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Advantech releases EPC-C301 for machine vision applications with Ubuntu 18.04 LTS

Advantech, a leading global provider of intelligent IoT systems and embedded platforms, is pleased to announce EPC-C301, a compact fanless box PC powered by 8th Gen. Intel® Core™ processor. This system features diverse domain-focused I/O and can operate in broad temperature ranges. EPC-C301 integrates Intel® and Canonical technologies, provides Ubuntu and OpenVINO toolkits, and is aimed at accelerating the advancement of AIoT.

August 2020 Update: Manage service and system categories in the web portal and define responsibilities centrally

Our August update now makes it easy to assign team responsibilities for individual systems through our categories. This is no longer only possible by each team member in the mobile app, but can now also be done centrally in the web portal by the team administrator. All details can be found in this blog article.

How to use Hardware Asset Management for Recording Keeping

In the life of a hardware asset, there is only one point when we know for sure we have what we purchased: When we first receive the asset. This hardware asset scenario reminds me being a little kid and playing catch with my neighbor. I would take a new baseball out of the package and throw it over the fence to him. He would catch it and then throw it back. Sometimes he would try to trick me and throw a different ball back over the fence: an old baseball, a softball, and one time a soccer ball.

How to Use Starlark with Telegraf

Our Telegraf Starlark Processor Plugin is an exciting new processor in Telegraf 1.15 that gives you the flexibility of performing various operations in Telegraf using the Starlark language. What is Starlark, you ask? Starlark (formerly known as Skylark) is a language intended for use as a configuration language. Starlark is a dialect of Python. Like Python, it is a dynamically typed language with high-level data types, first-class functions with lexical scope, and garbage collection.

New in Telegraf 1.15: Starlark, execd, Go, NGINX, Network Monitoring, Redfish, New Relic, MongoDB and More

Last week we released Telegraf 1.15 with new plugins for network monitoring and a large number of processors to help with your data ingestion. All packages were written in Go 1.14.5. This all couldn’t have been done without the 50+ community members who contributed to writing plugins, fixing bugs, reviewing code, and everything else to help make Telegraf better! Here’s a quick look into new plugins and features we launched in Telegraf 1.15.

Introducing SimData V1.2

Hopefully you caught our Splunk Developer Spring 2020 Update in May, if you haven’t yet what are you waiting for? It introduces many updates from Splunk, including Splunk’s latest simulation tool — SimData. SimData is the best way to simulate correlated data sets for your Splunk apps. Here, we’ll cover the basics, and we’ve provided some helpful links at the bottom of this post for more details. We’ve got your back.

Java Logging Best Practices: 10+ Tips You Should Know to Get the Most Out of Your Logs

Having visibility into your Java application is crucial for understanding how it works right now, how it worked some time in the past and increasing your understanding of how it might work in the future. More often than not, analyzing logs is the fastest way to detect what went wrong, thus making logging in Java critical to ensuring the performance and health of your app, as well as minimizing and reducing any downtime.

How to stream Graphite metrics to Grafana Cloud using carbon-relay-ng

In this post we’ll show how you can easily ship your existing Graphite metrics to Grafana’s managed metric offering using carbon-relay-ng. Carbon-relay-ng is a fast, go-based carbon-relay replacement that allows you to easily aggregate, filter and route your Graphite metrics. This post assumes you have a local carbon-relay-ng binary. You can download carbon-relay-ng binaries from the releases page and find documentation on Docker images, Linux packages, and how to build it yourself here.

Asynchronous CSV Exports with Discover

For as long as we can remember, Sentry has had some version of CSV Exports. They’ve been limited only 1000 rows of results, which did the job for the most part. However, the more you used Sentry, the more we found that limit wasn’t good enough. What if I told you there was a way to get all your data in the exports in a single CSV? That’s right, no more DIY python scripts. No more manually piecing CSVs together. No more feature-request tickets.