In v1.30.0, Telegraf will remove a few long-standing deprecated plugins. These plugins have been deprecated for a number of years, and plugins with better support and configuration options now replace them. This version of Telegraf also removes a number of configuration options. The full list of deprecated plugins includes: Starting from v1.30.0 Telegraf will show an error message and stop running if any of the plugins or options are present in your configuration.

Ensuring the reliability and performance of your network is essential for success in the modern software industry. In this article, you’ll learn about the basics of network monitoring and get an overview of some of the most popular tools used for network monitoring. Whether you’re managing a sprawling enterprise network or your home lab, understanding and deploying the right tools can mean the difference between smooth sailing and unforeseen downtime.

Program Logic Controllers (PLCs) have played an integral role in industrial automation since their initial creation during the 1960s.

Predictive analytics are a powerful tool, enabling organizations to make informed data-driven decisions. These tools are far-reaching and can deliver impactful results, either in the long term, like supply chain management and overall equipment effectiveness, or in the short term, like anomaly detection. Let’s take a look at what predictive analytics are and how to power predictive analytics engines for continued, meaningful insight into your data and operations.

Picture a bustling control room at a major aerospace company, where engineers and executives monitor aircraft performance, analyze flight data, and make critical decisions in real-time. In this dynamic environment, the ability to harness the power of real-time analytics becomes paramount. This is where InfluxDB 3.0, the latest version of InfluxData’s time series database, delivers an innovative edge to organizations with time-critical analytics needs.

Despite changes in technology, culture, economics, or virtually any other factor imaginable, the adage ‘time is money’ remains relevant. When it comes to data analysis, the faster you can conduct analysis, the better. However, increasing data volumes across the board make it challenging to analyze and act on data in a timely manner.

In the fast-paced world of software engineering, efficient data management is a cornerstone of success. Imagine you’re working with streams of data that not only require rapid analysis but also need to store that data for long-term insights. This is where the powerful duo of time series databases (TSDBs) and data lakes can help.

Monitoring the performance and health of infrastructure is crucial for ensuring smooth operations. From data centers and cloud environments to networks and IoT devices, infrastructure monitoring plays a vital role in identifying issues, optimizing resource utilization, and maintaining high availability. However, traditional monitoring approaches often struggle to handle the volume and velocity of data generated by modern infrastructures. This is where time series databases, like InfluxDB, come into play.

Imagine a data engineer working for a large e-commerce company tasked with building a system that can process and analyze customer clickstream data in real-time. By leveraging Amazon Kinesis and InfluxDB, they can achieve this goal efficiently and effectively. So, how do we get from idea to finished solution? First, we need to understand the tools at hand.

Database Administrators (DBAs) rely on time series data every day, even if they don’t think of time series data as a unique data type. They rely on metrics such as CPU usage, memory utilization, and query response times to monitor and optimize databases. These metrics inherently have a time component, making them time series data. However, traditional databases aren’t specifically designed to handle the unique characteristics and workloads associated with time series data.