The Cloud Application Migration Lifecycle

The Cloud Application Migration Lifecycle

The Cloud Application Migration Lifecycle is a set of stages in a process, similar to the software development lifecycle, for the migration of legacy applications to the cloud. The requirements phase is replaced by the assessment phase and the traditional development (or coding) phase is replaced by the migration phase. The assessment phase is where you assess the complexity and readiness of your current applications for migration to a cloud environment. I go through everyone of these phases in detail in the Great Cloud Migration.

Cloud Price War Continues – Part 2

In the last week, we saw the cloud computing competition hit yet another new level in the race to zero!  By that, I mean the race to near-zero cost of computing.  Three big announcements last week:

  1. CISCO announced a 1 billion dollar investment into the IaaS cloud space to take on Amazon.  Of course, everyone is trying to take on the leader.
  2. Google announced huge price drops and the ability to combine its compute engine and app engine offering.  Also, challenging Amazon…
  3. Amazon counter-punched all comers with another price drop

These are exciting times for the cloud computing space!  Stay tuned as more heavy-weights continue to slug it out for leadership in the cloud!

Hortonwork’s Hadoop Hype is Misleading

Hortonworks is making a play for “Hadoop everywhere” by pushing for Hadoop to augment a data warehouse in the enterprise and thereby create a “data lake”.  See their report here: http://hortonworks.com/blog/enterprise-hadoop-journey-data-lake/

The concept of a data lake basically says “store everything” in hadoop and you can access it at any time, do a “schema-on-read” after the fact and discover new insights at will.  What this ignores is the fact that the Hadoop HDFS is optimized for map reduce jobs on large homogeneous data sets.  That will not work for a “store everything” strategy.  Additionally, while the “schema on read” moniker gets thrown around a lot – I have yet to see many practical examples on the net that prove this.  I understand that Hive uses it but when you look at Hive tutorials they all still create the schema up front though I get it that you could change the schema afterwards because the schema is only enforced on the read.  Well, enforcing on the read and defining on the read are two different things.  I will be delving into this in much more detail in the ensuing weeks…

Overall, this report by Hortonworks really stretches the boundaries of Hadoop’s current capabilities and, to me, crosses the line.  Senior executives don’t need this type of far-fetched promises just to push a “hadoop-everywhere” agenda.  The simple truth should be – you use technology where it is best suited and NOT where the marketeers want you to use it.  Buyer beware.

The Cloud Price War Rages On!

The Cloud Price War Rages On!

Google just drastically slashed prices on its cloud storage which puts pressure on dropbox, box, skydrive and the myriad of other cloud storage vendors.  Of course, this is part of the larger trend towards do-it-yourself IT services and very-low-cost cloud computing.  As in the precedent of electricity, the price of cloud computing will continue to drop until every business and consumer realizes that it is much cheaper, just as secure and more reliable to do all their computing in the cloud.  Just as business no longer have their own power plant providing power to their business, most business and individuals will soon (within 10 years) no longer have our own data centers and servers.

The History of Cloud Computing

The History of Cloud Computing

Do you know the history of cloud computing and the trends that shaped it? The timelines are from my book the Great Cloud Migration and show all the key events in the history of cloud computing. Understanding the history is important to understanding the major influencing factors and forces that shape the current landscape.
Here is a summary of the events:
* 1961 – Professor John McCarthy propose computing be organized as a “public utility”.
* 1964 – IBM CP-40 Operating Systems uses Virtualization
* 1972 – IBM VM/370 is a virtual machine operating system
* 1991 – The World Wide Web popularizes the internet
* 1997 – First use of the term “Cloud Computing”
* 1999 – Salesforce.com and VMWare launch
* 2002 – Amazon Web Services (AWS) launches and SOA emerges
* 2003 – Seminal Google File System (GFS) paper published
* 2005 – Google Maps is a watershed event for browser-based apps (introduces AJAX).
* 2006 – Hadoop launched, shortly followed by Amazon S3 and Amazon EC2
* 2008 – Google App Engine launches
* 2009 – Microsoft Azure launches
* 2010 – GSA’s apps.gov launches (and federal Cloud-first policy).