> ## Documentation Index
> Fetch the complete documentation index at: https://devdocs-shaunak-branch.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Kubernetes Platform

<Warning>This content is currently WIP. Diagrams, content, and structure are subject to change.</Warning>

Kubernetes serves as the robust foundation of the C3 Agentic AI Platform's infrastructure, providing powerful capabilities for deploying, scaling, and managing containerized services. This enterprise-grade orchestration system enables the platform to deliver consistent performance, reliability, and security across diverse deployment environments.

## Kubernetes as the foundation

The C3 Agentic AI Platform runs on Kubernetes, an industry-standard container orchestration system that automates the deployment, scaling, and management of containerized applications. This architecture provides several key benefits:

![Kubernetes Platform](https://mintlify.s3.us-west-1.amazonaws.com/devdocs-shaunak-branch/images/overview-c3-infrastructure-layer.svg)

The diagram above shows how the C3 AI Infrastructure Layer uses Kubernetes to manage resources. This containerized approach enables:

* **Consistent deployment** across cloud providers and on-premises environments
* **Automatic scaling** based on workload demands
* **Self-healing capabilities** that recover from failures
* **Resource optimization** through efficient allocation of compute resources

## Core components

The C3 Agentic AI Platform on Kubernetes consists of several key components that work together:

<CardGroup cols={2}>
  <Card title="Containerized services">
    Each functional component of the C3 Agentic AI Platform runs as a containerized service, enabling independent scaling and updates.
  </Card>

  <Card title="Persistent storage">
    Kubernetes persistent volumes store application data, ensuring data survives container restarts and migrations.
  </Card>

  <Card title="Service mesh">
    Manages service-to-service communication, providing load balancing, service discovery, and security features.
  </Card>

  <Card title="Ingress controllers">
    Route external traffic to the appropriate services within the Kubernetes cluster.
  </Card>
</CardGroup>

## Deployment models

The C3 Agentic AI Platform supports multiple deployment models to meet different organizational needs:

### Cloud deployments

The platform can be deployed on major cloud providers including AWS, Azure, and Google Cloud. Each deployment leverages cloud-native services while maintaining a consistent application experience:

* **AWS deployments** use EKS (Elastic Kubernetes Service) with integration to services like S3, RDS, and CloudWatch
* **Azure deployments** use AKS (Azure Kubernetes Service) with integration to Azure Blob Storage, Azure SQL, and Azure Monitor
* **Google Cloud deployments** use GKE (Google Kubernetes Engine) with integration to Cloud Storage, Cloud SQL, and Cloud Monitoring

### On-premises deployments

For organizations with specific security or compliance requirements, the C3 Agentic AI Platform can be deployed on-premises:

* Uses the same Kubernetes architecture as cloud deployments
* Supports enterprise Kubernetes distributions like Red Hat OpenShift
* Integrates with existing storage and networking infrastructure
* Provides consistent management interfaces across deployment models

## Resource management

Kubernetes enables efficient resource management for the C3 Agentic AI Platform:

### Compute resources

The platform allocates CPU and memory resources based on workload requirements:

* **Request-based allocation** ensures each component has the resources it needs
* **Limit-based protection** prevents any single component from consuming excessive resources
* **Quality of Service (QoS)** classes prioritize critical services during resource contention

### Scaling mechanisms

The C3 Agentic AI Platform scales automatically to handle varying workloads:

* **Horizontal Pod Autoscaling (HPA)** adds or removes container instances based on CPU, memory, or custom metrics
* **Vertical Pod Autoscaling (VPA)** adjusts resource requests and limits based on actual usage
* **Cluster Autoscaling** adds or removes nodes to accommodate changing resource demands

For example, when processing data from thousands of wind turbines, the platform can automatically scale up data ingestion services to handle the increased load, then scale them back down when the processing is complete.

## Monitoring and health checks

Kubernetes provides robust mechanisms for monitoring the health of the C3 Agentic AI Platform:

### Pod health checks

Kubernetes uses two types of health checks to ensure services are functioning properly:

* **Liveness probes** detect when a service is running but unable to make progress, triggering a restart
* **Readiness probes** determine when a service is ready to accept traffic, preventing premature routing

### Resource monitoring

The platform includes comprehensive monitoring of resource usage:

* **Node-level metrics** track CPU, memory, disk, and network usage across the cluster
* **Pod-level metrics** monitor resource consumption of individual services
* **Application metrics** provide insights into the behavior of C3 Agentic AI Platform components

### Logging infrastructure

Centralized logging captures information from all platform components:

* **Container logs** collect output from application services
* **System logs** track Kubernetes events and operations
* **Audit logs** record administrative actions for security and compliance

## Disaster recovery and high availability

The Kubernetes architecture provides built-in resilience for the C3 Agentic AI Platform:

### High availability configurations

* **Multi-zone deployments** distribute workloads across multiple availability zones
* **Pod anti-affinity** ensures critical services run on different physical nodes
* **StatefulSet replication** maintains database and service state across instances

### Backup and recovery

* **Automated backups** of persistent data and configuration
* **Point-in-time recovery** capabilities for databases
* **Cross-region replication** for disaster recovery scenarios

## Security considerations

The C3 Agentic AI Platform on Kubernetes implements multiple layers of security:

* **Network policies** control communication between services
* **Role-Based Access Control (RBAC)** restricts administrative access
* **Secret management** securely stores and distributes credentials
* **Pod security policies** enforce container security best practices

## Related concepts

<CardGroup cols={3}>
  <Card title="Observability and Monitoring" href="/platform-architecture/observability-monitoring/overview">
    Learn about monitoring tools and practices for the C3 Agentic AI Platform.
  </Card>

  <Card title="Platform Architecture Fundamentals" href="/platform-architecture/how-the-c3ai-platform-works/c3-platform-architecture-fundamentals">
    Understand the architectural principles that structure the C3 Agentic AI Platform.
  </Card>

  <Card title="Platform Administration" href="/platform-architecture/platform-administration/overview">
    Explore administrative tasks for managing the C3 Agentic AI Platform.
  </Card>
</CardGroup>