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Iguazio Achieves AWS Outposts Ready Designation to Help Enterprises Accelerate AI Deployment in Hybrid Environments

Iguazio, the Data Science Platform built for production and real-time machine learning (ML) applications, announced that it has achieved the AWS Outposts Ready designation, part of the Amazon Web Services (AWS) Service Ready Program.

This is a notable development for AWS and Iguazio customers who can utilize Amazon SageMaker to develop artificial intelligence (AI) models and data pipelines, and easily deploy and manage these in production using the Iguazio Data Science Platform on AWS and now also on AWS Outposts, benefiting from the same high performance at scale in hybrid AWS environments.

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Two main challenges are hindering adoption of AI for Enterprises and Government agencies. The first is an increase in the need for hybrid solutions to manage data and data science applications, to address data locality in accordance with a rise in regulation and data privacy considerations. The second is an increase in first-hand experiences with the challenges and complexities involved in operationalizing machine learning, especially when considering hybrid deployment options, and when scaling data science across the organization.

AWS Outposts is a fully managed service that extends AWS infrastructure, AWS services, API and tools to virtually any datacenter, co-location space, or on premises facility for a truly consistent hybrid experience. Iguazio’s platform offers a fully automated MLOps solution for data engineers, data scientists, and DevOps teams, which includes a high-performance serverless framework and a fast online and offline feature store.

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The new seamless integration of Iguazio’s technology with AWS Outposts allows customers to build full blown, complex ML pipelines in weeks instead of months, with a lean team, and deploy them in hybrid environments while meeting all their performance, scale, and compliance needs. The Iguazio platform automates and accelerates the entire AI/ML pipeline, from data ingestion, feature engineering and training to real-time model serving, model monitoring and drift detection.

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“Customers are looking for more efficient ways to industrialize AI, and more flexibility in where they deploy their AI applications,” said Joshua Burgin, General Manager, AWS Outposts, Amazon Web Services, Inc. “With the Iguazio Data Science Platform for AWS Outposts, customers can now build end to end hybrid AI applications, developing ML models in Amazon SageMaker and running them in production with Iguazio on AWS Outposts, in AWS Regions, and on their own hardware.”

Deploying AI at the edge usually requires higher efficiency and performance. Iguazio on AWS Outposts achieves sub-millisecond latency performance and makes the rapid deployment of real-time ML pipelines at the edge a reality. Iguazio’s serverless, cloud-native technology enables data processing at scale across the ML pipeline with extreme efficiency. By implementing local AWS Outposts environments with the Iguazio platform, customers can save months on getting AI to production and allow their teams to focus on business logic instead data wrangling. This results in a faster time to market and lower operational costs for releasing and managing new AI services.

“Our customers want flexible, high-performance solutions for operationalizing machine learning, solutions that abstract away infrastructure, and provide the same consistent experience across hybrid environments” said Asaf Somekh, Co-Founder and CEO of Iguazio. “The seamless integration with AWS Outposts enables us to provide our customers with an enhanced solution that is fully integrated within businesses’ AWS Outposts environments, allowing them to choose where their applications reside based on data security and business considerations, and not performance or ease of use.”

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