Kubernetes has spent years becoming the infrastructure layer behind modern software.
Now AI is landing on top of it.
On June 18–19, 2026, KubeCon + CloudNativeCon India brought thousands of developers, platform engineers, architects and cloud-native teams together in Mumbai to talk about exactly that transition.
NitroStack was part of the room, and the overlap with what we're building was difficult to miss.
AI workloads. Platform engineering. Autoscaling. Observability. Security. Agent infrastructure.
For NitroStack, these aren't adjacent topics.
They're underneath the product.
KubeCon's AI conversation has moved into infrastructure
One of the strongest themes at KubeCon India this year was how Kubernetes changes as AI becomes a serious production workload.
The agenda went into GPU orchestration, AI agents, model routing, platform engineering, workload reliability, telemetry, zero-trust security and identity for agentic AI.
That's an important shift.
An agent can look simple from the outside: model, prompt, tools.
Run that application in production and suddenly you're dealing with containers, traffic spikes, deployments, credentials, permissions, logs, compute usage, failures and rollback strategies.
MCP eventually reaches the same infrastructure.
NitroStack is already built for that point.
NitroCloud turns cloud-native infrastructure into MCP infrastructure
NitroCloud takes many of the infrastructure patterns being discussed across KubeCon and packages them specifically around deploying Model Context Protocol servers and agentic applications.
Push an MCP project and NitroCloud can automatically containerize it and handle the rollout through its underlying cloud-native infrastructure.
There are no Dockerfiles or Kubernetes YAML files a developer needs to maintain for the standard deployment path.
Underneath that simpler experience is serious infrastructure:
- Scale-to-zero compute and automatic scaling
- Automatic containerization and Knative-based rollouts
- GitHub-native deployments and instant rollback
- CPU, memory, network and request observability
- Real-time log streaming
- TLS 1.3 and automatic SSL
- Encrypted secrets and role-based access control
- OAuth 2.1 and production authentication patterns
This is where NitroStack's position becomes interesting.
Kubernetes is extraordinarily powerful.
But an MCP developer shouldn't necessarily have to become a Kubernetes operator just to put an AI tool into production.
NitroStack keeps the cloud-native foundation and removes the operational tax.
From MCP code to production without assembling the stack yourself
That's also why NitroStack is much broader than MCP hosting.
The open-source NitroStack TypeScript SDK handles the application architecture.
NitroStudio handles building, testing, inspecting and debugging the MCP layer.
NitroCloud takes care of deployment and operation.
So the workflow becomes:
Build → Test → Deploy → Scale → Observe
The Kubernetes and cloud-native machinery still matters enormously.
The developer simply doesn't need to operate every piece of it manually.
That is exactly what good platform engineering is supposed to do.
KubeCon was also an important room for NitroStack
There was another side to being at KubeCon that mattered just as much.
The NitroStack team spent a significant amount of time talking directly with cloud-native engineers, infrastructure teams, founders and people building across the ecosystem.
Several of those conversations naturally moved toward partnerships, integrations and ways NitroStack's MCP infrastructure could fit into a broader cloud-native stack.
For a platform sitting at the intersection of agentic AI, open source and cloud infrastructure, those are the conversations we want to be part of.
Not as observers.
As builders with something concrete already running.
NitroStack is making cloud-native infrastructure usable for MCP
KubeCon India made one direction very clear: AI infrastructure is becoming cloud-native infrastructure.
Agents need identity.
AI workloads need observability.
Production systems need autoscaling, isolation, security and reliable deployment.
NitroStack already brings those pieces together around MCP.
And that's the bigger opportunity for us.
Not replacing Kubernetes.
Turning the power of cloud-native infrastructure into something an MCP developer can use without having to think like a Kubernetes platform team first.