April 2018 Summaries

In a Q&A interview with dotConferences, Paul Dix, founder and CTO of InfluxData, discusses his company's journey and future plans for InfluxDB, a time series database technology that has gained significant traction in the industry. Dix shares insights on lessons learned since 2015, the expansion of InfluxData's scope beyond its initial focus on databases, and the company's recent $35 million Series C funding round. He also touches upon his early bets on Go programming language and InfluxDB 2.0, highlighting the importance of innovation and adaptation in the tech industry.

At DevOpsDays Vancouver and Seattle, InfluxData attended the events to learn about the latest in DevOps and catch up with their community. The conferences were well-organized and provided opportunities for attendees to share their experiences with InfluxDB, a time series database that is increasingly being used as part of monitoring solutions for microservices. Many attendees were familiar with InfluxDB but had not used it recently, and the company's storage engineers have made significant improvements to the platform, making it performant and worth revisiting. The events also highlighted the commercial importance of DevOps and the need for tools like InfluxDB to ensure business continuity. InfluxData's booth received positive feedback from attendees who were impressed by the number of Telegraf plugins available and the company's ability to provide a hub for data from microservices.

To improve ease of installation and use, the developers of InfluxData's TICK Stack have optimized the package manager scripts to significantly reduce the time required to set up the entire stack on Linux systems. The new installation process takes only 3:30 minutes, compared to a previous record of over 5 minutes, making it faster and more efficient for users. This streamlined setup process is ideal for developers and organizations seeking a powerful and high-performance Time Series Database with ease of use.

Telegraf 1.6.1 has been released, marking a new maintenance update for the popular monitoring tool. The update brings bug fixes and stability improvements to enhance user experience. This release is considered a maintenance release, indicating that it addresses issues without introducing significant new features or breaking changes.

InfluxData has been recognized as one of the 50 most valuable brands in the industry, according to The Silicon Review Magazine. The company's work on time series data is gaining significance due to its potential to generate insights from instrumentation of both physical and virtual worlds. InfluxData was founded by Paul Dix, who created InfluxDB, a popular open-source time series database. The company has successfully pivoted from a SaaS model to a platform-based approach and secured initial investors through community traction. Its focus is on reducing Time to Awesome, which it believes can be achieved through the use of time series databases in IoT and application/information systems. InfluxData's CEO Evan Kaplan shares his vision for the company's future, highlighting its commitment to innovation and customer satisfaction.

Container Journal | Challenges of Monitoring Containers in Multicloud Environments` In multicloud environments, monitoring containers is a significant challenge due to the need for strategic and consistent monitoring of hybrid environments. Orchestration of monitoring across multiple hubs is also crucial, requiring consolidated monitoring servers. A time series data platform is considered the best architecture for metrics and events storage, as it addresses the data problem by providing a scalable and efficient solution. The unique properties of time series data make it an ideal choice for container monitoring in multicloud environments.

InfluxData has been recognized as one of the 50 Valuable Brands of the Year by The Silicon Review Magazine, acknowledging its customer retention health, financial status, and ability to deliver business value through its time series database platform. This distinction is a testament to InfluxData's success in empowering developers to build next-generation monitoring, analytics, and IoT applications that derive competitive advantage from real-time data analysis. With over 400 customers across industries, including manufacturing, financial services, energy, and telecommunications, InfluxData has established itself as the leader among Time Series Database management systems, enabling businesses to gain better insights, take data-driven actions, and drive digital transformation initiatives.

The Internet of Things (IoT) market is growing exponentially, with an estimated size of $1.7 trillion by 2019, driven primarily by the increasing demand for data management solutions. The IoT generates vast amounts of time-series data that requires specialized data management tools to handle its high volume and real-time processing needs. Traditional relational databases are not designed to handle the unique characteristics of IoT sensor data, which is typically generated in real-time and does not follow traditional CRUD data model patterns. As a result, the market for IoT data management solutions is expected to reach $69.7 billion by 2023, with companies like InfluxData, IBM, and PTC leading the charge. The key to unlocking the value of connected devices lies in developing a robust data layer that can efficiently collect, process, analyze, and act upon IoT sensor data, making it easier for businesses to predict, optimize, and improve their operations.

