Dynamic Scalability (Erl, Naserpour)
How can IT resources be scaled automatically in response to fluctuating demand?
ProblemIt is challenging to equip an IT resource to match its processing requirements. If the demand for the IT resource is below its capacity, then it is under-utilized and if the demand is above its capacity it is over-utilized or unable to meet the demand.
SolutionThe IT resource can be integrated with a reactive cloud architecture capable of automatically scaling it horizontally or vertically in response to fluctuating demand.
ApplicationDynamic horizontal scaling can be enabled via the use of pools of identical IT resources and components capable of dispersing and retracting workloads across each pool. Dynamic vertical scaling can be enabled via technology capable of swapping IT resource components at runtime.
MechanismsAutomated Scaling Listener, Cloud Storage Device, Cloud Usage Monitor, Hypervisor, Pay-Per-Use Monitor, Resource Replication, Virtual Server
Compound PatternsBurst In, Burst Out to Private Cloud, Burst Out to Public Cloud, Cloud Authentication, Elastic Environment, Infrastructure-as-a-Service (IaaS), Isolated Trust Boundary, Multitenant Environment, Platform-as-a-Service (PaaS), Private Cloud, Public Cloud, Resilient Environment, Resource Workload Management, Secure Burst Out to Private Cloud/Public Cloud, Software-as-a-Service (SaaS)
A sample dynamic scaling process.
An example of a dynamic scaling architecture involving an automated scaling mechanism (Part I).
An example of a dynamic scaling architecture involving an automated scaling mechanism (Part II).
An example of a dynamic scaling architecture involving an automated scaling mechanism (Part III).
NIST Reference Architecture Mapping
This pattern relates to the highlighted parts of the NIST reference architecture, as follows: