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To optimize a virtual database server, incorporate tools that enable you to monitor system performance and react to issues quickly.
Virtual database servers offer numerous advantages, but there's also a risk of them consuming large amounts of resources from the extensive use of storage and disproportionate file access traffic. If you've set up a virtual database server and deployed it in a VM, integrate monitoring tools to ensure its performance remains optimal.
Monitoring your virtual database server enables you to gather information on system performance and detect performance issues, such as memory or processor overcommitment, and network or I/O bottlenecks. Using alerts ensures you receive warnings about an issue before or as soon as it arises, and they might enable you to address and remediate issues before users even notice them.
You should avoid overcommitting VM memory or processors to ensure optimal performance of a virtual database server. You should also keep process counts low to keep a VM from using too many resources.
One way to keep database processes low is to have a few other VMs running on important virtual database servers. Another way to keep database processes low is to install guest OSs from scratch instead of converting them. This ensures there are no processes left over that are only necessary in physical environments.
Overcommitting memory could lead to potential performance issues such as increased CPU wait times, latency or application issues. For example, memory-sensitive services such as SQL VMs have this issue. SQL servers tend to be resource-intensive, so you shouldn't make them compete for resources with other VMs. One way to avoid this is to host a virtual SQL VM in a different server.
Using a monitoring tool can enable you to monitor virtual database server processor usage and memory so you can add or adjust resources in the database VMs as necessary. Reallocating data to higher-tier, better-performing storage might help with throughput, as well as latency performance issues.
The appearance of bottlenecks could be related to network usage between databases, storage or client-based systems. You can combine multiple network connections -- a process known as adapter teaming -- to increase network throughput.
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