Monthly Archives: August 2011
I was on my way to Singapore yesterday. At the departure lounge, I just started reading “Data Center Storage” by Hubbert Smith (ISBN#: 978-1439834879) yesterday and I learned something very interesting immediately. Then my thoughts started stirring and I thought I have a bit of fun with what I have learned from the book.
The single, most significant piece of the storage solution is the hard disk drive (HDD). Regardless of SAN or NAS protocols, the data is stored and served from the hard disk drives. And there are 4 key metrics of a HDD, which are
As storage professionals, we are often challenged to deliver the best storage solution to meet the customer’s requirements. Therefore, it is not about providing the fastest IOPS or the best availability or the lowest price. It is about providing the best balance of the 4 key metrics above.
The 4 metrics are of little help when they are standalone but if they are combined in relation to each other, you as a customer, can obtain some measurable ratios that will be useful to size for a requirements, keeping the balance of the 4 key metrics better defined rather than getting fluff and BS from the storage vendor.
In the book, the following table was displayed and I found it to be extremely useful:
|Key Ratios for HDDs
The relational ratios in red are going to be useful in determining the right type of storage for the requirement. And we will come back to this later. We begin our quest to obtain the information that we want – Performance, Capacity, Price, Power.
Capacity is the easy one because it is a given fact the size of the HDDs.
IOPS for each type of HDDs is also easy to obtain. See table below:
|Disk Type||RPM||IOPS Range|
The watt of each HDDs is also quite easy. Just ask the vendor to give the specification of the HDDs.
The pricing part would be part where we can have a bit of fun with the storage vendor. Usually, storage vendors do not release the price of a single HDD in the quotation. The total price is lumped together with everything else, making it harder to decipher the price. So, what can the customer do?
Easy. Get 4-5 quotations from the storage vendor, each with different type of HDDs. This is the customer’s rights. For example, I have created several fictitious quotations, each with a different type of HDDs/SSD and pricing.
Quote #1 (SATA 7200 RPM)
Quote #2 (SAS 10,000 RPM)
Quote #3 (SAS 15,000 RPM)
Quote #4 (SSD)
From the 4 quotations, we cannot ascertain the true price of a single disk, but we can assume that the 12 units HDDs/SSDs take up 50% of the entire quotation. With all things being equal, especially the quantity of 12, we can establish the very rough estimate of the price. Having fun asking the storage vendor to run around with the quotations is the added bonus.
But we can derive the following figures (rough estimates but useful when we apply them to the key ratios above)
1TB SATA = 3333.33; 300GB 10,000 RPM SAS = 5000.00; 300GB 15,000 RPM SAS = 6250.00; 100GB SSD = 10416.66
When we juxtapose the information that we have collected i.e. price, performance and capacity (ok, I am skipping power/watt because I am lazy to find out), we come up with a table below:
In the boxed area, we can now easily determine which HDDs/SSDs that give the best value for money either Performance/$ or Capacity/$. The higher the key ratio, the better the value.
From this aspect, the customer can now determine methodically which type of disk he should invest into, in order to get the best value.
This is just a very simplistic method to find the value of the storage solution to be purchased. Bear in mind that there are many other factors to consider as well, such as rack unit height, total power consumption, storage efficiency, data protection and many more.
I am not taking credit for what Hufferd Smith has proposed. All kudos to him but I am using his method to apply to what is relevant to us on the field.
In conclusion, the customer won’t be baffled and confused thinking that they got the best deal at lowest price or fastest performance. This crude method can help turn perception into something that is more concrete and analytical. It’s time we, as customer, know our rights, and know what we are buying into and have a bit of fun too with the storage vendor.
I just want to share a simple graph of what I wrote about in my previous blog entry. I think a picture is worth a thousand words. Have a look at the graph below. I found this in the “Cloud Storage for Dummies” book sponsored by HDS. Full credits to the authors of the book.
Interesting, isn’t it?
