- User-facing components: like web servers or APIs may require higher availability to ensure a seamless user experience.
- Backend components: such as data processing pipelines or batch jobs may have lower availability requirements, as temporary downtime is less critical.
- Compliance or Regulatory Requirements: Certain industries or data types may mandate stricter availability standards.
- Customer Segments: Different customer segments (e.g., enterprise vs. individual users) may have varying availability expectations.
- Cost considerations: For some non-critical components, a lower availability target may be acceptable to reduce costs.
🚀Kubernetes and Multi-Cloud Scaling Support
Wave Autoscale seamlessly integrates with Kubernetes, allowing you to adjust Deployment Replicas (instead of HPA) and leverage Service Mesh for traffic control. Additionally, it supports scaling across multiple public clouds, including AWS, GCP, and Azure.
📜Scaling Plan as Code
Wave Autoscale allows you to define your scaling plans, metrics, and component definitions as code using YAML files, enabling version control, collaboration, and reproducibility.
⚡A Variety of Metrics Support
⚙️Dynamic Scaling Triggers with JavaScript, Cron, HTTP
Craft precise scaling strategies using JavaScript expressions. With metrics fetched from collectors, you can design conditions tailored to your application's specific behavior and requirements. Also, schedule scaling operations with granular control using cron expressions. Whether you anticipate daily traffic spikes or have planned maintenance, ensure your infrastructure scales accordingly.
🚦Traffic Control
In addition to autoscaling, Wave Autoscale integrates with traffic control features such as rate limiting (WAFs), virtual waiting rooms, and load balancing, enhancing application performance and user experience.
📊Detailed Scaling History
Wave Autoscale maintains a detailed history of scaling events, providing visibility into resource adjustments, triggers, and audit trails for troubleshooting and analysis.