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Hyper-V Live Migration Across Data Centers

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There has recently been a lot of press, about executing virtual machines live migrations across long-distanced data centers, that herald VMware’s limited support for vMotion across Data Centers, or “long-distance vMotion” as I have seen it called. The details of the solution can be found on Cisco’s website here. While I think that is just great, I’d like to remind people that Microsoft Hyper-V has this same functionality today and has a lot less requirements and restrictions than VMware’s long-distance vMotion.

Where VMware has VMwareHA, vMotion and Site Recovery Manager (SRM) to take care of virtual machine availability, Microsoft provides the same functionality with Windows Server Failover Clustering and in fact in some cases goes beyond what VMware can provide in terms of virtual machine availability as I described in a previous post.

What I’d like to focus on today is Microsoft’s competitive offering to “long-distance vMotion”. To achieve the same functionality in Hyper-V, you simply deploy a multi-site Hyper-V cluster using Windows Server Failover Clustering and your favorite host or storage based replication solution that is certified to work in a Windows Server 2008 multi-site cluster. By doing this, you can use your existing network infrastructure and your existing storage infrastructure to do Live Migrations across data centers. As far as requirements, they really are the same as any multi-site cluster, except I would recommend that you span your subnets to avoid client reconnection issues that occur when moving a virtual machine to a new subnet, as the clients could cache to old IP address until the TTL expires.

A demonstration video of Live Migration across data centers using Windows Server 2008 R2 Hyper-V and SteelEye DataKeeper Cluster Edition can be seen here.

Reproduced with permission from https://clusteringformeremortals.com/2009/09/17/hyper-v-live-migration-across-data-centers/

Making Sense Of Virtualization Availability Options

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What Are The Virtualization Availability Options?

Microsoft Windows Server 2008 R2 and vSphere 4.0 are newly released. Let’s take a look at some Virtualization Availability Options when considering the availability of your virtual servers and the applications running on them.

I also will take this opportunity to describe some of the features that enable virtual machine availability. Additionally, I have grouped these features into their function roles to help highlight their purpose.

Planned Downtime

Live Migration and VMware’s VMotion are both solutions that allow an administrator to move a virtual machine from one physical server to another with no perceivable downtime. There is one key thing to remember. The move must be a planned event in order to move a virtual machine from one server to another without any downtime. A planned event is that the virtual machine’s memory is synchronized between the servers, before the actual switchover occur. This is true of both Microsoft’s and VMware’s solutions. Also keep in mind that both of these technologies require the use of shared storage to hold the virtual hard disks (VMDK and VHD files), which limits Live Migration and VMotion to local area networks. This also means that any downtime planned for the storage array must be handled in a different way. Important to note if you want to limit the impact to your virtual machines.

Unplanned Downtime

Microsoft’s Windows Server Failover Clustering and VMware’s High Availability (HA) are solutions that are available to protect virtual machines in the event of unplanned downtime. Both solutions are similar. They monitor virtual machines for availability. The VMs are moved to standby node if there is a failure. Then, the machines are rebooted for this recovery process. There was no time to sync the memory before failover.

Disaster Recovery

How do I recover my virtual machines in the event of a complete site loss? The good news is that virtualization makes this process a whole lot easier. A virtual machine is simply a file that can picked up and moved to another server. Up to this point, VMware and Microsoft are pretty similar in their availability features and functionality. However, here is where Microsoft really shines. VMware offers Site Recovery Manager which is a fine product. But is limited in support to only SRM-certified array-based replication solutions. Also, the failover and failback process is not trivial and can take the better part of a day to do a complete round trip from the DR site back to the primary data center. It does have some nice features like DR testing. In my experience with Microsoft’s solution for disaster recovery they have a much better solution when it comes to disaster recovery.

Microsoft’s Hyper-V DR solution

Microsoft’s Hyper-V DR solution is Windows Server Failover Clustering in a multi-site cluster configuration (see video demonstration). In this configuration, the performance and behavior is the same as a local area cluster, yet it can span data centers. Essentially, you can actually move your virtual machines across data centers with little to no perceivable downtime. Failback is the same process, just point and click to move the virtual machine resource back to the primary data center. There is no built-in “DR Testing”. Although I think it is preferable to do an actual DR test in just the matter of a minute or two with no perceivable downtime.

Host-Based Replication Vendors

One other thing I like about WSFC multi-site clusters is that the replication options include not only array-based replication vendors, but also host-based replication vendors. This really gives you a wide range of replication solutions in all price ranges and does not require that you upgrade your existing storage infrastructure.

