Unified traffic & autoscaling management for clouds and kubernetes
A structured and programmable approach with Scaling Plan as Code
Synchronize traffic and autoscaling control across containers, virtual machines, load balancers, virtual waiting rooms, WAF and more.
What is AutoScaling
Autoscaling is the dynamic adjustment of computational resources based on real-time demand. It ensures that your applications always have the right amount of resources to perform optimally, without over-provisioning or under-utilizing. Not only kubernetes, virtual machine groups, but also serverless functions, databases, and other components can be configured to adjust automatically based on demand.
AutoScaling Challenges
- Beyond CPU Utilization Scaling
- Simultaneous Scaling of Various Components
- Multi-Cloud, Multi-Region, Multi-Tenant Scaling
- Cost-Effective Scaling
- Intelligent Traffic-Aware Scaling
- Customized Scaling for Machine Learning Workloads
Wave Autoscale is designed to overcome these challenges, providing a more tailored and responsive approach to autoscaling that aligns with both technical complexities and business needs.
- Unified Management: Control various autoscaling components like Kubernetes (k8s), EC2 Autoscaling, and more from a single interface.
- Flexible Scaling Plans: Define custom scaling plans based on your unique requirements, such as traffic volume, business KPIs, and more.
- Wide Range of Metrics Integrations: Connect with numerous metrics sources, offering a complete understanding of application performance.
- Multi-Cloud, Multi-Region, Multi-Tenant Scaling: Handle different scaling components simultaneously, providing a one-stop solution for diverse infrastructure environments.
- Multi-Cloud: Scale across multiple cloud providers, including AWS, GCP, and Azure.
- Multi-Region: Scale across multiple regions within a cloud provider.
- Multi-Tenant: Scale across multiple tenants within a region.
- Cost Optimization or Performance Optimization: Define scaling plans based on cost optimization or performance optimization.
- Open-Source: Wave Autoscale is open-source, allowing you to customize and extend it to suit your specific needs. It's also free to use from small startups to enterprises, with no hidden costs or vendor lock-in.
Principles
Reliability
Built with reliability in mind, using Rust to ensure optimal resource allocation and application performance.
Integration
Seamlessly integrates with a wide range of metrics sources, including APM tools and system metrics, for easy incorporation into existing development workflows.
Customization
Offers extensive customization options for SREs and cloud engineers to tailor the solution to their specific needs, beyond traditional autoscaling for services such as EC2.
Key Feature#01
Unified Scaling Management
Scaling cloud components typically involves managing disparate strategies across distinct systems. With Wave Autoscale, we introduce a centralized approach to scaling management. By bringing together the management of various components—like load balancers, databases, and computing resources—we offer engineers a streamlined platform for efficient oversight. This centralization not only refines the management process but also ensures that every scaling action is synchronized across the entire infrastructure.
Key Feature#02
Metrics Integration for Efficient Scaling
Wave Autoscale integrates a comprehensive range of metrics from different system components such as load balancers and databases. This allows for more informed and efficient scaling decisions, ensuring that resources are used effectively. By centralizing these metrics, teams can easily monitor, analyze, and adjust their scaling strategies based on real-time data.
Key Feature#03
Adaptive Scaling Triggers
Key Feature#04
Support for Multi-Cloud, Multi-Region, Multi-Tenant Scaling
Get started with Wave Autoscale