October 2017 Summaries

InfluxData has joined the Cloud Foundry Foundation as a Silver member, bringing its expertise in time series analytics to the industry-standard platform for cloud applications. The company aims to extend its growth across the Cloud Foundry ecosystem and contribute to the development of cloud-native architecture. InfluxData's modern Open Source Platform is designed for analyzing metrics and events, providing tools and services for accumulating data, analysis, and action. The company shares a common goal with other Foundation members to help developers build applications faster, easier, and to scale in today's cloud native environment.

InfluxDB vs. Elasticsearch for Time Series Analysis` The article by Daniel Berman compares InfluxDB with Elasticsearch, two technologies designed to handle time series data analysis. InfluxDB was specifically developed to store and manage time series data, while Elasticsearch is a full-text search and analysis engine. The author concludes that further development of InfluxDB could make it a leader in time series data storage, given its initial strengths in this area.

In a review by Linux Journal's Products Editor James Gray, InfluxData is highlighted as a powerful platform designed for handling metrics and events, particularly for "ephemeral" data. The 1.3 Platform release is reviewed, showcasing its ability to handle one billion unique time series. This platform is built from the ground up for this specific use case, making it an attractive option for those looking to manage large amounts of ephemeral data.

Telegraf 1.4.3, InfluxDB 1.3.7, and Chronograf 1.3.10 have been released with new features including millisecond precision drill-down within dashboards, CSV file export of data displayed in dashboard cells, independent time ranges, and manual refresh options for dashboards. The releases also address a critical issue related to delete commands being issued, which could lead to broader data deletion than anticipated, and are now available for download on the InfluxDB website.

InfluxDB is a time series database that stores data in points with four components: measurement, tagset, fieldset, and timestamp. Points are associated with a measurement, which can have different tagsets or fieldsets. The data model includes a series, which is a group of points sharing the same measurement, tag set, and field key. InfluxDB receives points from clients through an HTTP POST endpoint, where each point is stored in a database and retention policy. Points are written to a write-ahead log (WAL) for durability and an in-memory cache for queryability. The WAL and cache work together to make incoming data durable but are insufficient for long-term storage. InfluxDB organizes its columnar format into time-bounded chunks, which are stored on disk as TSM files that can be compacted over time. The retention policy configures the duration, replication factor, and shard duration of a database, allowing users to manage their data's lifespan and query performance.

Millisecond Level Precision Graphs with Chronograf v1.3.10.0` Today marks the latest release of Chronograf, the UI for the TICK Stack, which now supports millisecond-level precision when displaying and drilling down into query results through dashboards. The new version automatically adjusts the query's 'group by' interval to sub-second values and allows for finer-grained zoom than in previous versions. Additionally, downloading query results as a CSV file is available in dashboards, each dashboard cell can have an independent time range, and there's a manual refresh button for triggering a dashboard refresh. The release also includes UI enhancements and bug fixes, with the next version planned to include user-level permissions and organizations, as well as a Kapacitor log viewer.

OpenTracing is an open standard for distributed tracing that enables developers to instrument their applications with minimal effort, providing visibility into complex systems and workflows. It offers a way to trace requests from beginning to end across touchpoints, understanding distributed systems at scale. A trace in OpenTracing is a directed acyclic graph (DAG) made up of spans named, timed operations representing contiguous segments of work, each component contributing its own spans. The standard aims to simplify troubleshooting in microservice platforms by collecting timing data needed to troubleshoot latency problems common with microservices. With the growing need for effective monitoring and understanding of distributed systems, OpenTracing adoption is increasing, driven by companies' desire to know what's happening in their applications and take appropriate action.

Dan Cech, with 12+ years of experience in developing high-performance web applications and backend systems, will be speaking at Influx/Days about data visualization and alerting using Grafana. He will provide an introduction to Grafana, show how to add data sources, create dashboards, and share tips on customizing dashboards to get the most out of data analysis and troubleshooting. Grafana is a popular tool used by many InfluxDB users for monitoring and visualizing data, and Dan's talk will help attendees understand how to effectively use it to improve their data analysis skills.

Baron Schwartz, a renowned expert on database internals and large-scale application development, will be speaking at Influx/Days in San Francisco this November. His talk, "What Good Is Anomaly Detection?", aims to educate attendees on how anomaly detection works, its limitations, and specific use cases where it excels. As an executive at Percona and founder of VividCortex, Baron brings valuable insights from his experience with various database communities, including MySQL, PostgreSQL, Redis, and MongoDB. His talk promises to be both informative and entertaining, offering a unique opportunity for attendees to learn from this expert and network with colleagues. By registering early, attendees can take advantage of the special promotion for bringing a friend or colleague.

