Cloud Optimization for
Cost Efficiency
Performance
Reliability
Autoscaling with Manifests Manually
Kubernetes HPA
apiVersion: autoscaling/v2
 
kind: HorizontalPodAutoscaler
metadata:
name: php-apache
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: php-apache
minReplicas: 1
maxReplicas: 10
metrics:
 
- type: Resource
  resource:
  name: cpu
  target:
  type: Utilization
  averageUtilization: 50
  status:
  observedGeneration: 1
  currentReplicas: 1
  desiredReplicas: 1
  currentMetrics:
- type: Resource
  resource:
  name: cpu
  current:
  averageUtilization: 0
  averageValue: 0
One-Click Autopilot
Why Wave Autoscale instead of default autoscaling?
Wave Autoscale is a cloud optimization solution designed for SREs and the cloud engineering teams. Currently, when you need to configure autoscaling, you might find yourself writing manifest files or adjusting options in the cloud console without know the optimal CPU utilization for your workloads. This is often why autoscaling doesn’t work as expected. Here is an explanation of the challenges with autoscaling. ("Autoscaling in Kubernetes: Why doesn’t the Horizontal Pod Autoscaler work for me?" - Expedia Group (opens in a new tab))
At Wave Autoscale, we address the challenges of autoscaling and rightsizing using advanced machine learning algorithms. Our solution adjusts your instances and pods with highly accurate numbers based on your specific traffic patterns or queue messages.
Features

🚀One-Click Autopilot

Wave Autoscale provides a one-click autopilot feature that automatically adjusts the number of instances by machine learning technology. This feature allows you to focus on developing your application without worrying about the infrastructure.

📏Rightsizing Instances, Pods

Rightsizing is the process of matching the resources of a cloud instance to the needs of an application. Wave Autoscale provides a rightsizing feature that allows you to optimize the number of instances based on the predicted load. This feature allows you to reduce costs by optimizing the number of instances.

🛡️With Traffic Protection

Wave Autoscale provides a traffic protection feature that prevents traffic spikes from affecting your application. This feature allows you to maintain the stability of your application even when traffic spikes occur.

🔮Proactive by Forecasting

Wave Autoscale provides a load forecasting feature that allows you to predict the load on your application. This feature allows you to optimize the number of instances based on the predicted load.

📊Visualized Autoscaling

Wave Autoscale provides a visualized autoscaling feature that allows you to monitor the number of instances in real-time. This feature allows you to monitor the number of instances and adjust the number of instances as needed.

🌐K8s, AWS, OpenStack

Wave Autoscale supports Kubernetes, AWS, OpenStack, and multi-cloud environments. This feature allows you to use Wave Autoscale in various environments.

Our company has developed traffic management solutions that are trusted by more than 500 customers
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