The worldwide abbreviation for Fahrenheit. Usually used when there is a guest speaker.
Understanding the storage architecture in a virtualized environment and getting your storage architecture right will have a major impact on your database performance and the success of your SQL Server virtualization project. However, if you have bad code and bad queries, we will make them run as fast as possible.
This chapter first covers the key aspects of storage architecture relevant to both physical and virtual environments as well as the differences you need to understand when architecting storage, specifically for virtualized SQL Server Databases.
We provide guidance on what our experience has taught us are important database storage design principles. We present a top-down approach covering SQL Server Database and Guest OS Design, Virtual Machine Template Design, followed by VMware vSphere Hypervisor Storage Design and then down to the physical storage layers, including using server-side flash acceleration technology to increase performance and provide greater return on investment.
Throughout this chapter, we give you architecture examples based on real-world projects that you can adapt for your purposes. When designing your storage architecture for SQL Server, you need to clearly understand the requirements and have quantitative rather than subjective metrics.
Our experience has taught us to make decisions based on fact and not gut feeling. You will need to benchmark and baseline your storage performance to clearly understand what is achievable from your design.
In this chapter, we discuss some of the important storage system component performance aspects that will feed into your benchmarking and baselining activities. These will help guide your design decisions and help you achieve acceptable performance both now and in the future.
These principles are important because over the past decade, CPU performance has increased at a much faster pace than storage performance, even while capacity has exploded. Your database is just an extension of your storage The first principle is highlighted in Figure 6.
A database is designed to efficiently and quickly organize, retrieve, and process large quantities of data to and from storage.
So increasing the parallelism of access to storage resources at low latency will be an important goal. Later in this chapter, we cover how to optimize the architecture of your database to maximize its storage performance and parallelism.
Performance is more than underlying storage devices The next key principle is that storage performance is more than just about underlying storage devices and spindles, although they are very important too. SQL Server storage performance is multidimensional and is tightly coupled with a number of different system components, such as the number of data files allocated to the database, the number of allocated vCPUs, and the amount of memory allocated to the database.
This interplay between resources such as CPU, Memory, and Network and their impact on storage architecture and performance will be covered in subsequent sections of this chapter. Size for performance before capacity Figure 6. Both quotes are extremely relevant to SQL Server database and storage performance.
In order to prevent poor performance from being a factor in your SQL Server virtualization project refer to Figure 6. Capacity is the easy part. We will show you later in this chapter how compromising on certain storage configurations on the surface can actually cost you a lot more by causing unusable capacity due to poor performance.
We were working with a customer, and they wanted to design and run a database on vSphere that could support sustained 20, IOPS. We are 19, short of where we need to be.
Playing the odds, we started with the disk subsystem. We quickly identified some issues. The main issue was the customer purchased for capacity, not performance.
They had to reorder the right disk. Once the new right disk arrived and was configured, the customer exceeded the 20, IOPS requirement. Virtualize, but without compromise The next principle is that virtualizing business-critical SQL Server databases is all about reducing risk and not compromising on SLAs.
Virtualize, but without compromise. There is no need to compromise on predictability of performance, quality of service, availability, manageability, or response times. Your storage architecture plays a big part in ensuring your SQL databases will perform as expected.
As we said earlier, your database is just an extension of your storage.
We will show you how to optimize your storage design for manageability without compromising its performance.
Believe it or not, as big of advocates as we are about virtualizing SQL Server, we have told customers in meetings that now is not the right time for this database to be virtualized.
This has nothing to do with the capability of vSphere or virtualization, but more to do with the ability of the organization to properly operate critical SQL systems and virtualize them successfully, or because they are not able or willing to invest appropriately to make the project a success.
Understand, document, and ensure requirements can be met through good design and followed by testing and validation.
Having a standardized and simplified design will allow your environment and databases to be more manageable as the numbers scale while maintaining acceptable performance see Principle 4.A dashboard using Telegraf and the Windows Performance Counters to display windows performance metrics.
The MySQL server maintains many system variables that configure its operation. Each system variable has a default value. System variables can be set at server startup using options on the command line or in an option file. Physical Disk: % Disk Time—Disk Time is the percentage of elapsed time that the selected disk drive is busy servicing read or write requests.
In other words, this counter provides an indication of how busy your disk subsystem is over the time period that you're measuring in PerfMon. Hi Noa. Sorry for the direct approach.. A quick question again, if I may. I'm trying to find the Avg.
Disk sec/Write and Avg. Disk sec/Read on disks in azure using log analytics, but I keep getting errors. The pictures below show an total average disk Read Queue length of around queued IOs with an average response time of about 1 millisecond each, which means pending IO values could be as high as milliseconds on a SQL database file level.
An Easy Fix for Your Slow VM Performance Explained. By Lauren @ Raxco • Mar 12, Latency problems arise when the sheer volume of disk I/O exceeds the ability of the read/write heads to respond in an acceptable time. The net effect is the elimination of disk latency issues and any queue contention.
When this unnecessary workload is.