The use of lightweight and portable containers is growing in popularity. In fact, according to a recent Gartner report, by 2023, more than 70% of global organizations will be running containerized applications in production.
With this growing popularity comes challenges in the area of monitoring. Container environments are inherently dynamic – containers are provisioned and de-provisioned across hosts based on business requirements and infrastructure load. This in turn means that your monitoring targets are no longer static.
Furthermore, the shift from monolithic to microservice architectures for enterprise applications complicates monitoring even more. You now have to be able to collect and correlate monitoring data for your applications from multiple containers across many hosts before you are able to make reliable decisions for alerting and troubleshooting.
Polaris automatically discovers containers as they come and go on each monitored host by continuously following their individual life cycles. Polaris comes with robust and configurable metric aggregations, application log monitoring, alerting and visualization functionality to continuously, reliably collect monitoring data from your containerized apps, non-containerized apps and container hosts in a uniform manner. By monitoring both hosts and containerized apps, Polaris can perform advanced correlations from data across the board. This provides the utmost level of real-time precision monitoring, troubleshooting and performance management.
In the following demo you will see the Polaris solution in action. The environment includes two Apache httpd docker containers representing frontend load balancers and one WebLogic Server container representing backend applications. For each one of the three containers, Polaris will dynamically follow its docker logs in order to collect metrics or events that interest us. For the frontend Apache containers, Polaris will collect and aggregate HTTP response codes and latencies by API endpoint. For the backend WebLogic Server container Polaris will collect and aggregate application error codes by application and severity. At the same time, Polaris will also monitor the egress throughput of the container host by network interface.
As you can see by this short demo, Polaris is a highly capable platform which can help your organization troubleshoot problems exhibited on frontend Load Balancers by correlating to backend application errors or host networking problems. This is all done in real time and can be added to a custom dashboard along with a number of other insightful metrics. To learn more about Polaris and see the platform in action, schedule a demo by submitting the form below.