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Go Beyond KEDA,
with Kedify

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    Production grade HTTP-based autoscaling

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    Prevent services overload with intelligent scaling rules

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    Push-based metrics collection for real-time autoscaling

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    Dynamically resize your workloads with zero downtime

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    Keep KEDA up-to-date and CVE-free

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    Define autoscaling policies that adjust automatically

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    Manage KEDA across many clusters and clouds

Why Kedify?

Reduce cloud costs with less complexity and better performance. Autoscale Kubernetes workloads on any cloud using any event.

Reduce AI Workload
Costs & Complexity

Optimize Cloud Costs
& Application Performance

Unify Your Environment
on Kubernetes

Scale your AI workloads—including LLM inference and GPU-intensive processes—using metrics like GPU usage, tokens, and requests per second to optimize infrastructure utilization.

Discover strategies for scaling AI workloads

Automatically adjust resources for any workload, from real-time HTTP/gRPC traffic to batch jobs, using key performance metrics and scale to zero to keep costs low.

Learn about HTTP scaling in production

Migrate from AWS Lambda, Azure Functions, or Google Cloud Run to a unified Kubernetes platform that streamlines deployment and observability while ensuring cost-efficient scaling.

Read on migrating to Kubernetes

Quick Kedify Platform Tour

Effortlessly scale your workloads with Kedify. It integrates seamlessly with Kubernetes and optimizes clusters in a few simple steps.

Kedify’s Latest Highlights

Kedify is trusted by:

“Before Kedify, scaling up was a constant challenge. Now, our platform adapts instantly to our users’ needs, and we’ve freed up our team to focus on new features rather than managing resource spikes.”

Rafael Tovar, Cloud Operations Leader @ Tao Testing

“With Kedify, our developers get the best of both worlds, cost-efficient scaling like Google Cloud Run, but fully integrated within our Kubernetes-based platform.”

Jakub Sacha, SRE @ trivago

Kedify's Key Features

Kedify streamlines Kubernetes autoscaling across clouds, delivering real-time efficiency gains.

HTTP-based autoscaling

Secure builds with updates

Real-time autoscaling

Dynamic resource recommendations

Production-ready HTTP-based autoscaling

Kedify’s HTTP Scaler is a production‑ready solution for dynamically scaling Kubernetes workloads based on HTTP traffic.

Key capabilities include automatic network traffic wiring, a fallback mechanism for continuous availability, built‑in health checks, plus support for gRPC and WebSockets.

The scaler maintain high performance while reducing infrastructure costs.

Keep KEDA up-to-date and CVE-free

Kedify’s secure builds ensure KEDA remains up-to-date and CVE-free, applying critical patches for the most demanding enterprise environments.

This streamlined patching process lets you confidently scale applications while maintaining robust security standards.

Real-time metrics collection & scaling

Kedify’s real-time Autoscaling provides metrics with minimal latency, ensuring near instant responsiveness to changes in traffic.

Whether it’s HTTP load or other telemetry data, Kedify’s push-based metrics collection drives real-time autoscaling decisions.

This approach delivers a stable, highly responsive environment that seamlessly adapts to fluctuating demand

Dynamically resize your workloads with zero downtime

Some applications, like Java or Python, demand extra resources at startup but need far less once running.

Kedify allows workloads to adjust CPU and memory requests precisely for each phase of your app’s lifetime, enabling in-place resource resizing without a full pod restart.

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8.6k

Github Stars

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400+

Contributors

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50+

Organizations

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65+

Scalers

Scalers

Support for 65+ proven scalers including HTTP & gRPC traffic, AWS SQS, Azure Service Bus, GCP services, Redis, Prometheus, Apache Kafka, RabbitMQ, Selenium and many more.

As featured on Hacker News

Read about the launch

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