December 2021 Summaries

This post discusses Telegraf as a consumer of MQTT messages in the context of writing them to InfluxDB. It covers topic parsing and payload parsing, which allow users to shape incoming data for compatibility with their destination data store. Topic parsing enables users to specify which portions of an MQTT topic they want to bring in as measurement, tags, or fields. Payload parsing allows users to parse the JSON payloads that are commonly used in this context. The post provides examples and configurations for both topic and payload parsing.

Telegraf 1.21.1 has been released as a maintenance update. The new version includes input plugin updates for File, Tail, Directory Monitoring Input, OpenStack Input, and SMART Input. Additionally, the go-sensu module has been updated to v2.12.0. Users can download the latest Telegraf release from the InfluxData Downloads page. For any issues or questions, join the InfluxDB Community Slack, post in the InfluxDB GitHub Repo, or visit the community site.

InfluxData has released Telegraf 1.21.0, which includes seven new plugins, performance improvements for the SNMP plugin, and deprecation warnings for certain plugins. The latest version also features enhancements to existing plugins such as MQTT topics extraction, JSON v2 Parser, Regex Processor, Modbus Input, OPC UA Input, Kafka Consumer Input, Directory Monitor Input, and more. Additionally, new inputs like Intel PMU Input Plugin, Logical Volume Manager Input Plugin, OpenStack Input Plugin, and a Starlark Aggregator have been added. New outputs include Azure Event Hubs Output Plugin, GroundWork Output Plugin, and MongoDB Output Plugin.

InfluxData is aware of two recently reported Apache log4j vulnerabilities CVE-2021-44228 and CVE-2021-45046. The company confirms that its software does not employ log4j, nor is it within their supply chain. All versions of InfluxData's services and software are covered by this statement, including InfluxDB OSS, InfluxDB Enterprise, InfluxDB Cloud, Telegraf, Kapacitor, and Chronograf. The company has patched its backend systems that include log4j as of December 10, 2021, which remain isolated from their cloud services infrastructure.

The article discusses how to write data from an edge device to a cloud instance of InfluxDB using Flux. It explains that writing data directly from IoT devices to InfluxDB Cloud is the most powerful and flexible method, offering benefits such as data preparation and cleaning before sending it to the cloud, selective data transmission, task isolation, and additional security layers. The article also introduces the 'to()' function which now supports writing data from an OSS v2.1 instance to an InfluxDB Cloud instance. It provides a step-by-step guide on how to use this function and highlights its limitations, suggesting using the mqtt.to() function for larger workloads. The article concludes by encouraging readers to take advantage of these features and share their experiences with the community.

This article provides an introduction to time series data and databases (TSDBs), focusing on InfluxDB as a leading TSDB. It explains why time series data is important, the advantages of using TSDBs over traditional databases, and why developers prefer InfluxDB. The article also covers how to use InfluxDB with Java, including setting up an instance, connecting via the InfluxDB Client Java library, inserting data points, querying data, and deleting data points. Finally, it touches on additional features of InfluxDB that developers can explore further.

This article provides a tutorial on how to use AWS Lambda serverless functions with InfluxDB for time series workloads. It covers setting up an InfluxDB instance, creating an AWS account, writing data to InfluxDB using the Javascript client library and AWS Lambda, querying InfluxDB using serverless functions, and working with stored data in InfluxDB. The article also discusses various use cases for InfluxDB such as data transformation, alerting based on defined thresholds, and integrating with other services like Slack and PagerDuty.

This blog post discusses how to collect and store automation data from PTC Kepware using InfluxDB. It provides a tutorial on setting up Telegraf, an open-source data collection tool, to stream data from Kepware to InfluxDB. The author explains two protocols for configuring this connection: OPC UA and MQTT. Instructions are provided for installing Telegraf, generating the necessary configuration files, and starting the service. Additionally, the post touches on topics such as security considerations, data visualization, and potential use cases for automation data.

The article discusses how to use Postman with the InfluxDB 2.0 API for interacting with an InfluxDB instance. It provides a step-by-step guide on importing and setting up the Postman project, configuring variables, and submitting requests. The author also mentions that while managing InfluxDB entirely through the API is possible, it's likely users will want to create some basic resources first using the InfluxDB UI or CLI.

The article discusses the use of Telegraf Operator as an alternative monitoring solution for Kubernetes environments. It explains that while Prometheus is a popular choice for monitoring Kubernetes, it may not be suitable for collecting metrics from non-Kubernetes environments. In contrast, Telegraf has hundreds of plugins that can collect metrics from various sources, making it more versatile. The article also provides instructions on how to install and configure the Telegraf Operator in a Kubernetes cluster.

The article discusses how to use the Flux deadman() function in InfluxDB Dashboards for visualizing uptime. It explains that the deadman function keeps the most recent row for each group (host), adding a dead column that is set to false if the most recent record happened after the time period to check for the deadman, or true if it happened before this time period, indicating a deadman. The article then provides a step-by-step guide on how to write a Flux query to use in a dashboard cell and includes an example of the complete query. It concludes by encouraging readers to ask questions or share their thoughts in the comments section.

Telegraf is a plugin-driven server agent for collecting and reporting metrics and events from databases, systems, andIoT sensors. It has over 200+ input plugins that cover a wide range of sources. However, to meet nearly any use case, it provides the Exec and Execd input plugins. The Exec plugin allows users to run arbitrary commands at each collection interval while the Execd plugin runs an external command as a long-running daemon. These plugins provide immense flexibility and freedom for collecting data from various sources.

This tutorial teaches how to create high-quality data visualizations easily by using the Nivo charting library with ReactJS. It also explains how to query data stored in InfluxDB, a database optimized for working with time series data, making charts dynamic and versatile. The tutorial covers setting up Nivo, understanding its components and props, setting up InfluxDB, writing data to it, querying data from it, visualizing the data with Nivo, and adding features to your project. It also provides additional resources for learning more about these tools.