Tim Hall | InfluxDB Roadmap | InfluxDays
In this talk, Tim will review the roadmap and will cover what you can expect in the future in terms of InfluxDB and Flux capabilities.
Operations | Monitoring | ITSM | DevOps | Cloud
The Place Where Modern Operations & Technology Come Together
Ronald McCollam | Flux Queries in Grafana 7 | InfluxDays
In this session, Ronald shows a few new features of Grafana 7, focusing on the new native Flux query support in Grafana. He shows you how you can query with both Flux and the older InfluxQL support, using both side by side to ease migration. As a bonus, you see how to combine Flux queries with other data to perform advanced analytics and joins to truly understand your entire environment!
Air Quality Monitoring Made Easy with the InfluxDB Air Quality Monitoring Template
Air quality monitoring is important as poor air quality is responsible for an estimated 60,000 premature deaths in the United States each year, and annual costs from air pollution-related illness are estimated at $150 billion. Air quality monitoring can help track and guide action to reduce air pollution, which can cause short-term and long-term health effects for children, older adults, and people with heart disease, asthma, and other respiratory conditions.
Paul Dix [InfluxData] | Opening Keynote | InfluxDays Virtual Experience NA 2020
In this keynote, InfluxData Founder and CTO Paul Dix shares updates on InfluxDB and Flux and announces an exciting new open source project, InfluxDB IOx — a powerful storage engine designed to execute increasing query workloads over time. InfluxDB IOx lifts restrictions on cardinality, data size and cluster size – expanding the possibilities for workloads across thousands of servers and petabytes of data.
Barbara Nelson | How Can I Put That Dashboard in My App? | InfluxDays
Many users love using the InfluxDB UI to visualize their time series data in a variety of different graphical representations. In this session, Barbara Nelson will show how to use Giraffe (the React-based visualization library powering the data visualizations in InfluxDB 2.0 UI) to visualize your time series data within your own app. You can bring the power of our visualization tools to your users, directly in your app, instead of requiring them to login to the InfluxDB UI to see a visual representation of your data.
InfluxData advances possibilities of time series data with general availability of InfluxDB 2.0
SAN FRANCISCO — November 10, 2020 — InfluxData, creator of the time series database InfluxDB, today announced the general availability of the next-generation open source platform for time series data, InfluxDB 2.0. Developers can now ingest, query, store and visualize time series data in a single unified platform, leverage new tools and integrations, and use familiar skills — making it faster and easier than ever to develop and deploy modern time-based applications.
InfluxDB 2.0 Open Source is Generally Available
Today, we are proud to announce that InfluxDB Open Source 2.0 is now generally available for everyone. It’s been a long road, and we couldn’t have done it without the amazing support and contributions of our community. This marks a new era for the InfluxDB platform, but it truly is just the beginning. Before we talk about the future, let’s take a look at some of the amazing new capabilities our team has been working on.
Announcing InfluxDB IOx - The Future Core of InfluxDB Built with Rust and Arrow
On November 12, 2013, I gave the first public talk about InfluxDB titled: InfluxDB, an open source distributed time series database. In that talk I introduced InfluxDB and outlined what I meant when I talked about time series: specifically, it was any data that you might ask questions about over time.
Scaling Kubernetes Deployments with InfluxDB & Flux
This article was written by InfluxDB Community member and InfluxAce David McKay. Eighteen hours ago, I was meeting with some colleagues to discuss our Kubernetes initiatives and grand plan for improving the integrations and support for InfluxDB running on Kubernetes. During this meeting, I laid out what I felt was missing for InfluxDB to really shine on Kubernetes.
Downsampling with InfluxDB v2.0
Downsampling is the process of aggregating high-resolution time series within windows of time and then storing the lower resolution aggregation to a new bucket. For example, imagine that you have an IoT application that monitors the temperature. Your temperature sensor might collect temperature data. This data is collected at a minute interval. It’s really only useful to you during the day.