Operations | Monitoring | ITSM | DevOps | Cloud

There are multiple ways to use Flux to bring in data from a variety of different sources including SQL databases, other InfluxDB Cloud Accounts, Annotated CSV from a URL, and JSON. However, previously you could only manually construct tables from a JSON object with Flux as described in this first example. We’ll describe how to work with three examples with increasingly complex JSON types. First we will describe how to work with these JSON types with metasyntactic examples.

MQTT is a standard messaging protocol used for the Internet of Things (IoT) because it requires minimal resources and can be executed by small microcontrollers found in connected devices. IoT devices have a real need for this type of lightweight protocol because it guarantees fast and reliable communication with minimal hardware requirements, keeping power consumption and manufacturing costs low.

If you’re a 1.x user of InfluxDB, you might be a Kapacitor user as well. If so, you’re also familiar with TICKscripts, the data processing and transformation language for Kapacitor, the batch and stream processor for InfluxDB. Kapacitor is a great tool, but it’s largely a black box, so using and implementing TICKscripts to execute data processing tasks, checks, and notifications can be a challenging developer experience.

In Part 1 of this series, we started to compare the uses of Kafka and MQTT within an IoT infrastructure. It was concluded that in a basic publish-and-subscribe model of an IoT device, Kafka might simply be overkill.

With the Kafka Summit fast approaching, I thought it was time to get my hands dirty and see what it’s all about. As an advocate for IoT, I heard about Kafka but was too embedded in protocols like MQTT to investigate further. For the uninitiated (like me) both protocols seem extremely similar if not almost competing. However, I have learned this is far from the case and actually, in many cases, they complement one another.

Keeping your systems secure is a never-ending challenge. Not only is it necessary to monitor and secure your own tech stack, but each new service a company uses creates another potential avenue for bad actors to try to exploit for their own ends.

The industrial revolution was a watershed period in human history. The shift from piecemeal, cottage-industry work to mechanized manufacturing transformed the way humans work. Since the 18th century, successive waves of innovation, such as the assembly line and the computer, continued to alter and change the nature of manufacturing. Today, we find ourselves in the midst of another industrial transformation.

Many Telegraf and InfluxDB users often spend a lot of time finding that perfect balance of getting the data they want in while not writing in too much data that they have to deal with unnecessary data in their database. This blog post will give you a better understanding of Telegraf’s data collection settings and help you fine-tune your configuration.

This article was originally published in The New Stack. As the technology landscape continues to change at a rapid pace, enterprise companies are in a rush to catch up and modernize their legacy IT and network infrastructure to capture the benefits of newly developed tools and best practices. By adopting modern DevOps techniques, they can reduce their operational costs, increase the reliability of their services and improve the overall speed and agility at which their IT teams are able to move.

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