Open Source

A Guide to Open Source Monitoring Tools

Open source is one of the key drivers of DevOps. The need for flexibility, speed, and cost-efficiency, is pushing organizations to embrace an open source-first approach when designing and implementing the DevOps lifecycle. Monitoring — the process of gathering telemetry data on the operation of an IT environment to gauge performance and troubleshoot issues — is a perfect example of how open source acts as both a driver and enabler of DevOps methodologies.


Introducing 'MLWatcher', Anodot's Open-Source Tool For Monitoring Machine Learning Models

Machine Learning (ML) algorithms are designed to automatically build mathematical models using sample data to make decisions. Rather than use specific instructions, they rely on patterns and inference instead. And the business applications abound. In recent years, companies such Google and Facebook have found ways to use ML to utilize the massive amounts of data they have for more profit.


Things You Need to Know About Open Source - The FAQ Edition

Open Source projects can be a great asset, or they can be a curse – it’s all in how you manage it. To be successful in using open source, there are several things to keep in mind, from licensing to updates. And if you ignore any of them, it can cause problems. Here are some things to consider. and Microsoft Azure: A Proud Partnership in Open Source

Today, I’m excited to announce a partnership between and Microsoft Azure. With this partnership, is now offering Azure customers a fully managed, scalable machine data analytics platform built on ELK and Grafana. What does that mean? Azure customers can now easily deploy, run, and scale ELK without the hassle and pain of maintaining and managing the stack themselves.