Batch processing involves processing large amounts of data in batches, whereas stream processing processes data as it becomes available, often in real-time. Kapacitor tasks can be configured to operate in either batch or stream mode, depending on the nature of the task and the type of data being processed. Stream processing is particularly useful for handling high-volume, high-velocity, and high-variance data streams, such as those found in IoT applications. Batch processing, on the other hand, is better suited for tasks that require more control over data processing, such as data aggregation or filtering. The choice between batch and stream processing ultimately depends on the specific requirements of the task and the characteristics of the data being processed. Kapacitor's flexibility allows developers to choose the approach that best fits their needs.

To visualize time series data using the Highcharts library, a container `div` with an ID of 'container' is needed to render the chart within it. The script tag from Highcharts.js is added to the head section of the HTML file, and another script tag to fetch data from the InfluxDB database is added to the body section. A simple fetch function retrieves the data based on the location name passed in and then uses Promise.all() to fetch all the data for four different locations. The fetched data is then mutated to fit into the required format referenced in the Highcharts documentation, and a Highcharts chart is constructed using the `chart()` method with various options such as colors, chart type, title, xAxis, yAxis, plotOptions, and series. The resulting graph displays time series data for four different locations, showcasing the capabilities of the Highcharts library for visualizing InfluxDB data.

The Eclipse IoT Developer Survey results highlight Google's declining market share in IoT development, with Azure and AWS dominating the field. Data collection and analytics have become a top concern for IoT developers, surpassing security concerns. InfluxDB is seen as a strong contender in this area, offering flexibility and ease of use. The survey also shows that traditional SQL databases like MySQL are still dominant, while Time Series Databases are gaining popularity. MongoDB's performance is questioned due to its slow ingestion rate, query duration, and disk usage compared to InfluxDB. The results suggest that using the right tool for the job is crucial in IoT development, and InfluxDB is well-suited for time series data.

The Node-Influx Client Library is a JavaScript library for interacting with InfluxDB, a time-series database. To get started with this library, install it using npm and require it in your server file. Connect to an InfluxDB instance by specifying the host, database, schema, and other options as needed. Create a database if one does not exist, then write data points into the database using `influx.writePoints()`. Finally, query the database for specific data using `influx.query()` with an InfluxQL statement. The library provides a simple API for most InfluxDB operations and is fully supported in Node.js and the browser without additional dependencies.

A Time Series data project is presented where participants' heartbeats are measured using a pulse sensor connected to an Arduino board, which sends the data to InfluxDB running on a virtual machine in the cloud. The data is then visualized using Chronograf. This project highlights commonalities between various data sets, including statistical methods and computer science algorithms. It also showcases the use of open-source hardware and software tools, such as InfluxDB and Telegraf, for time series data management and visualization.

In the IoT world, general-purpose databases are insufficient to handle the constant stream of time series data that needs to be collected, measured, and acted upon in real-time or near-real-time. The need for a purpose-built Time Series Platform has become increasingly necessary as more devices are being instrumented to collect data. This is leading companies to adopt a data-driven business model, where data analysis and decision-making are critical components. InfluxData Platform is introduced as a solution that can effectively manage time series data, enabling businesses to make timely decisions based on real-time or near-real-time insights.

Telegraf 1.6.0 has been released with several key feature highlights including a rewritten InfluxDB Output for stability and performance, complete rewrite of SQL Server Input queries and added support for AzureDB, as well as many Windows enhancements. Additionally, new plugins have been added such as HTTP Input, NATS Monitoring, Processor Plugin, and others. New maintenance releases are also available for InfluxDB and InfluxDB Enterprise, including a generally available feature called TSI that requires upgrading from previous versions.

