This company provides an autoscaling platform that dynamically resizes cloud workloads to optimize performance and prevent overloads. Their platform offers features like dynamic vertical autoscaling and cost-aware scaling across multiple cloud environments, helping businesses reduce downtime and control cloud costs.
Funding
$2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
OCFounders
Product
Problem
Managing cloud workload scaling can be complex and costly, often leading to over-provisioning or performance bottlenecks. Existing solutions may lack the granularity and real-time responsiveness needed to optimize resource utilization across diverse application types and cloud environments.
Solution
Kedify provides an elastic autoscaling platform for Kubernetes, powered by KEDA, that dynamically resizes cloud workloads based on real-time metrics and events. The platform supports autoscaling for a wide range of workloads, including HTTP/gRPC traffic, AI inference, and batch jobs, enabling businesses to optimize resource utilization and reduce cloud costs. Kedify offers features such as HTTP-based autoscaling, secure KEDA image builds with updates, multi-cluster management, and dynamic vertical autoscaling, all managed through a web-based dashboard. By unifying autoscaling across different cloud environments and application types, Kedify simplifies cloud infrastructure management and improves application performance.
Target Audience
Kedify targets DevOps engineers, SREs, and cloud architects who need to optimize resource utilization, reduce cloud costs, and simplify the management of Kubernetes workloads across multiple cloud environments.
Features
- Production-ready HTTP Scaler for autoscaling Kubernetes workloads based on HTTP traffic, with automatic network traffic wiring and built-in health checks
- Secure KEDA builds that remain up-to-date and CVE-free, ensuring robust security standards
- Real-time autoscaling with minimal latency through push-based metrics collection
- Dynamic vertical autoscaling, allowing in-place resource resizing without pod restarts
- Support for 65+ scalers, including HTTP, gRPC, AWS SQS, Azure Service Bus, GCP services, Redis, Prometheus, Apache Kafka, and RabbitMQ
- Web-based dashboard for managing KEDA deployments without command-line interaction
- Multi-cluster management for visibility and control over autoscaling across multiple Kubernetes clusters
- Dynamic resource recommendations based on workload and usage patterns