|By Eric Burgener||
|November 26, 2012 07:45 AM EST||
Legacy storage architectures do not perform very efficiently in virtual computing environments. The very random, very write-intensive I/O patterns generated by virtual hosts drive storage costs up as enterprises either add spindles or look to newer storage technologies like solid state disk (SSD) to address the IOPS shortfall.
SSD costs are coming down, but they are still significantly higher than spinning disk costs. When enterprises do consider SSD, how it is used and where it is placed in the virtual infrastructure can make a big difference in how much enterprises have to spend to meet their performance requirements. It can also impose certain operational limitations that may or may not be issues in specific environments.
Some of the key considerations that need to be taken into account are SSD placement (in the host or in the SAN), high availability/failover requirements, caching vs logging architectures, and the value of preserving existing investments vs rip and replace investments that promise storage hardware specifically designed for virtual environments.
There are two basic locations to place SSD, each of which offers its own pros and cons. Host-based SSD will generally offer the lowest storage latencies, particularly if the SSD is located on PCIe cards. In non-clustered environments where it is clear that IOPS and storage latencies are the key performance problems, these types of devices can be very valuable. In most cases, they will remove storage as the performance problem.
But don't necessarily expect that in your environment, these devices will deliver their rated IOPS directly to your applications. In removing storage as the bottleneck, system performance will now be determined by whatever the next bottleneck in the system is. That could be CPU, memory, operating system, or any number of other potential issues. This phenomenon is referred to as Amdahl's Law.
What you probably care about are application IOPS. Test the devices you're considering in your environment before purchase, so you know exactly the level of performance gain they will provide to you. Then you can make a more informed decision about whether or not you can cost justify them for use with your workloads. Paying for performance you can't use is like buying a Ferrari for use on America's interstate system - you may never get out of second gear.
Raw SSD technology generally can provide blazingly fast read performance. Write performance, however, varies depending on whether you are writing randomly or sequentially. The raw technical specs on many SSD devices indicate that sequential write performance may be half that of read performance, and random write performance may be half again as slow. Write latencies may also not be deterministic because of how SSD devices manage the space they are writing to. Many SSD vendors are combining software and other infrastructure around their SSD devices to address some of these issues. If you're looking at SSD, look to the software it's packaged with to make sure the SSD capacity you're buying can be used most efficiently.
Host-based SSD introduces failover limitations. If you have implemented a product like VMware HA in your environment to automatically recover failed nodes, any data sitting in a host-based SSD device that has not been written through to shared storage will not be available on recovery. This can lead to data loss on recovery - something that may or may not be an issue in your environment. Even though SSD is non-volatile storage, if the node it is sitting in is down, you can't get to it. You can get to it after that node is recovered, but the issue here is whether or not you can automatically fail over and have access to it.
Because of this issue, most host-based SSD products implement what is called a "write-through" cache, which means that they don't acknowledge writes at SSD latencies, they actually write them through to shared disk and then send the write acknowledgement back from there. Anything on shared disk can be potentially recovered by any other node in the cluster, ensuring that no committed data is unavailable on failover. But what this means is that you won't get any write performance improvements from SSD, just better read performance.
What does your workload look like in terms of read vs write percentages? Most virtual environments are very write intensive, much more so than they ever were in physical environments, and virtual desktop infrastructure (VDI) environments can be as much as 90% writes when operating in steady state mode. If write performance is your problem, host-based SSD with a write-through cache may not help very much in the big picture.
SAN-based SSD, on the other hand, can support failover without data loss, and if implemented with a write-back cache can provide write performance speedups as well. But many implementations available for use with SAN arrays are really only designed to speed up reads. Check carefully as you consider SSD to understand how it is implemented, and how well that maps to the actual performance requirements in your environment.
Caching vs Logging Architectures
Most SSD, wherever it is implemented, is used as a cache. Sizing guidelines for caches start with the cache as a percentage of the back-end storage it is front-ending. Generally the cache needs to be somewhere between 3% to 6% of the back-end storage, so larger data store capacities require larger caches. For example, 20TB of back-end data might require 1TB of SSD cache (5%).
Caches are generally just speeding up reads, but if you are working with a write-back cache, then the cache will have to be split between SSD capacity used to speed up reads and SSD capacity used to speed up writes. Everything else being equal in terms of performance requirements, write-back caches will have to be larger than write-through caches, but will provide more balanced performance gains (across both reads and writes).
