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Navigating Key Metrics for Growth and Success

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Source for Trends, Tips, and Timely Topics

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The Blueprint for Mastering Tools and Processes

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Bringing You the Top Stories as They Happen

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Exploring Critical Topics with Authoritative Research

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Easily Track and Maximize Your Investment Returns

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Optimize Your AI with Elastic GPU Service (EGS)

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About Us

Discover Our Mission and Core Values

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Join Our Team and Shape the Future Together

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Events and Webinars

Connecting You to Trends, Tools, and Thought Leaders

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Support

Helping You Navigate Challenges with Ease

FAQ

AI Performance with Elastic GPU Service (EGS)

Real-time, optimized GPU utilization with predictive algorithms and automated orchestration.

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Hype Cycle™ for

Zero Trust Networking, 2023

Gartner® names Avesha as a Sample Vendor for Kubernetes Networking in the 2023 Hype Cycle™ for Zero Trust Networking

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We’re Trusted

by Leading Enterprises

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Our products

solve your biggest Kubernetes problems

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FinOps Challenges

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1

Out-of-Control Kubernetes Costs

Lack of good cost reduction tools or principles that can be adopted by the developers.

2

Opaqueness on how to allocate costs by teams

Lack of tools to track costs by teams across multiple clusters and multiple namespaces.

3

Manage AI Workload Costs (GPUs)

GPUS are a scarce resource so it’s important to manage their costs efficiently for training and inferencing.

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App Dev Challenges

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1

Lack of automation to address application performance

Current methods involve manual performance tuning of each microservice and each release which is not scalable, thus compromising APDEX scores.

2

Difficulty in migrating to lower cost clouds

One of the challenges in migration is the dependance on existing hyperscaler managed services.

3

Automating Running of GPU Workloads

Data Scientists spend 65% of their time in scheduling and orchestration

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Platform Engineering/DevOps Challenges

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1

Unaware of application behaviors

Platform engineers are charged with scaling of infrastructure but do not know much about the application workloads.

2

Difficulty to scale for traffic spikes manually

No access to predictive tools that specifically handle spike scaling and burst capacity on demand.

3

Managing AI Infra Performance (GPUs)

Dearth of tools to for handling the complexities of GPU orchestration scaling.

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Our products

have proven impact

70%

Decrease

In Kubernetes Costs

50%

Decrease

In Response Times

80%

Increase

CPU/Memory Efficiency

1M+

Microservices

cloud-optimized

1K+

Apps

burst for extra capacity

10K+

Namespaces

tracked for cost across multiple regions

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Powerful products

for every business

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Smart Scaler

Predictive autoscaling based on application behaviors

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Smart Scaler

Smart Karpenter

Predictive autonomous scaling of pods and nodes

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Smart Scaler

Smart Event Scaler

AI assisted infrastructure scaling for peak traffic days

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Avesha Enterprise for KubeSlice

Service Connectivity Layer for managing fleet of clusters for better application performance

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KubeTally

Chargeback

Multi-cluster chargeback by application and teams

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KubeBurst

Application Bursting

On demand cloud capacity for datacenters

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KubeAccess

Multi-cloud app access

Service gateway for multi-cloud applications

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EGS

Elastic GPU Service

Multicluster and Multicloud GPU Provisioning and management platform

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Avesha Blogs

Explore our latest blogs and insights

Optimizing GPU Allocation for Real-Time Inference with Avesha EGS

Scaling RAG in Production with Elastic GPU Service (EGS)

Do You Love Your Cloud Credits? Here's How You Can Get More…

#1 Myth or Mantra of spike scaling – "throw more resources at it."

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Events & Webinars

View and participate in our events & webinars to learn all about Avesha's solutions for your network and optimization challenges.

Conference

No-Code Migration of Workloads to Retail Edge for Lowest Costs and Best Performance

Event Participation

Pytorch Conference 2024

In person Event

Oracle CloudWorld 2024

In person Event

Oracle Cloud Networking Event

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Insights from Your Industry Peers

“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 todays challenges, but as a framework to build additional networking products and capabilities in the future."

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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.”

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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.”

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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."

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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.”

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William Bell

EVP Products, Phoenix NAP

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