We have been taught that file systems are like folders, sub-folders and eventually files. The criteria in designing file systems is to ensure that there are few key features
- Ease of storing, retrieving and organizing files (sounds like a fridge, doesn’t it?)
- Simple naming convention for files
- Performance in storing and retrieving files – hence our write and read I/Os
- Resilience in restoring full or part of a file when there are discrepancies
In file systems performance design, one of the most important factors is locality. By locality, I mean that data blocks of a particular file should be as nearby as possible. Hence, in most file systems designs originated from the Berkeley Fast File System (BFFS), requires the file system to seek the data block to be modified to ensure locality, i.e. you try not to split up the contiguity of the data blocks. The seek time to find the require data block takes time, but you are compensate with faster reads because the read-ahead feature allows you to read extra blocks ahead in anticipation that the data blocks are related.
In Copy-on-Write file systems (also known as shadow-paging file systems), the seek portion is usually not present because the new modified block is written somewhere else, not the present location of the original block. This is the foundation of Copy-on-Write file systems such as NetApp’s WAFL and Oracle Solaris ZFS. Because the new data blocks are written somewhere else, the storing (write operation) portion is faster. It eliminated the seek time and it also skipped the read-modify-write action to the original location of the data block. Therefore, write is likely to be faster.
However, the read portion will be slower because if you want to read a file, the file system has to go around looking for the data blocks because it lacks the locality. Therefore, as the COW file system ages, it tends to have higher file system fragmentation. I wrote about this in my previous blog. It is a case of ENJOY-FIRST/SUFFER-LATER. I am not writing this to say that COW file systems are bad. Obviously, NetApp and Oracle have done enough homework to make the file systems one of the better storage file systems in the market.
So, that’s Copy-on-Write file systems. But what about SSDs?
Solid State Drives (SSDs) will make enemies with file systems that tend prefer locality. Remember that some file systems prefer its data blocks to be contiguous? Well, SSDs employ “wear-leveling” and required writes to be spread out as much as possible across the SSDs device to prolong the life of the SSD device to reduce “wear-and-tear”. That’s not good news because SSDs just told the file systems, “I don’t like locality and I will spread out the data blocks“.
NAND Flash SSDs (the common ones we find in the market and not DRAM-based SSDs) are funny creatures. When you write to SSDs, you must ERASE first, WRITE AGAIN to the SSDs. This is the part that is creating the wear-and tear of the device. When I mean ERASE first, WRITE AGAIN, I describe it below
- Writing 1 –> 0 (OK, no problem)
- Writing 0 –> 1 (not OK, because NAND Flash can’t do that)
So, what does the SSD do? It ERASES everything, writing the entire data blocks on the device to 1s, and then converting some of them to 0s. Crazy, isn’t it? The firmware in the SSDs controller will also spread out the erase-and-then write operations across the entire SSD device to avoid concentrating the operations on a small location or dataset. This is the “wear-leveling” we often hear about.
Since SSDs shun locality and avoid the data blocks to be nearby, and Copy-on-Write file systems are already doing this because its nature to write new data blocks somewhere else, the combination of both COW file system and SSDs seems like a very good fit. It even looks symbiotic because it is a case of “I help you; and you help me“.
From this perspective, the benefits of COW file systems and SSDs extends beyond resiliency of the SSD device but also in performance. Since the data blocks are spread out at different locations in the SSD device, the effect of parallelism will inadvertently help with COW’s performance. Make sense, doesn’t it?
I have not learned about other file systems and how they behave with SSDs, but it is pretty clear that Copy-on-Write file systems works well with Solid State Devices. Have a good week ahead !
An interesting question popped into my head yesterday. With all this push into the Cloud, the customer does not own most of the computer equipment. They are just getting services and when they want storage, do you think they care whether their storage is on a SAN or NAS?
I have mentioned this before, Cloud makes a lot of IT stuff irrelevant. Read my previous blog. This means that the demand for IT techies, sysadmins, consultant will suddenly be squeezed into who’s very good, good, not-so-good and the downright bad ones. Let’s the survival-of-the-fittest games begin!
