RCS (Rapid Container Service)

AI-Stack integrates containerization technology with the Kubernetes system . This allows developers to package development environments and dependencies into containers, ensuring consistent execution across environments . It also enables version control, improves development efficiency, and facilitates the transition from development to production .

Containers are orchestrated and managed using Kubernetes ⚙, which supports:

• Automated scaling

• Efficient management of large-scale apps

• Dynamic adjustments based on demand

By combining containerization and Kubernetes, AI-Stack boosts maintainability, scalability, and portability for AI applications.

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App Deployment Workflow

Here are the key steps to deploy and manage your application on AI-Stack:

1

Deploy Application – Define containers and specs

2

Deployment – Manage rollouts and scaling

3

Pods – Run and monitor your containers

4

Service – Provide stable network access

5

Secret – Store sensitive data securely

6

ConfigMap – Inject runtime config data

7

Volumes – Persist data across sessions

8

NetworkPolicy – Restrict pod communication

9

Ingress – Route external HTTP/HTTPS traffic

💡 Each of these will be covered in detail below. You can follow them step-by-step or jump to the section you need.

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