Grafana dashboards enable millions of users to visualize and analyze their data. And working behind the scenes of the widely used open source platform is React, a frontend JavaScript library for building user interfaces. In this post — which was inspired by my recent presentation at React Summit 2023 in Amsterdam — we’ll explore why we chose to use React for Grafana, and the benefits and challenges we’ve seen along the way.
Grafana k6 v0.45.0 has been released, featuring a new experimental module for gRPC streaming support, a new browser recorder extension for Firefox and Chrome, and tons of improvements for Grafana k6 OSS and Grafana Cloud k6. Here’s a quick overview of the latest k6 release and all the news from the community.
Looking to get started with log aggregation? Or perhaps take your logging game to a whole new, more advanced level? You’ve come to the right place. Grafana Loki is a key component of Grafana Labs’ open and composable Grafana LGTM stack (Loki for logs, Grafana for visualization, Tempo for traces, Mimir for metrics).
As your Kubernetes infrastructure — and your business — grows, so too does the headache of managing your stack. And since controlling costs is crucial for your organization’s well-being, you need visibility into your complex system to ensure you’re spending your money wisely. That’s why we’re excited to introduce Kubernetes cost monitoring as a new feature in Grafana Cloud.
We’re excited to introduce a dedicated Grafana Cloud integration for Apache CouchDB, a NoSQL document database that stores data in a JSON-based document format. Known for its scalability, availability, and easy replication of data across multiple servers, Apache CouchDB comes with a whole host of features designed to make it easy to run resilient distributed systems, with built-in bi-direcitonal replication allowing for simple replication across multiple servers and data centers.
Grafana is designed to visualize data in beautiful dashboards, no matter where the information lives. However, if you are considering the hosted Grafana Cloud observability stack for visualizing your data, you might run into a roadblock: network security. The problem is that some data sources, like MySQL databases or Elasticsearch clusters, are hosted within private networks.
The world of AI and machine learning has evolved at an accelerated pace these past few years, and the advent of ChatGPT, DALL-E, and Stable Diffusion has brought a lot of additional attention to the topic. Being aware of this, Grafana Labs prepared an integration for monitoring one of the most used machine learning model servers available: TensorFlow Serving. TensorFlow Serving is an open source, flexible serving system built to support the use of machine learning models at scale.
Grafana Cloud, our composable observability platform, is billed based on usage. A common question we get is: “How much will it cost to monitor N servers?” Well, the recently expanded Grafana Cloud Free tier includes up to 10,000 active series. To help you understand what that translates to in terms of time series requirements, here’s a rough guide to estimating what you’ll need.