Yes, the SAN and NAS, or even unified storage story doesn’t hold much weight anymore. However, to the cloud service provider, they will be out there looking for what is best for their bottom line, whether it will be a branded box or just a white box if they are willing to build the storage on their own. For those providers who have strong financials, obviously investing in premium brands like EMC, IBM, NetApp, and so on, makes sense because they need someone to blame and penalize when the shit hits the fan. For those who doesn’t have the financial prowess, this presents a whole new economy that resellers, partners, distributors can tap on to – build for these cloud providers at a cheaper price (hint, hint).
However, storage relies on a strong storage operating system to do just that. They are plenty of open source ones. Hey, you can practically build a simple iSCSI or NAS box with Linux. Consumer grade NAS such as NetGear, Synology and DLink have been using open-source Linux to penetrate the low-end, home storage market for years. The cloud providers will be a different ballgame, but the storage piece is fundamentally the same.
Things are changing folks, and for those consultants, product pre-sales, post-sales, sysadmins, operators of storage, you have to evolve to meet this new market. SAN and NAS do not matter anymore when customers are using the cloud services.
p/s: I have been spending time looking at some very, very cool cloud-ready storage operating systems. If you have the time, leave me a comment and we’ll talk.
Just saw the news. Here’s the link –http://www.themalaysianinsider.com/business/article/hp-may-drop-pcs-to-buy-autonomy-for-us11.7b/
HP could buy British software maker Autonomous. Just months ago, Autonomous just acquired Iron Mountain Digital’s asset with solutions such as Connected Backup, and the previous Mimosa Nearpoint.
Again, there is no value in the PC business anymore and it is only logical that HP is focusing on high value and high margin IT solutions. More news could follow.
The human capital is important in the IT industry. Yet, we are facing a situation where there is a steady supply of storage-related jobs, but the supply of human resources and skills to these jobs is seriously lacking. Even if there are many people applying for these positions, the good ones are far and few.
What’s happening? Malaysia has been stuck in a rut for quite a few years now trying to raise good quality human capital, especially in the IT sectors. God knows how hard agencies such as MDeC and others IT bodies have been trying to increase the awareness and supply of good quality IT people for the IT industry. In storage, the situation is even more acute because storage has been seen as the one of the unglamourous jobs. That is why there are likely to have more networking techies than storage techies.
We all know IT is all about data and information and the data and information are created, stored, modified, stored-again, replicated, migrated, archived and deleted IN STORAGE. Data has to reside in storage and memory before it can be used. And don’t forget that memory is temporary, volatile storage. It’s plain and simple – data has to be in some form of storage before it can be used.
I have been fairly disturbed by the fact that storage remains one of the most important foundations of IT and yet, the pool of good storage networking and data management professionals is seriously shallow, especially in Malaysia. The good ones are out there, kept as prized assets of the company they work for. But cloud computing is here, and the demand for storage professionals is greater than ever.
I went out and did some research, using the salary factor as the main criteria for storage jobs. And here’s what I found –>
The information source of the above chart is Certification Magazine Salary Survey 2009. I hope the table isn’t too small to read but here’s what I can summarize in the table below. The rows in red are the storage-related jobs.
Yes, the information is a bit old but it tells a tale. Storage professionals’ salary with the value that the storage certifications carry are in the upper echelons of the pay scale. At the same time during my research, I also found this page of information from Foote Partners LLC – 2011 IT Skills & Certification Pay Index.
And again, storage certification is usually higher in percentage than the median average pay premium.
However, all these information are from the US where skills and experience are valued highly because they drive innovation and sales.
Sadly, this cannot be always true in Malaysia because the IT economy in Malaysia has not reached the level of innovation that drives new technologies in the country’s economy. I think this is all our fault. Why? Here’s what I think
- We go for the easy ones
- We don’t want to learn anymore after we started working in IT
- We don’t set high targets for ourselves
- We accept things as they are – something to us being apathy towards things
- We have other things on our mind – like politics, inflation and so on
- We don’t innovate
And this is something that saddens me.
