{"id":75577,"date":"2020-03-27T07:42:08","date_gmt":"2020-03-27T05:42:08","guid":{"rendered":"https:\/\/prohoster.info\/blog\/administrirovanie\/fast-vp-v-shd-unity-kak-eto-rabotaet"},"modified":"2020-03-27T07:42:08","modified_gmt":"2020-03-27T05:42:08","slug":"fast-vp-v-shd-unity-kak-eto-rabotaet","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/administrirovanie\/fast-vp-v-shd-unity-kak-eto-rabotaet","title":{"rendered":"FAST VP in Unity SAN: How it works.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"<p>Today we're going to talk about an interesting technology implemented in the Unity\/Unity XT storage system \u2013 FAST VP. If you're hearing about Unity for the first time, you can find specifications for the system at the link at the end of the article. I worked on FAST VP for over a year as part of the Dell EMC project team. Today, I want to discuss this technology in more detail and reveal some details of its implementation, of course, only those that are permitted to be disclosed. If you're interested in efficient data storage or just haven't fully understood the documentation, this article will surely be useful and interesting. <\/p>\n<p><img decoding=\"async\" alt=\"FAST VP in Unity SAN: How it works.\" src=\"\/wp-content\/uploads\/2020\/03\/1f026bfb90e0b050da5222cebf537be7.jpeg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<noindex><a rel=\"nofollow\" name=\"habracut\"><\/a><\/noindex><br \/>\nLet me be clear about what this material will not cover. There will be no competitor analysis or comparisons with them. I also don't plan to discuss similar technologies from open source, because any curious reader is already aware of them. And of course, I have no intention of advertising anything.<\/p>\n<h2>Storage Tiering. Goals and Objectives of FAST VP<\/h2>\n<p>\nFAST VP stands for Fully Automated Storage Tiering for Virtual Pool. Sounds complicated? Don't worry, we'll break it down. Tiering is a method of organizing data storage, where there are multiple levels (tiers) at which this data is stored. Each has its own characteristics. The most important ones are: performance, capacity, and the cost of storing a unit of information. Naturally, there's a relationship among them.<\/p>\n<p>An important feature of tiering is that access to data is provided uniformly regardless of the storage level at which it currently resides, while the size of the pool equals the sum of the sizes of the resources it contains. This highlights the differences from caching: the size of the cache does not add to the overall resource volume (the pool in this case), and cached data replicates some fragment of data from the primary storage (or will replicate when the data from the cache has not been written yet). Also, the distribution of data across levels is hidden from the user. In other words, they do not see which specific data resides at each level, although they can indirectly influence this by defining policies (more on that later).<\/p>\n<p>Now let's look at the implementation features of storage tiering in Unity. Unity distinguishes 3 levels or tiers:<\/p>\n<ul>\n<li>Extreme performance (SSDs)<\/li>\n<li>Performance (SAS HDD 10k\/15k RPM)<\/li>\n<li>Capacity (NL-SAS HDD 7200 RPM)<\/li>\n<\/ul>\n<p>\nThey are listed in order of decreasing performance and price. Extreme performance includes only solid-state drives (SSD). The other two tiers consist of magnetic drives, differing in rotation speed and, consequently, performance.<\/p>\n<p>Data storage devices of the same level and size are combined into a RAID array, forming a RAID group; you can read about available and recommended RAID levels in the official documentation. From RAID groups of one or several levels, storage pools are formed, from which free space is then allocated. A portion of this pool is dedicated to file systems and LUNs.<\/p>\n<p><img decoding=\"async\" alt=\"FAST VP in Unity SAN: How it works.\" src=\"\/wp-content\/uploads\/2020\/03\/00591e7155982ba216b490d3d7214f4c.jpeg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<\/p>\n<h2>Why do I need Tiering?<\/h2>\n<p>\nIn short and abstract: <i>to achieve a greater result using minimal resources.<\/i> More specifically, the result typically refers to the set of characteristics of the storage system \u2014 speed and access time, cost of storage, and others. The minimal resources imply the lowest costs: money, energy, and so on. FAST VP implements mechanisms for redistributing data across different tiers in the Unity\/Unity XT storage systems. If you believe me, you can skip the next paragraph. For others, I'll explain in a bit more detail.