In today’s production data center, networked storage is at the center of everything, and it is one of the critical elements to consider when rolling out applications on VMware or any other platform. In development and test environments, VMware applications are typically run with local disk or direct-attached RAID storage. In production data centers, Virtual Machines (VMs) need to work with enterprise-class SAN or NAS — an infrastructure that is shared across a range of applications and workloads. Storage is ultimately about input/output (I/O), and it is important to make sure that the I/O workloads that are required by the server domain can be handled by all of the elements of the storage domain, including the host bus adapter (HBA), storage fabric and the storage array. One of the main causes of poor performance in both virtualized and traditional server environments is a mismatch between the front-end and the back-end. Frequently, contention for shared storage resources such as RAID groups causes I/O bottlenecks that result in queuing backlogs and poor end-to-end response time. Ultimately, this impacts the business application and the end-user. In a virtual world, this scenario is more complex. While it may be possible to run more virtual machines on a given server, it is also possible to go too far and overload the storage layer, resulting in negative unintended consequences. One of the most important things to understand is that enterprise storage is increasingly virtualized along with servers; as it is also a pooled, shared resource. A key to ensuring VMware application success in these environments is making sure that front-end workloads are matched to back-end storage capabilities, and to monitor these relationships consistently.
Best Practices
Here are five best practices for ensuring successful VMware projects on enterprise-class storage:
- Establish a “cross-domain” management orientation.
- Use “infrastructure response time” as a key metric.
- When there are VMware performance issues that are difficult to diagnose, look for contention and contention-based latency in the storage layer.
- Strive for “best fit” of workloads to storage resources.
- Work toward infrastructure performance service-level agreements (SLAs).
See what Tom, VP Akkori, has to say about those steps.
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