To celebrate the release of the Gravwell Community Edition we are also releasing a standalone collectd ingester. Collectd is an excellent tool for monitoring the health of hardware, systems, and applications. For this post we will be demonstrating the installation and configuration of collectd to monitor the health and status of a few machines. We will be providing dashboard import codes so that you can quickly and easily import our ready made dashboards. The collectd ingester is part of the core suite of ingesters and is open source on github.
This post is mostly about building your own docker images. If you're interested in getting up and running fast using Gravwell+Docker, head over to our docs that cover our pre-built images:
For this blog post we are going to go over the deployment of a distributed Docker-based Gravwell cluster. We will use Docker and a few manageability features to very quickly build and deploy a cluster of Gravwell indexers. By the end of the post we will have deployed a 6 node Gravwell cluster, a load balancing federator, and a couple ingesters. Also, the six node “cluster” is also going to absolutely SCREAM, collecting over 4 million entries per second on a single Ryzen 1700 CPU. You read that right, we are going to crush the ingest rate of every other unstructured data analytics solution available on a single $250 CPU. Lets get started.
It’s Thanksgiving Weekend in America and that means most people have acknowledged the blessings in their lives and are gearing up for something America does better than anyone: consumerism. I had a bit of down time and thought I’d do something else America is good at: Freedom Fighting.
For this post, the Gravwell analytics team ingested all 22 million+ comments submitted to the FCC over the net neutrality issue. Using Gravwell we were able to rapidly conduct a variety of analysis against the data to pull out some pretty interesting findings. We scraped the entirety of the FCC comments over the course of a night and ingested them into Gravwell afterward. It took about an hour of poking around to get a handle on what the data was and the following research was conducted over about a 12 hour period. So we went from zero knowledge to interesting insights in half a day. We’re kinda nerding out about it.