Grafana 9.4 is here! Get Grafana 9.4 With the latest Grafana release, we’re introducing a wealth of new features and improvements that makes getting started with Grafana even easier and that take your visualizations and observability best practices to the next level. In addition to enabling TraceQL, the new query language for distributed tracing in Grafana Tempo 2.0, for all Grafana Cloud users, the Grafana 9.4 release comes with a fresh round of features.

Automatic instrumentation is great, but to get the most out of your monitoring you often need to instrument your code. In this article I am going to explain how to instrument a Node.js express app with custom metrics using the Prometheus prom-client package. Although this article specifically addresses Node.js and express, my hope is that the general concepts are applicable to other languages too.

Railway passengers may think of trains simply as a way to get from one place to another, but at Siemens Mobility — a rail transportation company dedicated to delivering sustainable, smart transport — they are that and much more. Siemens Mobility works with more than 3,000 partners, and its customers include Eurostar and Trans Pennine Express. In the U.K., Siemens Mobility maintains about 500 train units and logs 65 million passenger miles per year.

This panel is in alpha version and still in development. To use it as is, you need to modify your configuration file and set enable_alpha = true in the panels section. More information can be found on this page. Two-dimensional graphics are the de facto way to visualize data within the observability realm, and Grafana is really good at plotting data this way.

A look at best practices, no-code and low-code platforms you can use, common visualization types, criteria for good data visualization and more. Organizations regularly generate an overabundance of data that is essential for decision-making. Data visualizations play an important role in helping people understand complex data and observe patterns and trends over a period of time.

Prometheus metrics are usually visualized as numeric values on a graph, with the metrics categorized by labels. But what do you do when the numerical value doesn’t matter, and all of the information is in the labels? In that case, you might need to visualize the labels themselves. This scenario can arise because you’re not always in control of how the metrics get reported, but you do often need to visualize what’s there.

Custom dashboards are essential tools in the data-driven world for businesses, organizations, and individuals. They provide an interactive and comprehensive representation of data, making it easier to identify trends, patterns, and outliers. Custom dashboards are highly customizable, allowing users to select the most relevant data sources, visualizations, and metrics to meet their specific needs.

Think of a monitoring tool — any monitoring tool. Got it? Good. Odds are, whatever came to mind was probably being used behind the scenes at Wells Fargo not too long ago. “You name it, and we probably had it at Wells Fargo,” said Senior Software Engineering Manager Nikhilesh Tekwani of the complex web of observability solutions that stretched across the U.S.-based financial institution.

Grafana is a powerful open-source data visualization platform created by Torkel Ödegaard in 2014. With its front-end written in Typescript and a Golang back-end, this data monitoring platform allows users to create and share interactive and dynamic dashboards with custom charts and panels using data from various sources, including InfluxDB, Prometheus, Elasticsearch, and many others. Template variables are also available as dropdown options to create dynamic and reusable dashboards.

You can now use the Cloud Logging datasource plugin to view your logs in Grafana.

Graphite provides time-series metrics in an open-source database. With Graphite dashboards, you can see key performance indicators (KPIs) as well as other metrics visually. Dashboards typically display data as graphs, charts, and tables and can be customized to meet the specific needs of an organization. Using dashboards, organizations can monitor and analyze various aspects of their performance, such as system utilization, application performance, and resource utilization, using web interfaces.

Working with technology means dealing with incidents or outages from time-to-time, so staying on top of problems is essential. Back in the spring of 2022, Clearco, the world’s largest e-commerce investor, had an alerting system set up to catch issues, except they had one problem: Clearco’s Customer Success team would learn of a problem before a notification even went off.

I lead the Grafana Loki project here at Grafana Labs, and I’ve always loved building things professionally and in my personal life, whether we’re talking about metalworking or coding — or, more recently, 3D printing. A couple years ago, I purchased my first 3D printer, a Prusa i3 MK3S+. I use it periodically to build functional items I use around my house in Upstate New York. For example, I recently decided to build a solar radiation shield for my outdoor weather station.

OpenSearch dashboards are a powerful tool for visualising and exploring data stored in an OpenSearch-compatible data store such as Elasticsearch. With OpenSearch's intuitive interface and advanced analytical tools, this visualisation tool makes it easy to gain insights into your data and monitor and alert upon key metrics. Throughout this article, we'll look at some of the most impressive OpenSearch dashboard examples that showcase it’s capabilities and versatility.

