GPU/Neocloud Billing using Rafay’s Usage Metering APIs
Cloud providers offering GPU or Neo Cloud services need accurate and automated mechanisms to track resource consumption.
Read Now
Streamline Kubernetes Cluster Lifecycle Management Across Public Clouds
Each cloud provider (AWS, Azure, GCP, OCI) has its own set of tools and interfaces for Kubernetes management, leading to increased operational complexity.
Regularly updating Amazon Machine Images (AMIs) and other components across clusters often requires significant manual effort, increasing the risk of errors and downtime.
SREs, developers, and other teams often provision clusters independently. Without centralized templates and policies, this leads to inconsistent configurations and operational risk.
Manage Kubernetes clusters across AWS, Azure, GCP, and OCI from a single interface, reducing complexity and improving operational efficiency.
Enforce uniform security, governance, and operational policies across all clusters, ensuring compliance and reducing the risk of configuration drift.
Manage Kubernetes clusters across AWS, Azure, GCP, and OCI from a single interface, reducing complexity and improving operational efficiency.
Enforce uniform security, governance, and operational policies across all clusters, ensuring compliance and reducing the risk of configuration drift.
Manage Kubernetes clusters across AWS, Azure, GCP, and OCI from a single interface, reducing complexity and improving operational efficiency.
Enforce uniform security, governance, and operational policies across all clusters, ensuring compliance and reducing the risk of configuration drift.
Manage Kubernetes clusters across AWS, Azure, GCP, and OCI from a single interface, reducing complexity and improving operational efficiency.
Enforce uniform security, governance, and operational policies across all clusters, ensuring compliance and reducing the risk of configuration drift.
Why Choose Rafay for Multi-Tenancy Infrastructure?
Centrally enforce the latest add-ons, policies and cost controls across all clusters and landing zone
Cloud providers offering GPU or Neo Cloud services need accurate and automated mechanisms to track resource consumption.
Read Now
Agentic AI is the next evolution of artificial intelligence—autonomous AI systems composed of multiple AI agents that plan, decide, and execute complex tasks with minimal human intervention.
Read Now
Whether you’re training deep learning models, running simulations, or just curious about your GPU’s performance, nvidia-smi is your go-to command-line tool.
Read Now
See for yourself how to turn static compute into self-service engines. Deploy AI and cloud-native applications faster, reduce security & operational risk, and control the total cost of Kubernetes operations by trying the Rafay Platform!