InfluxData has partnered with IBM and RedHat to simplify analyzing IoT data, addressing the disruption of traditional enterprise architecture and the need to collect, store, visualize and process time series data in a rapidly changing technological landscape. The partnership aims to provide a simplified solution for companies to handle the growing volume of IoT data, leveraging InfluxData's TICK Stack and building on IBM and RedHat's expertise in cloud computing and networking. By teaming up, the three entities hope to help organizations navigate the complexities of time series data management and unlock its full potential.

The ThingMonk 2017 conference was held in London from September 11-13, sponsored by InfluxData, and featured a diverse lineup of speakers and attendees. The conference covered various aspects of IoT, including MQTT 5.0, digital twins, data dimensionality, and blockchain. Some notable talks included Sebastien Lambour's presentation on using IoT to manage mood disorders, Yodit Stanton's talk on the reasons why IoT projects fail, and Gary Barnett's discussion on the "number one thing" in IoT. The conference also featured demos of digital twin technology, including a demo where attendees were scanned and their data was used to create a 3D virtual model of the conference. InfluxData showcased its backend data collection mechanism, InfluxDB, which was used by some attendees to collect environmental sensor data in real-time. The event highlighted the importance of diversity and inclusivity, with a strong emphasis on making the conference accessible to a wide range of speakers and attendees. Overall, ThingMonk 2017 was a unique and informative conference that provided valuable insights into the world of IoT.

InfluxData aims to reduce the "Time to Awesome" by providing a user-friendly experience for developers and businesses. To test this claim, the author installed and configured InfluxDB, Chronograf, Telegraf, and Kapacitor on a MacBook Pro, setting up a system-monitoring dashboard in under 5 minutes. The installation process was streamlined using Homebrew, a package manager for macOS, with only seven commands required to get everything up and running. This demonstrates the ease of use and speed of setup for InfluxData's products, making it an attractive option for those looking to quickly achieve results with minimal complexity and code.

Emily Nakashima is a full-stack JS developer who loves design, web performance, and metrics. She currently works at honeycomb.io as an engineer and has experience in full stack development, browser JavaScript, and browser monitoring. Emily has a genuine concern for user experience and will share her experiences in monitoring events that potentially indicate frustration with the UI in her talk at Influx/Days 2017. She will discuss strange cases she's seen in browsers, such as overseas proxy sites and rogue browser extensions, and provide advice on how to cut the noise and focus on minimum viable instrumentation to have visibility into user experience metrics.

The concept of a Digital Twin is being discussed in this text, where a digital representation of a physical thing is created to simulate its performance and make adjustments virtually. In the context of IoT, integrating external data sources can enhance the accuracy and usefulness of IoT data by validating it, giving a larger context, or augmenting its capabilities. The author shares an example of how they used publicly available real-time datasets from the National Weather Service observation stations to correlate with their own sensor data in InfluxDB Cloud, demonstrating the potential benefits of combining external data sources with IoT data. The possibilities for using such external data sources are nearly limitless, and the author is planning to explore further integration with Telegraf plugins to simplify the process.

The company InfluxData has announced that its time series data platform is now available on Red Hat OpenShift Container Platform, with certified container images published in the Red Hat Container Catalog. This move aims to simplify deployment for users of the platform and provide more confidence in a solution built on and certified with Red Hat’s environment. The partnership between InfluxData and Red Hat enables developers to build monitoring, alerting, and notification applications, as well as IoT applications that support millions of events per second, providing new business value through predictive maintenance and real-time alerting and control.

The author of the article is looking for ways to use InfluxDB to track real-time weather updates. He finds an RSS feed from the National Hurricane Center that provides live data on tropical storms and hurricanes, and uses Node-Red to parse the XML feed and extract relevant information such as storm name, type, center coordinates, pressure, movement direction, speed, and wind speed. The extracted data is then inserted into his InfluxDB instance, where it can be visualized using dashboards created with Grafana. The author also discusses the challenges of working with noisy RSS feeds and the need to handle non-numerical values such as "Stationary" for storm movement direction and speed. He concludes by mentioning that he is looking for other freely accessible real-time datasets to add to his InfluxDB instance.

