Problem Summary:
Finding the right high availability option can be difficult. Which choice is right for you can depend on the following:
- Budget – first and foremost, can you afford the HA solution you are looking for?
- Needs – what are the business requirements? Service Level Agreement (SLA), Recovery Time Objective (RTO), and Recovery Point Objective (RPO)?
- Hardware – what IT infrastructure you have to support the desired solution?
- SQL Server Version – Depending on which version of SQL you are running will determine what options are available.
- Level of Automation – Does the solution require a seamless failover?
- Skillset Of Your Team – What expertise is there within your team to implement and support a solution?
Given the number of options available, it may make you unsure which implementation will meet your business’s needs.
Red9 created the solution below for a customer who would like to use Windows Failover Clustering, taking advantage of the existing resources.
With this option:
- Have a HA/DR solution.
- Maximize the hardware usage where you have the two nodes in use Active/Active, instead of having passive hardware.
- Remove the 3rd server used for reporting; this can reduce cost.
- Have the reports running separated from your OLTP instance (SQLPROD1). Keep SQL Server using standard edition, reducing the costs from an enterprise edition.
Single point of failure
The storage is a single point of failure; if something happens to the shared storage, the SQL Server will not be available.
The good news is that the client’s storage team addressed this.
Conclusion
Understanding each technology’s strengths and weaknesses will help you design the best overall solution for your organization.
There are many other factors to consider: Backup methodologies, cloud strategies, virtualization techniques, different licensing price points, RTO, RPO, and much more!
Bring your data to Red9 and ensure that your SQL Server infrastructure on-premise or on cloud is deployed in an optimal way for your needs.
See more SQL Server Performance Optimization examples here.
