February 2022 Summaries

This article discusses the use of Tokio, a Rust runtime, for CPU-heavy tasks beyond its traditional use in network I/O. The author argues that while Tokio was initially thought to be unsuitable for such tasks due to potential performance issues, it can actually be a good choice when used correctly. The main points include: Tokio's work-stealing scheduler and language support for continuations (async/await) make it well-suited for CPU-bound tasks; the runtime's overhead can be amortized using vectorized processing; however, common objections to using Tokio include its potential impact on request tail latencies and high per-task overhead. To overcome these issues, the author proposes running tasks on a separate Tokio Runtime instance, which allows for better cache locality and avoids the overhead of the main runtime. The code example demonstrates how to create and use such a dedicated executor.

The Things Network has undergone changes since January 2021, including deploying The Things Stack Community Addition. This addition provides developer-friendly tools, accessibility and scalability features, and advanced protocols for accessing data. A new project was started to port a well-known IoT project, Plant Buddy, to The Things Network using the Arduino MKR WAN 1310 device. The architecture of this new project involves setting up the LoRaWAN device, wiring sensors, provisioning the device, and connecting it to the Things Network console. Once connected, the device can stream sensor data to InfluxDB using Telegraf and the MQTT Consumer Plugin.

To create an iOS and Android chart with data visualizations using React Native and Victory Native, you need to have a basic understanding of JavaScript and familiarity with ReactJS. You also need a running instance of InfluxDB to store time series data. The tutorial will guide you through installing Expo CLI, creating a new project, setting up the InfluxDB client library, and deploying your app to the web. It covers basic chart components such as VictoryBar and VictoryLine, useful props like data, x, y, style, and more. The example code uses InfluxDB to query air sensor data from the last 30 minutes, transforms the results, and passes them to a Victory chart component for visualization. The tutorial concludes with tips on cleaning up the project and resources for further learning.

This article discusses the challenges of remote work and the need for better support models and tools to meet the demands of a decentralized workforce. The author, Donal O Duibhir, who founded PanSift, shares his experience of building a productized offering to help technical teams support remote workers. PanSift uses InfluxDB as its core time series database (TSDB) to provide real-time monitoring and troubleshooting capabilities. The solution is designed to scale with the growing complexity of remote work environments, using a modular architecture that leverages trusted and scalable building blocks like Telegraf. By distributing data across multiple instances of InfluxDB, PanSift achieves horizontal elasticity, allowing for simple scaling, load balancing, and future traffic optimizations. The author believes that by empowering IT teams to remove toil and be more productive, PanSift can help create a more positive and decentralized future for remote workforces.

The latest release of InfluxDB Enterprise, version 1.9.6, includes several key highlights such as advancements in Flux, timezone support enhancements, integration with MQTT brokers, notification endpoint enhancements, SQL integration improvements, and other notable enhancements. Additionally, this release brings significant improvements to backup and restore operations, including estimating the size of backups and providing progress messages, as well as reverting damaged meta nodes to a previous state. Logging enhancements also include an audit log for meta nodes and logging active queries when a process is terminated. The release is available for InfluxDB Enterprise customers through the portal, and support can be reached through various channels including the InfluxDB Community Slack and GitHub Repo.

Pipedream is an integration platform that enables developers to build event-driven workflows by combining different tools together, providing a middle ground between custom API integrations and low-code platforms. It offers 400+ pre-built integrations with various APIs and provides features such as testing and debugging through its UI. Pipedream can be used for tasks like connecting SaaS apps, custom notifications and alerting, database automations, mobile app or JAMstack site backends, rate limiting, and more. The platform consists of three main components: workflows, triggers, and steps, which are used to define the actions taken on input data. To set up Pipedream with InfluxDB, users need to create a bucket for testing and sending alerts, insert sample data into it, and then connect their Pipedream account to the InfluxDB instance. The platform allows users to create flexible alerting and notification systems by combining different APIs accessible through Pipedream. Users can customize the workflow by adding steps such as HTTP API triggers, NodeJS steps, and email notifications, and configure checks and alerts using Flux scripts. Additionally, Pipedream offers features like conditional workflows, enriching data, and scheduled tasks, which enable users to extend their current workflow and create more complex use cases.

