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The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.

Introducing Relational Fields

We’re excited to bring you relational fields, a new feature that allows you to query spans based on their relationship to each other within a trace. Previously, queries considered spans in isolation: You could ask about field values on spans and aggregate them based on matching criteria, but you couldn’t use any qualifying relationships about where and how the spans appear in a trace.

Lessons learned from running a large gRPC mesh at Datadog

Datadog’s infrastructure comprises hundreds of distributed services, which are constantly discovering other services to network with, exchanging data, streaming events, triggering actions, coordinating distributed transactions involving multiple services, and more. Implementing a networking solution for such a large, complex application comes with its own set of challenges, including scalability, load balancing, fault tolerance, compatibility, and latency.

Going green: How to monitor your cloud carbon footprint using Kepler, Prometheus, and Grafana

At this point, the technical and operational benefits of cloud computing are pretty much indisputable. But the cloud industry, as a whole, still has a long way to go in one critical area: sustainability. In fact, as shocking as it may sound, it’s estimated that cloud data centers have a greater carbon footprint than the entire aviation industry. Ida Fürjesová and Niki Manoledaki, both software engineers at Grafana Labs, are passionate about helping to change that.

Significance of SQL Query Consumption Analysis

In the digital era, where data reigns supreme, the ability to extract meaningful insights from vast datasets has become indispensable. Though we have many data sources and data processing languages, SQL (Structured Query Language) stands as a cornerstone in this realm, empowering analysts, and data scientists to navigate through intricate databases with ease.

10 Hottest Network Monitoring Support Topics

Network monitoring is perhaps the most indispensable tool in a network professional’s toolbox because it offers a deep understanding of IT infrastructure. Many IT pros use network monitoring daily the same way a teenager stares for hours at TikTok. Progress WhatsUp Gold has been making IT lives easier since its beta release in 1996. Here are the ten most popular how-to videos to help you make the most out of WhatsUp Gold.

The Top 15 Real-Time Dashboard Examples

Monitoring your data with dashboards and visualizations is perfect for improving the efficiency of your team and facilitating data-driven decisions from insights. They provide a different perspective to your data and by utilizing this data and trends you can clearly view if your system, application, or server is performing optimally, and if it isn’t performing as expected you can analyze where the issue is and promptly rectify this.

IaC? CI? Shift Left? What do they really mean? - A DevOps Glossary

Look, we've all been there: there's a term, you've heard it one hundred times. You've nodded as others said it in meetings. And now, you've started to say it. The only tiny insignificant problem is that you're not 100% sure what it actually means or how it's different from another similar term. I feel you. So I wrote this DevOps glossary with my highly opinionated definitions of common DevOps industry terms.

Jaeger vs Tempo - key features, differences, and alternatives

Both Grafana Tempo and Jaeger are tools aimed at distributed tracing for microservice architecture. Jaeger was released as an open-source project by Uber in 2015, while Tempo is a newer product announced in October 2020. Jaeger is a popular open-source tool that graduated as a project from Cloud Native Computing Foundation. Grafana Tempo is a high-volume distributed tracing tool deeply integrated with other open-source tools like Prometheus and Loki.

Sumo Logic Flex Pricing: Is usage pricing a good idea?

When discussing observability pricing models, there are three dimensions that must be considered The first, Cost per Unit, is an easy-to-understand metric, but in practice it is often overshadowed by a lack of transparency and predictability for other costs. The question is simple: how does a usage based pricing model impact these variables?