Operations | Monitoring | ITSM | DevOps | Cloud

Modern businesses rely on a complex ecosystem of digital networks, databases, applications, user devices, and more. The tools and platforms supporting this ecosystem undergo constant refinement and upgrades. However, the basic methods for monitoring infrastructure and application performance have remained unchanged, and logging is one such methods. Every computer, server, networking device, and application produces logs, a timestamped record of events within a system.

The Stack Infra team at Elastic uses many services to provide downloads for projects like Elasticsearch and Kibana to our users. One of these services is Fastly, which helps us optimize delivery to regions around the world. Keeping an eye on the performance and behavior of our CDN is important to ensure we're operating at the level we expect.

Last week, the first OpenObservability conference took place. This event had amazing content contributions from open source project leaders, users, and influencers. We’ve seen massive growth and adoption in the open source observability space from the inspiring work being done across tracing, logging, and especially metrics. The new data stores and capabilities are growing at breakneck speed. There are more choices— yet more complexity—than ever before.

At STRABAG, we are using Elastic Cloud Enterprise (ECE) for two main use cases within our on-premises web applications. One to power different kinds of search and a second for operations where we ship more than 25,000 log entries per minute to Elastic from our load balancers. The ECE platform runs in an air-gapped environment, and we would still like to be able to use our corporate logins for the ECE platform.

Logs are an important part of troubleshooting and it’s critical to have them when you need them. When it comes to logging, Google Kubernetes Engine (GKE) is integrated with Google Cloud’s Logging service. But perhaps you’ve never investigated your GKE logs, or Cloud Logging? Here’s an overview of how logging works in GKE, and how to configure, find, and interact effectively with the GKE logs stored in Cloud Logging.

This post is the second in our series on system metrics where we cover: In the previous post, we went through some built-in tools and methods for identifying key metrics and values on your systems. In this post, we'll provide a tutorial on how to use Metricbeat to consolidate metrics, store and analyze them in the long term, and discuss some of the benefits of a centralized metric store.