Telegraf 1.21.4 has been released, addressing security vulnerabilities and introducing updates to various plugins, including Docker Input Plugin, JSON v2 Parser, and Go library, as well as adding new external plugins such as apt and knot for collecting stats from Knot DNS. The release includes fixes for issues with timestamp handling, memory usage calculation, and deprecated warnings for PreVista support. Additionally, the update includes dependencies updates to various libraries and frameworks, including Go, OpenTelemetry, and Kubernetes.

InfluxData, a company that creates time series platforms, has announced new customers and accelerated momentum in Industrial Data and Internet of Things (IoT) markets, driven by enhanced features and expanded partnerships with leading manufacturing providers such as Tesla, Rolls Royce, Airbus, Teck, Graco, and Graphite Energy. These companies use InfluxDB to collect industrial data from devices and sensors, providing a real-time digital view into operational performance. New InfluxDB enhancements for IoT and IIoT applications include features like run analytics at the edge with persistent and replicated data, broadcasting new data to thousands of devices simultaneously, intelligently deploying software at the edge with configurable packages, and contextualizing IoT data across multiple sources. Expanded partnerships with industry-leading IIoT platforms such as PTC, Siemens, Bosch, and others further drive InfluxDB's position as a leading time series platform for industrial and IoT applications.

InfluxDB is designed to handle the variety, volume, and velocity of IoT data, making it a key component in IIoT use cases such as predictive maintenance, optimized traffic routing, and enhanced water conservation. The platform includes powerful dashboarding tools for visualizing and analyzing sensor data, new capabilities to store IoT data at the edge, process and analyze that data locally, and push raw, aggregated, and otherwise actionable data to a network of InfluxDB hubs in the datacenter or cloud. These updates aim to expedite the development of IoT and IIoT solutions and enable accelerated insights for engineers working with industrial data at the edge. Additionally, InfluxDB has expanded its support for MQTT brokers, improved its flexibility for resource-constrained edge devices, and connected with a growing ecosystem of IIoT partners, including leading Industrial and IoT platforms and middleware software. The platform is used by several prominent organizations, such as Tesla and Rolls-Royce Power Systems, to collect and analyze industrial sensor data, and offers commercial relationships with organizations in the Industrial, Enterprise, and Consumer categories of the Internet of Things.

Graphite Energy has developed Thermal Energy Storage (TES) systems to help even out the distribution of energy from renewable sources and decarbonize industrial heat. These systems generate heat or steam for industrial processes, reducing reliance on fossil fuels and accelerating industrial decarbonization. The TES units are highly instrumented, collecting hundreds of data series and approximately 1 million data points per day, which are stored in InfluxDB Cloud for analysis. Graphite Energy uses a Node-RED workflow to collect and process the data, and then queries and transforms it using Flux to create a digital twin, a real-time model of the TES unit that is accurate to within 5% of actual machine performance. The digital twin enables predictive optimization and significant strides toward industrial decarbonization.

InfluxData has appointed Jeremy Freeland as its new Chief Legal Officer, bringing nearly three decades of global legal experience to the role, as the company continues to expand globally and enter its next phase of growth. The appointment reflects InfluxData's commitment to assembling a world-class leadership team to support its customers' scaling needs, with Freeland expected to lead the development of the company's legal department to drive revenue growth and customer success. With his experience working with early to late-stage technology companies, Freeland is well-positioned to help InfluxData build transformative applications with its time-stamped data, which powers IoT, analytics, and cloud applications for major organizations such as Cisco, IBM, Siemens, and Tesla.

