KubeSlice
Avesha Enterprise for KubeSlice
Service Connectivity Layer for managing fleet of clusters for better application performance
KubeBurst
On demand cloud capacity for datacenters
KubeTally
Multi - cluster chargeback by application and teams
KubeAccess
Service gateway for multi-cloud applications
Smart Scaler
Smart Scaler
Predictive autoscaling based on application behaviors
Smart Karpenter
Predictive autonomous scaling of pods and nodes
Elastic GPU Service
EGS
Single/Multi-cluster and multi-cloud GPU provisioning and management platform
KubeAgent
KubeAgent
KubeAgent adds intelligence and autonomy to Kubernetes
EGS Resources
Explore Resources for Elastic GPU Service
Analyst Reports
Navigating Key Metrics for Growth and Success
Blog
Source for Trends, Tips, and Timely Topics
Documentation
The Blueprint for Mastering Tools and Processes
Customer Case Studies
Success stories from our valued customers and partners
Orchestration, Optimization
and Observability for your Compute (GPU/CPU)
AI Agent Layer (Avesha KubeAgent) Learn More
GPU and CPU
Unified Orchestration for AI Workloads
Modern AI workflows require seamless collaboration between CPUs and GPUs. Avesha orchestrates the perfect balance between compute resources, ensuring your training, inference, and real-time applications run with maximum efficiency. By intelligently managing workloads across CPU and GPU infrastructures, we unlock the full potential of hybrid compute environments.
What does this mean for you?
Optimized Workloads
Efficiently allocate jobs to CPUs and GPUs based on task complexity and resource needs.
Cost Efficiency
Avoid overprovisioning while ensuring peak performance for compute-intensive tasks.
Enhanced Scalability
Easily scale across multi-cloud and on-prem environments without compromising on speed or cost.
EGS Benefits
Elastic GPU Service Enterprise
Cost Optimization
Achieve up to 40% savings in GPU costs while maintaining peak performance for your workloads
Predictive Cost Management
Leverage data-driven insights to forecast resource needs and align costs with usage patterns.
Spot Instance Utilization
Prioritize cost-effective spot GPUs for batch jobs and non-critical tasks, cutting compute costs significantly.
Dynamic Resource Allocation
Automatic GPU allocation based with EGS’ time-slice feature. Unused GPU capacity automatically reallocated for efficient use.
Observability with Real Time Clarity
Eliminate inefficiencies before they become bottlenecks, ensuring every GPU cycle delivers value.
Monitoring
Leverage data-driven insights to forecast resource needs and align costs with usage patterns.
Proactive Insights
Prioritize cost-effective spot GPUs for batch jobs and non-critical tasks, cutting compute costs significantly.
Cost Transparency
Automatic GPU allocation based with EGS’ time-slice feature. Unused GPU capacity automatically reallocated for efficient use.
Smart Orchestration
Run large-scale, distributed workflows without worrying about resource bottlenecks or overspending
Dynamic Scaling
Our system provisions GPUs precisely when and where they’re needed and decommissions them when they’re not
Cross-Cloud Flexibility
EGS orchestrates workloads across multiple cloud environments, enabling you to leverage the best pricing and performance options
Workflow Optimization
Whether it’s training an LLM or running real-time inference, EGS ensures every task in DAG pipelines are optimized for speed and reliability
EGS Automation
Save time, reduce errors, and scale operations effortlessly with automation that works around the clock
Auto-Provisioning
Automatically allocate GPUs based on workload demands, ensuring zero idle resources.
Self-Healing Systems
Detect and resolve workflow failures without manual intervention, keeping your operations running smoothly.
Cost-Aware Automation
Schedule non-critical tasks during off-peak hours or prioritize cost-efficient resources like spot instances.
Empower
Who We Empower
For AI Cloud Providers
Enable a new generation of cloud services with Avesha. Our solutions provide seamless GPU and CPU orchestration to help you deliver:
Cost-effective GPUaaS
Provide GPU-as-a-Service without overburdening resources.
Elastic Compute Scaling
Scale compute resources dynamically to meet customer demand spikes.
Multi-Tenant Isolation
Ensure secure and efficient resource sharing for your users.
For Enterprise AI
Empower your research and development teams with unmatched infrastructure efficiency. Avesha enables
Faster Model Training
Distribute compute-intensive AI training jobs intelligently across CPUs and GPUs.
Seamless Multi-Cloud Workflows:
Work across diverse environments without worrying about infrastructure bottlenecks.
Real-Time Inference:
Accelerate low-latency AI workloads to keep up with your application demands.
Enterprise Ready
Best-in-Class Experience for
Data Scientists, AI Engineers, and Platform Engineers
45%
Increase
In Node Allocations
30%
Reduction
In GPU Wait Time
47%
Reduction
In GPU Cost
Testimonials
Insights from Your Industry Peers
“With Avesha's Elastic AI Services we're able to optimize our GPU workloads dynamically, ensuring we maximize performance without overpaying for underutilized resources. This allows us to scale efficiently while keeping our research and operational costs predictable and manageable.”
Tulasee Rao Chintha
CTO, InpharmD
“Partnering with Avesha allows us to have our on-premises and cloud clusters securely communicate with each other. It also ensures that the same namespaces can be used in multiple environments.”
Alexander Leschinsky
Co-Founder & CEO, G&L Systemhaus
“Cox Edge operates a complex and highly distributed edge cloud network across data centers in the US, so the ability to establish secure, low latency connectivity, and intelligently manage traffic routing is a core requirement. We evaluated all sorts of network solutions, and Avesha’s KubeSlice really stood up not only as a solution to today's challenges, but as a framework to build additional networking products and capabilities in the future.”
Ron Lev
GM, Cox Edge
“Humans aren’t good at managing that level of complexity in a stressful scenario, even without the stressful scenario it’s really complicated. So that is where technology (like Smart Scaler) does a really good job. It can crunch numbers for you, and take your business requirements, and implement them without you having to be there under pressure.”
Shlomo Bielak
Head of Engineering, The Score
“To date, application and cloud operations teams spend a lot of underappreciated effort trying to predict the cost and performance tradeoffs of different settings for autoscaling pods. Solutions like Avesha’s Smart Scaler can offload the heavy lifting of these estimation processes so cloud native engineers can realize just-in-time optimized HPA settings across their Kubernetes application environments.”
Jason English
Principal Analyst at Intellyx
“Avesha KubeSlice is a smart tool that allows us to easily connect workloads from datacenters to clouds. If you are running Kubernetes in Hybrid Cloud, you get faster resiliency with Avesha KubeSlice. Also the ability to isolate workloads by tenant with Slices is a game changer for Hybrid Cloud.”
John Repucci
Director of Solution Architecture, Ensono
“We are excited to partner with Avesha to continue to innovate and make it easier to work with multi cluster applications and provide a whole suite of capabilities that the Avesha platform provides.”
William Bell
EVP Products, Phoenix NAP
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