<\/p>\n<p>Proper data distribution across storage tiers allows for savings on the overall cost of the storage system, sacrificing access speed to some rarely used information, while enhancing performance by shifting frequently used data to faster devices. Some may argue that even without tiering, a competent admin knows where to place certain data, what storage characteristics are desired for their task, etc. This is undoubtedly true, but manual data distribution has its drawbacks:<\/p>\n<ul>\n<li>it requires time and attention from the administrator; <\/li>\n<li>it is not always possible to \"reshuffle\" storage resources under changing conditions;<\/li>\n<li>it loses an important advantage: unified access to resources located across different storage tiers. <\/li>\n<\/ul>\n<p>\nTo alleviate storage admins\u2019 concerns about job security, I'll add that proper resource planning is essential here as well. Now that the tasks of tiering have been briefly outlined, let's see what to expect from FAST VP. This is the perfect time to return to the definition. The first two words - Fully Automated - translate literally as \"fully automated\" and mean that the tiering process occurs automatically. The term Virtual Pool refers to a pool of data that incorporates resources from different storage tiers. Here's how it looks:<\/p>\n<p><img decoding=\"async\" alt=\"FAST VP in Unity SAN: How it works.\" src=\"\/wp-content\/uploads\/2020\/03\/75259df2b7f65ad9707c1199dd88f7f6.jpeg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nTo get ahead of myself, FAST VP moves data only within a single pool, not between multiple pools. <\/p>\n<h2>Tasks addressed by FAST VP<\/h2>\n<p>\nFirst, let's talk abstractly. We have a pool and some mechanism that can redistribute data within this pool. Keeping in mind our goal of achieving maximum performance, let's ask ourselves: what are the ways to achieve it? There can be several, and FAST VP has much to offer the user, as the technology is more than just storage tiering. Here are the ways FAST VP can enhance the performance of the pool:<\/p>\n<ul>\n<li>Data distribution across different types of disks and tiers<\/li>\n<li>Data distribution among disks of the same type<\/li>\n<li>Data distribution during pool expansion<\/li>\n<\/ul>\n<p>\nBefore we discuss how these tasks are solved, we need to know some essential facts about the operation of FAST VP. FAST VP operates with blocks of a specific size \u2013 256 megabytes. This is the minimum continuous \"chunk\" of data that can be moved. In the documentation, it's referred to as a slice. From FAST VP's perspective, all RAID groups consist of a set of such \"chunks.\" Accordingly, all input-output statistics are accumulated for these data blocks. Why was this block size chosen, and will it be reduced? The block is large enough, but it strikes a compromise between data granularity (a smaller block size leads to more precise distribution) and the available computing resources: given the existing tight memory constraints and the large number of blocks, the statistics can take up too much space, and the number of calculations will grow proportionally.<\/p>\n<h2>How FAST VP allocates data within the pool. Policies<\/h2>\n<p>\nTo manage data placement in a pool with FAST VP enabled, the following policies exist:<\/p>\n<ul>\n<li>Highest Available Tier<\/li>\n<li>Auto-Tier<\/li>\n<li>Start High then Auto-Tier (default)<\/li>\n<li>Lowest Available Tier<\/li>\n<\/ul>\n<p>\nThey affect both the initial placement of the block (when data is first written) and subsequent redistribution. Once the data is placed on disks, redistribution will be initiated on a schedule or manually.<\/p>\n<p>Highest Available Tier attempts to place a new block at the most performant level. If there is insufficient space, it will move to the next level of performance, but later, data may be moved to a higher-performance level (if space allows or displacing other data). Auto-Tier places new data at different levels depending on the amount of available space, while redistribution occurs based on demand and available space. Start High then Auto-Tier is the default and also recommended policy. During initial placement, it operates like Highest Available Tier, and subsequently, data is moved based on its usage statistics. The Lowest Available Tier policy aims to place data at the least performant level. <\/p>\n<p>Data migration is done with low priority so as not to disrupt the useful operation of the storage system; however, there is a setting called 'Data relocation rate' that changes this priority. Here, there's a peculiarity: not all data blocks have the same queue for redistribution. For instance, blocks marked as metadata will be moved to a faster level first. Metadata, so to speak, is 'data about data', additional information that is not user data but describes it. For example, information in the file system about which block a specific file is in. This means the access speed to data depends on the access speed to metadata. Given that metadata is usually much smaller in size, the benefit from moving it to more performant disks is expected to be greater.