Foundry and Kubernetes across those many Kubernetes clusters. That makes the tooling you need to build a real application developer platform with both Cloud Foundry and Kubernetes, or only Kubernetes if you want to. Or only Cloud Foundry if you want to. It’s modular and it can be, you know, just used in a flexible way. And I think AI needs a runtime. If you, if you run code, you know, that runs in the cloud, it needs to run somewhere and it either runs in Cloud Foundry or it runs in Kubernetes, in my opinion. And if it carries state, it needs data services. And if you have data services, they need to be orchestrated. So I think we are building the foundation that is necessary for AI to thrive.
