Elastic

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Monitoring Microsoft SQL Server using Metricbeat and Elasticsearch

We are pleased to introduce support for Microsoft SQL Server as part of our generally available Metricbeat modules to capture database metrics. Microsoft SQL Server has been a popular and successful SQL database over the years, and we are really excited about this new addition to the Metricbeat family.

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Scaling Elasticsearch on a hyper-converged infrastructure at IHG

InterContinental Hotels Group, or IHG, is a multinational hospitality company that operates over 5,000 hotels in nearly 100 countries around the globe. IHG’s global technology organization, based in Atlanta, GA, has about 13,000 corporate employees, many of whom are using Elastic to do their jobs. With the success and continued adoption of IHG’s Elastic platform across the company, IHG has explored interesting ways of scaling its infrastructure, most notably the shift to hyper-converged.

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Monitoring MySQL, Percona Server, and MariaDB with the Elastic Stack

Databases are a fundamental keystone of most applications, and there are many options for many different use cases. Even a single database can be used in a variety of ways, but regardless of the database type, implementation, or use case, the need for a good solution for monitoring them remains a common denominator. Databases keep the most precious information of any company, and any hiccup can be a reason for alarm.

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Improving speed and reliability with the Elastic Stack and Elastic Cloud Enterprise

CSG International is a multinational corporation headquartered in Greenwood Village, Colorado. Although historically a cable and satellite billing company, in recent years CSG has sought to expand into the digital services realm. In 2015, CSG launched Ascendon, a cloud-based platform that helps companies offer digital services — from live-streamed sporting events and concerts to seamless shopping experiences — to consumers.

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Analysing Linux auditd anomalies with Auditbeat and machine learning

Auditbeat is an extremely popular Beat that allows you to collect Linux audit framework data to monitor processes running on Linux systems. It has the ability to stream a multitude of information — from security-related system information, to file integrity data, to process information — from the Linux auditd framework.

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User annotations for Elastic machine learning

User annotations are a new machine learning feature in Elasticsearch available from 6.6 onwards. They provide a way to augment your machine learning jobs with descriptive domain knowledge. When you run a machine learning job, its algorithm is trying to find anomalies — but it doesn’t know what the data itself is about. The job wouldn't know, for example, whether it was dealing with CPU usage or network throughput.