Organizations using Amazon Web Services (AWS) cloud traditionally leveraged Reserved Instances (RI) to realize cost savings by committing to the use of a specific instance type and operating system within the AWS region. Nearly 2 years ago, AWS rolled out a new program called Savings Plans, which give companies a new way to reduce costs by making an advanced commitment of a one-year or three-year fixed term.
If a picture is worth a thousand words, then a well-done data visualization is worth a million. The quality of a dashboard can make or break an application. In this tutorial, you will learn how to make high-quality data visualizations easily by using the Nivo charting library with ReactJS. You will also learn how to query data stored in InfluxDB to make your charts dynamic and versatile.
This is a short blog post about a pattern that we’ve observed more frequently among some of the large enterprises: the use of AWS S3 as both an observability lake and a data bus. AWS S3’s simple API, ubiquitous language support, unmatched reliability and durability, retention options, and numerous pricing plans have made it the de facto standard for storing massive amounts of data.
Like many cool tools out there, this project started from a request made by a customer of ours. Having recently migrated to our service, this customer had ~30TB of historical logging data. This is a considerable amount of operational data to leave behind when moving from one SaaS platform to another. Unfortunately, most observability solutions are built around the working assumption that data flows are future-facing.
