Predictions about the tech industry generally aren’t worth the bytes they cost to send over the Internet, but I figured it would be fun to make some of my own anyway. So here are seven predictions about some things we will and won’t see in 2017 with a few thoughts about why I think each could be accurate.
Continue reading 7 predictions about the technology industry and developer tools in 2017
Two weeks ago after almost three years of designing, coding and testing,we released the 1.0 version of the entire TICK stack (Telegraf, InfluxDB, Chronograf and Kapacitor). In addition on the same day we announced the general availability of the 1.0 version of our InfluxEnterprise product which included support for high availability configurations and scale out clusters for those users with high throughput requirements.The response to those releases has been tremendous and today we are excited to announce the completion of a $16M Series B financing round led by Battery Ventures.
Continue reading InfluxData raises 16M in new funding led by Battery Ventures
Today we’re very excited to announce the public beta of Influx Enterprise. This release includes high availability and scale out clustering for InfluxDB along with management features for the cluster, performance monitoring, and an all new Chronograf Data Explorer interface for quickly digging into your time series data. During the beta we’re giving unrestricted cluster sizes and features for testing and preview.
Influx Enterprise Features
The Enterprise release of InfluxDB has features for high availability and scale out clusters with the ability to move data around and restore from outages. An InfluxDB cluster is set up in two tiers: Meta servers and Data servers. The Meta Servers contain all information about the cluster, databases, users, and shards in the cluster. The Data Servers hold all the raw time series data along with metadata for what measurements, fields, and tag key/value pairs exist. The Data Servers are also responsible for handling all queries and writes.
Influx Enterprise clustering has rebalancing functions for moving shards of data from one server to another, giving users the ability to recover downed nodes, expand the cluster, increase the replication factor, or offload historical data to servers with lower priced spinning disk storage. The cluster is also able to add and remove either Data or Meta nodes with a command from the command line.
The Enterprise product has expanded role based access control, giving administrators finer grained control over what users can do on databases and within a cluster.
The Enterprise Web application is a web UI for looking at the performance of the cluster including how many writes and queries are being processed along with average query latency. Enterprise Web also has a screen for looking at long running queries and the ability to kill queries with a single click. User and role management can also be handled from the Web UI.
Finally, the Enterprise Web UI features a brand new version of Chronograf that is focused on data exploration. It gives regular users the ability to drill down in their measurement, tag and field data while drawing multiple graphs on a page and customizing what aggregate functions and which tag key/value pairs show up in the graph. We think it’s an easy way for non-experts to start looking at their time series data on the fly. Administrators can also give users access to this feature without giving them access to the rest of the administrative UI.
For an extend demo of InfluxEnterprise, check out the webinar playback from earlier this week here. Continue reading Announcing InfluxEnterprise Beta: Clustering, Monitoring & Data Exploration for InfluxDB
InfluxData is excited to announce that it now supports the ability stream log event data to InfluxDB with out-of-the-box patterns for popular servers like Nginx and Apache. Log monitoring support is the latest addition to Telegraf’s already impressive list of 90+ input and output data plug-ins. In addition to standard format logs, custom log parsing and patterns based on the popular “grok” patterns are also supported.
What is Telegraf? Telegraf is a metric collection daemon that can collect metrics from a wide array of inputs and write them into a wide array of outputs. It is plugin-driven for both collection and output of data so it is easily extendable. It is also written in Go, which means that it is a compiled and standalone binary that can be executed on any system with no need for external dependencies, no npm, pip, gem, or other package management tools required.
With Telegraf you can not only parse logs to create metrics and store them as time-series data, InfluxDB also has the ability to store raw log lines along-side the metrics. We should caution that this new capability is not intended to be a replacement for full text search tools, rather for aiding in root cause analysis during specific windows of triage. So, if you are investigating performance metrics within a band of time, you can search via regex for any log errors that occurred in that same band. All the data is conveniently in one place, making it fast to lookup and correlate data. Continue reading Parsing Logs into InfluxDB using Telegraf’s logparser Plugin
As InfluxDB has grown in popularity over the past two and a half years, we’ve seen it used in many different use cases across custom DevOps monitoring, real-time analytics, and the Internet of Things (IoT). Each of these domains has its own patterns, standards, and protocols, so we’ve been working hard to make Telegraf, our open-source data collection agent, support as many services and systems as possible. This helps our users get data into and out of InfluxDB easily and enables developers to keep building awesome new applications.
