If you’re new to the Splunk Dashboards app (beta) on Splunkbase and you’re trying to get started with building beautiful dashboards, this blog series is a great place to start. The Splunk Dashboards app (beta) brings a new dashboard framework, intended to combine the best of Simple XML and Glass Tables, and provides a friendlier experience for creating and editing dashboards.
Amid a year of challenges and change, Grafana made great strides in 2020. Grafana currently boasts more than 600,000 active installations and millions of dashboards in use across the globe. And this year, after 18,000 commits and 3,699 pull requests from 362 contributors, we revealed the next chapter of our observability story.
Every enterprise has its arsenal of tech tools to tackle an array of different challenges. Useful, and necessary, but often a pain to monitor. Whatever your data sources, being able to bring all these metrics into a unified dashboard provides valuable context, which in turn helps you identify and correlate problems more quickly, resulting in improved reaction time and decision making.
Over the last several months, there have been a variety of service providers that have launched Managed Prometheus offerings. This is a testament to the rise in popularity of the Prometheus project, and how it’s becoming a de facto standard for metrics. The most recent announcement in the Managed Prometheus landscape came from AWS. During a re:Invent keynote on Dec. 15, Amazon announced its AWS Managed Service for Prometheus.
Being able to visualize data from all of your tools in a unified dashboard experience has become critical to most enterprises today. With SquaredUp dashboards, you can not only correlate data from SCOM and Azure, but also surface critical information from your other tools and data sources – including ServiceNow, Azure Log Analytics, App Insights, all SQL databases and any Web API. In short, you can get unified dashboards with real-time operational intelligence for all teams across all tools.
Having good observability is vital to the health of your cloud infrastructure and applications, and a key element to using that information effectively is being able to create dashboards with relevant metrics. Today we are announcing a new dashboard creation experience from Cloud Monitoring that allows you to generate a greater variety of visualization types, introduces better flexibility for dashboard layouts, and makes data manipulation easier so you can create dashboards that better fit your needs.
Our Open Access feature enables easy, and unlimited sharing of dashboards across your organization – with any audience at all. A highly popular feature, these shared dashboards help you bring better visibility and collaboration – conveying the shared “truth”! With our latest release SquaredUp 5.0, we have made Open Access dashboards fully interactive, like the rest of our dashboards, so you can see that next level of detail you’ve been wanting.
In collaboration with the AWS team, we have just launched another AWS integration, the AWS IoT SiteWise plugin for Grafana. AWS IoT SiteWise is a managed service that helps users collect, store, organize, and monitor data from industrial equipment, across facilities, at scale.
Cloud native observability is at a watershed moment. The explosion of microservices has created previously unseen amounts of monitoring data, limiting the ability of humans and computer systems to extract meaning from data with last-generation tools. Debugging is often a process of detecting correlation, and then turning correlations into causal connections. This is where modern cloud native tooling comes in.
In this blog post you’ll learn how to create visualizations for Kibana dashboards from Jupyter Notebooks. The good news for you as a Python developer: You won’t have to spend time writing cumbersome plain JSON documents or even JavaScript code. Under the hood, we’re going to make use of Kibana’s Vega plugin which became generally available with Elastic Stack 7.10.
