OpenShift Architecture Considerations
Red Hat OpenShift is an enterprise container platform based on Kubernetes, offering simplified application development, deployment, and management. It provides tools for container orchestration, scaling, networking, storage, and security, with added features and enterprise-grade capabilities.
When architecting a OpenShift, environment there are several considerations to keep in mind to optimize performance and ensure efficient resource utilization. Here are some common architecture decisions:
Bare Metal vs Virtual Machines
There are considerations when running OpenShift on bare metal compared to virtual machines. Running OpenShift on bare metal requires dedicated hardware infrastructure. Bare metal deployments allow for more efficient utilization of hardware resources since there is no overhead from virtualization layers. This can result in improved performance and reduced resource contention. Bare metal deployments provide stronger isolation between workloads, as there is no shared hypervisor layer. This can be advantageous for security and compliance requirements. Running OpenShift on virtual machines allows for more flexibility in resource allocation and consolidation of workloads. Virtualization enables the efficient use of hardware resources by running multiple virtual machines on a single physical server. With virtual machines, resources can be shared among multiple workloads. However, this can also introduce resource contention if not properly managed. Ensure proper resource allocation and monitoring to avoid performance degradation. Virtual machines offer features like live migration, which allows moving workloads between hosts without downtime. This feature can enhance high availability and ease maintenance operations. Virtualization introduces some level of overhead due to the hypervisor layer, which can impact performance compared to bare metal deployments. Monitoring and optimizing resource allocation are important to mitigate any potential performance impact. Ultimately, the choice between running OpenShift on bare metal or virtual machines depends on specific requirements, infrastructure capabilities, and trade-offs between performance, flexibility, scalability, and security. Organizations need to evaluate their specific needs and consider these factors when deciding on the deployment approach.
Node Sizing
Properly size your OpenShift cluster nodes based on the expected workload. Consider the number of pods, containers, and expected resource utilization. Ensure that the nodes have sufficient CPU, memory, and storage capacity to handle the workload.
Pod Placement
Utilize OpenShift's scheduling capabilities to ensure efficient pod placement. Take advantage of labels, selectors, and node affinity/anti-affinity rules to distribute workloads across the cluster nodes and achieve optimal resource utilization. Avoid placing pods with conflicting resource requirements on the same node. When building nodes, choose the appropriate number of worker and infrastructure nodes. Some applications will require a minimum of three pods spread across three nodes. Limiting the environment to just three nodes can impact maintenance and downtime activities.
Persistent Storage
Consider the storage requirements of your applications, especially those that require persistent storage. Evaluate different storage options available in OpenShift, such as local storage, network-attached storage (NAS), or distributed storage systems, and choose the most suitable option based on performance, scalability, and reliability needs.
OpenShift Router Tuning
If you are using the OpenShift Router for external traffic routing, consider tuning its parameters to optimize performance. Adjusting the maximum number of connections, timeout values, and other configuration options can improve the router's efficiency. The OpenShift Router (based on HAproxy) is the default and most commonly used load balancer in OpenShift. It is based on the HAProxy load balancer and provides HTTP(S) routing for applications within the cluster. The OpenShift Router routes traffic to the appropriate pods based on hostname, path, or other routing rules defined in route objects. OpenShift can integrate with external load balancers, both software-based and hardware-based. These load balancers sit outside the cluster and distribute traffic to the OpenShift services. Examples of external load balancers commonly used with OpenShift include F5 BIG-IP, Citrix ADC, and NGINX Plus. Ingress controllers provide advanced routing and load balancing capabilities for OpenShift. They act as an entry point for external traffic to reach services within the cluster. Popular ingress controllers used with OpenShift include NGINX Ingress Controller, Traefik, and Istio's Gateway. OpenShift can also utilize Istio, a service mesh, which provides advanced traffic management, load balancing, and observability capabilities. Istio uses its own built-in load balancing mechanisms to distribute traffic among the services within the cluster.
Image Management
Effectively manage your container images to minimize storage usage and improve deployment times. Employ image registries, such as Red Hat Quay, to store and distribute container images efficiently. Consider using image streams and image pruning strategies to keep your image repository organized and avoid unnecessary overhead. If possible, keep your image repositoires (or a cache) close to your cluster from a network perspective. This will shorten redeployment and refresh times.
Documentation
Keep yourself updated with the latest Red Hat OpenShift documentation, release notes, and best practices. Red Hat provides comprehensive documentation and resources to help you understand various tuning options specific to your OpenShift version.
Remember, the architecture considerations may vary depending on your specific use cases, workload characteristics, and infrastructure setup. It's always recommended to perform thorough testing and benchmarking to validate the effectiveness of tuning changes in your particular environment.
