Blogging about open source virtualization. Collecting benchmark results is the first step to solving disk IO performance problems. Unfortunately, many bug reports and performance investigations fall down at the first step because bogus benchmark data is collected. This post explains common mistakes when running disk IO benchmarks. Disk IO patterns. Skip this section if you are already familiar with these terms. Before we begin, it is important to understand the different IO patterns and how they are used in benchmarking. Sequential vs random IO is the access pattern in which data is read or written. Sequential IO is in order data access commonly found in workloads like streaming multimedia or writing log files. Random IO is access of non adjacent data commonly found when accessing many small files or on systems running multiple applications that access the disk at the same time. It is easy to prefetch sequential IO so both disk read caches and operating system page caches may keep the next piece of data ready even before it is accessed. Random IO does not offer opportunities for prefetching and is therefore a harder access pattern to optimize. Block or request size is the amount of data transferred by a single access. Small request sizes are 5. B through 4 KB, large request sizes are 6. KB through 1. 28 KB, while very large request sizes could be 1 MB although the maximum allowed request size ultimately depends on the hardware. Fewer requests are needed to transfer the same amount of data when the request size is larger. Therefore, throughput is usually higher at larger request sizes because less per request overhead is incurred for the same amount of data. Read vs write is the request type that determines whether data is transferred to or from the storage medium. Reads can be completed cheaply if data is already in the disk read cache and, failing that, the access time depends on the storage medium. Traditional spinning disks have significant average seek times in the range of 4 1. Writes can be completed cheaply by leaving data in the disk write cache unless the cache is full or the cache is disabled. Queue depth is the number of in flight IO requests at a given time. Latency sensitive workloads submit one request and wait for it to complete before submitting the next request. Wireshark tutorial learn one of the most important tool every programmer and network admin should know. Once you install Wireshark CLI tools, you can start using editcap and mergecap tools. Filter a Pcap File. Permission is granted to copy, distribute andor modify this document under the terms of the GNU General Public License, Version 2 or any later version. The Wireshark Certification Program strives to test a candidates knowledge and ability to troubleshoot, optimize and secure a network based on evidence found by. I set up a virtual PC to capture the IP address of a scammer then used this IP address to identify the people behind the scam. Sorry for the abrupt ending. This is queue depth 1. Parallel workloads submit many requests without waiting for earlier requests to complete first. The maximum queue depth depends on the hardware with 6. Maximum throughput is usually achieved when queue depth is fairly high because the disk can keep busy without waiting for the next request to be submitted and it may optimize the order in which requests are processed. Random reads are a good way to force storage medium access and minimize cache hit rates. The only authorized Lab Manual for the Cisco Networking Academy Introduction to Networks course in the CCNA Routing and Switching curriculum Introduction to Networks. I hope I selected the correct topics. I have about 10GB of WireShark PCaP capture files. Reason I did the capture, the developers where pointing out to. Security Analyst, Cognitive Psychology PhD Researcher, Author, and BBQ Pit Master. There are some simple ways to check the connection performance between Office 365 and your business that will let you establish a rough baseline of your connectivity. Wireshark Compare Capture Files' title='Wireshark Compare Capture Files' />Sequentual reads are a good way to maximize cache hit rates. Fn 1905 Serial Numbers. Which IO pattern is appropriate depends on your goals. Real life workloads are usually a mixture of sequential vs random, block sizes, reads vs writes, and the queue depth may vary over time. It is simplest to benchmark a specific IO pattern in isolation but benchmark tools can also be configured to produce mixed IO patterns like 7. The goal when configuring a benchmark is to produce the IO pattern that is critical for real life workload performance. Use a real benchmarking tool. It is often tempting to use file utilities instead of real benchmarking tools because file utilities report IO throughput like real benchmarking tools and time taken can be easily measured. Therefore it might seem like there is no need to install a real benchmarking tool when file utilities are already available on every system. Do not use cp1, scp1, or even dd1. Instead, use a real benchmark like fio1. Whats the difference Real benchmarking tools can be configured to produce specific IO patterns, like 4 KB random reads with queue depth 8, whereas file utilities offer limited or no ability to choose the IO pattern. Since disk performance varies depending on the IO pattern, it is hard to understand or compare results between systems without full control over the IO pattern. KB/searchArticle!viewBlob.action?attOid=8629' alt='Wireshark Compare Capture Files' title='Wireshark Compare Capture Files' />The second reason why real benchmarking tools are necessary is that file utilities are not designed to exercise the disk, they are designed to manipulate files. This means file utilities spend time doing things that does not involve disk IO and therefore produces misleading performance results. The most important example of this is that file utilities use the operating systems page cache and this can result in no disk IO activity at all Bypass the page cache. One of the most common mistakes is forgetting to bypass the operating systems page cache. Files and block devices opened with the ODIRECT flag perform IO to the disk without going through the page cache. This is the best way to guarantee that the disk actually gets IO requests. Files opened without this flag are in buffered IO mode and that means IO may be fulfilled entirely within the page cache in RAM without any disk IO activity. If the goal is to benchmark disk performance then the page cache needs to be eliminated. It is not sufficient to echo 3 procsysvmdropcaches before running the benchmark instead of using ODIRECT. Although this command is often used to make non disk benchmarks produce more consistent results between runs, it does not guarantee that the disk will actually receive IO requests. In addition, the page cache interferes with the desired benchmark IO pattern since page cache prefetch and writeback will alter the actual IO pattern that the disk sees. Bypass file systems and device mapperfio1 can do both file IO and disk IO benchmarking, so its often mistakenly used in file IO mode instead of disk IO mode. When benchmarking disk performance it is best to eliminate file systems and device mapper targets to isolate raw disk IO performance. File systems and device mapper targets may have their own internal bottlenecks, such as software locks, that are unrelated to disk performance. File systems and device mapper targets are also likely to modify the IO pattern because they submit their own metadata IO. IO benchmarking. Without a block device filename parameter, the benchmark would create regular files on whatever file system is in use. Remember to double and triple check the block device filename before running benchmarks that write to the disk to avoid accidentally overwriting important data like the system root disk Example benchmark configurations. Here are a few example fio1 jobs that you can use as a starting point. High throughput parallel reads. This job is a read heavy workload with lots of parallelism that is likely to show off the devices best throughput globalfilenamepathtodeviceruntime1. Latency sensitive random reads. This job is a latency sensitive workload that stresses per request overhead and seek times globalfilenamepathtodeviceruntime1. Warcraft Ii Battle Net Edition Keygen Generator. Mixed workload. This job simulates a more real life workload with an IO pattern that contains boths reads and writes globalfilenamepathtodeviceruntime1. Conclusion. There are several common issues with disk benchmarking that can lead to useless results. Using a real benchmarking tool and bypassing the page cache and file system are the basic requirements for useful disk benchmark results. If you have questions or suggestions about disk benchmarking, feel free to post a comment.