<\/p>\n<h2>The criteria that Fast VP uses in its operation<\/h2>\n<p>\nThe main criterion for each block, if very roughly put, is the characteristic of the 'demand' for data, which depends on the number of read and write operations of a data fragment. This characteristic is referred to as 'Temperature' in our context. There are demanded (hot) data that are 'hotter' than undemanded data. It is calculated periodically, by default at one-hour intervals. <\/p>\n<p>The temperature calculation function has the following properties:<\/p>\n<ul>\n<li>In the absence of input\/output, the data 'cools down' over time.<\/li>\n<li>With a fairly consistent load over time, the temperature first increases and then stabilizes within a certain range.<\/li>\n<\/ul>\n<p>\nNext, the policies described above and the free space on each tier are taken into account. For clarity, I will provide a picture from the documentation. Here, blocks with high, medium, and low temperatures are marked in red, yellow, and blue, respectively.<\/p>\n<p><img decoding=\"async\" alt=\"FAST VP in Unity SAN: How it works.\" src=\"\/wp-content\/uploads\/2020\/03\/4815ae20d2e33a8f7f47279da0965ae0.jpeg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nBut let's return to the tasks. So, we can start analyzing what is being done to solve the FAST VP tasks.<\/p>\n<h4>A. Distribution of data across different types of disks, levels<\/h4>\n<p>\nThis is essentially the main task of FAST VP. The others, in a sense, are derivatives from it. Depending on the chosen policy, data will be distributed across different storage tiers. First and foremost, the placement policy is considered, followed by block temperature and the size\/speed of RAID groups. <\/p>\n<p>For the Highest\/Lowest Available Tier policies, everything is quite straightforward. For the other two, it works like this. Data is distributed across different levels taking into account the size and performance of RAID groups: so that the ratio of the total 'temperature' of the blocks to the 'conditional maximum performance' of each RAID group is approximately the same. Thus, the load is distributed fairly evenly. More demanded data is moved to faster storage, while rarely used data goes to slower ones. Ideally, the distribution should look something like this: <\/p>\n<p><img decoding=\"async\" alt=\"FAST VP in Unity SAN: How it works.\" src=\"\/wp-content\/uploads\/2020\/03\/08ecbdc3dbf0409ba67eaf51eed24745.jpeg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<\/p>\n<h4>B. Distribution of data among disks of the same type<\/h4>\n<p>\nRemember, in the beginning, I mentioned that storage devices from <b>one or several<\/b> How are levels combined into a single pool? In the case of a single level for FAST VP, there is also work to be done. To ensure the performance of any level is maximized, data should be evenly distributed across the disks. This theoretically allows for the maximum number of IOPS. Data within a RAID group can be considered evenly distributed among the disks, but this is not always the case between RAID groups. In the event of an imbalance, FAST VP will move data between RAID groups proportionally to their size and 'conditional performance' (in numerical terms). For clarity, here\u2019s a rebalancing scheme among three RAID groups:<\/p>\n<p><img decoding=\"async\" alt=\"FAST VP in Unity SAN: How it works.\" src=\"\/wp-content\/uploads\/2020\/03\/df92c278bbc9138beb109de0c05db705.jpeg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<\/p>\n<h4>Q. Data distribution when expanding the pool<\/h4>\n<p>\nThis task is a specific instance of the previous one and is carried out when a RAID group is added to the pool. To prevent the newly added RAID group from idling, some data will be moved to it, thereby redistributing the load across all RAID groups.<\/p>\n<h2>SSD Wear Leveling<\/h2>\n<p>\nThrough wear leveling, FAST VP can extend the lifespan of SSDs, although this function is not directly related to Storage Tiering. Since temperature data is already available, the number of write operations is also taken into account, and we are capable of moving data blocks, it would be logical for FAST VP to also address this issue.<\/p>\n<p>In cases where the number of writes to one RAID group significantly exceeds the number of writes to another, FAST VP will redistribute data according to the number of write operations. On one hand, this alleviates the load and preserves the resource of some disks; on the other hand, it adds 'work' for the less loaded disks, thus enhancing overall performance.<\/p>\n<p>Thus, FAST VP takes on traditional Storage Tiering tasks and goes a bit further. All this allows for quite efficient data storage in the Unity family of storage systems.<\/p>\n<h2>Several Tips<\/h2>\n<p><\/p>\n<ol>\n<li>Don't neglect reading the documentation. There are best practices, and they work quite well. If you follow them, serious problems usually do not arise. The other tips mainly repeat or complement them.<\/li>\n<li>If you have set up and enabled FAST VP, it's better to keep it on. Let it distribute data in its allocated time gradually rather than once a year, which could seriously impact the performance of other tasks. In such cases, data redistribution can take a long time.