If you have any experience with comparing open source data visualisation tools then it is very likely you will have encountered both Kibana and Grafana during your research and discovery phase. As two of the most popular solutions for logs and metrics analysis, it can be difficult to distinguish between the two and make the choice to use either Grafana or Kibana depending on the analysis task at hand.

Chemelot is an industrial park in the Netherlands with more than 150 companies in chemical and process industries that are working to build the most sustainable and competitive chemical site in Western Europe. Sitech Services is part of making that happen. The Dutch technology firm brings together maintenance and engineering specialists with data scientists to create multidisciplinary solutions that achieve optimal safety, efficient infrastructure, and efficient processes for the plants.

Martin Falch, co-owner and head of sales and marketing at CSS Electronics, is an expert on “CAN bus” data. Martin works closely with end users, typically OEM engineers, across diverse industries (automotive, heavy-duty, maritime, industrial). He is passionate about open source software and has been spearheading the integration of the CANedge with InfluxDB databases and Grafana telematics dashboards.

If you want to understand the popularity of your GitHub repositories, knowing the number of stars isn’t enough. GitHub understands this, and that’s why the team released traffic insights. Anyone with push access to a repository can view these insights, which include: full clones, visitors from the past 14 days, referring sites, and popular content in the traffic graph.

At Grafana Labs, we have a “big tent” philosophy: We believe our users should be able to determine their own observability strategy and choose their own tools, so we help users bring different data sources together. Datadog is a powerful product used by many teams, and we hear a lot from customers about how we should further embrace and support this critical data source — which is why we created the Datadog data source plugin a few years ago.

Here at Grafana, we’re constantly shipping new features to help our users get the most out of Grafana Cloud. Over the last few months, we’ve made it even easier to get started with out-of-the-box dashboards and new visualizations in Grafana Cloud. We also introduced capabilities like query caching, a “prettify JSON” option and commands for cortex-tools to make your data, dashboards, and queries more efficient.

Grafana 8 brought with it many exciting new features, including the launch of a new alerting system and the expansion of Grafana’s live and streaming data functionality. We didn’t stop there. In Grafana 8.1, alongside new additions like the Geomap and Annotations panel, we introduced some new features to the Time series panel as well as two transformations to help make panel configuration more dynamic.

The AWS IoT SiteWise plugin for Grafana was created to enable AWS IoT SiteWise customers to visualize and monitor industrial equipment data using Grafana dashboards. Industrial customers use AWS IoT SiteWise to collect, process, and monitor their industrial data at scale. This plugin allows them to use Grafana dashboards to monitor this data, stored by AWS IoT SiteWise in the AWS Cloud.

Chris Sackes is a Software Engineer at Lightstep. A New Yorker by birth, he loves public transportation, architecture photography, and urban exploration. He’s spent the last five years engineering delightful user experiences for a variety of applications. Lightstep’s powerful metrics reporting and analysis are now available for Grafana users. Using the new Lightstep Metrics plugin for Grafana, you can view metrics data reported to Lightstep directly in your Grafana instance.

We are excited to announce the launch of query caching in Grafana Cloud, which can significantly reduce load times and costs of your most popular Grafana dashboards. Now, when the same query is submitted repeatedly, the results will come back from the cache rather than the data source itself. This not only lowers load times for popular dashboards, but will also reduce API costs for your data sources and decrease the likelihood that those APIs will rate-limit or throttle requests.