March 2021 Summaries

The article announces the speaker lineup for InfluxDays EMEA 2021 Virtual Experience, a two-day event focused on time series data applications and use cases. The event will take place on May 18-19, 2021, and is free to attend. Key speakers include Paul Dix from InfluxData, Andy Charlton from InfluxData's Storage team, Jess Ingrassellino from InfluxData's data acquisition team, Vasilis Papavasiliou from Mist.io, Tim Hall and Ryan Betts from InfluxData, Aengus Rooney from Grafana Labs, Kristina Robinson from InfluxData's UI engineering team, Saiyam Pathak from Civo Cloud, Brooke Jamieson from PlaceOS, and Michael Hall from InfluxData. The event will also feature on-demand sessions by David Henthorn from Rose-Hulman Institute of Technology, Sebastian Spaink from InfluxData, Maksim Vazhenin from Dell Technologies, and Phil Day from Configured Things.

The author installed a Flume Water sensor in their home to track water usage and connected it to InfluxDB Cloud using Telegraf. They developed a Golang client for interacting with the Flume Water API, then wrote an external plugin for Telegraf to collect data from the Flume Water sensor. Finally, they connected the data into their InfluxDB Cloud account. The author encourages others with IoT devices and APIs to contribute custom Telegraf Input plugins.

The article discusses how to get started with InfluxDB on Google Cloud. It highlights the advantages of using InfluxDB on Google Cloud, such as handling large-scale time-stamped metrics and events generated by modern microservices, devices, and sensors. The author also mentions various use cases for InfluxDB on Google Cloud, including IoT event processing and analytics, DevOps monitoring, and integration with other Google services and products like Kubernetes, PubSub, and Data Studio. Finally, the article provides information on how to get started with InfluxDB Cloud on Google Cloud Marketplace.

Telegraf 1.18 has been released with a range of new plugins including Elastic Beats, directory monitoring, NFS, XML parsing and some aggregators and processors to help with data ingestion. The release includes an NFS plugin, a Directory Monitoring Input Plugin, an AWS EC2 Metadata Processor Plugin, a GeoIP Processor Plugin, an XML parser, new aggregators for quantile and derivative calculations, plugins for sending data to Grafana Loki, Google BigQuery, Splunk SignalFX, and Sensu. The Windows binaries include a signed executable and can be viewed in the telegraf.exe properties.

Giraffe is a graphing library by InfluxData that works with data from its time series database, InfluxDB. It has features like legends and colorization without much configuration. To get started with Giraffe, you need to set up and install InfluxData, either in the cloud or locally. Then, you can use Telegraf to set up data for your dashboards. Giraffe provides sample projects that demonstrate how to create line graphs using direct API and query API. The first project is a pass-through solution that shows an existing graph from InfluxDB on another page, while the second project allows users to make their own Flux queries.

Telegraf 1.18.0 has been released with new features such as updated Go version, code signing for Windows and macOS, additional SNMP v3 authentication protocols including SHA-512, support for DataDog distributions metric type, and more. The release also includes new inputs, outputs, external plugins, aggregators, processors, parsers, and serializers. Contributions from over 70 open source community members are acknowledged in this effort.

InfluxDB has released maintenance updates for its OSS (Open Source Software) and Enterprise versions 1.7.11. These releases are not the most recent versions of InfluxDB, but they contain fixes to support users who do not wish to upgrade to a more current version at this time. The latest version of InfluxDB OSS and Enterprise on the 1.x line is 1.8. For those using InfluxDB v2.0.x, it's the latest across all versions. Users can find download links for InfluxDB 1.7.11 in the community section of the website.

Anais Dotis-Georgiou's article provides an introduction to time series data science, emphasizing its importance for beginners in data science due to its unique characteristics, such as being chronologically indexed and often exhibiting autocorrelation. The text outlines the challenges posed by these attributes, especially with conventional algorithms, and highlights the utility of statistical methods for forecasting and anomaly detection. It suggests using Jupyter Notebooks and InfluxDB as key tools for learning and experimenting with time series data. Additionally, the article introduces a Notebooks repository that offers resources for getting started with various algorithms and data science tasks using InfluxDB, including anomaly detection and forecasting with tools like FB Prophet and LSTMs. The author encourages engagement and feedback from the community, providing avenues for support and further exploration.

Pi Day is celebrated on March 14th, a perfect opportunity to honor some of the notable women in the field of mathematics. Early trailblazers include Ada Lovelace, Sofia Kovalevskaya, Mary Cartwright, and Joan Clarke. Boundary breakers of NASA include Dorothy Vaughan, Katherine Johnson, and Mary W. Jackson. Modern marvels include Grace Hopper, Karen Uhlenbeck, and Maryam Mirzakhani. These women have made significant contributions to the field of mathematics and continue to inspire future generations.

InfluxDB allows users to process data on a schedule with tasks and write custom alerts. However, sometimes these tasks may fail. This article provides tips for debugging tasks using both the InfluxDB UI and CLI. The InfluxDB UI features include a task run status toggle, an export button, a view task runs button, and a run task button. These can be used to understand more about the tasks being run and to troubleshoot issues. The InfluxDB CLI also provides functionalities for debugging tasks such as retrying failed tasks or rerunning any task run. Additionally, it's recommended to use InfluxDB to monitor your own tasks by creating an alert that notifies you of failed runs with the corresponding task ID and run ID.

This article discusses how software developers can use Telegraf Execd Processor Plugin for time series forecasting and anomaly detection. The author explains that Telegraf is a lightweight collection agent that can be configured with a single TOML configuration file to gather metrics from over 180 inputs and write data to various outputs and platforms. It also acts as a processor, aggregator, parser, and serializer. The Execd Processor Plugin makes Telegraf extensible in any language, allowing developers to process their data however they need. The author demonstrates how this plugin can be used to continuously generate forecasts and perform anomaly detection using Python scripts. The article also provides an example dataset from a beer brewing setup monitored by InfluxDB, highlighting the importance of maintaining constant temperature during fermentation. It discusses considerations for choosing an algorithm suitable for this purpose, such as requiring minimal data for training and generating accurate predictions for short forecast periods. The author explains that using the Telegraf Execd Processor Plugin offers several advantages, including being extremely responsive with new forecasts generated every time a point is written to InfluxDB. Additionally, it can run an external process once, saving startup costs compared to running scripts like cron jobs. Finally, the author encourages developers to take advantage of this plugin and contribute their own external plugins by opening a pull request on GitHub. They also invite feedback and assistance with any problems encountered while using or contributing to Telegraf.

This blog post discusses how to use Telegraf to convert JSON data into Line Protocol format for use with InfluxDB. It explains that Telegraf has many input plugins for collecting JSON data, including HTTP Scraper, HTTP Listener, Socket listener, Kafka Consumer, Execd/Exec, File/Tail, and more. The post then focuses on the Starlark Processor plugin as a method to transform JSON data. It provides an example of how to configure Telegraf with the Starlark processor and includes sample code for parsing JSON using Starlark. Finally, it explains the Line Protocol format that results from this process.

Flux Training is back by popular demand as part of InfluxDays EMEA 2021 Virtual Experience on May 10-11, 2021. The course uses an IoT-sensor-enabled pizza oven and corresponding time-stamped data to teach Flux, a powerful language from the makers of InfluxDB that allows developers to explore and analyze data across time. Over two days, participants will become familiar with InfluxDB Cloud and Flux through lectures, demos, hands-on practices, homework, polls, and breakout sessions for better 1:1 time with instructors. The course is capped at 50 students and costs £350.00, which includes registration for InfluxDays EMEA 2021.