Effective Monitoring of Cloud Pak for Integration on OpenShift with Instana

Here in this blog, we will learn about effective monitoring of cloud pak for integration on open shift with Instana

Red Hat OpenShift makes it easy to deploy and manage applications. But because containerized environments change rapidly, you need advanced monitoring to keep workloads running smoothly. Instana provides detailed insights into OpenShift workloads, from compute resources to networking.

Instana monitors OpenShift by tracking cluster health, node performance, container metrics, application workloads, networking, and middleware services. It provides insights into resource usage, service mesh, persistent storage, and network policies. Additionally, it offers distributed tracing, security compliance, and custom metrics/log integration for comprehensive visibility and troubleshooting.

CP4I Components Monitoring

IBM API Gateway (DataPower)

Instana checks DataPower’s request and response times, throughput, and error rates. You can monitor resource utilization, such as CPU, RAM, and connection pools, to ensure that the gateway runs smoothly. It also offers information on policies used for security, routing, and data transformation.

IBM API Connect

API Connect metrics measure API traffic and performance. Instana monitors request and response times, success and failure rates, and latency. You may examine usage patterns, monitor security and transformation policies, and track API key and subscription activity. Alerts for authentication failures or gateway timeouts can help you handle problems promptly.

IBM App Connect

Instana’s App Connect monitors integration flows, providing data on execution times, success and failure rates, and the health of connectors that connect your applications to services. Resource utilization for deployed integration servers, such as CPU and memory, is monitored, and detailed error logs reveal mapping or connectivity issues.

IBM MQ

Instana helps IBM MQ understand message flow and dependability. It monitors queue depths, message rates, and transaction success to ensure that messages arrive as expected. Channel health measures, such as status and throughput, contribute to stable communication. Errors such as dead-letter queue use or message expiration are marked for rapid attention