Arctic Wolf has integrated the Databricks Data Intelligence Platform into its own Aurora Platform. The new collaboration enables the processing of more than eight trillion security observations per week.
According to Omar Khawaja, Databricks Field CISO and VP Security, SecOps at scale requires a data architecture optimized for performance and real-time insights. “Arctic Wolf has been a pioneer in an integrated approach to security operations through a single platform,” said Khawaja. The collaboration enables Arctic Wolf to extend the Aurora Platform and add more functionality.
Eight trillion observations per week
Arctic Wolf’s Aurora Platform processes more than eight trillion security observations every week. That’s more than 300 petabytes of data every year. The integration with Databricks consolidates telemetry from endpoints, cloud applications, identity systems, and firewalls into a single environment. This should enable all these data points to lead to meaningful insights more quickly.
Arctic Wolf serves more than 10,000 customers worldwide and undoubtedly has a large overlap with Databricks’ customer base. The so-called Alpha AI features are designed to implement best practices that should deliver more than 10 million cumulative hours of SOC work. This AI helps in particular to reduce alert volume and speed up investigations.
Alert fatigue quickly cripples SOC teams worldwide. After all, with too much data and potential threats, it is impossible to see the forest for the trees. Solutions to this problem are everywhere, with security players each trying to position their platform as the central console for the necessary simplicity.
Lakehouse architecture as a foundation
The Databricks integration with Arctic Wolf uses lakehouse architecture for data unification, governance, and compliance. This technical approach combines the advantages of data lakes and data warehouses, which we have discussed in detail before:
Read also: Databricks moves from lakehouse to data intelligence
“Modern cybersecurity is a data scale problem,” said Dan Schiappa, President of Technology and Services at Arctic Wolf. “The volume, variety, and velocity of telemetry require a platform that can translate complexity and noise into clear results.”