<\/li>\n<li>Pay close attention to selecting the relocation window. Although it may seem obvious, try to choose a time with the least load on Unity and allocate enough time.<\/li>\n<li>Plan for storage expansion and do it in a timely manner. This is general advice that is also important for FAST VP. If the amount of free space is very small, data movement may slow down or become impossible. Especially if you neglected point 2.<\/li>\n<li>When expanding the pool with FAST VP enabled, you shouldn\u2019t start with the slowest disks. You should either add all planned RAID groups at once or first add the fastest disks. In this case, redistributing data to new 'fast' disks will increase the overall speed of the pool. Otherwise, starting with 'slow' disks could lead to an unpleasant situation. Initially, data will move to the new, relatively slow disks, and later, when adding faster ones, the opposite will happen. There are nuances related to different FAST VP policies, but in general, such a situation is possible.<\/li>\n<\/ol>\n<p>\nIf you are looking at this product, you can try Unity for free by downloading the Unity VSA virtual appliance.<\/p>\n<p><img decoding=\"async\" alt=\"FAST VP in Unity SAN: How it works.\" src=\"\/wp-content\/uploads\/2020\/03\/a6ce6116c4ba028b14447157a270e5d2.jpeg\" style=\"display:block;margin: 0 auto;\" \/><br \/>\n<br \/>\nIn conclusion, I would like to share a few useful links:<\/p>\n<ul>\n<li>Page <noindex><a rel=\"nofollow\" href=\"https:\/\/www.delltechnologies.com\/ru-ru\/storage\/unity.htm\">Unity Storage<\/a><\/noindex><\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/community.emc.com\/docs\/DOC-70939\">Dell EMC Unity: FAST VP Theory of Operation<\/a><\/noindex> \u2013 brief description of the feature<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.dellemc.com\/en-us\/collaterals\/unauth\/white-papers\/products\/storage\/h15086-emc-unity-fast-technology-overview.pdf\">A more complete and detailed description<\/a><\/noindex>, PDF format<\/li>\n<li><noindex><a rel=\"nofollow\" href=\"https:\/\/www.dellemc.com\/en-us\/products\/trial-software-download\/index.htm\">Unity VSA\/Cloud edition<\/a><\/noindex><\/li>\n<\/ul>\n<p><\/p>\n<h2> Conclusion <\/h2>\n<p>\nI want to write about many things, but I understand that not all details will be of interest to the reader. For example, I could elaborate on the criteria by which FAST VP decides to relocate data, or the processes for analyzing input-output statistics. The topic of interaction with <noindex><a rel=\"nofollow\" href=\"https:\/\/www.dellemc.com\/resources\/en-us\/asset\/white-papers\/products\/storage\/h16289-dell_emc_unity-dynamic_pools.pdf\">Dynamic Pools<\/a><\/noindex>, which warrants a separate article, has also not been touched upon. One might even fantasize about the development of this technology. I hope it wasn't boring, and I didn\u2019t wear you out. Until next time!<br \/>\n<br \/>Source: <a content=\"nofollow\" rel=\"nofollow\" href=\"https:\/\/habr.com\/ru\/company\/dell_technologies\/blog\/493136\/\">habr.com<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"<p>\u0421\u0435\u0433\u043e\u0434\u043d\u044f \u0440\u0435\u0447\u044c \u043f\u043e\u0439\u0434\u0435\u0442 \u043e\u0431 \u0438\u043d\u0442\u0435\u0440\u0435\u0441\u043d\u043e\u0439 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438, \u0440\u0435\u0430\u043b\u0438\u0437\u043e\u0432\u0430\u043d\u043d\u043e\u0439 \u0432 \u0421\u0425\u0414 Unity\/Unity XT, \u2013 FAST VP. \u0415\u0441\u043b\u0438 \u0432\u044b \u0432\u043f\u0435\u0440\u0432\u044b\u0435 \u0443\u0441\u043b\u044b\u0448\u0430\u043b\u0438 \u043e Unity, \u0442\u043e \u043f\u043e \u0441\u0441\u044b\u043b\u043a\u0435 \u0432 \u043a\u043e\u043d\u0446\u0435 \u0441\u0442\u0430\u0442\u044c\u0438 \u043c\u043e\u0436\u043d\u043e \u043e\u0437\u043d\u0430\u043a\u043e\u043c\u0438\u0442\u044c\u0441\u044f \u0441 \u0445\u0430\u0440\u0430\u043a\u0442\u0435\u0440\u0438\u0441\u0442\u0438\u043a\u0430\u043c\u0438 \u0441\u0438\u0441\u0442\u0435\u043c\u044b. \u0412 \u043f\u0440\u043e\u0435\u043a\u0442\u043d\u043e\u0439 \u043a\u043e\u043c\u0430\u043d\u0434\u0435 Dell EMC \u044f \u0440\u0430\u0431\u043e\u0442\u0430\u043b \u043d\u0430\u0434 FAST VP \u0431\u043e\u043b\u0435\u0435 \u0433\u043e\u0434\u0430. \u0421\u0435\u0433\u043e\u0434\u043d\u044f \u0445\u043e\u0447\u0443 \u0440\u0430\u0441\u0441\u043a\u0430\u0437\u0430\u0442\u044c \u043e\u0431 \u044d\u0442\u043e\u0439 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u0438 \u043f\u043e\u0434\u0440\u043e\u0431\u043d\u0435\u0435 \u0438 \u0440\u0430\u0441\u043a\u0440\u044b\u0442\u044c \u043d\u0435\u043a\u043e\u0442\u043e\u0440\u044b\u0435 \u0434\u0435\u0442\u0430\u043b\u0438 \u0435\u0435 [&hellip;]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":1,"featured_media":75578,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[688],"tags":[],"class_list":["post-75577","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-administrirovanie"],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.2 - 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