Logging architectures, by definition, speed up writes, making them a good fit for write-intensive workloads like those found in virtual computing environments. Logs provide write performance gains by taking the very random workload and essentially removing the randomness from it by writing it sequentially to a log, acknowledging the writes from there, then asynchronously de-staging them to a shared storage pool. This means that the same SSD device used in a log vs used in a cache will be faster, assuming some randomness to the workload. The write performance the guest VMs see is the performance of the log device operating in sequential write mode almost all the time, and it can result in write performance improvements of up to 10x (relative to that same device operating in the random mode it would normally be operating in). And a log provides write performance improvements for all writes from all VMs all the time. (What's also interesting is that if you are getting 10x the IOPS from your current spinning disk, given Amdahl's Law, you may not even need to purchase SSD to remove storage as the performance bottleneck.)
Logs are very small (10GB or so) and are dedicated to a host, while the shared storage pool is accessible to all nodes in a cluster and primarily handles read requests. In a 20 node cluster with 20TB of shared data, you would need 200GB for the logs (10GB x 20 hosts) vs the 1TB you would need if SSD was used as a cache. Logs are much more efficient than caches for write performance improvements, resulting in lower costs.
If logs are located on SAN-based SSD, you not only get the write performance improvements, but this design fully supports node failover without data loss, a very nice differentiator from write-through cache implementations.
But what about read performance? This is where caches excel, and a write log doesn't seem to address that. That's true, and why it's important to combine a logging architecture with storage tiering. Any SSD capacity not used by the logs can be configured into a fast tier 0, which will provide the read performance improvements for any data residing in that tier. The bottom line here is that you can get better overall storage performance improvements from a "log + tiering" design than you can from a cache design while using 50% - 90% less high performance device (in this case, SSD) capacity. In our example above, if you buy a 256GB SAN-based SSD device and use it in a 20 node cluster, you'll get SSD sequential write performance for every write all the time, and have 56GB left over to put into a tier 0. Compare that to buying 1TB+ of cache capacity at SSD prices.
With single image management technology like linked clones or other similar implementations, you can lock your VM templates into this tier, and very efficiently gain read performance improvements against the shared blocks in those templates for all child VMs all the time. Single image management technology can help make the use of SSD capacity more efficient in either a cache or a log architecture, so don't overlook it as long as it is implemented in a way that does not impinge upon your storage performance.
Purpose-Built Storage Hardware
There are some interesting new array designs that leverage SSD, sometimes in combination with some of the other technologies mentioned above (log architectures, storage tiering, single image manage-ment, spinning disk). Designed specifically with the storage performance issues in virtual environments in mind, there is no doubt that these arrays can outperform legacy arrays. But for most enterprises, that may not be the operative question.
It's rare that an enterprise doesn't already have a sizable investment in storage. Many of these existing arrays support SSD, which can be deployed in a SAN-based cache or fast tier. It's much easier, and potentially much less disruptive and expensive if existing storage investments could be leveraged to address the storage performance issues in virtual environments. It's also less risky, since most of the hot new "virtual computing-aware" arrays and appliances are built by startups, not proven vendors. If there are pure software-based options to consider that support heterogeneous storage hardware and can address the storage issues common in virtual computing environments, allowing you to potentially take advantage of SSD capacity that fits into your current arrays, this could be a simpler, more cost-effective, and less risky option than buying from a storage startup. But only, of course, if it adequately resolves your performance problem.
If there's one point you should take away from this article, it's that just blindly throwing SSD at a storage performance problem in virtual computing environments is not going to be a very efficient or cost-effective way to address your particular issues. Consider how much more performance you need, whether you need it on reads, writes, or both, whether you need to failover without data loss, and whether preserving existing storage hardware investments is important to you. SSD is a great technology, but your best value from it will come when you deploy it most efficiently.
The IoT market is on track to hit $7.1 trillion in 2020. The reality is that only a handful of companies are ready for this massive demand. There are a lot of barriers, paint points, traps, and hidden roadblocks. How can we deal with these issues and challenges? The paradigm has changed. Old-style ad-hoc trial-and-error ways will certainly lead you to the dead end. What is mandatory is an overarching and adaptive approach to effectively handle the rapid changes and exponential growth.
Oct. 8, 2015 04:00 PM EDT
Today’s connected world is moving from devices towards things, what this means is that by using increasingly low cost sensors embedded in devices we can create many new use cases. These span across use cases in cities, vehicles, home, offices, factories, retail environments, worksites, health, logistics, and health. These use cases rely on ubiquitous connectivity and generate massive amounts of data at scale. These technologies enable new business opportunities, ways to optimize and automate, along with new ways to engage with users.
