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Big Data And AI/ML

Easily run big data and AI/ML workloads on Kubernetes

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The Challenge

Big Data and AI/ML can lead to a number of challenges as it relates to your Kubernetes strategy. For example, storage infrastructure doesn’t map to scale-out compute clusters. Slow volume provisioning makes it hard to quickly scale compute, and it is difficult to support IOPS-intensive workloads and batch jobs on the same infrastructure

Many Apps

Each data service has its own operational practices, but hiring specialists or buying support agreements for each is prohibitively expensive.

Many Environments

Containers solve the infrastructure differences between clouds and on-prem data centers for compute, but don't address the challenges of running stateful apps in different environments.

Uncontrolled Self-service

Developers want self-service, but you can't risk giving up control of corporate policies like security, data retention, backups, and more.

The Diamanti Solution

Enterprises from manufacturing, financial services, utilities, and many other industries are implementing big data and AI/ML strategies to generate business intelligence and drive value across the organization, especially in areas like process automation, improving customer experience, cost reduction and revenue growth. However, it can be a challenge to run complex, I/O-intensive workloads on infrastructure with “noisy neighbors” — while maximizing compute and storage resource utilization. 

Recovery Point

Objective/Recovery Time Objective (RPO/RTO) of zero Storage-Level Mirroring, Snapshots, Replication.

Data Security

Enhance security, availability, and scalability to bring production-ready enterprise applications to Kubernetes.

High Availability and Multi-Zone Deployments

Diamanti multi-zone clusters allow Kubernetes nodes to be distributed across different availability zones (failure domains), ensuring applications can achieve.

Backup and Failover

Diamanti's unique storage and network architecture ensures databases are highly available with quick and easy migration across zones, providing an RPO/RTO of zero.

Big data And AI/ML

Enable business intelligence at enterprise scale

Enterprises from manufacturing, financial services, utilities, and many other industries are implementing big data and AI/ML strategies to generate business intelligence and drive value across the organization, especially in areas like process automation, improving customer experience, cost reduction and revenue growth. However, it can be a challenge to run complex, I/O-intensive workloads on infrastructure with “noisy neighbors” — while maximizing compute and storage resource utilization. 

Diamanti makes it easy to deploy big data and AI/ML workloads on Kubernetes, effortlessly optimize CPU, storage and networking resources while supercharging performance and lowering the cost of your large-scale data investments. 

Lightning Performance With Simplified Deployment, Storage And Networking

Diamanti provides a true end-to-end platform to accelerate big data and AI/ML use cases. With GPU support for high-performance workloads, I/O acceleration and Kubflow integration for machine learning workloads in Kubernetes, Diamanti makes it easy to supercharge your performance and optimize costs — whether on-premises or in the cloud. Moreover, with simplified management for GPU and non-GPU-based resources, data scientists have the flexibility they need to accelerate model training and deploy CPU-optimized workloads to the same cluster. 

Proven Results For Large-Scale Containerized Workloads

Supercharge any cloud native big data or AI/ML project with guaranteed DIamanti QoS. Leveraging  Diamanti for large-scale workloads, enterprises are able to:

  • Deploy GPU and CPU-targeted workloads to the same cluster
  • Maximize resource utilization and return on investment
  • Experiment, train and run production ML models on a single platform
  • Reduce footprint by >50%

Data Services

Run popular data management and processing services on Kubernetes

Kafka
Elastic
Group 5531
TensorFlowLogo
PostgreSQL
Group 5521

Diamanti Machine Learning

Diamanti ML Platform with NVIDIA GPU support provides a turnkey solution for deploying containerized workloads on Kubernetes, ideal for the demanding requirements of emerging AI/ML applications.

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