QoS is an end-to-end problem. For application-originated IO, the same level of service needs to be delivered at various levels of the IO stack (guestOS, hypervisor, network, storage). Typically, storage appliances are unaware of VMs, but Tintri is an exception. Because of Tintri’s tight integration with hypervisor environments like VMware, Hyper-V, etc., the Tintri file…
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By monitoring IO requests at the vDisk and VM level and integrating with vCenter APIs, Tintri VMstore knows the identity of the corresponding VM for each IO request, and can determine if latency occurs at the hypervisor, network, or storage levels. For each VM and vDisk stored on the system, IT teams can use Tintri…
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Another axis of thinking about performance is managed performance. This is different from the highest raw performance one can extract from a storage system. Given a fixed amount of performance that a storage system can produce, how should this performance be shared between the many applications (VMS) running on it? Not all applications have the…
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The first generation of commodity SSDs was at least two orders of magnitude faster than HDDs for random reads. But they were not without problems; the random write case was more complex. The random write performance was not as good and had latency spike issues that the SSD FTL took many generations to improve. Even…
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Having an end-to-end view into the performance of individual VMs can be tremendously helpful in virtualized environments. In this chapter, we’ll discuss the challenges IT faces in pinpointing performance issues, and how Tintri VMstore and Tintri Global Center deliver deep insight into utilization and performance, helping IT detect trends and enhance troubleshooting.