Capillary reduced ops tickets by 95%

“Our releases are fast. And with less developer time needed our teams can focus on building exciting features. We’ve saved countless hours and costs.”

Piyush K,
Chief Architect, Capillary Technologies,

Treebo reduced production issues by 70%

"With Facets, our staging environments look identical to production environments. So in case of production issues, we can be sure there are no infra drifts."

Kadam Jeet Jain,
Co-Founder & CTO, Treebo Hotels and Hotel Superhero.

GGX switched from AWS to GCP in 2 weeks

"Facets has radically changed our DevOps for the better. They did all the heavy lifting and saved us precious time and resources in our when we switched from AWS to GCP."

Kaustubh Bhoyar,
Head of engineering, GGX

Trusted by companies to run production at scale

Capillary | FacetsMPL | FacetsTreebo | FacetsPurplle | Facets

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Application Orchestration

Keda

KEDA (Kubernetes-based Event-Driven Autoscaling) is an open-source project built to provide event-driven autoscaling capabilities for Kubernetes workloads

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Github
Documentation

Stars

7643

Fork

961

Open Issues

217

Closed Issues

1829

Open PRs

26

Closed PRs

2742

Summary

KEDA (Kubernetes-based Event-Driven Autoscaling) is a powerful tool designed to enable event-driven autoscaling for Kubernetes applications. It seamlessly integrates with various event sources, such as Azure Queue, Kafka, and Prometheus, allowing applications to dynamically scale based on real-time events. With KEDA, developers can efficiently manage resource utilization, improve application performance, and optimize costs by automatically adjusting the number of instances based on workload demands, ensuring optimal performance and responsiveness.

Key Features

  • Scales Kubernetes workloads dynamically based on various event sources, such as Azure Queue, Kafka, and Prometheus.
  • Supports both horizontal and vertical scaling of application instances to meet changing workload demands.
  • Automatically adjusts the number of instances based on workload requirements, optimizing resource utilization and cost efficiency.
  • Offers an architecture for adding custom event sources and scaling strategies, providing flexibility to tailor autoscaling behavior according to specific use cases.

How does it work?

Real world example

Pros

  • Enables efficient autoscaling of Kubernetes workloads based on real-time events, ensuring optimal performance and resource utilization.
  • Helps reduce cloud costs by automatically adjusting the number of instances based on workload demands, ensuring optimal resource allocation.
  • Offers extensible architecture for adding custom event sources and scaling strategies, enhancing flexibility and customization options.

Cons

  • Setting up and configuring KEDA for specific use cases may require understanding of Kubernetes and event source configurations.
  • Requires monitoring of event sources and workload metrics to ensure effective autoscaling, which may add operational overhead.

Deployment Activity

Related Tools

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Capillary reduced ops tickets by 95%

“Our releases are fast. And with less developer time needed our teams can focus on building exciting features. We’ve saved countless hours and costs.”

Piyush K,
Chief Architect, Capillary Technologies,

Treebo reduced production issues by 70%

"With Facets, our staging environments look identical to production environments. So in case of production issues, we can be sure there are no infra drifts."

Kadam Jeet Jain,
Co-Founder & CTO, Treebo Hotels and Hotel Superhero.

GGX switched from AWS to GCP in 2 weeks

"Facets has radically changed our DevOps for the better. They did all the heavy lifting and saved us precious time and resources in our when we switched from AWS to GCP."

Kaustubh Bhoyar,
Head of engineering, GGX

Trusted by companies to run production at scale

Capillary | FacetsMPL | FacetsTreebo | FacetsPurplle | Facets

Get in touch with us

Tell us your queries and we’ll get back to you

Prefer email? Reach out to us at info@facets.cloud