ion to implement a hybrid cloud. In this blog post we will explain the technical details on how Open vStorage can be used in a hybrid cloud context.
For frequent readers of this blog the different Open vStorage components should not hold any secrets anymore. For newcomers we will give a short overview of the different components:
- The Edge: a lightweight software component which exposes a block device API and connects across the network to the Volume Driver.
- The Volume Driver: a log structured volume manager which converts blocks into objects.
- The ALBA Backend: an object store optimized as backend for the Volume Driver.
Let’s see how these components fit together in a hybrid cloud context.
The 2 main components of any hybrid cloud are an on-site, private part and a public part. Key in a hybrid cloud is that data and compute can move between the private and the public part as needed. As part of this thought exercise we take the example where we want to store data on premises in our private cloud and burst with compute into the public cloud when needed. To achieve this we need to install the components as follows:
The Private Cloud part
In the private cloud we install the ALBA backend components to create one or more storage pools. All SATA disks are gathered in a capacity backend while the SSD devices are gathered in a performance backend which accelerates the capacity backend. On top of these storage pools we will deploy one or more vPools. To achieve this we run a couple of Volume Driver instances inside our private cloud. On-site compute nodes with the Edge component installed can use these Volume Drivers to store data on the capacity backend.
The Public Cloud part
For the Public Cloud part, let’s assume we use Amazon AWS, there are multiple options depending on the desired performance. In case we don’t require a lot of performance we can use an Amazon EC2 instance with KVM and the Edge installed. To bring a vDisk live in Amazon, a connection is made across the internet With the Volume Driver in the private cloud. Alternatively an AWS Direct Connect link can be used for a lower latency connection. Writes to Vdisk which is exposed in Amazon will be sent by the Edge to the write buffer of the Volume Driver. This means that writes will only be acknowledged to the application using the vDisk once the on premises located write buffer has received the data. Since the Edge and the Volume Driver connect over a rather high latency link, the write performance isn’t optimal in this case.
In case more performance is required we need an additional Storage Optimized EC2 instance with one or more NVMe SSDs. In this second EC2 instance a Volume Driver instance is installed and the vPool is extended from the on-site, private cloud into Amazon. The NVMe devices of the EC2 instance are used to store the write buffer and the metadata DBs. It is of course possible to add some more EBS Provisioned IOPS SSDs to the EC2 instance as read cache. For an even better performance, use dedicated Open vStorage powered cache nodes in Amazon. Since the write buffer is located in Amazon the latency will be substantially lower than in the first setup.
As last part of this blog post we want to discuss some use cases which can be deployed on top of this hybrid cloud.
Note that based upon the above architecture, a vDisk in the private cloud can be cloned into Amazon. The cloned vDisk can be used for business analytics inside Amazon without impacting the live workloads. When the analytics query is finished, the clone can be removed. The other way around is of course also possible. In that case the application data is stored in Amazon while the business analytics run on on-site compute hardware.
Another use case is disaster recovery. As disaster recovery requires data to be on premises but also in the cloud additional instance need to be added with a large amount of HDD disks. Replication or erasure coding can be used to spread the data across the private and public cloud. In case of a disaster where the private cloud is destroyed, one can just add more compute instances running the Edge to bring the workloads live in the public cloud.
A last use case we want to highlight is for users that want to use public clouds but don’t thrust these public cloud providers with all of their data. In that case you need to get some instances in each public cloud which are optimized for storing data. Erasure coding is used to chop the data in encrypted fragments. These fragments are spread across the public clouds in such a way that non of the public clouds store the complete data set while the Edges and the Volume Drivers still can see the whole data set.