Operations | Monitoring | ITSM | DevOps | Cloud

In previous posts we covered why it’s important to monitor APIs and how to monitor and validate data from APIs. In this post we’ll focus on a simple but key feature that helps Splunk Synthetic Monitoring users create robust checks for availability, response time, and multi-step processes: Request Headers

There is a lot of buzz in the world of machine learning (ML) and as a layperson it can be hard to keep up with it all. Therefore, we decided to write down some of our thoughts and musings on how we are approaching ML at Netdata. We’ll touch on the current state of applied ML in industry in general, and zoom in on ML in the monitoring industry.

GraphQL is a query language for APIs developed by Facebook in 2012. It was then open-sourced in 2015. GraphQL enables frontend developers or consumers of APIs to request the exact data that they need, with no over-fetching or under-fetching. In this article, we will learn how to monitor GraphQL APIs with the open-source APM tool, SigNoz. GraphQL has become a popular alternative to REST because of its ease of use. It enables developers to pull data from multiple data sources in a single API call.

Users of open-source log collectors and log monitoring solutions often preferred these solutions due to them being well suited for speed, flexibility and their ability to attract talented contributors who are willing to invest time to maintain technology projects they are passionate about. In this post, we’ll look at some of the best free and open-source logging tools out there today.

The question of how to get data into a database is one of the most fundamental aspects of data processing that developers face. Data collection can be challenging enough when you’re dealing with local devices. Adding data from edge devices presents a whole new set of challenges. Yet the exponential increase in IoT edge devices means that companies need proven and reliable ways to collect data from them.