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rackspace: All content tagged as rackspace in NoSQL databases and polyglot persistence

Rackspace: BYOD to Your Preferred Storage

While Amazon Web Services approach is bring-your-own-data to our storage and processing solutions, Rackspace’s strategy seems to be “whatever popular NoSQL storage engine you like, we have your back. Just bring your data“.

Last month Rackspace bought MongoDB hosting provider ObjectRocket and now they acquired Exceptional Cloud Service which brings Redis hosting on board.

It’s difficult to say how well is Amazon’s strategy working as the company doesn’t do a lot to get their customers’ case studies out there—I still need to find a list of 10 companies that are using Amazon Dynamo. But this doesn’t mean a thing. On the other hand, I can see Rackspace’s strategy working and getting a lot of traction considering they’re looking after the most popular NoSQL tools.

✚ The Register writes about this acquisition too: Rackspace gobbles Exceptional Cloud Services for Redis smarts. I assume many others are asking the same question:

So, with Redis and MongoDB due to make their way into the Rackspace cloud proper, what other technologies are catching the web hoster turned cloud whisperer’s eyes?

Original title and link: Rackspace: BYOD to Your Preferred Storage (NoSQL database©myNoSQL)


MongoDB Represents the Perfect Opportunity for Rackspace's Fanatical Support

Rackspace in a post explaining why they bought into MongoDB through the acquisition of ObjectRocket:

MongoDB is easy to get started, but complex to manage and scale.

I bet 10gen loves reading things like this. It also serves well the adoption of MongoDB.

Original title and link: MongoDB Represents the Perfect Opportunity for Rackspace’s Fanatical Support (NoSQL database©myNoSQL)

via: http://www.rackspace.com/blog/why-mongodb/


Rackspace Buys MongoDB Hosting Provider ObjectRocket

According to GigaOm, Rackspace has acquired MongoDB hosting provider ObjectRocket, of which I’ve heard about only recently when I learned something absolutely fascinating:

The cloud is broken. It’s not designed to properly run persistent data stores like MongoDB. ObjectRocket is designed from the ground up to fix this problem.

Rackspace first thing to do after signing the docs is to take this page out.

Original title and link: Rackspace Buys MongoDB Hosting Provider ObjectRocket (NoSQL database©myNoSQL)


Amazon EBS, SSD, and Rackspace IOPS Per Dollar

Staying on the subject of IOPS in the cloud, Jeff Darcy did some testing with GlusterFS against Amazon EBS, Amazon SSD, Storm on Demand SS, and Rackspace instance storage and computed for each IOPS/$:

  • Amazon EBS: 1000 IOPS (provisioned) for $225/month or 4.4 IOPS/$ (server not included)
  • Amazon SSD: 4300 IOPS for $4464/month or 1.0 IOPS/month (that’s pathetic)
  • Storm on Demand SSD: 5500 IOPS for $590/month or 9.3 IOPS/$
  • Rackspace instance storage: 3400 IOPS for $692/month (8GB instances) or 4.9 IOPS/$
  • Rackspace with 4x block storage per server: 9600 IOPS for $811/month or 11.8 IOPS/$ (hypothetical, assuming CPU or network don’t become bottlenecks)

Original title and link: Amazon EBS, SSD, and Rackspace IOPS Per Dollar (NoSQL database©myNoSQL)

via: http://pl.atyp.us/wordpress/index.php/2012/10/rackspace-block-storage/


Whirr and Hadoop Quickstart Guide: Automating a Rackspace Hadoop Cluster

Even if most of the examples show Whirr in action on the Amazon cloud, Whirr it’s cloud-neutral. Bob Gourley uses Whirr to fire up a CDH1 cluster on Rackspace.


  1. Cloudera Distribution of Hadoop. 

Original title and link: Whirr and Hadoop Quickstart Guide: Automating a Rackspace Hadoop Cluster (NoSQL database©myNoSQL)

via: http://ctovision.com/2012/01/hadoop-quickstart-use-whirr-to-automate-standup-of-your-distributed-cluster-on-rackspace/


Cassandra, Zookeeper, Scribe, and Node.js Powering Rackspace Cloud Monitoring

Paul Querna describes the original architecture of Cloudkick and the one that powers the recently announced Rackspace Cloud Monitoring service:

Development framework: from Twisted Python and Django to Node.js

Cloudkick was primarily written in Python. Most backend services were written in Twisted Python. The API endpoints and web server were written in Django, and used mod_wsgi. […] Cloud Monitoring is primarily written in Node.js.

Storage: from master-slave MySQL to Cassandra

Cloudkick was reliant upon a MySQL master and slaves for most of its configuration storage. This severely limited both scalability, performance and multi-region durability. These issues aren’t necessarily a property of MySQL, but Cloudkick’s use of the Django ORM made it very difficult to use MySQL radically differently. The use of MySQL was not continued in Cloud Monitoring, where metadata is stored in Apache Cassandra.

Even more Cassandra:

Cloudkick used Apache Cassandra primarily for metrics storage. This was a key element in keeping up with metrics processing, and providing a high quality user experience, with fast loading graphs. Cassandra’s role was expanded in Cloud Monitoring to include both configuration data and metrics storage.

Event processing: from RabbitMQ to Zookeeper and a bit more Cassandra

RabbitMQ is not used by Cloud Monitoring. Its use cases are being filled by a combination of Apache Zookeeper, point to point REST or Thrift APIs, state storage in Cassandra and changes in architecture.

And finally Scribe:

Cloudkick used an internal fork of Facebook’s Scribe for transporting certain types of high volume messages and data. Scribe’s simple configuration model and API made it easy to extend for our bulk messaging needs. Cloudkick extended Scribe to include a write ahead journal and other features to improve durability. Cloud Monitoring continues to use Scribe for some of our event processing flows.

Original title and link: Cassandra, Zookeeper, Scribe, and Node.js Powering Rackspace Cloud Monitoring (NoSQL database©myNoSQL)

via: http://journal.paul.querna.org/articles/2011/12/17/technology-cloud-monitoring/


Reliable, Scalable, and Kinda Sorta Cheap: A Cloud Hosting Architecture for MongoDB

Using MongoDB replicate sets:

At Famigo, we house all of our valuable data in MongoDB and we also serve all requests from Amazon EC2 instances. We’ve devoted many mental CPU cycles to finding the right architecture for our data in the cloud, focusing on 3 main factors: cost, reliability, and performance.

Original title and link: Reliable, Scalable, and Kinda Sorta Cheap: A Cloud Hosting Architecture for MongoDB (NoSQL database©myNoSQL)

via: http://www.codypowell.com/taods/2011/08/a-cloud-hosting-architecture-for-mongodb.html


Redis Part of the Rackspace OpenStack

Redis seems to be more and more associated with the cloud:

Soren Hansen (Rackspace) ☞ mentions Redis:

OpenStack (so far, at least) has two main components to it: A “compute” compenent called “Nova” and a “storage” component called “Swift”.

[…]

Nova is written in Python and uses Twisted.

[…]

Nova currently uses Redis for its key-value store. Nova can use either LDAP or its key-value store for its user database.