Real-Time Continuous Kubernetes & Containers Optimization

Autonomous, Application Driven Orchestrated Workload Optimization

Harness automation and OS-level resource management optimization to simplify and improve Kubernetes performance at scale

Reduce
Costs By

60%

Reduce
Response
Time By

40%

Increased
Throughput

5X

Code
Changes

0

Automated Full Stack Optimized Containers and Pods

Granulate is pioneering real-time continuous optimization in dynamic containerized or Kubernetes environments. Leveraging continuous OS-level adaptations, Granulate creates a streamlined environment, improving performance and reducing costs.

Technology Stack

Real Time Continuous Optimization

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Easily Deploy and Optimize Any Environment

Native deployment of Granulate agents as a side car based on DaemonSet, docker image, or any other provisioning method in self managed or managed service such as OpenShift, EKS, ECS, AKS, ACS, GKE.

Simple Installation

Deploy Granulate agents using a DaemonSet in less than a minute

Single Agents

All in-one container and kubernetes optimization for any application

Zero Maintenance

Fully automated application-driven resource management optimization

No Code Changes

Optimization of the operating system resource management without any code changes

Quick Time To Value

Enjoy better container or pod performance and reduce the amount of resources they need

3 Steps, One Week For 60% Cost And Performance Optimization

Install

15 Minutes

Start a limited free trial of Granulate

Free Trial

Evaluate

1 Week

Sit back and watch Granulate autonomously learn the application and specific workload

Deploy

15 Minutes

Activate Granulate and be amazed, start experiencing performance improvements you didn’t think were possible.

Kubernetes and Container Environments

Granulate seamlessly integrates with highly dynamic microservices environments. Integrating Granulate’s agents to the CI/CD process ensures the very workload and microservice you deploy is automatically optimized.
  • Continuous automatic learning of microservices and containers with no code or image changes required.
  • Autonomous performance optimizations of the operating system for the running containers or pods with zero manual efforts required.
  • Ensure applications/services are performing optimally in the context of end user experience.
  • Go beyond the native provisioning and placement optimization decisions by optimizing the pods and containers interaction with the operating systems resources.

Kubernetes and Container Native
Application-Driven Optimization

Workload Driven Resource Management

Real-time continuous operating system resource management adaptations to squeeze the best performance for each workload

 

Better
SLA

Enjoy improved performance by streamlining and solving resource contentions for each container and pod

Minimize
Costs

Native support for elastic environments, continue scaling based on existing policies with significantly less compute resources

See How It Works