Fault Tolerance

Fault tolerance basically eliminates the need to reboot a virtual machine in the event of an unexpected failure. VMware has the edge here in that it offers VMware FT. There are a few other 3rd party hardware and software vendors that play in this space as well. There are plenty of limitations and requirements when it comes to implementing FT systems. This is an option if you need to ensure a hardware component failure results in zero downtime vs. the minute or two it takes to boot up a VM in a standard HA configuration. You probably want to make sure that your existing servers are already chock full of hot standby CPUs, RAM, power supplies, etc. And you have redundant paths to the network and storage. Otherwise you may be throwing good money after bad. Fault tolerance is great for protection from hardware failures. What happens if your application or the virtual machine’s operating system is behaving badly? That is when you need application level clustering as described below.

Application Availability

Everything I have discussed up to this point really only takes into consideration the health of your physical servers and your virtual machines as a whole. This is all well and good, however, what happens if your virtual machine blue screens? Or what if that latest SQL service pack broke your application? In those cases, none of these solutions are going to do you one bit of good. For those most critical applications, you really must cluster at the application layer. Look into clustering solutions that run within the OS on the virtual machine vs. within the hypervisor. In the Microsoft world, this means MSCS/WSFC or 3rd party clustering solutions. Your storage options, when clustering within the virtual machine, are limited in scope to either iSCSI targets or host-based replication solutions.  Currently, VMware really does not have a solution to this problem. It would defer to solutions that run within the virtual machine for application layer monitoring.

Summary

With the advent of virtualization, it is really not a question of if you need availability. And more of a question of what Virtualization Availability Options will help meet your SLA and/or DR requirements. I hope that this information helps you make sense of the availability options available to you.

Reproduced with permission from https://clusteringformeremortals.com/2009/08/14/making-sense-of-virtualization-availability-options-2/

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Part 1: AI is All About the Data: The Shift from Computer Science to Data Science

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This is the first post in a two-part series. Part 2 is available here. We are highlighting the shifting roles of IT as artificial intelligence (AI) driven data science evolves.

You may think that the words “artificial intelligence” or “machine learning” sound like trendy buzzwords. In reality, much of the hype about this technology is true. Unlike past periods of excitement over artificial intelligence, today’s interest is no longer an academic exercise. Now, IT has a real-world need for faster solutions to problems that are too complex for humans alone. With virtualization, IT teams gain access to a huge variety and volume of real-time machine data. They want to use to understand and solve the issues in their IT operations environments. What’s more, businesses are seeing the value in dedicating budget and resources to leverage artificial intelligence, specifically machine learning, and deep learning. They are using this powerful technology to analyze this data to increase efficiency and performance.

Data Science to the Rescue Artificial Intelligence

The complexity of managing virtual IT environments is stressing out traditional IT departments. However, IT pros are discovering that the solution lies in the data and in the artificial intelligence-based tools that can leverage it. Most are in the process of understanding how powerful data is in making decisions about configuring, optimizing, and troubleshooting virtual environments. Early stage virtualization environments were monitored and managed in the same way physical server environments were. That is, IT pros operated in discrete silos (network, storage, infrastructure, application). They used multiple threshold- based tools to monitor and manage them focusing on individual metrics – CPU utilization, memory utilization, network latency, etc. When a metric exceeds a preset threshold, these tools create alerts – often thousands of alerts for a single issue.

If you compare a computer science approach to a data science (AI) approach, several observations become clear. IT based the traditional approach on computer science principles that they have used for the last 20 years. This threshold-based approach originated in relatively static, low-volume physical server environments. IT staff analyze individual alerts to determine what caused the problem, how critical it is, and how to fix it. However, unlike physical server environments, components in virtual environments are highly interdependent and constantly changing. Given the enormous growth of virtualized systems, IT pros cannot make informed decisions by analyzing alerts from a single silo at a time.

Artificial Intelligence, Deep Learning, and Machine Learning

To get accurate answers to key questions in large virtualized environments, IT teams need an artificial intelligence -based analytics solution. They need a solution capable of simultaneously considering all of the data arising from across the IT infrastructure silos and applications. In virtual environments, components share IT resources and interact with one another in subtle ways. You need a solution that understands these interactions and the changing patterns of their behavior over time. It should understand how it changes through a business week and as seasonal changes occur over the course of a year. Most importantly, IT needs AI-driven solutions that do the work for IT. It should identify root causes of issues, recommend solutions, predict future problems, and forecast future capacity needs.

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Understanding The Emerging field of AIOps – Part II

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This is the second post in a two-part series highlighting how AIOps is changing IT performance optimization. Part 1 explained the basic principles of AIOps. The original text of this series appeared in an article on Information Management.  Here we look at the business requirements driving the trend to AIOps.

Why do businesses need AIOps?

IT pros move more of their business-critical applications into virtualized environments. As a result, finding the root cause of application performance issues is more complicated than ever.  IT managers have to find problems in a complex web of VM applications, storage devices, network devices and services. These components that are connected in ways IT can’t always understand.