MQTT is an example of one of the aforementioned protocols, which is heavily used in industrial monitoring and has become increasingly popular in IoT applications. We recently added support to Telegraf for consuming data from MQTT brokers, but given the amount of segmentation in the MQTT broker space and the specific requirements of high-performance brokers (e.g. very high numbers of concurrent connections), we started to pursue the possibility of building our own MQTT broker to ensure the tightest possible integration with the rest of our products and allow us to more effectively work with customers and partners to build IoT solutions backed by InfluxDB.
We’re huge supporters of the Go programming language, as we’ve discussed in the past, so it was important to us that the project be written in Go for optimal productivity, performance, and community engagement. When we began our investigation, we discovered the SurgeMQ project, written in Go by the brilliant and incredibly talented Jian Zhen. After a few weeks of initial discussions, we received Jian’s blessing to officially take over the project. Says Jian, “I’ve been watching the InfluxDB project from its early days, and I’m a huge fan. I’m happy to see SurgeMQ helping people use InfluxDB in new ways.”
Effective immediately, we’ll be working to finish turning SurgeMQ into a standalone server and begin building packages for it alongside the rest of our products. Continue reading Improved MQTT Support in InfluxDB with SurgeMQ
The team at InfluxData is excited to announce the immediate availability of InfluxDB 1.0 Beta plus the rest of the components in the TICK stack: Telegraf, Chronograf, and Kapacitor. While there are many new features like exponential smoothing via Holt Winters queries, templates for Kapacitor TICKscripts, Telegraf Cloudwatch integration, and dozens of bug fixes, this release marks a significant point in the development of these projects.
We’ve had customers and community members running the TICK-stack in production at significant scale for months and we are therefore comfortable that the quality of the codebase is worthy of the 1.0 moniker. Second, we’re ready to lock down the API and make a commitment to zero breaking changes for a significant length of time. This is especially important for organizations building products and services on top of the InfluxData stack whose products may have longer development cycles or require a higher degree of stability from the code base to ensure continuity for their customers and users.
Getting to 1.0 GA
This release is the first Beta of the upcoming 1.0 GA release. We still have some known bugs to fix, but from here until 1.0 we’ll be focused on testing, benchmarking and bug fixes. What about new features? They’ll come in the point releases after 1.0. For community members, this Beta is what you should be testing against. For some users, the Beta may even be suitable for production use. Many fixes have gone into all the projects since the 0.13 release nearly 4 weeks ago. Continue reading Announcing InfluxDB 1.0 Beta – A Big Step Forward for Time-Series
The team at InfluxData is excited to announce the immediate availability of v0.13 of the TICK stack!
What’s the TICK stack? It’s InfluxData’s end-to-end platform for collecting, storing, visualizing and alerting on time-series data at scale. Learn more.
We are also pleased to announce early access to InfluxEnterprise. If you have been waiting for InfluxDB clustering to run on your infrastructure with the ability to rebalance nodes, plus a slick UI to deploy, manage and monitor the deployment, InfluxEnterprise is for you.
Like what you see? Contact us to request a demo, get early access plus pricing from one of our solutions architects.
v0.13 is a significant InfluxDB release delivering robust features and stability to the single server experience. This is also our final major milestone before we launch 1.0. New in this release:
- Upgrade to Go v1.6.2 delivering performance gains
- Support for DELETE FROM
- Time Zone Support – offset argument in the GROUP BY time(…) call
There’s a total of 27 new features and 32 bug fixes! Detailed release notes can be found here and downloads here.
New in this release:
- New Input Plugin: “filestat” to gather metrics about file existence, size, etc.