A few years ago, I was at a local FOSScon where the open source geeks and nerds and gurus convene. I was there for 2 reasons – to have a bit of fun, but more importantly, I was looking for people who had skills with kernel and file systems. Sadly, I found none after 2 days at the event. Almost all developers I spoke to where developing in PHP, mySQL, Python, Ruby-on-Rails and so on. This was a clear signal that most Malaysian developers were taking the easy way out (point #1 above). No one was programming in C, C++, and working on hardcore stuff like device drivers, networking protocols and so on.
Since we did not go out and outdo ourselves and innovate, we did not create an innovative IT economy that is the key for creating demand. Most IT companies in Malaysia would prefer playing the pass-through game i.e. “let’s pass through this deal with this reseller”, knowing full well that the reseller is there for relationship connections, not value-add. Hence point #1 again.
I recall another incident that also vivid in my mind. I was decommissioning some Sun JavaStations in the backroom of a premier, “multimedia” university in Melaka. I looked at the lecture that was going on and the instructor was teaching ApplixWord. I asked one of the students and he told me that the course was 2 (or was it 1) credit hours. It came as a big shocker to me because an premier IT multimedia university was teaching the most basic of the basics of word processing. A university is supposed to be the institution to ignite creativity and innovation, but this university was droning its students on word processing. No wonder our IT economy sucks because we set such f*cking low standards for ourselves (point #3).
What I would like to see if IT people go out of the box they didn’t know they were confined to in the first place, and learn/share and learn/share and learn/share. Be creative, be innovative, be bold.
I have been blessed with like-minded people who can do a good hack and build something that can compete with the big boys like EMC, IBM, HP and the likes. But these people are far and few.
Today, I am looking for more of such people, people who are f*cking (pardon me French but I am the passionate one) good with storage networking and data management stuff. I am looking for people who can innovate to create the real Silicon Valley culture in Malaysia. We don’t need fancy ministers to officiate or glamourous events launching but the real hackers, entrepreneurial junkies and those pioneering spirited wackos (in a good way), to define what this IT economy is all about!
In my previous blog entry, I mentioned the write penalty for RAID-5/6. This factor will figure heavily in the way we size the RAID-level for performance capacity planning.
It is difficult to ascertain what kind of IOPS and throughput that are required for an application, especially a database, to run well with additional room to grow. From a DBA or an application developer, I believe they would have adequate information to tell what is the numbers of users that the application can support, both average and peak, transactions per second (TPS), block size required for logs, database files and so on.
But as we are all aware, most of the time, these types of information are not readily available. So, coming from a storage angle, the storage administrator can advise the DBA or the application developer that the configured RAID group or volume or LUN is capable of delivering a certain number of IOPS and is able to achieve a certain throughput MB/sec. These numbers will be off the box itself immediately. Of course, other factors such as HBA speed, the FC/iSCSI configurations, the network traffic and so on will affect the overall performance delivery to the application. But we can safely inform the DBA and/or the application developer that this is what the storage is delivering out of the box.
The building blocks of all storage RAID groups/volumes/LUNs are pretty much your hard disk drives (HDDs) and/or Solid State Drives (SSDs). The manufacturer of these disks will usually publish the IOPS and throughput of individual drives but if these information is not available, we can construct IOPS of an individual HDD from its seek and latency times.
