![]() In this article, I will share how we built our ELK stack to monitor our own service performance. Ultimately, software service operations teams use these graphs to present their results. Then, the data needs to be shipped to Logstash, stored and aggregated in Elasticsearch, and then turned into Kibana graphs. Probes are required to run on each host to collect various system performance metrics. ![]() In order to use ELK to monitor your platform’s performance, a couple of tools and integrations are needed. So, I decided that I wanted to have one pane-of-glass to view performance metrics combined with all the events generated by the apps, operating systems, and network devices. To find that out, I had to jump between New Relic/Nagios and the ELK Stack. ![]() Very often, when I was troubleshooting performance issues, I saw a service that is or a couple of machines that are slowed down and reaching high-CPU utilization. This might mean that it lacks resources because of high load, but very often it means that there is a bug in the code, an exception, or an error flow that over-utilizes resources.
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