- HAProxy socket support
- Support for Docker container IDs to track per container metrics
There’s a total of 17 new features and 21 bug fixes! Detailed release notes can be found here and downloads here.
New in this release:
- Design update and performance improvements to the visualization index pages
- “Visualization cards” have been replaced with more performant list items
Downloads are here.
InfluxDB’s native data processing and alerting engine now supports BYOA (bring your own algorithm) analytics. UDFs written in languages of your choice running in Docker containers can be launched independent of Kapacitor by exposing a Unix socket. On startup Kapacitor will connect to the socket and begin communication, applying the UDF logic to the time series data being processed.
New in this release:
- UDFs can be connected over a Unix socket. This enables UDFs from across Docker containers to be applied to the Influx data pipeline.
- CLI features to ID, list and delete tasks, recordings and replays
- API lock down to a stable 1.0 version
There’s a total of 18 new features and 8 bug fixes! Detailed release notes can be found here and and downloads here.
But wait, there’s more…
FREE Technical Papers
Today we also launched a new “Technical Papers” landing page on influxdata.com where developers and architects can download long reads that dive deep into a variety of InfluxDB related topics. Right now we’ve got three papers posted:
Make sure to check back often as we’ll be uploading new papers every other week!
FREE Virtual Training Summer Schedule is Live!
We’ve just added eight sessions to the virtual training schedule. In addition, we’ll be debuting three new topics including:
- Benchmarking InfluxDB and Elasticsearch for Time-Series Data Management
- Migrating from InfluxDB 0.8 and Up to 0.13
- Intro to Kapacitor for Alerting and Anomaly Detection
Update: Since I wrote this post we’ve delivered on the things I’ve promised.
- We have continued to improve our open source platform with 88 new features and 133 bug fixes to InfluxDB. This includes performance enhancements and all new query functionality like Holt-Winters, moving averages, and killing long running queries.
- We created influx-relay as a pure open source option for high-availability setups.
- We released managed clusters of InfluxDB on InfluxCloud on April 19th.
- On September 8th we made an affordable on-premise InfluxEnterprise offering at the promised price of $399/month.
“How does InfluxData make money?” That’s a question I’ve been asked many times over the course of developing the InfluxDB project and building the company, InfluxData, around it. Currently, we have our cloud offering, a managed hosted platform for InfluxDB, and we offer support with an SLA plus professional services.
Over the last few months we’ve had conversations with other open source vendors and looked at the different models of open source monetization. From our discussions, we’ve heard that support alone isn’t a viable model to ensure that we can continue keeping everything open source. It appears that despite continued significant contributions to the open source projects customers eventually drop support as their infrastructures mature and they look to reduce operating costs.
Continue reading Update on InfluxDB Clustering, High-Availability and Monetization
We are excited to announce several new releases today to the TICK stack!
What’s the TICK stack?
The TICK stack is the first purpose-built, end-to-end solution for collecting, storing, visualizing and alerting on time-series data at scale. All the components of the stack are designed to work together seamlessly. The TICK stack is InfluxData’s vision for a complete data platform to manage time-series data.
InfluxDB v0.10 Release Candidate
We’ve all been eagerly awaiting the release of v0.10 and thanks to the testing, benchmarking and contributions of the community we are pleased to announce the immediate availability of the v0.10 Release Candidate now available on our downloads page.
Continue reading TICK Stack Update: InfluxDB Release Candidate, Kapacitor & Chronograf v0.10
Today we’re announcing that InfluxDB, the company, is now InfluxData. This is the beginning of delivering on our long term vision: to create the platform for developing apps, services and IoT architectures that rely on time series data. To us, time series data is important not just because it tracks things changing in time, but because tracking that change is exactly what informs historical trends, intelligence, insight, and prediction. We believe that developers need a platform that enables them to quickly build new and innovative applications on top of all these data. In this blog we’ll outline why we think time series data is important; the TICK stack (the stack we are building our platform on); and our continued development on the InfluxDB database.
Continue reading InfluxDB is now InfluxData, the Platform for Time-Series data