For example, if the HDD’s
average latency = 2.8 ms; average read seek = 4.2 ms; average write seek = 4.8 ms
then the IOPS can be calculated as
1 IOPS = --------------------------------------- (average latency) + (average seek time)
Therefore from the details above,
1 IOPS = ------------------- = 136.986 IOPS (0.0028) + (0.0045)
That’s pretty simple, right? But of course, it is easier to just accept that a certain type of disk will have a range of IOPS as shown in the table below:
|Disk Type||RPM||IOPS Range|
The information from the table above is just for reference only and by no means a very accurate one but it is good enough for us to determine the IOPS of a RAID group/volume/LUN. Let’s look at the RAID write penalty again in the table below:
|RAID-level||Number of I/O Reads
||Number of I/O for Writes
||RAID Write Penalty|
|1 (1+0, 0+1)||1||2||2|
Next, we need to know what is the ratio of Reads vs Writes for that particular database or application. I mentioned earlier that in OLTP-type of applications, we usually take a 2:1 or 3:1 ratio in favour of Reads.
To make things simpler, let’s assume we create a RAID-6 volume of 6 data disks and 2 parity disks in a RAID-6 (6+2) configuration. The disks used are SATA disks of 7,200 RPM, with each individual disk of 100 IOPS. Assume we are using a ratio of 2:1 in favour of Reads, which gives us 66.666% and 33.333% respectively for Reads and Writes.
Therefore, the combined IOPS of the 8 disks in the RAID-6 configuration is probably about 800 IOPS. However, because of the write penalty of RAID-6, the effective IOPS for the RAID-6 volume will be lower than that. Let’s do some calculation to see what happens:
1) Read IOPS + Write IOPS = 800 IOPS
2) (0.66666 x 800) + (0.33333 x 800) = 800 IOPS
3) Read IOPS will be 0.66666 x 800 = 533.328 IOPS
4) Write IOPS will be 0.33333 x 800 = 266.664 IOPS. However, since RAID-6 has a write penalty of 6, this number has to be divided by 6. 266.664/6 will be 44.444 IOPS for Writes
Therefore, what the RAID-6 volume is capable of is approximately 533 IOPS for Reads and 44 IOPS for Writes.
We have determined IOPS for the RAID volume but what about throughput. Throughput is determined by the block size used. Assume that our RAID-6 volume uses a 4-K block size. With a combined effective IOPS of 577 (533+44), we multiply the IOPS with the block size
Throughput = 577 IOPS x 4-KB = 2308KB/sec
Therefore when I/O is sustained in a sequential manner, the effective throughput is 2308KB/sec.
On the other hand, we often were told to add more spindles to the volume to increase the IOPS. This is true, to a point, where the maximum amount of IOPS that can be delivered will taper into a flatline, because the I/O channel to the RAID volume has been saturated. Therefore, it is best to know that adding more spindles does not always equate to a higher IOPS.
Performance sizing for a database or an application is both a science and an art. Mathematically, we can prove things to a a certain amount of accuracy and confidence but each storage platform is very different in the way they handle RAID. Newer storage platforms have proprietary RAID that nowadays, it does not matter much what kind of RAID is best for the application. Vendors such as IBM XIV has RAID-X which both radical in design and implementation. NetApp will almost always say RAID-DP is the best no matter what, because RAID-DP is all NetApp.
So there is no right or wrong to choose the RAID-level for the application. But it is VERY important to know what are the best practice are and my advice is everyone is to do Proof-of-Concepts, and TEST, TEST, TEST! And ASK QUESTIONS!
It’s a beautiful Saturday morning … the sun is out, and the birds are chirping … and here I am, thinking about RAID-5/6. What’s wrong with me?
Anyway, have you ever wondered almost all your volumes are in a RAID-5/6 configuration? Like an obedient child, the answer would probably be “Oh, my vendor said it is good for me …”
In storage, the rule is applications-read, applications-write. And different applications have different behaviors but typically, they fall under 2 categories:
- Random access
- Sequential access
The next question to ask is how much Read/Writes ratio (or percentage) is in that Random Access behavior and how much of Read/Write ratio in Sequential Access behavior.
We usually pigeonhole transactional databases such as SQL Server, Oracle into OLTP-type characteristics with random access being the dominant access method. Similarly, email applications such as Exchange, Lotus and even SMTP into similar OLTP-type characteristics as well. We typically do a 2:1 or 3:1 ratio for OLTP-type applications with Read heavy and less of Writes. Data warehouse type of databases tend to be more sequential.
