Operations | Monitoring | ITSM | DevOps | Cloud

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.

Looking to level up your performance tuning game? Check out three new videos on tempdb, unstable query plans, and identifying blocking chains with SQL Monitor. I got to work with some of my favorite folks from the SQL Monitor team last week to build some new workload patterns for our online monitoring demo site. Here are three videos sharing some highlights of performance tuning features in SQL Monitor.

We’re excited to share that the official Elastic Cloud Terraform provider is now available in beta. Operations and SRE teams often rely on Terraform to safely manage production-related infrastructure using methodologies such as infrastructure as code, which allows you to apply peer-reviewed infrastructure changes in an automated and controlled fashion. The provider works with Elasticsearch Service on Elastic Cloud, Elastic Cloud Enterprise, and Elasticsearch Service Private environments.

At the recent Illuminate conference, Dave Sudia from GoSpotCheck shared the process that led them to choosing Sumo Logic for their observability needs.

Aurora, a hosted relational database service available on the Amazon cloud, is a popular solution for teams that want to be able to work with tooling that is compatible with MySQL and PostgreSQL without running an actual MySQL or PostgreSQL database. In order to leverage Aurora’s benefits fully, it’s critical to log and analyze the various types of monitoring data that are available from an Aurora environment.

With more people working from home due to the COVID-19 crisis, businesses of all sizes need to know when their employees are working. You need an effective way to track working hours and know what your employees are doing while they are working. One effective way to do this without having to invest in an expensive online time tracking system for employees is by using server monitoring software and file monitoring software.

Last month we announced InfluxDB IOx (pronounced: eye-ox), a new Rust and Apache Arrow based core for InfluxDB. While InfluxDB IOx is a columnar database built on top of object storage, that’s only part of its role. In addition to query functionality, one of the big goals of InfluxDB IOx is to help manage the data lifecycle for time series data. This post will cover the design for how InfluxDB IOx plans to manage that data lifecycle.