Operations | Monitoring | ITSM | DevOps | Cloud

Software services are at the heart of modern business in the digital age. Just look at the apps on your smartphone. Shopping, banking, streaming, gaming, reading, messaging, ridesharing, scheduling, searching — you name it. Society runs on software services. The industry has exploded to meet demands, and people have many choices on where to spend their money and attention. Businesses must compete to attract and retain customers who can switch services with the swipe of a thumb.

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.