However, even within these OLTP applications, there are also sequential access behaviors as well, as the following table for a database shows:
|Operation||Random or Sequential||Read/Write Heavy||Block Size|
|DB-Log||Random (Sequential in log recovery)||Write Heavy unless you are doing log recovery||1KB – 64KB|
|DB-Data Files||Random||Read/Write mix dependent on load||4KB – 32KB|
|Batch insert||Sequential||Write Heavy||8KB – 128KB|
|Index scan||Sequential||Read Heavy||8KB – 128KB|
We will look into 4 RAID-levels in this scenario and see how each RAID-level applies to an OLTP-type of environment. These RAID levels are RAID-0, RAID-1 (1+0, 0+1 included), RAID-5 and RAID-6.
RAID-0 is the baseline, with 1 x Read and 1 x Write being processed as per normal.
In RAID-1, it would require 2 x Writes and 1 x Read, because the write operation is mirrored. The RAID penalty is 2.
To avoid the cost of RAID-1, RAID-5 is almost always the RAID level of choice (unless you speak to those NetApp fellas). RAID-5 is a parity-based RAID and require 2 x Read (1 to read the data block and 1 to read the parity block) AND 2 x Write (1 to write the modified block and 1 to write the modified parity). Hence it has a RAID penalty of 4.
RAID-6 was to address the risk of RAID-5 because disk capacity are so freaking large now (3TB just came out). To rebuild a large-TB drive would take longer time and the RAID-5 volume is at risk if a second disk failure occurs. Hence, double parity RAID in RAID-6. But unfortunately, the RAID penalty for RAID-6 is 6!
To summarize the RAID write penalty,
|RAID-level||Number of I/O Reads
||Number of I/O for Writes
||RAID Write Penalty|
|1 (1+0, 0+1)||1||2||2|
So, it is well known that RAID 0 has good performance for reads and writes but with absolutely no protection. RAID-1 would be good for random reads and writes but it is costly. RAID-5 is good for applications with a high ratio of sequential reads vs writes (2:1, 3:1 as mentioned), and RAID-6, errr … should be taken similarly as RAID-5 with some additional performance penalty.
With that in mind, a storage administrator must question why a particular RAID-level was proposed to the database or any like-applications.
I am going out to enjoy the Saturday now … and today, August 13th is the World’s Left-Handed Day. More about this RAID penalty and IOPS in my next entry.
This has been bugging me for a long time and I have to let it out.
First of all, cloud computing can mean a million things coming from different people. I am still in a haze sometimes of where this cloud thingy could lead too. Every IT vendor is “cloud-something” and I am not going to contest that because I am no cloud expert myself.
But one thing is imminent. The entire landscape from the IT infrastructure to the economics of IT, is changing into the utility model. This-as-a-Service, That-as-Service and so on. Customers and companies are beginning to realize the opportunity and the ability to lease IT services as a pay-as-you-use utility just like any public utility such as electricity and water.
In IT, we are used to the model of manufacturer –> vendor —> distributor –> reseller –> end customer. This has been the scheme of things and for those of us working as professionals for vendors, distributors and resellers, that’s our livelihood. But the cloud computing model is in the horizon. We are not too far off from such a scheme, where IT is operated as a utility company. This means that IT is directly provisioned to the end customer, likely to be bypassing the reseller model. Suddenly the model becomes manufacturer –> end customer. You get it, right?
We can still include the vendor, distributor and reseller into the new cloud computing landscape, but there is little value-add, and with market dynamics, the end customer would want to get their IT services supply directly from the manufacturer, in this case, the cloud service provider.
So where does that leave us? We could be the end-user OR we could work for a cloud service provider. That would mean little differentiation for IT engineers and sysadmins, IT sales reps and marketing people.
