Databricks improves visibility of cloud assets

Traditional asset management and configuration monitoring tools fall short on visibility, openness and flexibility. To achieve the highest level of security, Databricks required a cloud-first tool that enabled the business. Download the case study to get the full story.

How Databricks automated asset discovery and ownership accountability

The first requirement for any tool Adam Youngberg, Kishore Fernando and the security engineering team at Databricks adds is it must enable the company to continue to achieve the highest level of security.

Security has always been at the core of Databricks’ mission. So when Adam and Kishore were brought on board at Databricks by Caleb Sima, VP, Security, they were tasked with finding or building a solution that enabled greater visibility and discoverability across their cloud assets, as well as the owners of those assets. “Centralization and visibility can enable greater security and speedier remediation,” noted Adam.

Most asset management and configuration monitoring tools fell short on visibility, openness and flexibility. Not only that, most seemed to lean towards legacy, on-prem businesses with cloud as an afterthought. They wanted something cloud first.

Download this case study to find out how Databricks used JupiterOne to:

  • ensure S3 bucket security,
  • simplify vulnerability management,
  • broaden visibility for incident response, and
  • build the foundation of their security program

What we see in JupiterOne is something better than what we would have built ourselves, without actually having to build it. Being cloud-native, it really resonated that JupiterOne is cloud-first.

 

Adam Youngberg — Security Engineer, Databricks