Kubernetes is an open-source platform designed to automate the deployment, scaling, and operation of application containers. It groups containers that make up an application into logical units for easy management and discovery. Kubernetes is used because it facilitates both declarative configuration and automation, enabling scalable, fault-tolerant, and distributed systems. It helps in maximizing hardware resources to run applications efficiently and supports a variety of containerization technologies.

A Kubernetes cluster is essential for orchestrating complex containerized applications, providing a robust framework for automating deployment, scaling, and operations. It enables:

1. High Availability: Ensures that applications are always accessible and can withstand failures of individual components.
2. Scalability: Automatically adjusts the number of running containers based on demand, improving resource utilization and efficiency.
3. Load Balancing: Distributes network traffic and workload efficiently across all containers to maintain optimal performance.
4. Automated Rollouts and Rollbacks: Facilitates the deployment of new versions of applications and automatically rolls back to the previous stable version in case of failure.
5. Self-healing: Automatically replaces or restarts failing containers to ensure the application continues to operate faultlessly.
6. Resource Optimization: Efficiently allocates and manages the computational resources among all the containers based on predefined policies.
7. Consistent Environment: Provides a consistent environment for development, testing, and production, ensuring that applications run the same regardless of where they are deployed.

By using a Kubernetes cluster, organizations can manage their containerized applications more effectively, making their infrastructure more flexible, scalable, and resilient.

In Kubernetes, a node and a cluster represent different components within the ecosystem, each serving a distinct role:

Node: A node is an individual machine, either physical or virtual, that serves as a host for running the containers. Each node contains the services necessary to run pods (groups of one or more containers) and is managed by the master components. It includes the container runtime, such as Docker or containerd, and the kubelet, which communicates with the master to receive commands and ensure the containers are running as expected.

Cluster: A cluster refers to a set of nodes grouped together. It’s the entire system that constitutes the Kubernetes platform, managing the orchestration of containers across multiple nodes. A cluster includes at least one master node (which controls and manages the scheduling of containers, maintaining the desired state, and managing cluster-wide networking) and multiple worker nodes (where the actual containers are run). The cluster ensures that resources are used efficiently and that the application remains available, even if individual nodes fail.

In summary, the node is the individual worker machine hosting containers, while the cluster is the complete set of nodes managed as a single entity, providing the high availability, scalability, and distributed nature of the Kubernetes platform.

The Kubernetes Cluster solution is available for automatic installation via platform Marketplace under the Clusters category (or use Search to locate).

Within the opened installation frame, customize the available options to get a cluster specifically for your needs:

• Version – choose a Kubernetes version for your cluster
• K8s Dashboard – select between the v2 and Skooner options (note that some metrics in the skooner dashboard don’t work with the HAProxy ingress controller)
• Topology
  • Development – one control-plane (1) and one scalable worker (1+)
  • Production – multi control-plane (3) with API balancers (2+) and scalable workers (2+)
    Note: The development topology is not recommended for production projects as it cannot handle high load reliably due to a single control-plane instance.
• Ingress Controller – choose the preferable ingress controller for your cluster (NGINX, Traefik, or HAProxy). We recommended using NGINX as it provides the most flexibility
• Deployment
  • Clean cluster with pre-deployed HelloWorld example
  • Custom helm or stack deployed via shell command – chose this option to manually provide commands for custom application deployment from the helm repository
• NFS Storage – enable to attach a dedicated NFS Storage with dynamic volume provisioning (disable if you want to register own storage class, requires in-depth K8s knowledge)
• Modules (can be enabled later via the add-ons)
  • Prometheus & Grafana – check to install these monitoring tools (recommended). This deployment requires an additional 5GB of disk space for persistent volumes and consumes about 500 MB of RAM
  • Jaeger Tracing Tools – tick to install Jaeger tracing system for monitoring and troubleshooting
  • Remote API Access – check if you plan on using the kubectl command-line tool or some other remote clients
• Environment – provide a name for your environment
• Display Name – specify an alias
• Region – choose a region (if available)

Click Install and wait a few minutes for the platform to automatically configure your Kubernetes cluster.

Affordable Kubernetes cluster hosting is achievable through several strategies:

Pay-Per-Usage Pricing: Opt for providers that offer pay-per-usage pricing, allowing you to pay only for the resources you consume. This model can significantly reduce costs compared to fixed pricing models.
Auto-Scaling: Utilize auto-scaling capabilities to adjust resources automatically based on demand. This ensures you’re not paying for idle resources during low traffic.
Choose the Right Plan: Assess your needs and choose a hosting plan that matches your usage patterns. Some providers offer plans optimized for small to medium-sized deployments, which can be more cost-effective.
Managed Services: Consider managed Kubernetes services. While there might be a premium, they often come with optimizations and management features that can reduce overall costs by improving efficiency.

Our on-demand pricing model for Kubernetes cluster hosting ensures that you have complete control over your expenses and only pay for what you actually use. Here’s how our pricing works:

• Resource-Based Billing: Charges are based on the computing resources (CPU, memory, storage) and network bandwidth consumed by your cluster.
• No Hidden Fees: Transparency is key to our pricing model. We provide detailed breakdowns of costs, so you know exactly what you’re paying for.
• Estimation Tools: Use our online calculator to estimate your costs based on your anticipated resource usage. This tool can help you budget more effectively and make informed decisions about scaling your operations.

Kubernetes cluster on-demand pricing in general refers to a billing model where you pay for compute resources on an as-needed basis. Key points include:

1. Flexibility: On-demand pricing offers the flexibility to scale resources up or down based on actual usage, ideal for applications with variable workloads.
2. Cost-Effective: Only pay for the resources you use, making it a cost-effective option for startups and businesses looking to optimize their operational costs.
3. No Long-Term Commitments: This pricing model typically does not require long-term contracts or commitments, allowing businesses to adapt quickly to changing needs.
4. Immediate Access to Resources: On-demand resources are available immediately, enabling quick scaling during traffic spikes without prior planning or reservation.

Our on-demand pricing is designed to adapt to your project’s needs, offering flexibility and scalability without locking you into long-term contracts or flat-rate fees.