But this is not a doom-and-gloom story. In my opinion, this is the best time for IT geeks and nerds to become one notch better. Know your subject well in what you do, learn and grow your knowledge in the right direction, AND be DAMN good! That is where we can differentiate ourselves; move ourselves up the value chain and enhance our position. Don’t take the easy way out and be one of the ordinary. Be X-TRAordinary!!!
Unfortunately, I am having a COW about it!
Snapshots are the inherent offspring of the copy-on-write technique used in shadow-paging filesystems. NetApp’s WAFL and Oracle Solaris ZFS are commercial implementations of shadow-paging filesystems and they are typically promoted as Copy-on-Write filesystems.
As we may already know, snapshots are point-in-time copy of the active file system in the storage world. They perform quick backup of the active file system by making a copy of the block addresses (pointers) of the filesystem and then updating the pointer maps to the inodes in the fsinfo root inode of the WAFL filesystem for new changes after the snapshot has been taken. The equivalent of fsinfo is the uberblock in the ZFS filesystem.
However, contrary to popular belief, the snapshots from WAFL and ZFS are not copy-on-write implementations even though the shadow paging filesystem tree employs the copy-on-write technique.
Consider this for a while when a snapshot is being taken … Copy —- On —- Write. If the definition is (1) Copy then (2) Write, this means that there are several several steps to perform a copy-on-write snapshot. The filesystem has to to make a copy of the original data block (1 x Read I/O), then write the original data block to a new location (1 x Write I/O) and then write the new data block to the location of the original data block (1 x Write I/O).
This is a 3-step process that can be summarized as
- Read location of original data block (1 x Read I/O)
- Copy this data block to new unused location (1 x Write I/O)
- Write the new and modified data block to the location of original data block (1 x Write I/O)
This implementation, IS THE copy-on-write technique for snapshot but NetApp and possibly Oracle guys have been saying for years that their snapshots are based on copy-on-write. This is pretty much a misnomer that needs to be corrected. EMC, in its SnapSure and SnapView implementation, called this technique Copy-on-First-Write (COFW), probably to avoid the confusion. The data blocks are copied to a savvol, a separate location to store the changes of snapshots and defaults to 10% of the total capacity of their storage solutions.
As you have seen, this method is a 3 x I/O operation and it is an expensive solution. Therefore, when we compare the speed of NetApp/ZFS snapshots to EMC’s snapshots, the EMC COFW snapshot technique will be a tad slower.
However, this method has one superior advantage over the NetApp/ZFS snapshot technique. The data blocks in the active filesystem are almost always laid out in a more contiguous fashion, resulting in a more consistent read performance throughout the life of the active file system.
Below is a diagram of how copy-on-write snapshots are implemented
What is NetApp/ZFS’s snapshot method then?
It is is known as Redirect-on-Write. Using the same step … REDIRECT —- ON —– WRITE. When a data block is about to be modified, the original data block is read (1 x Read I/O) and then the data block is written to a new location (1 x Write I/O). The active file system then updates the filesystem tree and its inode address to reflect the location of the new data block. The original data block remained unchanged.
- Read location of original data block (1 x Read I/O)
- Write modified data block to new location (1 x Write I/O)
The Redirect-on-Write method resulted in 1 Write I/O less, making snapshot creation faster. This is the NetApp/ZFS method and it is superior when compared to the Copy-on-Write snapshot technique discussed earlier.
However, as the life of the filesystem progresses, fragmentation and holes will cause the performance of the active filesystem to degrade. The reason is most related data blocks are no longer contiguous and the active file system will be busy seeking the scattered data blocks across the volume. Fragmented filesystem would have to be “cleaned and reorganized” to regain its performance lustre.
Another unwanted problem using the Redirect-on-Write snapshot technique is the snapshot resides in the same boundary as the active filesystem. Over time, if the capacity consumed by the snapshots could overwhelm the active filesystem, if their recycle schedule is unchecked.
I guess this is a case of “SUFFER NOW/ENJOY LATER” or “ENJOY NOW/SUFFER LATER”. We have to make a conscious effort to understand what snapshots are all about.