Yesterday, @splunk announced a legal action against @cribl_io, where I am CEO and Co-Founder. As a former Splunk customer and employee, this news makes me sad. Splunk now enters the realm of incumbents who litigate rather than innovate. These claims are baseless, and unsurprisingly I have a few things to say. The core of Splunk’s intellectual property claims stem from accusing me personally of stealing IP from Splunk in order to create Cribl. These claims are baseless as I will establish in this thread.

Artificial Intelligence and Machine Learning will not solve your monitoring and observability challenges. Sorry, to be the bearer of bad news, but we're going to need humans to build and administer monitoring and observability tools for the remainder of my lifetime. I've been referencing this quote quite a bit recently. I think it's very applicable. What buyers want is a system that with zero configuration tells them about problems in their environment. "Look, see that spike in that graph, why can't AI find that?"

https://twitter.com/alexstamos/status/1121429719507984386?s=12

When determining the health of your system storing and querying Terabytes or Petabytes of data is wasteful. A sample is totally sufficient. @dritan walks you through how to do this with @cribl_io while keeping the full fidelity in cheap storage. blog.cribl.io/2018/10/24/rou…
Thread 1/? The advent of cheap storage and distributed systems like @Splunk, @elastic or Hadoop have led to an approach whereby which we defer decision making on the value of data until later. This assumes the costs of the lazy approach to data management is affordable.