[Cloud Computing]Patterns: Intra-Storage Device Vertical Data Tiering

Intra-Storage Device Vertical Data Tiering (Erl, Naserpour)

How can the dynamic vertical scaling of data be carried out within a storage device?

Problem

When required to maintain data within a single cloud storage device, the storage and processing capacity of the data will be limited to that of the device.

Solution

A cloud storage device capable of supporting multiple disk types is used to enable dynamic vertical scaling confined to the device.

Application

Complex cloud storage technology is utilized to establish storage tiers through which data can be scaled up or down via LUN migration.

Mechanisms

Automated Scaling Listener, Cloud
Storage Device, Cloud Usage Monitor, Pay-Per-Use
Monitor

Compound Patterns

Burst 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 conventional horizontal scaling system involving two cloud storage devices (1, 2) is transitioned to an intra-storage device system (3) capable of vertically scaling through disk types graded into different tiers
(4). Each LUN is moved to a tier that corresponds to its processing and storage requirements (5).


An intra-device cloud storage architecture resulting from the application of this pattern (Part I).


An intra-device cloud storage architecture resulting from the application of this pattern (Part II).


An intra-device cloud storage architecture resulting from the application of this pattern (Part III).

NIST Reference Architecture Mapping

This pattern relates to the highlighted parts of the NIST reference architecture, as follows: