November 2018 Summaries

InfluxData's Chronograf offers predefined dashboards that simplify data visualization and make it easier to access key metrics. The latest release of Chronograf includes improved onboarding, allowing users to quickly collect and visualize their data. With a user-friendly interface, users can easily build custom dashboards using pre-configured templates for popular systems like Kubernetes, Redis, Apache, and more. By providing a seamless experience from collecting metrics to visualizing them in a meaningful way, Chronograf's predefined dashboards enable developers to gain insights into their applications without requiring extensive setup or expertise.

Techzone360 | Pushing IoT Analytics to the Edge` The process of pushing IoT analytics to the edge is essential for efficiently collecting and analyzing the vast amounts of real-time data generated by IoT devices. This approach can significantly reduce costs associated with data collection and transmission, making it a crucial requirement for many IoT deployments. To achieve this, a performant gateway device is needed that can handle the demands of IoT data collection, along with highly efficient software to run on it. Building an edge device requires careful consideration of its attributes, including its ability to process time-series data efficiently. As IoT data is inherently time-series in nature, having a robust platform for data collection and analysis is vital for unlocking its full potential.

AWS customers can now easily monitor and analyze their Kubernetes environments using InfluxData's modern Open Source Platform on AWS Marketplace for Containers, offering a one-click capability to run Amazon EKS Monitoring and deploying InfluxDB Enterprise or Open Source on containers. The new solutions simplify monitoring, accelerate deployment, and empower organizations to reduce their "Time to Awesome" for analytics and machine learning, with improved observability and instrumentation of Kubernetes environments. With the launch, AWS Marketplace has extended its benefits and features to container products, offering a curated catalog of trusted software from reputable vendors.

Sensu has partnered with InfluxData to integrate InfluxDB Enterprise Edition and InfluxDB Cloud as its preferred time series data store, enhancing Sensu's monitoring software for critical applications and enterprise infrastructure. The collaboration allows Sensu to handle large workloads of time series data from any infrastructure source that sends data to Sensu. This joint solution enables developers using Sensu Core to collect, process, analyze, and store even larger data workloads using InfluxData's products. The partnership aims to deliver a product that scales with the needs of IT organizations, helping them eliminate downtime and revenue loss as a result. With this integration, Sensu will include InfluxData products as its preferred time series platform in its core and enterprise products, respectively.

The Growth of an Open Source Community` Telegraf's growth from its initial creation by Paul Dix on April 1, 2015 to the present day has been a remarkable journey, as visualized in the video `telegraf-git`. The project's number of contributors has exploded over time, with Telegraf relying heavily on its community for input and output plugins. This growth is a testament to the power of open source software development and the importance of contributions from developers and contributors. As a result, Telegraf has become a robust and versatile tool for gathering statistics and metrics, used daily by its creator and many others. The project's success is a special thank you to all those who have contributed to its growth and development over the years.

K-Means is a clustering algorithm used for anomaly detection in time series data, as demonstrated by Anais Dotis-Georgiou's work with InfluxDB and Chronograf.` `She successfully applied K-Means to detect anomalies in EKG data using the InfluxDB Python Client Library, and utilized Chronograf to manage alerts and autogenerate a TICKscript for Kapacitor.` `This approach allows for efficient detection of unusual patterns in time series data, enabling better insights into system behavior and potential issues.

Telegraf 1.9.0 has been released, featuring improved performance and new features such as a `max_undelivered_message` option to prevent over-consumption when reading from queue consumers, and the ability for input plugins to add metrics to the output buffer even when writing is slow. The HTTP listener plugin has also been renamed to `influxdb_listener`, while a new `http_listener_v2` plugin has been introduced as a service input plugin that listens for metrics sent via HTTP. Additionally, Telegraf now supports Kubernetes targets using the `prometheus.io/scrapelabel`, and new inputs have been added including Jenkins, Nginx Plus, Nginx VTS, Wireless, and Google Stackdriver outputs. The binaries can be found on the downloads page.

The article provides a walkthrough on building Flux queries in Chronograf by IoT Developer Evangelist David Simmons. The author explains how to convert InfluxQL queries to Flux, highlighting his experience with an embedded IoT gateway proof-of-concept device that runs the TICK Stack and collects data from various sensors. The discussion focuses on the Chronograf Dashboard Builder and how to build Flux queries using InfluxDB 1.7, Chronograf 1.7, and the new Flux Builder along with the Schema Explorer.

