InfluxData

BIG NEWS from #InfluxData and @awscloud. We’re expanding InfluxDB 3 on Amazon Timestream for InfluxDB with support for clusters up to 15 nodes, unlocking massive ingestion throughput, higher query concurrency, and true workload isolation for the most demanding time series workloads. We’re also introducing a seamless migration path from InfluxDB 3 Core to Enterprise, so teams can scale from a single node to enterprise-grade clusters without downtime or rearchitecting their system. As telemetry grows from minute-level metrics to high-resolution, real-time data streams, developers need infrastructure that scales just as fast. Read more from our CMO, Pat Walsh: bit.ly/40AfQWQ

What does it actually look like to build with time series data? In this hands-on project, @SuyashJoshi walks through building “Plant Buddy” with #InfluxDB 3, combining real-time data, queries, and visualization. A practical example for devs working with live telemetry 🌱 bit.ly/4rII24W

🌌 Physical AI in space needs deterministic answers, not probabilistic guesses. High-fidelity time series data is what powers everything from Mars rovers to autonomous satellites navigating LEO: bit.ly/3L1qnFR by @evankaplan, CEO, InfluxData via @SpaceNews_Inc #InfluxDB

@tado° now powers its real-time IoT infrastructure with #InfluxDB 3. With InfluxDB 3 behind the scenes, tado° turns raw telemetry into instant insight, fueling the app experience, cutting emissions, and keeping systems running with precision. Read their story: bit.ly/40B9LJR

#InfluxDB handles time series data with deterministic collection and real-time processing at scale. InfluxData CEO @evankaplan explains how developers are using it for AWS integrations and why open source matters for the database ecosystem: bit.ly/3YkjOSd via @TechstrongTV

#InfluxDB pairs with tools like Telegraf for collection, Grafana for visualization, and Power BI for analytics. 🤩 Build powerful time series solutions with integrations that fit your workflow! ⏬ bit.ly/3KorYWw

You *can* use a relational database for time series data. The question is: when does it become the bottleneck? This perspective from Matt Aslett on @ISG_news explains why purpose-built time series databases like #InfluxDB are fundamental, especially in industries like #IIoT 👉 bit.ly/4dubyYG

New to #InfluxDB 3 Core or Enterprise? The launch hub has tutorials, videos, and technical walkthroughs to get you from zero → real-time data fast. 👉 bit.ly/4dpDAVe

Attending @WECONECT Manufacturing IT/OT Summit in Boston? Don’t miss our tech talk at Booth 29 on March 23. #InfluxDB Staff Engineer Andrew Lamb will break down how time series databases enable predictive analytics, anomaly detection, and real-time monitoring for modern factories. bit.ly/4bx0NCi

How do you fix a satellite 40,000 km away? You don't. You predict the failure first. Thales Alenia Space is leveraging continuous time series telemetry and ML models to power true predictive maintenance. They keep critical satellites operational where physical repairs are simply impossible. bit.ly/4if3ADk #InfluxDB

AI is changing what it means to be a DBA. In this piece, @joemckendrick explores how data roles are evolving—and what it takes to keep up. Featuring insights from #InfluxDB Developer Advocate @suyashcjoshi. 🧠 bit.ly/4bvoNpA

In BESS operations, latency isn’t just a delay—it’s a risk. If your system can’t answer “what’s happening right now?”, you’re already behind. Here’s how Last Value Cache helps deliver real-time state at scale with #influxdb ⚡ bit.ly/4bPJn5a

Physical AI is powering LEO satellites and Mars missions, but it needs high-fidelity time series data to work. Thousands of sensor readings per second feed models that make deterministic decisions, not probabilistic guesses. The leaders in space are building on purpose-built time series infrastructure to power real-time monitoring, autonomy, and predictive anomaly detection. Turning telemetry into intelligence is what will set the next generation of space systems apart: bit.ly/3NnTtB6 by #InfluxDB CEO @evankaplan via @SpaceNews_Inc

TOMORROW: Manufacturers generate massive streams of machine data. See how #InfluxDB helps turn that data into predictive maintenance, process optimization, and operational insights. Watch the on-demand demo and join our live Community Slack Q&A with Solutions Engineer Ben Corbett on March 19 (8AM PT | 3PM GMT). Save the link to join tomorrow bit.ly/4sJmdmG

AI requires formidable data infrastructure, especially at enterprise scale. Are we ready? #InfluxDB developer advocate @influxcole speaks to @joemckendrick for @dbtrends about the need for a clean and well-defined data model to serve as documentation for AI. Read the article to find out how the experts are approaching this paradigm shift. bit.ly/3PceY8w

The #InfluxDB 3 downsampling plugin automates time series rollups, turning millions of high-frequency data points into structured summaries that keep queries fast and storage costs predictable as systems scale. 📈 bit.ly/4ox5Rer

@wideopenwest monitors 650,000+ cable modems with #InfluxDB to maintain network uptime. Their team collects telemetry data every five minutes from their fiber-to-the-node network, tracking signal strength, uptime, and SNR across the entire service delivery infrastructure. 🔎 The result: real-time visibility into network health and faster troubleshooting when issues arise: bit.ly/460PcIu

Getting started with #InfluxDB takes less than 10 minutes! ⏱️ Install InfluxDB 3 Core, set up Telegraf to collect metrics, and query your time series data with SQL. Everything you need to go from zero to running queries. 🕶️

ICYMI: InfluxDB 3 on Amazon Timestream for #InfluxDB now supports clusters up to 15 nodes, giving developers a new performance tier for time series workloads. We’re also introducing a seamless migration path from InfluxDB 3 Core to Enterprise, so teams can scale their architecture without downtime or data migration. InfluxData Product Manager @PeteWithProduct breaks down the announcement and what it unlocks for high-volume, high-resolution workloads. ⬇️ bit.ly/41b7ftW

#InfluxDB offers multiple data ingestion methods, each with distinct advantages for different use cases. Learn which approach fits your architecture and workload requirements. ↓ bit.ly/3N6xYVl