InfluxData has developed a modern open source time series database platform designed to simplify metrics and events handling in various applications such as DevOps monitoring, IoT, and real-time analytics.

OpenTracing is an open standard for distributed tracing that aims to provide a uniform way to collect, store, and analyze traces across multiple services in a distributed system.` It was developed by InfluxData as part of the OpenTracing project. `The goal of OpenTracing is to simplify the process of implementing distributed tracing in modern microservices-based systems, reducing the complexity and overhead associated with existing solutions.` By providing a common language for defining traces, OpenTracing enables developers to easily integrate their services into a single, unified view of system performance and behavior.

The latest version of Chronograf, 1.3.9.0, has been released with several new features, including an editor for TICKscript, support for fill() functions, and the ability to download queries as CSV files. This release builds on previous updates, such as customizable dashboards, InfluxDB administration, and support for Kapacitor alerts, and is designed to address community requests. The new TICKscript editor allows users to view and edit scripts directly within Chronograf, while also enabling batch and stream processing script management. Future plans include integrating log information via the log API in Kapacitor 1.4.0, time-based comparison, and user-level permissions and organizations in a forthcoming release.

Chronograf 1.3.9.0 has been released, featuring enhancements such as a new TICKscript editor integration with Kapacitor, customizable dashboard cells, and improved Data Explorer functionality including export to .csv format and query sharing via URL encoding.

The developer of Telegraf, a popular open-source monitoring system, has released version 1.4.2 as a maintenance update, addressing various issues and improving overall stability and performance. This release is intended to provide a smoother user experience for Telegraf users, who can access the detailed release notes by navigating to the provided link. The update is now available for download, allowing users to take advantage of the improvements made in this version.

Dan Vanderkam, a Senior Software Engineer at Sidewalk Labs, will be speaking at InfluxDays 2017 about dygraphsan open source JavaScript charting library. Dygraphs is an appealing visualization for dashboards due to its combination of performance and interactivity. Dan's talk will cover how to add dygraphs to projects and facilitate interactive data exploration, as well as the challenges of maintaining open source projects over time. Dan has a background in working on projects at Google and Mt. Sinai’s HammerLab, and has experience with web search and search logs analysis. He is excited to share his knowledge and expertise with attendees at InfluxDays 2017.

Jared Lander is a rising star in data science and was featured in the Wall Street Journal for his work on dissecting the 2016 NFL draft. He is also the Chief Data Scientist of Lander Analytics, organizer of several meetups and conferences, author of R for Everyone, and an adjunct professor at Columbia University. Jared will be speaking at Influx/Days 2017 about modeling time series data in R, discussing various techniques including traditional methods like ARMA, tools like Prophet, and machine learning models like XGBoost. He has experience in both academic research and industry, is active in the data community, and frequently speaks at conferences around the world.

InfluxData's Time Series Platform, InfluxDB Cloud, is now available on IBM Cloud, allowing companies to integrate high-performance cloud infrastructure with advanced development services such as monitoring and real-time alerting into their IT environments, providing a more comprehensive solution for managing time series data.

InfluxData's Time Series Platform has been made available on IBM Cloud, enabling companies to integrate high-performance cloud infrastructure and development services into their IT environments. The platform provides real-time monitoring, alerting, and notification capabilities for DevOps initiatives, IoT applications, and real-time analytics applications. Developers can easily get started with InfluxDB Cloud directly from the IBM Cloud console, making it easier to implement monitoring on any application or service created within the console.

The TICK Stack, consisting of Telegraf, InfluxDB, and Chronograf, has received new releases with version numbers 1.4.1 for Telegraf, v1.3.6 for InfluxDB, and v1.3.8.3 for Chronograf. These updates are now available for download on the InfluxData portal. Additionally, a maintenance release is also available for InfluxDB Enterprise customers, which can be accessed through their customer portal.

Kapacitor is a tool that can enrich data coming from Telegraf and sending it to InfluxDB by adding computed values such as time periods, allowing for more complex queries on the data. To accomplish this, users need to configure Telegraf to write to Kapacitor instead of directly to InfluxDB, create a TICKscript that processes the data, and then define the task in Kapacitor. The process allows users to add custom business logic to their data without needing to create custom plugins for Telegraf. Kapacitor can be used to filter data based on time periods such as business hours or shift periods, enabling more complex queries on the data.