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

Ten years ago NewRelic, DataDog, Splunk, Dynatrace and SolarWinds built tools we loved to use. They were easy to implement and solved problems quickly and efficiently. Each company was known primarily for a single, well-conceived product. NewRelic’s APM. Splunk’s log file analyzer. DataDog’s server monitor. SolarWinds’ network performance monitor. These companies were beloved by users during the 2000s. Fast forward to 2020 and the world is very different.

We are pleased to announce that all users can now benefit from having their stacks hosted on NVMe (Non-Volatile Memory Express) SSDs. NVMe is one of the newest high-performance networking technologies changing the landscape of scalable infrastructure and assisting in decreasing infrastructure costs on a revolutionary scale.

These days, “SIEM” (Security Information and Event Management) is all over the place. SIEM tools work by collecting data from multiple systems and noticing patterns in the data. This adds immediate value to the business by providing insights, security recommendations, and actionable intelligence. Despite being helpful tools for many companies, SIEM tools do have their drawbacks. This article will describe the four main ones and offer suggestions for how they might be overcome.

Google Cloud Platform (GCP) is a suite of cloud computing services for deploying, managing, and monitoring applications. A critical part of deploying reliable applications is securing your infrastructure. Google Cloud Audit Logs record the who, where, and when for activity within your environment, providing a breadcrumb trail that administrators can use to monitor access and detect potential threats across your resources (e.g., storage buckets, databases, service accounts, virtual machines).

So I've only been at Splunk for 8 months, and in the short amount of time I've been here, one of the most common questions I've been asked is “How do I get an alert when Splunk is not receiving logs?". As a matter of fact, if I had $0.05 each time I was asked this question, I would have $0.25! Surprisingly, with this being such an often-asked question, I haven't been able to find much documentation on how to accomplish this using the native features of Splunk.

Editor’s note: This is a follow up to a recent post on how to use Cloud Logging with containerized applications running in Google Kubernetes Engine. In this post, we’ll focus on how DevOps teams can use Cloud Monitoring and Logging to find issues quickly. Running containerized apps on Google Kubernetes Engine (GKE) is a way for a DevOps team to focus on developing apps, rather than on the operational tasks required to run a secure, scalable and highly available Kubernetes cluster.