With native SQL support coming to InfluxDB, we can broaden the scope of developer tools used to analyze and visualize our time series data. One of these tools is Apache Superset. So let’s break down the basics of what Superset is, look at its features and benefits, and run a quick demo of Superset in action.

At Grafana Labs, we’re all about open source, and this year we took it to a whole new level. Many of you are familiar with the acronym “LGTM,” which is shorthand for “Looks good to me” and commonly used in code reviews. At Grafana Labs, LGTM has also been a guiding rubric in developing our observability stack.

Logging as a service (LAAS) is a type of cloud computing service that allows organizations to store and manage their log data in a central location. This type of service typically includes features such as centralized storage, real-time analytics, and search capabilities, as well as tools for visualizing and analyzing log data. Logs help you debug and troubleshoot your applications. They are also useful for other purposes like auditing and compliance, performance monitoring, and security.

Outlier Detection is now available as part of the Grafana Machine Learning toolkit in Grafana Cloud for Pro and Advanced users. With this feature, you can monitor a group of similar things, such as load-balanced pods in Kubernetes, and get alerted when some of them start behaving differently than their peers. There’s supposed to be a video here, but for some reason there isn’t. Either we entered the id wrong (oops!), or Vimeo is down.

As your experience and knowledge of a system grow, change becomes inevitable. Your application requirements change, your bug fixes require code changes, and your APIs evolve. A key challenge in the software ecosystem is managing changes—especially when they concern APIs. Because you’re likely using APIs in multiple applications, you must document all updates and changes made to your APIs. This is where API versioning becomes crucial.

Large IoT environments are highly complex and comprise multiple layers of disparate devices that must move data between each other, across potentially unreliable connections. Having visibility into each layer of your IoT environment is critical for quickly identifying problems with your deployment that could negatively impact user experience.