Blog

John Floren

John's been writing Go since before it was cool and developing distributed systems for almost as long.
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Recent Posts

Introducing the Key-Value Search Module

Oct 1, 2019 2:35:15 PM / by John Floren posted in Gravwell Story, Software Updates, Logging

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With Gravwell 3.2.4 we've introduced a new search module: kv, short for 'key-value'. This module is designed to help you extract key-value data from text entries without having to hand-craft regular expressions. It also interfaces with the fulltext indexer automatically, so you can analyze your indexed data more quickly.

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Announcing Gravwell Version 3.2

Jul 31, 2019 9:26:42 AM / by John Floren posted in Software Updates, DevOps Analytics

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We are happy to announce the immediate availability of Gravwell version 3.2.0!

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Fighting social media propaganda

Feb 19, 2019 9:55:00 AM / by John Floren posted in Software Updates, ingester, reddit

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We're continuing to work with investigative reporters to research unscrupulous activity on social media. Most recently, Engadget published a piece on nefarious political influencers on Reddit. We’ve written in the past about analyzing social media comments, but didn’t make the ingesters publicly available. With an increasing need for research in this area, we decided that releasing our Reddit and Hacker News ingesters could help new users get started with Gravwell even faster, so we open-sourced them. Read on to learn how to get the ingesters, how to run them, and how to get started with the data.

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Announcing the new Gravwell HTTP Ingester

Feb 7, 2019 11:22:19 AM / by John Floren posted in Gravwell Story, ingester, Community Edition

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Gravwell recently introduced a new ingester which accepts entries via HTTP POST requests. Now it's easy to send arbitrary data to Gravwell via scripts using only the curl command. In this blog post, we'll use the HTTP ingester to build a weather-monitoring dashboard!

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Gravwell 2.2.1 Released!

Aug 1, 2018 3:48:22 PM / by John Floren posted in Software Updates, ingester, docker, Community Edition

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We’re pleased to announce the release of Gravwell 2.2.1! For a point release, it’s got some very cool new features; read on to learn what we’ve added.

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Monitoring Netflow with Gravwell Community Edition

Jul 18, 2018 1:21:59 PM / by John Floren posted in Network Analytics, Community Edition, Home Operations Center

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Gravwell Community Edition is perfect for monitoring your home network. With a generous 2GB/day ingest quota, you can capture netflow records, DNS requests, WiFi hotspot associations, and more. In this blog post, we’ll show how to ingest and analyze netflow records. We’ll assume you’ve already set up a Gravwell instance as described in the quickstart (https://dev.gravwell.io/docs/#!quickstart/community-edition.md); for this post, we’ll assume the Gravwell instance is at 192.168.1.52. Your instance will almost certainly be different, so be sure to substitute your own information.

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Ingesting Google Cloud Platform PubSub

Apr 24, 2018 10:05:25 AM / by John Floren posted in ingester, Integrations

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Thanks to Gravwell's Google PubSub ingester, it's easy to collect logs and other data from services deployed in the Google Cloud Platform. In this blog post, we'll show how to set up Gravwell in GCP and ingest system logs from your virtual machines.

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Distributed Webserver Frontends in Gravwell

Apr 19, 2018 8:06:36 AM / by John Floren posted in Software Updates, docker, cluster

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With the release of Gravwell 2.0, Gravwell customers can now deploy multiple webservers tied to a central storage system. This means you can deploy multiple webservers behind a load balancer for better search performance; the webservers synchronize resources, user accounts, dashboards, and search history behind the scenes so users don’t need to worry about which server they’re actually using.

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Amazon Kinesis Streams and Gravwell

Dec 5, 2017 1:11:03 PM / by John Floren posted in developer, API, Amazon, AWS, ingester, Kinesis

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Amazon’s Kinesis Streams service provides a powerful way to aggregate data (logs, etc.) from a large number of sources and feed that data into multiple data consumers. For instance, a large enterprise might use one Kinesis stream to gather log data from their cloud infrastructure and another stream to aggregate sales data from the web services running on that infrastructure. Once the data is in the stream, it remains available for up to a day (or optionally longer) for any number of applications to read it back for processing and analysis. This is particularly useful to customers that want to deploy and destroy virtual machines on a whim; data is stored in the stream, rather than the ephemeral VMs.

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