Back

Top 7 best practices for monitoring your OpenShift environment

OpenShift monitoring


Red Hat OpenShift is an open-source container platform that provides a complete environment for developers to create, launch, and manage applications in both cloud and on-premises settings, leveraging the potential of container technology.

With increasing popularity in container orchestration, OpenShift's strong scalability and features attract developers and IT experts. Nonetheless, the intricacy and changing aspects of OpenShift setups demand a tailored strategy for monitoring and observation.

In this blog, we will explore the significance of monitoring OpenShift, the typical problems that arise when it is not monitored, and the most effective methods for monitoring it, leading to a more efficient and secure platform. This blog is an excerpt from our extensive whitepaper, A guide to monitoring OpenShift environments.  

Why should you monitor OpenShift? 

Monitoring OpenShift is essential for maintaining smooth operation of container-based applications. Effective monitoring enables IT administrators to oversee and manage all deployments, proactively identifying and addressing potential issues before they escalate.


Some common issues faced when OpenShift is left unmonitored
  • Deployment failures: Unmonitored deployment issues can halt operations.
  • Performance bottlenecks: Problems may arise from CPU, memory, disk usage, network latency, or I/O bottlenecks.
  • High CPU utilization: Overuse of CPU resources may hinder application deployment.
  • Lost workloads: The dynamic changes that happen within workloads can cause tracking issues.
  • Log management: Aggregating and analyzing logs from multiple sources can be challenging.
  • Security: Ensuring security within OpenShift is complex but vital.
Key benefits of monitoring OpenShift
  • Maintaining stability and efficiency: Regular tracking of resource consumption, application efficiency, and system well-being helps avoid interruptions.
  • Faster troubleshooting: Quick identification and resolution of issues minimizes downtime and enhances user satisfaction.
  • Optimized resource management: Ensuring resources are appropriately allocated prevents bottlenecks and improves performance.

Seven tips for a healthy OpenShift environment 

To ensure your OpenShift environment is healthy and stable, consider these seven tips:

1. Observability

OpenShift’s built-in monitoring system offers a good start but may not suffice for comprehensive analysis. Choose a monitoring solution that integrates AI intelligence for more profound insights and minimal manual intervention. OpenShift observability entails not only monitoring metrics but also tracing and logging, which helps detect anomalies and resolve issues. OpenShift observability lets you dive into your environment and delve deep into your applications, so you can pinpoint issues and expose vulnerabilities.


2. High availability 

Ensure your OpenShift platform is available at all times. Your monitoring tool is invaluable during these periods. Utilize node redundancy, multiple pod replicas, and load balancing. Regularly back up your monitoring data and configurations, and adjust your monitoring setup to accommodate environmental changes. Make sure that the monitoring tool you employ is highly accessible. This is crucial to avert the possibility of losing sight of your workloads during disruptions.

3. Critical metrics for resource utilization 

Monitor critical metrics such as CPU and memory usage, disk capacity, and network statistics at the cluster, node, pod, namespace, and container levels and also at the individual workload levels. Understanding these metrics helps rectify discrepancies swiftly. Check out our whitepaper for more insights into the critical metrics to monitor in OpenShift.

4. Customized monitoring setup 

Every organization has its own unique IT setup. Alter and repurpose the monitoring stack to fit your specific requirements. Create custom dashboards and reports to visualize critical components and set customized thresholds for alerts.


5. AIOps integration 

Utilize AI intelligence to foresee resource consumption and adjust accordingly. Incorporating observability enhanced with AIOps facilitates the detection and analysis of problems promptly, offering a more comprehensive understanding of your environment.

6. Automate remedial actions 

Set up automation rules for scenarios like traffic spikes to maintain performance. Automate recurring tasks and issue resolutions to ensure reliability and productivity. Use alerts to stay informed about potential issues.

7. Security 

Implement security monitoring to track potential threats. Monitor system configurations, assign checks  for various components, and follow guiding principles to ensure a secure platform.

Beyond basic monitoring 

Explore Site24x7’s OpenShift observability solution, powered by AI. Go beyond basic monitoring with proactive anomaly detection, resource management, and high availability. Gain insights into specific pods and containers, plan capacity based on forecast data, and ensure optimal resource usage. Create custom dashboards, get alerted via multiple tools, and safeguard your OpenShift environment with comprehensive monitoring and security measures.

By adhering to these optimal practices, your OpenShift environment can achieve peak performance and availability, ensuring a smooth, efficient, and secure operational experience. For more comprehensive information on OpenShift monitoring and Observability, please refer to our whitepaper, A guide to monitoring OpenShift environments. 

Comments (0)