When Grafana Labs CEO and co-founder Raj Dutt announced to the team that the company would be relicensing our core open source projects from Apache 2.0 to AGPLv3, he opened the floor for discussion and encouraged anyone who had further questions to reach out. We believe in honesty and transparency, so we collected hard questions from Grafanistas, and Raj answered them for this public Q&A. The time felt right. As I’ve said publicly before, I’ve been thinking about this topic for years.

Grafana Labs was founded in 2014 to build a sustainable business around the open source Grafana project, so that revenue from our commercial offerings could be re-invested in the technology and the community. Since then, we’ve expanded further in the open source world — creating Grafana Loki and Grafana Tempo and contributing heavily to projects such as Graphite, Prometheus, and Cortex — while building the Grafana Cloud and Grafana Enterprise Stack products for customers.

Technology has accelerated changes toward information-based healthcare delivery and management. Today’s multi-disciplinary approach to delivering better healthcare outcomes coupled with advanced imaging and genetic-based customized treatment models depend on AI/ML driven information systems. At Robin.io, we believe machine learning is the life-saving technology that will transform healthcare. AI/ML challenges the traditional, reactive approach to healthcare.

‍Resilience in Action is a podcast about all things resilience, from SRE to software engineering, to how it affects our personal lives, and more. Resilience in Action is hosted by Kurt Andersen. Kurt is a practitioner and an active thought leader in the SRE community. He speaks at major DevOps & SRE conferences and publishes his work through O'Reilly in quintessential SRE books such as Seeking SRE, What is SRE?, and 97 Things Every SRE Should Know.

A common challenge in data engineering is to combine traditional data warehousing and BI reporting with experiment-driven machine learning projects. Many data scientists tend to work more with Python and ML frameworks rather than SQL. Therefore, their data needs are often different from those of data analysts. In this article, we’ll explore why having a data lake often provides tremendous help for data science use cases.

Back in December, Amazon Web Services (AWS) and Grafana Labs partnered to launch the Amazon Managed Service for Grafana in a preview to a limited set of customers. Amazon Managed Service for Grafana is a scalable managed offering that provides AWS customers a native way to run Grafana directly within AWS alongside all their other AWS services.

Telecom companies monitor their network using a variety of monitoring tools. There are separate fault management and performance management platforms for different areas of the network (core, RAN, etc.), and infrastructure is monitored separately. Although these solutions monitor network functions and logic – something that would seem to make sense — in practice this strategy fails to produce accurate and effective monitoring or reduce time to detection of service experience issues.

Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week we explore the rising scope of location intelligence in improving the overall customer experience.

Why we felt there was a need for a full stack open source observability platform and how we went about building it.

In the last blog post, I walked you through how to connect to the Microsoft Graph API so you can start pulling in the M365 analytics to create a dashboard in SquaredUp. In this blog post, I’ll walk you through exactly how to create this dashboard. This dashboard will allow you to monitor key metrics for Microsoft 365 SharePoint, Exchange Online, and Teams so you can be proactive in assigning storage.