Oct. 8, 2015 03:45 PM EDT
The buzz continues for cloud, data analytics and the Internet of Things (IoT) and their collective impact across all industries. But a new conversation is emerging - how do companies use industry disruption and technology enablers to lead in markets undergoing change, uncertainty and ambiguity? Organizations of all sizes need to evolve and transform, often under massive pressure, as industry lines blur and merge and traditional business models are assaulted and turned upside down. In this new data-driven world, marketplaces reign supreme while interoperability, APIs and applications deliver un...
Oct. 8, 2015 03:30 PM EDT Reads: 209
The Internet of Things (IoT) is growing rapidly by extending current technologies, products and networks. By 2020, Cisco estimates there will be 50 billion connected devices. Gartner has forecast revenues of over $300 billion, just to IoT suppliers. Now is the time to figure out how you’ll make money – not just create innovative products. With hundreds of new products and companies jumping into the IoT fray every month, there’s no shortage of innovation. Despite this, McKinsey/VisionMobile data shows "less than 10 percent of IoT developers are making enough to support a reasonably sized team....
Oct. 8, 2015 03:30 PM EDT Reads: 128
You have your devices and your data, but what about the rest of your Internet of Things story? Two popular classes of technologies that nicely handle the Big Data analytics for Internet of Things are Apache Hadoop and NoSQL. Hadoop is designed for parallelizing analytical work across many servers and is ideal for the massive data volumes you create with IoT devices. NoSQL databases such as Apache HBase are ideal for storing and retrieving IoT data as “time series data.”
Oct. 8, 2015 02:45 PM EDT Reads: 489
Clearly the way forward is to move to cloud be it bare metal, VMs or containers. One aspect of the current public clouds that is slowing this cloud migration is cloud lock-in. Every cloud vendor is trying to make it very difficult to move out once a customer has chosen their cloud. In his session at 17th Cloud Expo, Naveen Nimmu, CEO of Clouber, Inc., will advocate that making the inter-cloud migration as simple as changing airlines would help the entire industry to quickly adopt the cloud without worrying about any lock-in fears. In fact by having standard APIs for IaaS would help PaaS expl...
Oct. 8, 2015 02:30 PM EDT Reads: 641
There are so many tools and techniques for data analytics that even for a data scientist the choices, possible systems, and even the types of data can be daunting. In his session at @ThingsExpo, Chris Harrold, Global CTO for Big Data Solutions for EMC Corporation, will show how to perform a simple, but meaningful analysis of social sentiment data using freely available tools that take only minutes to download and install. Participants will get the download information, scripts, and complete end-to-end walkthrough of the analysis from start to finish. Participants will also be given the pract...
Oct. 8, 2015 02:15 PM EDT Reads: 219
SYS-CON Events announced today that ProfitBricks, the provider of painless cloud infrastructure, will exhibit at SYS-CON's 17th International Cloud Expo®, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. ProfitBricks is the IaaS provider that offers a painless cloud experience for all IT users, with no learning curve. ProfitBricks boasts flexible cloud servers and networking, an integrated Data Center Designer tool for visual control over the cloud and the best price/performance value available. ProfitBricks was named one of the coolest Clo...
Oct. 8, 2015 01:00 PM EDT Reads: 756
Organizations already struggle with the simple collection of data resulting from the proliferation of IoT, lacking the right infrastructure to manage it. They can't only rely on the cloud to collect and utilize this data because many applications still require dedicated infrastructure for security, redundancy, performance, etc. In his session at 17th Cloud Expo, Emil Sayegh, CEO of Codero Hosting, will discuss how in order to resolve the inherent issues, companies need to combine dedicated and cloud solutions through hybrid hosting – a sustainable solution for the data required to manage I...
Oct. 8, 2015 01:00 PM EDT Reads: 469
NHK, Japan Broadcasting, will feature the upcoming @ThingsExpo Silicon Valley in a special 'Internet of Things' and smart technology documentary that will be filmed on the expo floor between November 3 to 5, 2015, in Santa Clara. NHK is the sole public TV network in Japan equivalent to the BBC in the UK and the largest in Asia with many award-winning science and technology programs. Japanese TV is producing a documentary about IoT and Smart technology and will be covering @ThingsExpo Silicon Valley. The program, to be aired during the peak viewership season of the year, will have a major impac...
