This is something I’ve been thinking about quite a bit lately, and in fact just a few days ago I was happy to learn that our paper, Disaster Recovery as a Cloud Service: Economic Benefits & Deployment Challenges, has been accepted into this year’s Workshop on Hot Topics in Cloud Computing (HotCloud 2010).  In our paper, we survey why we think cloud computing platforms are going to become increasingly popular for providing cheap disaster recovery services.

Clouds can be used to provide a variety of backup mechanisms ranging from cold replicas that are periodically synchronized up to hot standbys that are always in sync and can take over as soon as a failure is detected.  In practice, we think that a middle class of warm replicas is where the cloud can provide the greatest benefit.  A warm replica could be implemented as an EC2 VM that is not aways running, but whose disk (an EBS volume) is kept regularly up to date by a replication manager VM.  This replication manager can handle synchronizing the disk state for a large number of applications, but the customer will not have to pay for the active VM costs of those applications until a failure actually occurs and the VMs are booted up.

Check the paper for all the details, including a cost analysis of providing DR for various application types.

If you are interested, you can read the full version, or look through my slides.  It should make for absolutely thrilling bed time reading.

Here is the executive summary of what I’ve worked on:

Deployment

I start by looking at the deployment challenges of transitioning to a virtual environment and figuring out where to place VMs. This is an interesting area because virtualization can provide great benefits such as improved server consolidation, but also adds new challenges in the form of virtualization overheads.

MOVE (Modeling Overheads of Virtual Environments)

When you first consider transitioning from running applications natively to using virtual machines, it is important to understand how application resource requirements will change due to the overheads incurred by the virtualization layer. The MOVE project is designed to help predict these resource changes by building a regression model that relates the native and virtual platforms. This was work that I started during an internship at HP Labs in the summer of 2007, working with Lucy Cherkasova.

• Profiling and Modeling Resource Usage of Virtualized Applications. Timothy Wood, Ludmila Cherkasova, Kivanc Ozonat, and Prashant Shenoy. In proceedings of ACM International Conference on Middleware 2008.

Memory Buddies – Guiding VM placement with memory information

Once you know your resource requirements, you need to figure out where to put each of your virtual machines.  The Memory Buddies project tries to place virtual machines in order to maximize the amount of memory sharing that can be achieved — if VMs are running similar operating systems or applications, then the virtualization layer can share copies of these duplicated pages. In order to make this practical in a data center with many thousands of VMs, we propose an efficient fingerprinting technique that uses Bloom filters to quickly compare virtual machine memory contents.

• Memory Buddies: Exploiting Page Sharing for Smart Colocation in Virtualized Data Centers.  Timothy Wood, Gabriel Tarasuk-Levin, Prashant Shenoy, Peter Desnoyers, Emmanuel Cecchet, and Mark Corner. In proceedings of the International Conference on Virtual Execution Environments, VEE 2009.

Resource Management

Making data centers more efficient is a key concern throughout all of my work.  Virtualization’s greatest benefit comes in the promise of improved server utilization, leading to lower hardware costs and decreased energy consumption.

Sandpiper – automated VM loadbalancing

Alright, now we’ve figured out initial resource allocations and placements for all of our virtual machines, but those initial decisions may not be sufficient (or efficient) if an application’s workload changes over time. Sandpiper is a system which monitors the resource utilization and performance of a set of VMs and dynamically adjusts their resources or migrates them between hosts in order to prevent servers from becoming overloaded. This was the first project I worked on when I came to grad school, and now there are several commercial products out there doing similar things. We recently revised and extended this paper for a journal.

• Black-box and Gray-box Strategies for Virtual Machine Migration. Timothy Wood, Prashant Shenoy, Arun Venkataramani, and Mazin Yousif. Proceedings of the Fourth Symposium on Networked Systems Design and Implementation (NSDI), Cambridge, MA, April 2007.
• Sandpiper: Black-box and Gray-box Resource Management for Virtual Machines. Timothy Wood, Prashant Shenoy, Arun Venkataramani, and Mazin Yousif. To appear in Computer Networks Journal Special Issue on Virtualized Data Centers 2009. (Extended version of NSDI 07 paper)

Reliability

High performance systems are only useful if they are reliable. The remaining work for my thesis uses virtualization to decrease the cost of high availability and fault tolerance systems.

ZZ: Cheap Practical Byzantine Fault Tolerance

Byzantine Fault Tolerance is a way of providing very strong reliability guarantees, even in the face of malicious users or application components.  Unfortunately, BFT has a very high cost because each application request must be executed 2f+1 times in order to handle f simultaneous faults. In ZZ, we try to reduce this cost down to only f+1, by using an additional f sleeping VM replicas which are only woken up after a fault is detected.

• ZZ: Cheap Practical BFT Using Virtualization. Timothy Wood, Rahul Singh, Arun Venkataramani, and Prashant Shenoy. University of Massachusetts Technical Report TR14-08, 2008.

CloudNet: Wide Area Resource Management and Availability

My most recent work was started while at AT&T in Fall 2008, and looks at how VPNs can be combined with cloud computing platforms to make data center resources appear seamlessly connected to an enterprise’s existing infrastructure. We are further exploring this area to see how we can provide disaster recovery services so that if a data center becomes unavailable, the critical applications running within it can transparently fail over to servers at a different data center.

• The Case for Enterprise-ready Virtual Private Clouds. Timothy Wood, Alexandre Gerber, K.K. Ramakrishnan, and Jacobus van der Merwe. In proceedings of the Workshop on Hot Topics in Cloud Computing, HotCloud 2009.

You can find a copy of our paper here, and my slides here. Or you can get a summary of our ideas below.

Here are the three key features we feel are lacking from existing cloud platforms:

Security: Enterprises need strong security guarantees about the isolation of both the computation and network resources they are getting from the cloud. Existing systems rely on firewall rules for security that must be configured on a per-VM basis. While firewalls are a very powerful form of access control, they are incredibly fine grain and need to be carefully configured. This is a especially a problem in highly dynamic (ie. cloud) environments where new VMs are often being created or moved between servers.

Transparency: Another problem with cloud computing is that the resources it gives you are completely separated from the systems an enterprise is already running within its data centers. This makes it difficult to deploy applications since you can’t get the abstraction of having your cloud resources seamlessly connected to your existing LANs within the enterprise.

Resource Flexibility: There are two issues here. First, existing cloud platforms grant users very limited control over the network resources connected to their VMs.  This means, for example, that it is impossible to do something like reserve a high bandwidth link between a pair of VMs, and certainly not between a VM and the enterprise site that is going to be accessing it. Secondly, cloud platforms are not as flexible as they should be: if you replicate a VM to increase the processing power of an application you need to deal with these security and transparency issues all over again.

To help provide these three features, we propose the idea of a Virtual Private Cloud, that uses VPNs to securely connect groups of VMs within a cloud data center back to the enterprise sites that will use them.  VPNs make it so that the cloud resources are only accessible by other members of the same VPN.  This is a much coarser grain access control mechanism than firewalls, but it is much cleaner and we use MPLS based VPNs that have the benefit of being both highly scalable for enterprises that may run many hundreds or thousands of VMs, and that require no endhost configuration on the VMs — the VPN is entirely setup at the routers at the cloud and enterprise sites.  Finally, there is the option of using layer 2 VPNs (a Virtual Private LAN Service) to bridge the cloud computing data center and enterprise networks, giving the abstraction that cloud resources are seamlessly connected to the enterprise’s own LAN.

We are building a system that will implement this sort of system, and are exploring how it can be used to simplify VM migration over the WAN and for providing high availability services capable of seamlessly failing an application over from one cloud data center to another.