Discover how Volumez is pioneering the next generation of cloud data infrastructure with our groundbreaking DIaaS (Data Infrastructure as a Service) platform. Read the press release. With an innovative, dynamic approach, Volumez enables enterprises to tap into the full power of cloud resources—delivering high performance, low latency, and unprecedented throughput for the most demanding data-intensive workloads.
Balanced systems in the cloud: Beyond human cognition
Modern workloads in the public cloud require new ways of storing and managing data. Infrastructure as a Service (IaaS) offers robust, discrete components to serve these workloads – yet the complexities of finding optimized configurations of compute, network, and storage defy human cognition. The resulting systems are unbalanced, generating performance and waste challenges. Volumez exists to dynamically construct tailored, balanced systems optimized for a specific workload or aggregations of workloads in the public cloud.
No resource is an island
Cloud IaaS resources cannot be considered in isolation. Storage, for example, does not stand alone; its performance, cost, and availability characteristics must be set in the context of the network topology and the compute instance to which it connects. A balanced system can only be created when these resources are combined as a whole – creating a data infrastructure in which storage is an anchor.
Storage often becomes the performance bottleneck that hinders GPU and CPU operations. Imagine high-performance GPUs sitting idle, waiting for data. Volumez eliminates this inefficiency by dynamically configuring storage and compute to work in perfect unison, ensuring zero idle time and maximum performance.
Beyond storage to data infrastructure: Balanced systems in the cloud with DIaaS
Our platform doesn’t just optimize storage—it creates balanced, high-performance data infrastructure across all cloud resources. By offering a SaaS-based control plane that interacts with cloud provider APIs, Volumez continuously collects data, learns from performance patterns, and configures the optimal infrastructure for each workload. These operations comprise a functional hierarchy.
Figure 1: The Volumez DIaaS platform – dynamic and tailored cloud infrastructure for unprecedented results.
Cloud awareness is the foundation of balanced systems in the cloud
The foundation of “cloud awareness” involves active profiling and pressure testing of IaaS components, including compute instances (especially storage-optimized instances), network, and storage objects. This analysis results in deep understanding of cloud object performance capabilities, resilience levels, cost structure, physical location, network topology, and compatibilities/constraints with other objects – among other metadata collected and stored in a continuously updated repository. Cloud awareness is generated on an existing class of objects and also applied to new objects introduced by the cloud provider, to enable new capabilities and economics to be introduced into a data infrastructure. In this sense, Volumez future proofs a user’s data infrastructure.
Cloud awareness informs composition of IaaS objects
A user, API call, or infrastructure as code like Terraform application issues a declarative policy to Volumez DIaaS declaring the workload requirements for its supporting data infrastructure. The workload may already have its compute instance configured and deployed. Through machine learning and statistical analysis methods operating on the “cloud aware” repository of profiled and tested IaaS objects, DIaaS identifies and composes the optimal configuration to meet the requirements and constraints of the workload’s declarative policy. Composition is a hard constraint problem, resolving a complex matrix of performance, availability, cost, governance, among other elements.
DIaaS orchestrates composed objects
Once a solution of composed objects is assembled that fits the workload’s policy, DIaaS orchestrates the objects into a deployed data infrastructure, configuring the cloud provider’s operating system on the compute instance, network settings, and storage targets. Volumez does not insert any proprietary or third-party code, it does not introduce a storage controller, it does not introduce a device driver – it is 100% cloud provider IaaS components, containing a 100% Linux-based data path.
You manage DIaaS with Data Infrastructure as Code (DIaC)
Using the functions outlined above, DIaaS dynamically tailors data infrastructure from discrete IaaS components to deliver extreme performance, ultra-low latency, unprecedented throughput, and maximized GPU utilization at transformative economics for AI/ML, databases, and other data-intensive workloads. “Tailoring” is automated through declarative policies formed through the UI, API, SAML, or any Infrastructure as Code platform. We call this Data Infrastructure as Code, inspired by (and integrated with) the IaC platform engineering approach to toolchains.
Read the white paper: Uncovering DIaaS design principles
Our white paper, “Volumez Data Infrastructure as a Service: Architecture Guide,” delves deeper into the specifics of how our platform’s architecture supports the increasing complexity of today’s data environments. The white paper explores how our infrastructure is optimized for a range of workloads, from AI/ML data pipeline processes to high-performance databases and beyond.
Inside the white paper, you’ll discover:
- Innovative design principles that allow for dynamic scaling and workload optimization.
- Workload-specific infrastructure designed to meet the demands of a wide variety of industries and use cases.
- A closer look at the architecture behind the platform that enables seamless data mobility, intelligent system balancing, and cost-effective resource management.
Download the white paper here to learn how Volumez is setting a new standard for Data Infrastructure as a Service.
MLCommons MLPerf Storage 1.0 AI/ML Training Benchmark
This workload-aware data infrastructure alignment can be demonstrated by the exceptional results in the first MLCommons® MLPerf® Storage 1.0 AI/ML Training Benchmark that Volumez announced today. Volumez DIaaS for AI/ML achieved extraordinary linear scaling and an impressive average throughput of 1.079 TB/sec with 92.21% GPU utilization1 on AWS. To learn more about the MLPerf Storage AI/ML Training Benchmark, read the press release and blog.
Embracing the future with Volumez
Volumez’ DIaaS platform isn’t just about keeping up with the future of data management—it’s about leading the way. With scalable, secure, and high-performance solutions tailored to your business’s needs, we’re here to ensure that your data infrastructure is a catalyst for growth, not a limitation.
Get Started Today: Reach out to us to learn how Volumez’ DIaaS can transform your data strategy and take your business to the next level. Contact us here.
1 Results verified by MLCommons Association. Retrieved from https://mlcommons.org/benchmarks/storage/. The MLPerf name and logo are registered and unregistered trademarks of MLCommons Association in the United States and other countries. All rights reserved. Unauthorized use strictly prohibited. See www.mlcommons.org for more information.