Automatic Scaling Within and Across Servers
Jelastic dynamically allocates granular units of resource to applications called “Cloudlets”. Each cloudlet represents 128MB RAM and 200MHz CPU.
The minimum and maximum amount of resources that the application can consume is set by the user via the user interface or API.
Jelastic automatically scales resources up and down within a single server or across multiple servers based on the application load.
Save Resources and Money
Jelastic’s fully elastic scalability means that server utilization is significantly increased, with at least 30% improvements in density. Jelastic users have saved up to 73% of server resources and cost when compared to solutions that allocate fixed VMs or large blocks of resource.
Improved Server Density
Automatic Vertical Scaling
Jelastic is the only cloud platform which can automatically vertically scale any application. This is made possible by Jelastic’s ability to change the amount of resources (RAM and CPU) provided to a server.
If an application’s load increases, Jelastic simply makes additional resources available to it. If the load is reduced, the platform automatically re-allocates unused resources to the cloud.
Jelastic measures resources in cloudlets. A cloudlet is roughly equivalent to 128 MB RAM and 200Mhz CPU core. Cloudlets are allocated and de-allocated to the application dependent upon:
- the application resource demand
- the minimum and maximum resource limits defined by the user
Jelastic’s unique container-based management technology provides maximum application density and saves considerable resources when compared to solutions that allocate VMs or large chunks of RAM/CPU to applications “just in case”.
Applications can be pre-configured to scale across multiple servers via the user interface. When additional server nodes are defined, load balancers are automatically configured and activated to distribute the application load.
Application instances can be configured for maximum performance and availability using horizontal scaling.