The author uses K-Means clustering for anomaly detection on EKG data using InfluxDB and Chronograf. The process involves segmentation, windowing, clustering, reconstruction, normal error calculation, and anomaly detection. The author uses Python to perform these steps, including data exploration, segmentation, and reconstruction, and then detects anomalies in the EKG data by comparing the reconstructed data to the original data. The anomalies are then written to a database, where Kapacitor is used to set a threshold and alert on any errors that exceed the normal max reconstruction error of 8.8, which results in an alert being sent to the author via Slack when an anomaly is detected.

Flux queries can be easily created using the Flux Builder in Chronograf, with similar syntax to InfluxQL, but with additional features such as automatic window sizing and aggregate functions like mean(). The new language is designed for working with time series data and allows for flexible querying of data from InfluxDB. The Flux query syntax is similar to InfluxQL, but with some key differences in how the `window()` function is used and the addition of aggregate functions.

A new maintenance release for Chronograf has been made available, featuring enhancements such as a loading spinner when creating predefined dashboards and resolving issues with MacOS path settings, database retention policies, and pre-created dashboard templates for various databases.` `The update also includes improvements to the BASE_PATH variable to prevent trailing slash issues and fixes for GROUP BY options and dashboard creation.` `Binaries for the latest open source release can be found on Chronograf's downloads page.

Flux is InfluxData's new functional data scripting language designed for querying, analyzing, and interacting with data. The developers who attended last week's InfluxDays event in San Francisco got to see Flux in action as well. To bring the community up to speed on Flux, InfluxData will be releasing Flux-focused blog posts which highlight the capabilities of the language with examples to help users get started. Additionally, Flux Office Hours are being scheduled where top engineering experts will answer questions around Flux and gather community feedback to improve the language. The goal is to make Flux an extensible, contributable, and shareable language.

In a recent DevOps.com article, Alan Shimel interviews Evan Kaplan, CEO of InfluxData, which boasts over 200,000 users of its open-source database, InfluxDB. The conversation focuses on systems instrumentation and its significance for developers and teams, as well as the evolution from instrumentation to observability and automation. Kaplan shares his journey, including meeting the founder of InfluxData, Paul Dix, and the company's rapid growth. He emphasizes the importance of understanding what big data and velocity mean for developers and how instrumentation can help bridge the gap between development and operations teams.

Flux 0.7 Technical Preview is integrated into InfluxDB 1.7, enabling users to query, analyze and interact with data using a new functional data scripting language called Flux. The technical preview is included in the release of Chronograf 1.7, which provides a user interface for building queries using Flux. To enable Flux, users need to set `flux-enabled` to true under the `[http]` section of their InfluxDB configuration file. Flux uses buckets as named locations where data is stored with retention policies, and from() function requires a bucket parameter. The language returns data in tabular format, using the pipe-forward operator extensively to chain operations together. Users can write their first Flux script using Chronograf's Data Explorer, which provides access to the Schema, Script, and Flux Functions panes. The Script Wizard allows users to quickly select a bucket, measurement, one or more fields, and a function to get started with building queries.

InfluxData is betting on a significant market for its time series data platform, citing the growing demand driven by IoT sensors, Kubernetes adoption, and a focus on developers as key factors in its strategy.` `The company has responded to increasing Kubernetes adoption by rolling out new features giving developers more control over containers, and recently built a relationship with Google, announcing a new Telegraf agent for Cloud IoT Core.

InfluxData has released an enhanced version of its leading Time Series Database, InfluxDB 1.7, which delivers major query performance and data compaction improvements to support faster and more efficient processing of time series data used in various applications such as DevOps, IoT, containers, real-time analytics, and cloud computing. The new release was announced at InfluxDays San Francisco 2018 and provides developers with robust tools to query and process large amounts of time series data. Additionally, the company has also announced a technical preview of Flux, a query language designed for InfluxDB.

InfluxDB 1.7 has been released, offering significant query performance and data compaction enhancements to improve the Time Series Database's capabilities for handling large amounts of time-stamped data. The new release is expected to deliver superior performance and meet the needs of advanced developers in DevOps monitoring, application metrics, IoT sensor data, and real-time analytics. InfluxData aims to maintain its leadership position in this category with these improvements.