Often, the components a VMware or other virtual environment are interdependent and intertwined. When an IT manager moves a workload or makes a change to one component, they cause problems in several other components without their knowledge. If the components are in different so-called silos (network, infrastructure, application, storage, etc.), IT pros have even more trouble figuring out the actual cause of the problem.

Too Many Tools Required to Find Root Causes of Performance Issues

AIOPs Survey
SIOS AIOPS Survey

The process of correlating IT performance issues to its root cause is  difficult, if not impossible for IT leaders.  According to a recent SIOS report, 78 percent of IT professionals are using multiple tools to identify the cause of application performance issues in VMware. For example, they are using tools such as application monitoring, reporting and infrastructure analytics.

Often, when faced with an issue, IT assembles a team with representatives from each IT silo or area of expertise. Each team member uses his or her own diagnostic tools and looks at the problem their own silo-specific perspective. Next, the team members compare the results of their individual analyses identify common elements. Frequently, this process is highly manual. They look at changes in infrastructure that show up in several analyses in the same time frame. As a result, IT departments are wasting more and more of their budget on manual work and inaccurate trial-and-error inefficiencies.

To solve this problem and reduce wasted time, they are using an AIOPs approach. AIOps applies artificial intelligence (i.e., machine learning, deep learning) to automate problem-solving. The AIOPs trend is an important shift away from traditional threshold-based approaches that measure individual qualities (CPU utilization, latency, etc.) to a more holistic data-driven approach. Therefore, IT managers are using analytics tools to analyze data across the infrastructure silos in real-time. They are using advanced deep learning and machine learning analytics tools that learn the patterns of behavior between interdependent components over time.  As a result, they can automatically identify behaviors between components that may indicate a problem. More importantly, they automatically recommend the specific steps to resolve problems.

What’s Next for AIOps?

Virtual IT environments are creating an enormous volume of data and an unprecedented level of complexity. As a result, IT managers cannot manage these environments effectively with traditional, manual methods. Over the next few years, the IT profession will rapidly move from the traditional computer science approach to a modern “data science” AIOPs approach. For IT teams, this means embracing machine learning-based analytics solutions, and understanding how to use it to solve problems efficiently and effectively. Finally, executives need to work with their IT departments to identify to right AIOps platform for their business.

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Optimize SQL Server Performance and 5 Other Things to Do at VMworld 2016

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#1. Experience an Augmented Reality Guided Tour of SIOS iQ Machine Learning Analytics Solution for SQL Server Performance

Root cause of SQL Server performance issues with SIOS iQ machine learning analytics
SIOS iQ machine learning analytics with enhanced reality headset.

Try to improve your SQL Server performance in this fun augmented reality demo. See how you can save money by solving performance issues in one click. Identify wasted virtual resources.  Optimize your VMware application environment.

#2. Attend Breakout Session

SIOS CTO Sergey Razin, Ph.D., and SQL Sentry’s Brian Davis present – Use Cases in Performance Root Cause Resolution for SQL Server. They show you how to use vRealize Operations Manager, SIOS iQ Analytics, and SQL Sentry Performance Advisor. Learn best practices for identifying and resolving application performance issues in SQL Server. Identify SQL Server performance issues using VMware vRealize Operations Manager, characterize infrastructure root causes and recommended solutions with SIOS iQ machine learning analytics solutions, and define application-specific root causes with SQL Sentry Performance Advisor.  9/1/2016 for Use Cases in SQL Server Performance Root Cause Resolution.


#3.  Stop by SIOS Speaking Session in Tegile Booth #2057 to Learn Keys for Implementing Cost-Efficient Storage Accelerationtegile performance

SIOS Director of Field Engineering will be a guest presenter in the
Tegile booth #2057. He will talk about using machine learning analytics for a successful storage acceleration strategy. He will show how to use it to accelerate SQL Server performance.


#4.  Stop by Book Signing with vExpert Michael Corey in SIOS Booth #2361corey book

VMware vExpert and noted author Michael Corey will be in the SIOS booth on August 30 to sign his book Virtualizing SQL Server with VMware: Doing IT Right. The first 10 attendees to arrive at the book signing will receive a free copy. The book is also available in the show bookstore.


#5. Join Guest Presenter: SQL Sentry in SIOS Booth #2361 for Demo of Integration of SIOS iQ and SQL Sentry Performance Advisor

SQL_Sentry

Stop by SIOS Booth #2361 on Monday, August 29 at 2:00 PM-3:00 PM and Tuesday, August 30 at 11:00 AM to noon to see a demonstration by SQL Sentry’s Brian Davis for a live demonstration of integration of SIOS iQ with SQL Sentry Performance Advisor. Learn how this integration bridges a critical gap between IT infrastructure administrators and SQL Server administrators. See how easy it is to find and resolve SQL Server performance issues with SIOS iQ and SQL Sentry.