November 2015 Summaries

InfluxDB has released version 0.9.5, which is now available for download. The company also announced Telegraf 0.2.1 with UDP support and other improvements. Additionally, InfluxDB is being used in various production environments, such as Gigaspaces' Cloudify, where it serves as the default metric storage engine, and E4e5, an IT consulting company that uses it to store system, performance, and business metrics for analytics and fast predictions. Spreedly, a service that minimizes PCI compliance and payment integrations complexity, also utilizes InfluxDB for tracking service usage and providing customers with views into their account billing and quota levels. Various events are also being organized, including meetups in San Francisco, where attendees can learn more about InfluxDB and connect with other users.

Chronograf 0.3 has been released with major new features including dashboards, UI/UX improvements, and data exploration enhancements. The tool is designed to be accessible for both developers and non-developers, allowing users to easily navigate and visualize their InfluxDB data. A key aspect of the release is the introduction of dashboards as a collection of graphs, which can be customized and used in various ways. Additionally, improvements have been made to the query builder, making it easier to explore and analyze large datasets. The tool continues to evolve with new features planned for future releases, including templating, cloud integration, and different types of visualizations.

In the article, deploying and configuring an instance of the time series database InfluxDB using Ansible is covered as a simple example project. The use of Ansible's simplicity and ease-of-use features makes it unique among configuration management tools. InfluxDB itself offers a balance between ease-of-use and power with language support for multiple programming languages, making it suitable for various use cases. To deploy InfluxDB using Ansible, the process involves setting up the repository, installing InfluxDB, configuring its hostname, starting the service, and optionally loading sample data. The full deployment is made possible by creating a task file that enumerates all the steps required to configure the server, and then running it with Ansible's playbook feature.

Telegraf 0.2.1 has been released with several new features and improvements, including support for writing UDP data to InfluxDB, multiple outputs of the same type, and a revised test suite. The release also includes bug fixes and updates to existing plugins, such as NSQ output, Prometheus output, and Jolokia plugin. Additionally, Telegraf now compiles on FreeBSD and allows users to specify outputs as lists, making it easier to manage complex data pipelines.

InfluxDB has seen a significant increase in community pull requests following a recent blog post on contributing to InfluxDB, prompting the creation of an active Slack channel for community support. The Gopher Slack community is vibrant and ideal for developers who want to learn Go as well as contribute to projects like InfluxDB. To join the #influxdb channel, users can request a free invite by filling out a form, which will be followed by an email with an invitation link to complete registration.

InfluxDB has been gaining traction, with several notable projects and companies utilizing its capabilities, including the National Institute of Standards & Technology's ARTIQ project, which uses InfluxDB as a backend to log and analyze quantum physics experiments. The project found InfluxDB compelling due to its speed, ease of use, and ease of integration. Additionally, InfluxDB has been featured in various events, meetups, and conferences, including QConSF, San Francisco InfluxDB Meetup, and Women Who Go Meetup. The community is actively engaged, with recommendations for the tool being shared on social media platforms like Twitter. Furthermore, InfluxDB's developer-friendly features, such as its ease of deployment and integration with other tools like Grafana, have made it an attractive choice for companies looking to build scalable data pipelines.

InfluxDB 0.9.5-rc2 is now available, bringing 32 new features and 75 bug fixes, including improvements related to clustering, hinted hand-off, and stability enhancements. The release has been delayed from previous versions due to ongoing work on the Time Structured Merge Tree (TSM) storage engine, which is not yet complete but will be included in future releases. Users are advised to upgrade to take advantage of these improvements, with some features still awaiting testing on the TSM engine. Future work includes reworking the query engine to support advanced functionality and clustering improvements, with a predictable release cadence planned for the next six months.

As a developer who spent 15 years writing software on closed-source platforms, I joined the InfluxDB team in December 2014 and was immediately thrown into contributing to their codebase. I learned that code quality is crucial, including clear variable names, useful comments, and well-organized code. I also experienced my first code review, which taught me to be open to feedback and grateful for constructive criticism. What surprised me was how comfortable I became with the idea that everyone could see my code, but this discomfort turned out to be a great learning experience when even a "rockstar" like Dave Cheney reviewed one of my pull requests. To work full-time on an open-source project, you don't need to be an expert; what's important is being willing to learn and grow from the community. I encourage everyone to contribute, whether it's with code or issues, as every contribution makes each open-source project better for everyone.

InfluxDB's Continuous Queries allow pre-computing and storing query results, enabling efficient execution without overloading the database. The Continuous Querier service executes queries behind the scenes, mimicking user interaction and running continuously. A continuous query is created using the `CREATE CONTINUOUS QUERY` statement, parsed, validated, and stored in the cluster-wide database metastore. The querier service schedules executions based on the group by interval, estimated using a formula that considers compute-runs-per-interval and max frequency settings. Continuous queries automatically recompute previous intervals to handle lagged data, writing results to disk with an optional retention policy. InfluxDB's continuous query execution provides automatic downsampling, making it suitable for applications requiring real-time data processing.

This week's InfluxDB Week in Review highlights various content related to the platform, including blogs, videos, articles, and tutorials on its usage and features. Notable users of InfluxDB include LeTV, a Chinese entertainment company, which uses it for real-time monitoring of millions of metrics; GfK, a market research company that will use InfluxDB as part of a new research platform to process metrics in real-time; and ProcessOut, a payment aggregation gateway, which chose InfluxDB for its user statistics repository due to its ease of use and lightweight design. The review also includes events and tech tips related to InfluxDB, such as the possibility of creating a single node that can be integrated with another node later on, forming a cluster.

InfluxDB is an open-source project that relies heavily on its community for development, including bug reports and performance numbers. The community can also contribute by improving the source code, which can be a source of pride knowing it will run on thousands of developers and companies worldwide. InfluxDB has selected a set of issues marked with the "help-wanted" label that are considered approachable, along with introductory notes to help new contributors get started. Before contributing, new contributors should check out the CONTRIBUTING guide and sign the CLA. As an incentive, anyone whose PR is merged will receive an InfluxDB t-shirt. The community can also contribute by learning how a time-series database works through getting into the code.

InfluxDB has been featured in several recent articles, including an announcement of Telegraf 0.2 with improved scalability and features such as StatsD, MQTT, and a new SQL-like query language. The company eBay uses InfluxDB for trend checks on their data from various systems, finding clustering to be one of its most compelling features. Muzzley, a home automation platform, also utilizes InfluxDB to monitor their systems and services in real-time, while Mothership1, a cloud deployment provider, uses it for monitoring their apps and services across multiple data centers. Various events have been announced, including meetups and conferences, and InfluxDB is seeking user-submitted success stories to feature on its website.