Clusters

Clusters, which represent your Kubernetes clusters, are the foundational units within the PDS platform. They consist of groups of servers, often referred to as instances, that work together to manage, store, and process data. This collaborative approach enables clusters to provide high availability, scalability, and fault tolerance for the data services running on them.

For more information about the Clusters interface in PDS and the procedures to connect your clusters and manage them, see Clusters.

Components of clusters

• Instances: Individual servers that form the building blocks of a cluster. Each node contributes its CPU, memory, and storage resources to the cluster.
• Control Plane: Manages the overall state and operation of the cluster, including scheduling of workloads, monitoring, and maintaining cluster health.
• Data Plane: Handles the actual storage, retrieval, and management of data across the nodes in the cluster. Clusters Overview

Clusters overview

This section in the PDS UI provides a comprehensive summary of all clusters managed within the platform. This section is crucial for administrators and operators to monitor and manage the connection and performance of their clusters. Key details include, whether a cluster is connected to the control plane or not. The Details section displays the Portworx Enterprise and agent versions installed, the PDS operator version, and the status of Portworx agent and security.

Example: In a large enterprise, the Clusters Overview might show multiple clusters such as Development Cluster, Staging Cluster, and Production Cluster, each with different health statuses and resource usage patterns. This allows the IT team to quickly identify which environments are running smoothly and which might need attention.

Namespaces

Namespaces are a critical feature for organizing and isolating resources within a cluster. They provide a logical separation of resources, making it easier to manage applications and data services independently.

• Isolation: Namespaces ensure that resources and workloads in one namespace do not interfere with those in another. This is particularly useful for multi-tenant environments where different teams or departments need isolated environments.
• Resource quotas: Administrators can set resource limits on namespaces to control the amount of CPU, memory, and storage that can be consumed. This helps in preventing any single application or service from monopolizing cluster resources.
• Access control: Namespaces can have specific access controls, ensuring that only authorized users and services can interact with the resources within a namespace.

Example: An organization might create namespaces for different departments such as HR, Finance, and Engineering. Each department can manage its applications and data services within its namespace without affecting the others. The Engineering namespace might have more resources allocated to it due to its higher demand for processing power and storage, while the HR namespace might have tighter access controls to protect sensitive employee data.

Cluster usage example

Consider an organization with the following environments:

Development cluster

• Purpose: Used for developing and testing new features.
• Characteristics: May have frequent changes, experimental configurations, and non-critical data.
• Namespaces: Separate namespaces for different projects or teams to avoid conflicts and manage resources effectively.
• Resource allocation: Moderate resources, but flexible to accommodate various development needs.
• Monitoring: Focus on identifying bugs and performance issues before features are moved to staging.

Production cluster

• Purpose: Hosts live applications serving end-users.
• Characteristics: Stable configurations, optimized for performance and reliability, handling critical and real-time data.
• Namespaces: Isolated namespaces for different services such as Web, Database, and Analytics to ensure smooth operation and security.
• Resource Allocation: High resources with redundancy and failover mechanisms to ensure high availability.
• Monitoring: Continuous monitoring for uptime, performance metrics, and quick issue resolution.

Staging cluster

• Purpose: Intermediate environment between development and production for final testing.
• Characteristics: Mirrors production environment closely to catch issues that may not appear in development.
• Namespaces: Similar to production to ensure the transition is seamless.
• Resource Allocation: Adequate resources to simulate production loads.
• Monitoring: Focus on performance testing and pre-deployment checks.

In this scenario, the organization leverages the PDS platform's clustering capabilities to maintain a structured, efficient, and secure environment for their software lifecycle. By using clusters and namespaces strategically, they ensure that their development, testing, and production processes are well-organized, resource-efficient, and secure. This approach enhances productivity and minimizes the risk of deployment issues.