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Announcing InfluxDB Edge Data Replication: Combining the Power of the Cloud with the Precision of the Edge

There are technical and business reasons to have a time series data presence both at the edge and in the cloud – InfluxDB has always played a key role in both contexts. Today, we’re announcing Edge Data Replication, a new feature that combines these two deployment strategies. With this announcement, InfluxData begins a greater initiative to accommodate both edge and cloud data workloads in one unified solution.

InfluxData Announces InfluxDB Edge Data Replication

SAN FRANCISCO, June 15, 2022 – InfluxData, creator of the leading time series platform InfluxDB, today announced Edge Data Replication, a new capability for centralized business insights in widely distributed environments. Edge Data Replication enables developers to collect, store and analyze high-precision time series data in InfluxDB at the edge, while replicating all or subsets of this data into InfluxDB Cloud.

Master IoT software updates with validation sets on Ubuntu Core 22

If you are packaging your IoT applications as snaps or containers, you are aware of the benefits of bundling an application with its dependencies. Publishing snaps across different operating system versions and even distributions is much easier than maintaining package dependencies. Automated IoT software updates make managing fleets of devices more efficient.

What you're missing out if you don't try Ubuntu Core 22

Ubuntu Core, the Ubuntu flavour optimised for IoT and edge devices, has a new version available. With a 2-year release cadence, every new release is both an exciting and challenging milestone. Ubuntu Core is based on Ubuntu. It is open source, long-term supported (LTS), binary compatible and offers a unified developer experience. It allows developers and makers to build composable and software-defined appliances built from immutable snap container images.

Canonical Ubuntu Core 22 is now available - optimised for IoT and embedded devices

15 June 2022: Canonical today announced that Ubuntu Core 22, the fully containerised Ubuntu 22.04 LTS variant optimised for IoT and edge devices, is now generally available for download from ubuntu.com/download/iot. Combined with Canonical’s technology offer, this release brings Ubuntu’s comprehensive and industry-leading operating system (OS) and services to a complete range of embedded and IoT devices.

What is Ubuntu Core 22?

IoT manufacturers face complex challenges to deploy devices on time and within budget. Ensuring security and remote management at scale is also taxing as device fleets expand. Ubuntu Core 22 helps manufacturers meet these challenges with an ultra-secure, resilient, and low-touch Operating System, backed by a growing ecosystem of silicon and ODM partners. Ubuntu Core 22 is a minimal, fully containerised Ubuntu 22.04 LTS variant optimised for IoT and edge devices.

6 Software Innovations That Are Worth Introducing To The Office

In the modern workplace, innovative software is just as important as the employees. There are tools that help with everything from keeping deadlines to task management and more. They come with relatively easy-to-navigate interfaces so that you can easily find what it is that you're looking for and work more efficiently. Let's take a look at a few classes of software as well as a few recommendations that are well worth introducing into the workplace.

Defining the Edge for IoT with InfluxDB

The 'edge' is the place where the physical world meets the digital world. More and more businesses rely on workloads at the edge, especially in the IoT and IIoT spaces. Define the edge to fit your needs. InfluxDB has the tools and resources to use data at the edge and in the cloud, and to create reliable, durable data pipelines between them.

Getting started with Azimuth - a tool to help understand datasets and models in text classification

In our previous video, you were introduced to AZIMUTH, an open-source software project from ServiceNow. Azimuth is an application that helps AI practitioners better understand their dataset and model predictions by performing thorough dataset and error analyses. The application leverages different tools, including robustness tests, semantic similarity analysis, and saliency maps, unified by concepts such as smart tags and proposed actions.