This tutorial guides users in creating an Arduino application for recording climate data in an InfluxDB instance over WiFi. The process involves setting up an ESP32 board, pairing it with a DHT11 temperature and humidity sensor, and using the InfluxDB client library to send data to an InfluxDB instance. The code initializes the necessary libraries, sets up the WiFi connection, reads data from the sensor, adds fields to a Point object, and writes the data point to the InfluxDB instance. The tutorial demonstrates the potential behind pairing Arduino with time series databases like InfluxDB, enabling users to log any sensor data they can imagine and analyze longitudinal data.

InfluxData's time series platform, InfluxDB Cloud, has been named a winner in the 2021-22 Cloud Awards category for Best Use of the Cloud in the Internet of Things. This recognition highlights the platform's ability to manage massive volumes of IoT data and engage in device monitoring and analytics on a faster and broader scale. The platform enables developers to quickly build and integrate time-stamped data applications, identify trends over time, and ensure mission-critical processes are more consistent, efficient, and reliable. InfluxDB Cloud is designed to handle the challenges of managing IoT data, including its volume, variety, and velocity, with real-time processing capabilities that allow for human interaction-free actions.

This tutorial provides a comprehensive overview of the InfluxDB API, covering authentication methods, data insertion, querying, and retrieving data from a time series database. The author explains how to use the token-based authentication method, which is preferred for its flexibility and security. They demonstrate how to create an organization, user, and bucket, generate an API token, and use it to authenticate with the InfluxDB instance. The tutorial also showcases how to insert data into a bucket using the write endpoint and query data from a bucket using the Flux language. Additionally, the author highlights best practices for schema design in time series use cases and emphasizes the importance of considering the relational paradigm when designing solutions for time series databases like InfluxDB.

InfluxData is a company that offers a time series database product, which is part of a larger trend towards exponential growth in data usage due to the increasing connectivity of devices through the Internet of Things (IoT). The author joined InfluxData after feeling inspired by the company's values and mission, particularly its emphasis on embracing failure as a means to improve and grow. The author was drawn to the product because it has numerous applications across various industries, including space exploration, where time series data is crucial for understanding and analyzing vast amounts of data from satellites and other sources.

InfluxDB is a time series database designed to store and retrieve time-stamped data on measurements or events collected over a specified period of time. It's fast, easy to use with no dependencies, offers multiple data compression algorithms, and works with open-source Telegraf plugins for better developer experience. To set up InfluxDB with a Dart application, users need to install the InfluxDB client library, launch InfluxDB via HTTPS, and connect the client library to InfluxDB. The client library can be used to insert, read, update, and delete data in InfluxDB. It's recommended to use SSL/TLS when connecting to the database and update it whenever possible. InfluxDB provides detailed insights into app users and traffic types, helping businesses make informed decisions.

The latest release of Chronograf includes several security improvements, including an upgrade to the bluemonday component to resolve a known vulnerability (CVE-2021-29272) and enhanced access controls to prevent users from accessing multiple organizations simultaneously. Additionally, this release introduces features such as the ability to rename TICKscripts, improved InfluxDB Query Management, HTTP proxy support, token command enhancements, OAuth client improvements, Kapacitor client updates, Flux client changes, and enhanced logging capabilities. These improvements aim to improve the overall user experience, security, and performance of Chronograf.

InfluxData celebrated Lunar New Year with its employees, who participated in traditional celebrations such as eating dumplings and noodles, exchanging red envelopes, and attending local Chinatown parades. The company's mascot for its popular product Telegraf, the tiger, plays a significant role in InfluxData's branding and merchandise. Employees decorated their homes with red paper lanterns, prepared traditional foods like dumplings and noodles, and even gave out red pockets to kids. InfluxData also hosted a virtual Blinner where employees could join for breakfast, lunch, or dinner depending on their time zone. The celebration coincided with the Year of the Tiger, which is believed to bring good luck and prosperity in Asian cultures.