Operations | Monitoring | ITSM | DevOps | Cloud

Missed the last Netdata updates? Here is what is new.

Modern distributed applications are composed of potentially hundreds of disparate services, all containing code from different internal development teams as well as from third-party libraries and frameworks with limited external visibility. Instrumenting your code is essential for ensuring the operational excellence of all these different services. However, keeping your instrumentation up to date can be challenging when new issues arise outside the scope of your existing logs.

ITSM, which stands for IT service management, is a strategy for delivering IT services and support to an organization, its employees, customers and business partners. ITSM focuses on understanding end users’ expectations and improving the quality of both IT services and their delivery. In the early days of computers, employees relied on the company IT department for help whenever a computer issue arose.

In in order to achieve DevOps success, you must measure how well your DevOps initiatives work. Tracking the right DevOps metrics will help you evaluate the effectiveness of your DevOps practices. In this article, I’ll explain many DevOps metrics, including their significance, the key metrics for various goals, and — best of all — tips for improving the score of each DevOps metric discussed here.

Microsoft's release of Windows 10 modernized how IT teams approach device management. Windows 10 is not a strict evolution of Windows 7 and 8. It’s an evolution of Windows Phone 8 and 10, where an MDM API was available to manage all aspects of a device, such as DLP, restrictions, software distribution and so on.

If there’s anything I’ve learned, monitoring data is the lifeblood of the business and a superpower for any IT practitioner. Monitoring allows organizations to react to changes, identify and recover, and understand the true health of the business.

Welcome to the second chapter of the handbook on Anomaly Detection for Time Series Data! This series of blog posts aims to provide an in-depth look into the fundamentals of anomaly detection and root cause analysis. It will also address the challenges posed by the time-series characteristics of the data and demystify technical jargon by breaking it down into easily understandable language. This blog post (Chapter 2) is focused on different types of anomalies.

SharePoint Online (SPO) has become a cornerstone for many organizations seeking a robust, scalable, and collaborative platform. It’s a place where teams can seamlessly work together, share documents, and enhance their workflow efficiency. However, while SPO offers a plethora of benefits, the cost associated with its usage can be a potential hurdle, especially for businesses with large volumes of data.

The shift in remote working has seen an increase in demand to utilize smartphones to host meetings, check emails and message colleagues on Microsoft Teams. Keeping up with this trend, the Kelverion team have created a mobile app version of our popular Self-Service Automation Portal, which previously has been a web-based solution typically used on a desktop device. The portal is available for iPhone devices and can be downloaded from iOS app store.

Industrial IoT (IIoT) machines and sensors generate valuable time series data. It’s impossible to derive the insights necessary to inform decisions as a company to produce or operate more efficiently without sending operational technology (OT) data to informational technology (IT) systems.