Chronograf 1.4.4.1 has been released, addressing a critical security fix for users employing Github or Generic OAuth implementations, and providing performance enhancements across various features such as dashboards, templates, graphs, and TICKscript editing. The update also includes new UI capabilities, such as cloning dashboards and cells, and expanded graph color customization options. Users are advised to upgrade to the latest version as soon as possible due to the security vulnerability.

InfluxData's Product Manager Russ Savage discusses the benefits of using TICKscripts to optimize Kapacitor, highlighting various development tools and a standardized process for deploying TICKscripts in production.

InfluxData continues to maintain its leadership position in the rapidly growing time series database category, with a 49% increase in popularity over the past 12 months and a significant lead over its closest competitor. According to DB-Engines' latest results, InfluxDB is outpacing the competition with its user base more than three times larger than the nearest competitor. The growth of the time series database category is being fueled by increased adoption of Kubernetes, containerization, IoT sensor data, and the need for a consolidated metrics and events platform. InfluxData's unique features enable customers to quickly build monitoring, alerting, and notification applications, as well as real-time analytics applications that support streaming data and anomaly detection. With over 400 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, empowering developers to build next-generation monitoring, analytics, and IoT applications faster, easier, and to scale.

Kapacitor is a Continuous Query engine designed for use with time-series databases, allowing developers to run long-running queries in real-time without impacting system performance. The tool was developed to address the limitations of traditional query engines and provides an efficient way to manage continuous data processing tasks. To determine which tool best serves a given use case, developers should consider questions such as whether they need real-time data processing capabilities, how complex their queries are, and what level of performance is required. By understanding these factors, developers can choose between Kapacitor and other tools, like InfluxDB, to meet their specific needs.

The State of TICKscript Development discusses various tools available for writing TICKscripts, including editors and IDEs with plugins, to help developers aggregate, analyze, and alert on data in InfluxDB. The recommended development workflow emphasizes standardizing a process for moving scripts from local developer machines into production systems, using source control, deployment environments, and testing frameworks. A consistent repository structure is also crucial, with files encoded with searchable information and unit tests written to verify script functionality.

Tim Hall, the VP of Products at InfluxData, will be speaking at InfluxDays in London about Chronograf, sharing its features and best practices for setting thresholds and building dashboards. He introduced Chronograf 1.0 as part of InfluxData's TICK Stack in May 2017, which provides a simple and user-friendly interface with templates and libraries to rapidly build real-time visualizations of data. The upcoming talk will cover where he plans to take the product in the next 12-18 months, offering insights into future developments and enhancements. Early registration tickets are available until May 25, 2018, for those interested in attending the event.

The InfluxDB Ruby client is a powerful tool for interacting with InfluxDB, an open-source time series database. It provides a simple and intuitive API for reading data from local or remote instances of InfluxDB, including support for authentication via username and password. The client also allows writing data to InfluxDB, with options such as specifying the time precision for timestamp values. With great documentation and a community-driven maintenance team, the Ruby client is an excellent choice for developers looking to integrate InfluxDB into their applications.

Monitoring Kubernetes Architecture` by Gianluca Arbezzano introduces two key considerations for monitoring a Kubernetes architecture: understanding the underlying bare metal infrastructure and every service, ingress, and pod deployed. The author shares practices used by InfluxData's team to gain visibility into clusters, including deploying Telegraf on every node to collect metrics from hosts and services. By setting up effective monitoring with Telegraf, users can get insights into their Kubernetes architecture and improve cluster performance.

In the age of instrumentation, marketing has evolved significantly from its traditional art form days, with CMOs now taking on multiple roles including data integration, analytics, and strategy. The shift is driven by the increasing availability of data and analytics tools, allowing for more accurate measurement of marketing impact. Today's CMOs must navigate not only creative campaigns but also technical aspects of data management and analysis to drive effective marketing strategies. This evolution has led to a broader understanding of marketing's role in driving business growth and competitiveness.