Operations | Monitoring | ITSM | DevOps | Cloud

As Elasticsearch users are pushing the limits of how much data they can store on an Elasticsearch node, they sometimes run out of heap memory before running out of disk space. This is a frustrating problem for these users, as fitting as much data per node as possible is often important to reduce costs. But why does Elasticsearch need heap memory to store data? Why doesn't it only need disk space?

Let’s be honest. No one wakes up in the morning thinking of reasons to contact customer support. It’s tedious, onerous, and can eat into your evening Netflix time. Thankfully, most brands realize that customer experiences drive brand loyalty and repeat purchases.

Binary classification aims to separate elements of a given dataset into two groups on the basis of some learned classification rule. It has extensive applications from security analytics, fraud detection, malware identification, and much more. Being a supervised machine learning method, binary classification relies on the presence of labeled training data that can be used as examples from which a model can learn what separates the classes.

To achieve unified observability, we need to gather all of the logs, metrics, and application traces from an environment. Storing them in a single datastore drastically increases our visibility, allowing us to monitor other distributed environments as well. In this blog, we will walk through one way to set up observability of your Kubernetes environment using the Elastic Stack — giving your team insight into the metrics and performance of your deployment.

Six months ago we celebrated the joining of forces between Endgame and Elastic under the banner of Elastic Security and announced the elimination of per endpoint pricing. Simultaneously, while the newest members of Elastic Security were getting acquainted with the Elastic SIEM team, a few of our analysts were locked away in an office at MITRE HQ for round 2 of MITRE’s APT emulation.