Algorithmia Goes the Extra Mile for MLOps Security and Compliance

Seattle-based machine learning model management company has upgraded its MLOps capabilities for greater security with AWS C2S and GovCloud, better performance with the latest AWS and Azure hardware and streamlined software development practices.

Algorithmia has introduced new feature upgrades to its machine learning (ML) operations and management platform for enterprises in financial services, insurance, healthcare and laboratory sciences and other industries. He platform now features the following:

• Support to AWS C2S, AWS GovCloud
• Support to AWS and Azure GPU Hardware
• Software Development Lifecycle Updates

This is being done to enable organizations with machine learning capabilities and address the software development and operational requirements. Algorithmia CEO Diego Oppenheimer said, “Algorithmia Enterprise allows customers to control the provenance of all components of ML operations, including certificate authorities, operating system, container images, code, dependencies and ML models used in their ML enabled applications.”

Learn More: Don’t Leave Cloud Data Security Behind: 5 Best Practices to FollowOpens a new window

Updates to the Algorithmia MLOps platform include

1. Support to AWS C2S, AWS GovCloud

Algorithmia is extending support to AWS C2S or Commercial Cloud Services and AWS GovCloud specifically to warrant enterprise adherence to securityOpens a new window systems and compliance policies. Under it, enterprises can leverage air-gapped method of deployments, use fully and uniquely hardened OS images, implement authenticated proxies, private certificate authorities, a private Docker hub as well as dependency mirrors.

The AWS GovCloud recently attained the highest level of Federal Risk and Authorization Management Program of FedRAMP accreditation, the Provisional Authority to Operate (P-ATO). This signifies AWS GovCloud meets scrupulous security standards set by the United States government.

Tech News: McAfee’s Endpoint Security Platform Gets An AI MakeoverOpens a new window

2. Support for AWS and Azure GPU Hardware

As the software constantly evolves, a need for supporting hardware becomes a necessity. AWS and Azure GPUs running large-scale workloads thus are upgraded as and when the demand arises. With the upgrade, Algorithmia Enterprise is well positioned to support the latest GPU hardware by both AWS and Azure. Oppenheimer adds, “Organizations today are utilizing advanced ML models that require more memory and GPU performance, while driving down costs, and new hardware is being created specifically to meet the needs of these models.”

3. Software Development Lifecycle Updates

Algorithmia’s integrated development environment now enables users/developers to debug code and algorithms on the local machine, bringing a shift in the software development process. This extension creates new integration with tools such as PyCharm, additional to existing integrations with Jupyter Notebooks, R Shiny, Android, IOS, Cloudinary, Datarobot, H2O.AI. Integration with PCharm opens the SDLC to error checking, code analysis, testing, project navigation etc.

Speaking exclusively with Toolbox, Algorithmia CEO Diego Oppenheimer shared,“Companies often use a patchwork of tools to deploy machine learning-based applications. Unfortunately, using the wrong tools can expose companies to cyberattacks and breaches of data security and compliance,” said Diego Oppenheimer, CEO at Algorithmia. “The security updates we’re announcing today to our industry leading MLOps platform have been designed to help companies protect themselves from just these kinds of problems.”

Let us know if you liked this news on LinkedInOpens a new window , TwitterOpens a new window , or FacebookOpens a new window . We would love to hear from you!