NetApp's Senior Director, AI and Data Engineering - Iguazio Customer Testimonial
“What used to take months, takes a week now.”
Shankar Pasupathy, Sr Director Active IQ AI and Data Engineering at NetApp shares his experience with the Iguazio platform, and how he was able to drive the following gains:
· 6-12x improvement in time to develop and deploy new AI services
· 50% reduction in operating costs
· 16x storage capacity reduction
· 3-6x fewer compute nodes
· End-to-end platform for analytics and AI
Read the full case study here: https://go.iguazio.com/netapp-case-study
Iguazio provided NetApp with a serverless, cloud-native data science platform that was deployed at the core of Active IQ. The platform analyzes 10 trillion data points per month from storage sensors worldwide and harnesses this data to generate actionable intelligence and run real-time predictive maintenance.
Modern AI and ML workloads require the utmost flexibility and speed. They also need data—the more, the better. For the best results, you need a solution that can unify your data pipeline across edge, core, and cloud.
The Iguazio solution enables the full data analytics and AI and ML lifecycle on one ready-to-use platform. Users can ingest data from a variety of sources, explore and prepare data at scale, run distributed training, and automatically deploy models or complex applications to production. Data scientists, data engineers, DevOps, and app developers can collaborate efficiently on one secure self-service platform.
Iguazio’s data science platform enabled NetApp to leverage a prescriptive approach to protecting and optimizing NetApp systems while enabling its customers to make smarter decisions about storage.
NetApp used Iguazio to achieve real-time processing of the massive and growing streams of data delivered by its storage arrays. Leveraging Iguazio’s ability to analyze trillions of historical and real-time diagnostic records, Active IQ can continuously perform risk assessments and detect patterns in incoming data streams to identify potential and actual anomalies such as hardware defects, pending capacity shortages, and performance slowdowns.
Essentially, Iguazio simplified the orchestration and management of the AI data pipeline, enabling NetApp to analyze this data, generate actionable intelligence in real-time, and relay predictive maintenance messages back to the arrays. Automate the data science pipeline with serverless functions and build highly accessible end-to-end ML pipelines
Deploying Iguazio supplied NetApp with access to one of the fastest open-source serverless frameworks in the world, Nuclio, to automate its data science pipeline. This solution leverages Kubeflow to speed up the running of ML pipelines and enables a layer of automation and monitoring for popular ML and analytics frameworks on top of Kubernetes. With its serverless functions, NetApp was able to build highly accessible end-to-end ML pipelines and achieve full automation and CI/CD for its ML and analytics workloads.
Iguazio’s Data Science Platform enabled NetApp to minimize development and maintenance overhead and speed up the development and deployment of new AI services for Active IQ. NetApp used the platform’s friendly pipeline orchestration tools and extremely fast multi-model data layer to facilitate end-to-end machine learning pipeline automation while enabling real-time MLOps for incoming data streams.
Iguazio reduces the complexities of MLOps at scale, providing NetApp with an end-to-end solution for the entire data science lifecycle with enterprise support. Its data science platform facilitated seamless collaboration between NetApp’s developers by streamlining the integration of traditional data analytics tools into the AI pipeline and simultaneously providing access to several big data and AI microservices. This enabled them to collaborate efficiently on one secure self-service platform, avoid tedious integrations, and focus on building applications to meet business demands.
#ml #datascience #mlops #machinelearning
