A Reference Architecture for Cloud Storage

Over the last twelve months, the SNIA Cloud Storage Technical Working Group has been busily defining an industry-wide standard for cloud data storage and management. This standard, the Cloud Data Management Interface (CDMI), is currently available for public review, with an updated draft scheduled for release in later in December.

The below diagram illustrates how the CDMI standard fits into emerging cloud ecosystems:

One of the most important aspects to understand about the CDMI standard is that it is not intended to replace existing cloud data access standards. This allows CDMI to be used with existing and new clouds that store data via non-CDMI protocols such as Amazon S3's API and traditional file system protocols such as NFS, CIFS, WebDAV.

CDMI builds on top of these existing data access paths to bring rich management semantics for data in the cloud, and facilitates emerging cloud use-cases including cloud peering, federation and differentiated services. In addition, CDMI provides standard mechanisms to enable the integration of clouds with other external systems (or clouds) for notification, workflow, audit, billing and authorization purposes.

A Reference Architecture for a CDMI-Native Cloud Storage

In order to illustrate how CDMI can enable to creation of next-generation cloud architectures, I've put together an example reference architecture for a CDMI-based cloud storage system, illustrating the different components and primary data flows that would be found in most cloud implementations that fully support CDMI.

The below diagram shows a logical representation of the major components of a cloud storage system build around the CDMI standard:

Looking at the diagram, we have the following major logical components:

Filesystem Clients and Protocol Gateways

CIFS, NFS, FTP, WebDAV, iSCSI, Fibre Channel, FCoE and other standard network file and block protocol clients can be attached to cloud storage via protocol gateways. These protocol gateways translate non-cloud storage protocols into CDMI cloud transactions, and are notified about changes to management metadata in the cloud such that it can export portions of the cloud via these non-cloud protocols.

Existing Cloud Clients and API Protocol Gateways

Existing cloud clients programmed to use cloud protocols such as Amazon's S3 HTTP API can communicate with a CDMI storage cloud through an API protocol gateway. An API protocol gateway translates these non-CDMI cloud storage protocols into CDMI cloud transactions. When a given non-CDMI cloud protocol supports features not directly supported by CDMI, the API gateway can either map these operations into CDMI operations, or use vendor extensions to CDMI to implement the required functionality.

CDMI Clients

Clients that implement the CDMI protocol natively can connect directly to the CDMI storage cloud without having to go through any protocol translation layers. These clients can access the full set of CDMI functionality, and can access and manage content stored by all clients, even if the content was not stored via CDMI.

Low Latency Object Stores

In almost all implementations, CDMI transactions will be routed to one or more low-latency object stores that are able to quickly satisfy storage and retrieval requests. Multiple low-latency object stores will often be connected together, peered, or federated, to allow for data dispersion, replication and other data management functions. Once safely stored, the cloud will be ready to interpret the data system metadata that determines the optimal placement characteristics desired by the cloud user.

High Latency Object Stores

Some vendors may choose to implement higher latency object stores, such as power-managed disk or tape storage tiers. Stored objects will typically be migrated to these stores from low-latency object stores based on the CDMI data system metadata.

Object Catalogue

In order to keep track of the locations where cloud objects are stored, and the namespace in which the objects are stored, many CDMI implementations will include an object catalogue. This catalogue keeps track of objects across all object stores (and external peered and federated clouds), and provides CDMI functions such as object notification, query and billing. Notification provides updates to internal cloud components and to external systems to enable additional cloud functions such as indexing, e-discovery, classification, object processing, format conversion, workflow and advanced analytics.

Data System Manager

In a CDMI system, the data system manager is responsible for interpreting the data system metadata specified for objects and containers through the CDMI interface, and performing operations to attempt to satisfy the requests for data dispersion, redundancy, geographic placement, performance, etc. Each time an object is created or modified, the data system manager will be notified, and if the constraints specified are not met, it can further replicate or migrate content across object stores or clouds. The SDSC iRODS (Integrated Rules-Oriented Data System) is an example of an existing Data System Manager that can play this role within or to federate clouds.

Putting it all Together

When you put all of these components together, you get a cloud that fully implements the main components of the CDMI specification, and provides rich cloud functionality. On top of this foundation, a cloud vendor can innovate and create additional value added services, such as integration with computing clouds, cloud virus scanning, QoS monitoring, and much, much more.

This degree of flexibility demonstrates much of the value that CDMI has to offer the industry, both to cloud users and vendors, and it will be exciting to see these sorts of interoperable architectures emerge over time as CDMI becomes adopted and the cloud marketplace matures.


Anonymous said...


Great blog post. Thanks!

-- mark

M. Behrens said...

Interesting. I like the simple REST mechanism for data storage that CDMI provides. A just have a quick question - would you envision that this interface would be a good candidate to be used as the access point for datastores such as Hadoop?

David Slik said...

I'm glad that you have found the spec to your liking — We've spent a lot of time trying to make it both simple and powerful.

With respect to emerging cloud storage models, such as noSQL stores, key-value stores, and Hadoop/HDFS, we see that there is a significant amount of value that CDMI can bring to these worlds, however, since they are still in their early stage, the working group's view was that the interface is premature to standardize at this point.

Once the more common access methods are standardized in CDMI, we intend to return to these areas and work on this.

Specifically for HDFS, one could relatively easily make a Hadoop cluster accessible via CDMI by implementing a CDMI interface that provides CDMI read and write access to the cluster. Alternatively, HDFS could be another export type.