Operations | Monitoring | ITSM | DevOps | Cloud

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.

We hosted our first ever virtual Elastic{ON} Gov Summit with one primary goal: recreate the collaboration and community-building we normally enjoy at our in-person Gov Summit in a new, virtual format. And we were humbled to be able to do just that. The event gathered more than 2,000 registered attendees from across government agencies and partners to collaborate while so many of us were social distancing across the nation.

We're happy to announce that we have just launched our improved integration for the Azure Event Hub, allowing DevOps & Security professionals to send log data for analysis easier than ever. This announcement comes as Microsoft’s Azure Event Hub reaches its highest global popularity as a data ingestion service. The integration ensures best-in-class performance across a variety of use cases using Azure.

Data visualisations allow users to organise and present log data in a practical, usable, and sensible manner. This tool in log management ensures that the data collected communicates real-time, actionable insights that will support timely and informed decision-making. Knowing which types of visualisation best suits a particular data set is critical in giving data visualisation optimal business value. Here is how to pick the right type of log data visualisation. Pie charts