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Smart ScalerReduce your cloud costs from 20-70% with continuous predictive autoscaling of Kubernetes resources driven by AI
Smart Scaler Banner Image
Reinforcement Learning engine continuously optimizes number of pods
Predicts traffic based on learned patterns
Predicts number of pods needed based on load
Smart Scaler accurately predicts demand ahead of time and 'precisely' scales up or down infrastructure and application resources.

Smart Scaler

Reduce your cloud costs from 20-70% with continuous predictive autoscaling of Kubernetes resources driven by AI Smart Scaler accurately predicts demand ahead of time and 'precisely' scales up or down infrastructure and application resources.
Reinforcement Learning engine continuously optimizes number of pods
Predicts traffic based on learned patterns
Predicts number of pods needed based on load
Smart Scaler Banner Image
Smart Scaler Features
extracts performance
Extracts performance data from Prometheus
pod capacity estimator
Pod capacity estimator predicts number of pods needed for a given load.
traffic pattern predictor
Traffic pattern predictor predicts traffic based on learned patterns
reinforcement
Reinforcement Learning Engine accurately estimates K8s resources
Smart Scaler Diagram
Avesha Reinforcement Learning Model - Results
Avesha Reinforcement Learning Model - Results
sla violation less
SLA Violations Less
proactive
Proactively creating pods for internal load
reducing pods
Reducing pods as load increases
Hyperscalar Autoscaling Performance - Results
Hyperscalar Autoscaling Performance - Results
sla violation less
Maintain SLA
reactive
Proactively scale with demand
no learning
Reduce wastage when load decreases
Smart Scaler Benefits
Companies are raking up huge costs due to lack of predictive capabilities in current autoscaling solutions. Smart Scaler is the only “intelligent” HPA (Horizontal Pod Autoscaling) Solution in the market
Reduces cloud costs

Reduces cloud costs

Reduces carbon footprint

Reduces carbon footprint

Maintains SLAs

Maintains SLAs

Eliminates Over Provisioning

Eliminates Over Provisioning

Uses AI and Reinforcement Learning

Uses AI and Reinforcement Learning

Multi-cluster and Multi Cloud “Intelligent” HPA

Multi-cluster and Multi Cloud “Intelligent” HPA

How to set up Smart Scaler?
Setting up Smart Scaler RL autoscaling to reduce Kubernetes cloud costs.
smart scaler diagram
Gather historical system performance and application metrics for the service to train smart scaler RL model.
Estimate the capacity of the pod for the service.
Train the RL model for the service.
Deploy smart scaler HPA model to performance testing environment.
Reduce costs by deploying smart scaler RL to production environment.
Monitor and re-train model for traffic and environment changes.
Smart scaler diagram
Gather historical system performance and application metrics for the service to train smart scaler RL model.
Estimate the capacity of the pod for the service.
Train the RL model for the service.
Deploy smart scaler HPA model to performance testing environment.
Reduce costs by deploying smart scaler RL to production environment.
Monitor and re-train model for traffic and environment changes.
Cloud image
Cloud image
Cloud image
Star image
Star image
How to set up Smart Scaler?
Setting up Smart Scaler RL autoscaling to reduce Kubernetes cloud costs.
smart scaler diagram
Gather historical system performance and application metrics for the service to train smart scaler RL model.
Estimate the capacity of the pod for the service.
Train the RL model for the service.
Deploy smart scaler HPA model to performance testing environment.
Reduce costs by deploying smart scaler RL to production environment.
Monitor and re-train model for traffic and environment changes.
Smart scaler diagram
Gather historical system performance and application metrics for the service to train smart scaler RL model.
Estimate the capacity of the pod for the service.
Train the RL model for the service.
Deploy smart scaler HPA model to performance testing environment.
Reduce costs by deploying smart scaler RL to production environment.
Monitor and re-train model for traffic and environment changes.

Testimonials

intellyx
“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 EnglishPrincipal Analyst at Intellyx
Learn about our other products
Avesha KubeSlice consists of other products that enable automation, easy interconnectivity across a wide area network, and adaptive & autonomous configuration of the network based on the application's needs.
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