The latest release of Chronograf, a data exploration and visualization tool from InfluxData, introduces several key features to enhance user experience and workflow efficiency. Predefined dashboards have been added, allowing users to easily import and use as a starting point for building their own custom dashboards. The Data Explorer page has also undergone significant changes, enabling users to select any data source or visualization type without leaving the page. Additionally, full Flux query support has been introduced, providing a powerful new language for exploring and visualizing InfluxDB data. Other enhancements include scoped annotations, notes on dashboards, and improvements to the Log viewer and Alert Rules page. Overall, these features aim to make exploring and working with data in Chronograf easier and more intuitive for users.

### InfluxData Time Series Database Extends Industry Lead with Performance and Data Compaction Enhancements in Latest Release InfluxData has released InfluxDB 1.7, a major update to its leading Time Series Database, delivering significant query performance and data compaction enhancements. This release further solidifies InfluxDB's position as the industry leader among Time Series Database management systems. The company also announced the technical preview of Flux, its first purpose-built functional query language for time series data, which combines data query and processing in a single powerful and extensible open source language. Developers are encouraged to use Flux and provide feedback to help shape its future development. With this release, InfluxData aims to empower developers to build next-generation monitoring, analytics, and IoT applications faster, easier, and to scale, delivering real business value quickly.

InfluxDB 1.7.0 and Chronograf 1.7.0 have been released with significant performance improvements, including boosted shard compaction and faster query performance through the Time Series Index (TSI). The new release also introduces Flux v0.7, a functional query language that unlocks new capabilities within InfluxDB. Additionally, Chronograf has received numerous feature additions, including predefined dashboards for various platforms, markdown notes on dashboards, scoped annotations, and UI improvements to the Data Explorer page. The binaries are available on the downloads page, with an InfluxDB Enterprise 1.7 release planned for later this month.

InfluxData Roadshows are coming to Europe in December, targeting local users who reside near the roadshow location and featuring InfluxData VP of Products Tim Hall as a presenter. The event aims to bring InfluxData's product leadership closer to its user community, focusing on educating and enabling attendees to instrument and automate systems using the industry-leading Time Series Platform. Sessions cover various topics including customer case studies, architecture and best practices, and technical roadmap discussions. Registration is limited and on a first-come-first-serve basis, making it an exclusive opportunity for those interested in learning about time series data and its applications.

Playtech has deployed InfluxData's InfluxDB Time Series Database to power its predictive monitoring and alerting system for a distributed global gaming network, leveraging the platform's visibility into system behavior, causes, relationships between components, and needed actions to improve network observability. The company was looking for more precise early performance predictions than previous solutions could deliver, particularly in its production gambling system across over 50 sites with many brands located globally. With InfluxData, Playtech can track and monitor user behavior in real-time, gather important metrics, and prevent outages and malicious behavior. The platform's observability features have proven critical to the company's business, enabling early detection of security attacks and service-start problems.

As a developer, I used to think it didn’t matter what product I worked on as long as I worked with great people. However, I've learned that I have to be working on something that contributes to the industry and the world in a meaningful way. InfluxData builds products that help developers store, parse, and understand large datasets to extract meaningful information, which is incredibly valuable in today's data-driven era. The company's core values of humility and embracing failure resonate with me, as I've struggled to embody these qualities in the past. I'm heartened to find a company that understands the importance of humility and failure as foundational aspects of learning and thriving.

Introducing Developer Support from InfluxData InfluxData is introducing a new developer support service for its open-source time series data platform, which will provide email-based support to users of Telegraf, InfluxDB, and Chronograf. The company has always focused on delivering faster 'Time to Awesome' for developers and now aims to help open-source users achieve their goals with timely guidance and problem-solving. This new support offering complements existing Enterprise and Cloud customer support, while providing tutorials, webinars, and open documentation to aid developers in solving time series problems. The service is designed to speed up InfluxDB adoption and get developers on a fast track to resolving their challenges.

InfluxData has been selected to present at several industry events worldwide, including the Open Source Monitoring Conference and DevOpsCon in Germany, Data @Scale in Boston, and KubeCon + CloudNativeCon North America 2018 in Seattle. The company will be addressing growing interest in time series platform knowledge and expertise as metrics, events, and other time-based data are generated at an exponential rate. InfluxData's comprehensive platform provides tools and services to analyze time series data, empowering developers to build next-generation monitoring, analytics, and IoT applications. With over 420 customers across various industries, including manufacturing, financial services, energy, and telecommunications, InfluxData is pioneering the shift to time series in a modern metrics and events platform.