Databricks Adds New Security, ML Automation Tools to Analytics Platform
Databricks has announced a series of security and scalability updates to its Unified Analytics Platform, according to a press release on the company’s website. These upgrades come on the heels of Databricks’ February unveiling of Databricks Ingest and a new Data Ingestion Network of partners. Cloud-native security in this release comes via the addition of customer-owned revocable data encryption keys and customized private networks to run clusters.
Databricks offers a unified analytics platform that allows users to prepare and clean data at scale and continuously train and deploy machine learning models for AI applications. The product handles all analytic deployments, ranging from ETL to models training and deployment. It is also available as a fully managed service on Microsoft Azure and Amazon Web Services.
New administration features are aimed at supporting teams with thousands of users that create thousands of compute instances. For full transparency, organizations can now audit and analyze all the activity in their account, as well as set policies to administer users, control budget and manage infrastructure.
Databricks features an API-driven approach that enables customers to product ionize analytics and machine learning quickly with continuous integration and continuous delivery. The platform’s new addition of git support means that APIs for everything from user management, workspace provisioning, cluster policies and application and infrastructure monitoring can be automated by DevOps teams throughout the data and machine learning lifecycle.
In a media statement about the news, Databricks Vice President of Product Management David Meyer said: “Databricks is the only platform that has successfully achieved the massive scale and simplicity that enables enterprises to make data, business analytics and machine learning pervasive enterprise-wide. We’re committed to preserving this for our customers, regardless of if and how their cloud strategies evolve over time. These new features are a great example of how we’re doing that.”
Learn more about what’s new with the Databricks platform.