With k6 Cloud, Grafana Labs is in the business of generating load — lots of load, distributed across a cluster of computers. So while our customers care about the systems they load, we care that our system can generate the load that they need and process the test metrics for them in an intuitive, explorable way.

Artificial Intelligence (AI) - or more specifically Machine Learning (ML) - and automation were big topics for many of our customers in 2022. Common reasons for the interest in AI and automation were to: increase efficiency, reduce manual processing, minimise human error and - especially for the use of ML - identify ‘unknown unknowns’.

Customers choose Embrace to help mobile development teams build fantastic mobile app experiences. Embrace provides best-in-class mobile insights that help users prioritize, understand, and resolve issues. All of which leads to better development decisions. But in modern software engineering, no team exists in a vacuum.

× As organizations shift to service-centric environments, they are generating substantially more data. This in turn has placed strains on monitoring and observability teams, who now must sift through an abundance of data in order to identify and resolve issues — a challenge exacerbated by the number of various monitoring tools they’ve implemented over the years.

Grafana Faro and xk6-browser are both new tools within the Grafana Labs open source ecosystem, but the pairing is already showing a lot of potential in terms of frontend monitoring and performance testing. Faro, which was announced last November, includes a highly configurable SDK that instruments web apps to capture observability signals that can then be correlated with backend and infrastructure data.

I’ve always been wary about vendor events. In my experience, many of them are mostly marketing pitches, with little or no content that is applicable to my use cases. Despite that, last year I decided to convince my manager to let me attend ObservabilityCON 2022 to see what I could learn from it. My hope was that I would be able to get practical knowledge that could be applied as soon as I got back to work. (Spoiler alert: I did!)

Flaky tests are a problem that are found in almost every codebase. By definition, a flaky test is a test that both succeeds and fails without any changes to the code. For example, a flaky test may pass when someone runs it locally, but then fails on continuous integration (CI). Another example is that a flaky test may pass on CI, but when someone pushes a commit that hasn’t touched anything related to the flaky test, the test then fails.

At Grafana Labs, we love tracing, which is why we’ve been hard at work on Grafana Tempo, an open source, highly scalable distributed tracing backend. Tempo just had its 2.0 release. In conjunction with that release, we are excited to show off TraceQL — a powerful new query language designed for distributed tracing. In this blog, we’ll provide an overview of why we created TraceQL, how it works, how you can put it to use today, and what we have planned for future iterations.

We recently launched a new design for our technical documentation. The goal of the redesign was to make our technical documentation more accessible, modern, and scalable as we grow. In addition to a new look (hello, new typeface and layout!), our updated docs pages reveal the underlying work our team has done to evolve and enhance our technical documentation.

While more and more teams are adopting Kubernetes as their standard container orchestration technology, cost insight is lacking. Teams often don’t know how much they’re spending, where in their organization they are spending, or what is driving their infrastructure cost increases. OpenCost helps alleviate this problem by bringing real-time cost monitoring to Kubernetes workloads with a solution that encompasses both an open specification and an open source project.

Our latest open-source project, Helm-Dashboard, just crossed 3K stars on GitHub (and hundreds of daily active users), only three months since it was released! We thought this milestone was a good chance to take a look back at our journey, announce the release of v. 1.0.0, discuss future plans, and, most importantly, give our utmost thanks to the amazing contributors and Kommunity members that made it all possible! What capabilities would you like to see next in Helm-Dashbaord?

Grafana Tempo 2.0 is finally here, and it’s being released with two new important features. It took us longer than we would have liked to get this release going, but it turns out that rewriting your backend AND building a new query language is quite difficult. Thanks to a massive team effort, we are proud to release Tempo with support for TraceQL and with Apache Parquet as the default backend storage format. Read on to get a quick overview of this huge release.

Here at Grafana Labs, we aim to create products which integrate well with open standards and are easy to install everywhere. Today, we’re excited to announce Grafana Agent v0.31, which allows you to connect to even more types of observability signals for both scraping and remote writes. And to help you install the Agent more easily, there is now an official Windows Docker image and an official Helm Chart. Here’s a breakdown of the latest features and upgrades in Grafana Agent v0.31.