Kazuhm
Unify your company's existing compute resources including desktops, servers, cloud, and Edge devices, to run containerized workloads, save cloud costs, reduce latency, and improve performance. Set up Kubernetes clusters with a few clicks.
Cost / License
- Freemium (Subscription)
- Proprietary
Platforms
- Online
- Software as a Service (SaaS)
Kazuhm
Features
- Low Latency
- Distributed Computing
- Data science
Tags
- enterprise-kubernetes
- Containers
- workload-management
- hybrid-cloud
- enterprise-software
- saas-for-business
- DevOps
Kazuhm News & Activities
Recent activities
Kazuhm information
Developed by
Kazuhm Licensing
Proprietary and Freemium product.Pricing
Subscription that costs up to $500 per month + free version with limited functionality.Alternatives
0 alternatives listedSupported Languages
- English
What is Kazuhm?
Kazuhm revolutionizes how companies process workloads through a new type of distributed computing technology. The Kazuhm SaaS platform unifies the compute resources of an organization from desktops, to servers, to cloud, to edge, creating a private grid where containerized workloads can be intelligently placed and processed to optimize IT costs, security, and performance.
Through an easy user interface, customers leverage Kazuhm today to simplify Kubernetes, build their own private distributed compute networks, run workloads on-premises enabling the lowest possible latency, and easily manage multi-cloud and hybrid cloud environments.
Sign up for the base platform for free at https://blog.kazuhm.com/free-signup
Features and Benefits:
Container Orchestration --- Kubernetes-Made-Easy means deployment is super quick with container placement and host monitoring intuitively simple.
Multi-Cloud, Hybrid-Cloud Management --- Escape from vendor lock-in and centrally manage all your Public Cloud Hosts for FREE.
Offset Cloud Costs --- Get “Cloud Smart”. Process containerized workloads on your Linux and Windows desktops and servers to offset cloud costs.
Data Science Anywhere --- Simplify deployment of Spark and Jupyter and process workloads both on-premise and in the cloud.
Low-Latency Workload Processing --- Reduce latency and improve performance by processing your data on-premise or at the edge – when milliseconds count.
Distributed Computing Anywhere --- Connect your desktops – Windows and Linux – and servers or even your edge devices to create a powerful compute fabric.