November 7, 2022
Following the Data Documentation post, I decided to keep them coming with recent findings from a conversation with the one and only Andrew Duca, Cribl’s Director of Professional Services. During our chat, we focused on two things (1) his beard (if you know, you know… that’s what the kids say, right?) (2) customer readiness. As a seasoned professional services consultant, Duca knows a thing or two when it comes to making sure customers are ready to get started on the right foot when it comes to software deployments.
As you probably already know, at Cribl, we want to make it as easy as possible for anyone to learn about and use our products. Whether you’re a potential future customer, a new user at an existing customer, or a partner, we believe knowledge about our products should be readily available, so I decided to “steal” the Customer Readiness guide our Professional Services team members use during engagements and share it to enhance your Cribl experience through curated Docs links and use case templates. Some of this might be too much for your project and some of it might be too elementary for the undertaking you just started, regardless, I do believe some pieces might help in the long run. Let’s take a look!
Just like the data documentation project, you may or may not have started yet, we suggest publishing this type of documentation in your company’s team collaboration tool of choice (Confluence, SharePoint, Google Drive, Asana, or Slack [don’t forget to pin it!])
<Brief overview of project & problems we’re looking to solve>
<What are you trying to accomplish and how do you believe you’ll tackle this project?>
Stream Leader Hardware
Stream Worker Hardware
Cribl Sizing is based on a combination of Inbound (Ingest) and Outbound (Egress) leaving the system. Note, licensing is only based on ingest and not on the combination of ingest+egress.
The general rule is 200
The following site can be used to take an initial pass at the required number of worker nodes, but will need to be adjusted based on a number of factors (Datacenter allocation, Failover requirements, and data segmentation)