High Elasticity in Azure is similar to High Scalability in that it is designed to increase or decrease system capacity based on the current workload placed on the system. The key point to understand about High Elasticity is that it is Automatic. Elasticity is also referred to cloud elasticity or elastic computing. Elastic computing makes it possible to expand or decrease computer processing, memory, and storage with no human interventions. It is automatic.
How High Elasticity Works
With high elasticity you might have a Virtual Machine running and if the demands begin to overcome that server, the high elasticity service begins to add new Virtual Machines of the same type to meet the demand. What did we learn about adding more servers of the same type and size? That’s right, we call that Horizontal Scaling. Specifically, if we are Scaling Out, then more servers of the same size are being added to the system. Scaling In would mean that peak demand has passed, and the extra server(s) of the same size can now be removed.
Horizontal Scaling is the means by which high elasticity is achieved. In general, you don’t want to use Vertical Scaling since it is difficult for traditional architecture to handle especially with regard to storage drives where if the sizing is changed on the drive you could lose data as the scaling takes place.
Azure VM Scale Sets
One way to implement high elasticity in Azure is with the use of Virtual Machine Scale Sets. VM Scale Sets make it possible to deploy and manage a collection of virtual machines that work with a load balancer. Then, the actual number of Virtual Machines in that scale set can dynamically and automatically increase or decrease based on demand thus fulfilling the High Elasticity paradigm. Scale sets work well with compute, containerization, and even big data applications.
High Elasticity Use Cases
Implementing high elasticity with scale sets in Azure provides redundancy and better performance. Load Balancing makes sure that requests are distributed evenly across active VM instances in the scale set. Should there be a need to complete an update on an instance or perform maintenance, then the load balancing ensures service is not interrupted as those requests go to a different instance during any maintenance period. Scale Sets offer:
- High Availability and Resiliency
- Effective Even At Large Scale
- Scaling Is Automatic
- Easy To Manage Several Virtual Machines
SQL Server Stretch Database
The SQL Server Stretch Database service is another example of high elasticity in Microsoft Azure. It works in conjunction with Microsoft SQL Server to offer high elasticity by stretching warm and cold transactional data across SQL Server and Azure. This service provides the ability to have longer data retention times at lower costs to the business. Data can move without query changes with advanced security options. SQL Server Stretch Database streamlines data maintenance and is easy to manage.
Learn More About Microsoft Azure High Elasticity
- What Is Cloud Elasticity (blog.iron.io)
- What Is Elasticity And How Does It Affect Cloud Computing (solutionsreview.com)
- Cloud Elasticity Concepts (cloudzero.com)
- Glossary Content Cloud Elasticity (vmware.com)
- Cloud Computing Elasticity Vs Scalability (theappsolutions.com)
- Cloud Computing and Cloud Elasticity (jigsawacademy.com)
- Cloud Concepts Scalability And Elasticity (skylinesacademy.com)
- What Is Elastic Computing (azure.microsoft.com)