Oct. 8, 2015 01:00 PM EDT Reads: 251
Apps and devices shouldn't stop working when there's limited or no network connectivity. Learn how to bring data stored in a cloud database to the edge of the network (and back again) whenever an Internet connection is available. In his session at 17th Cloud Expo, Bradley Holt, Developer Advocate at IBM Cloud Data Services, will demonstrate techniques for replicating cloud databases with devices in order to build offline-first mobile or Internet of Things (IoT) apps that can provide a better, faster user experience, both offline and online. The focus of this talk will be on IBM Cloudant, Apa...
Oct. 8, 2015 12:45 PM EDT Reads: 504
WebRTC is about the data channel as much as about video and audio conferencing. However, basically all commercial WebRTC applications have been built with a focus on audio and video. The handling of “data” has been limited to text chat and file download – all other data sharing seems to end with screensharing. What is holding back a more intensive use of peer-to-peer data? In her session at @ThingsExpo, Dr Silvia Pfeiffer, WebRTC Applications Team Lead at National ICT Australia, will look at different existing uses of peer-to-peer data sharing and how it can become useful in a live session to...
Oct. 8, 2015 12:00 PM EDT Reads: 600
As a company adopts a DevOps approach to software development, what are key things that both the Dev and Ops side of the business must keep in mind to ensure effective continuous delivery? In his session at DevOps Summit, Mark Hydar, Head of DevOps, Ericsson TV Platforms, will share best practices and provide helpful tips for Ops teams to adopt an open line of communication with the development side of the house to ensure success between the two sides.
Oct. 8, 2015 12:00 PM EDT Reads: 571
SYS-CON Events announced today that IBM Cloud Data Services has been named “Bronze Sponsor” of SYS-CON's 17th Cloud Expo, which will take place on November 3–5, 2015, at the Santa Clara Convention Center in Santa Clara, CA. IBM Cloud Data Services offers a portfolio of integrated, best-of-breed cloud data services for developers focused on mobile computing and analytics use cases.
Oct. 8, 2015 11:00 AM EDT Reads: 724
"Matrix is an ambitious open standard and implementation that's set up to break down the fragmentation problems that exist in IP messaging and VoIP communication," explained John Woolf, Technical Evangelist at Matrix, in this SYS-CON.tv interview at @ThingsExpo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
Oct. 8, 2015 07:00 AM EDT Reads: 5,865
WebRTC has had a real tough three or four years, and so have those working with it. Only a few short years ago, the development world were excited about WebRTC and proclaiming how awesome it was. You might have played with the technology a couple of years ago, only to find the extra infrastructure requirements were painful to implement and poorly documented. This probably left a bitter taste in your mouth, especially when things went wrong.
Oct. 8, 2015 06:00 AM EDT Reads: 756
The broad selection of hardware, the rapid evolution of operating systems and the time-to-market for mobile apps has been so rapid that new challenges for developers and engineers arise every day. Security, testing, hosting, and other metrics have to be considered through the process. In his session at Big Data Expo, Walter Maguire, Chief Field Technologist, HP Big Data Group, at Hewlett-Packard, will discuss the challenges faced by developers and a composite Big Data applications builder, focusing on how to help solve the problems that developers are continuously battling.
Oct. 8, 2015 04:00 AM EDT Reads: 485
Nowadays, a large number of sensors and devices are connected to the network. Leading-edge IoT technologies integrate various types of sensor data to create a new value for several business decision scenarios. The transparent cloud is a model of a new IoT emergence service platform. Many service providers store and access various types of sensor data in order to create and find out new business values by integrating such data.
Oct. 8, 2015 04:00 AM EDT Reads: 540
WebRTC converts the entire network into a ubiquitous communications cloud thereby connecting anytime, anywhere through any point. In his session at WebRTC Summit,, Mark Castleman, EIR at Bell Labs and Head of Future X Labs, will discuss how the transformational nature of communications is achieved through the democratizing force of WebRTC. WebRTC is doing for voice what HTML did for web content.
Oct. 8, 2015 03:00 AM EDT Reads: 1,376
Developing software for the Internet of Things (IoT) comes with its own set of challenges. Security, privacy, and unified standards are a few key issues. In addition, each IoT product is comprised of at least three separate application components: the software embedded in the device, the backend big-data service, and the mobile application for the end user's controls. Each component is developed by a different team, using different technologies and practices, and deployed to a different stack/target - this makes the integration of these separate pipelines and the coordination of software upd...
Oct. 8, 2015 03:00 AM EDT Reads: 279