Operations | Monitoring | ITSM | DevOps | Cloud

Latest Posts

How to Run a Time Series Database on Azure

Today we’re pleased to announce the general availability of InfluxDB Enterprise on Microsoft’s Azure Marketplace. We’ll dive into all of these below, but first, let’s take a step back in case you’re not familiar with time series databases. If you’re looking for a time series database, here are three things to look for.

How LineMetrics Uses InfluxDB to Launch Its IoT Monitoring Platform

“What would it be like to have an asset monitoring solution that can be installed within minutes and is independent of all existing IT systems, without endangering existing processes?” LineMetrics was founded in 2012 in Haag, Austria, in response to questions just like this one. LineMetrics developed a complete real-time asset monitoring solution delivered through its end-to-end Internet of Things (IoT) platform.

Monitoring a Pulse Oximeter with InfluxDB - A Parent's Perspective

This article was contributed by Michael Hinkle, Probe Engineering and Manufacturing Supervisor at Texas Instruments. My name is Mike Hinkle, and I use InfluxDB to monitor my daughter’s pulse oximeter and to better understand her overall health. Through my career as an engineer, currently at Texas Instruments, I was aware of time series databases and I love to play with various technologies.

Writing Tasks and Setting Up Alerts for InfluxDB Cloud

If you are using InfluxDB to monitor your data and systems, then alerts may be an essential part of your workflow. We currently have a system for monitoring your data whether it enters a critical or non-critical state. Here I’m going to give a detailed guide on setting up alerts using our InfluxDB Cloud product as well as some best practices for having a good experience using alerts.

Datadog vs. InfluxDB

If you’re responsible for monitoring, chances are you’ve heard of Datadog. Like InfluxDB, Datadog is a monitoring platform for cloud applications, bringing together data from containers, servers, databases, and third-party services. InfluxData and Datadog approach monitoring from different starting points. InfluxDB is an open-source time-series data platform that can be used for a range of use cases, one of which is monitoring.

InfluxData expands in Asia Pacific region with Digital China and Hyundai BS&C partnerships

New distribution partnerships will support increased demand for InfluxDB across the region SAN FRANCISCO — April 29, 2020 — InfluxData, creator of the time series database InfluxDB, today announced its expansion into the Asia-Pacific (APAC) region through new strategic partnerships. Digital China and Hyundai BS&C will be the exclusive value-added distributors of InfluxDB in China and South Korea, respectively. The company also teamed up with Intellify, a reseller in Australia.

InfluxDB Templates: Easily Share Your Monitoring Expertise

If you’re the resident expert in your company on a particular technology, you probably get asked a lot of questions about it: how to set it up, how to maintain it, how to monitor it. While it’s great to be recognized as the expert, all these requests for help can steal time away from your day job. Thankfully, we’ve got something that will help: InfluxDB Templates.

So How Are Developers Feeling During the COVID Health Crisis? We Decided to Ask...

As a developer-focused company, InfluxData is always interested in how the community is doing. During the first two weeks of April, we conducted an online survey to find out how developers are handling life and work during the COVID-19 pandemic. A total of 324 self-identified software developers/engineers from across the world responded (46% from North America, 44% from Europe, 9% from South America, and 1% from Africa) to share their feelings during this unprecedented global event.

Apache Arrow, Parquet, Flight and their ecosystem are a game changer for OLAP

Apache Arrow, a specification for an in memory columnar data format, and associated projects: Parquet for compressed on disk data, Flight for highly efficient RPC, and other projects for in-memory query processing will likely shape the future of OLAP and data warehousing systems. This will mostly be driven by the promise of interoperability between projects, paired with massive performance gains for pushing and pulling data in and out of big data systems.