Curiosity drives cloud computing

I like asking questions and I like getting good answers even better. It is because of that, I now have a love / hate relationship with search engines. Most of the time they give me a 50% answer, a kind of direction, a suggestion, a kind of coaching to the real answer. It is like the joke about the consultant; “the right answer must be in there somewhere, because he or she gives me so many responses”.

PH03797IIn spite of all kind of promises, search engines have not really increased their intelligence. Complex questions with multiple variables are still nearly impossible to get answered and the suggestions to improve my question are mostly about my spelling or because the search engine would have liked a different subject to be questioned on.

So nothing really good is coming from search engines then? Well most arguably search engines have brought us cloud computing and a very powerful access to lots and lots and lots of data, otherwise known as ‘the world wide web’.

No wonder I envision that powerful access and cloud computing are the two most important values we want to keep while increasing the capacity and intelligence to do real analytics on large data sets.

In a whitepaper of the Atos Scientific Community, these 2 elements are explored in great depth:

  • Data Analytics needs cloud computing to create an “Analytics as a Service” – model because that model addresses in the best way how people and organizations want to use analytics.
  • This Data Analytics as a Service – model (DAaaS) should not behave as an application, but it should be available as a platform for application development.

The first statement on the cloud computing needs suggests we can expect analytics to become easily deployed, widely accessible and not depending on deep investments by single organizations; ‘as a service’ implies relatively low cost and certainly a flexible usage model.

The second statement about the platform capability of data analytics however, has far reaching consequences for the way we implement and build the analytic capabilities for large data collections.

Architecturally, and due to the intrinsic complexities of analytical processes, the implementation of DAaaS represents an important set of challenges, as it is more similar to a flexible Platform as a Service (PaaS) solution than a more “fixed” Software as a Service (SaaS) application

It is relatively easy to implement a single application that will give you an answer to a complex question; many of the applications for mobile devices are built on this model (take for example the many applications for public transport departure, arrival times and connections).

This “1-application-1-question” approach is in my opinion not a sustainable business model for business environments; we need some kind of workbench and toolkit that is based on a stable and well defined service.

The white paper describes a proof of concept that has explored such an environment for re-usability, cloud aspects and flexibility. It also points to the technology used and how the technology can work together to create ‘Data Analytics as a Service’.

This blog post was previously published at


The PaaS cloud computing lock-in and how to avoid it

Cloud Computing changed from choosing an easy solution, into making a difficult decision.

The reason is the proliferation of cloud offerings at all layers; today we do not only find ‘everything-as-a-service’ cloud solutions, but also ‘everything-is-tailored-for-your-specific-situation-as-a-service’ tagged as cloud solutions.

Is this good? I do not think so.

My main objection is that you will end up with a cloud solution that is no different than any solution you have previously designed and installed yourself, at a cheaper rate and lower quality SLA.

True cloud solutions should not only focus on cost reduction, increased agility and flexible capabilities. You should also be buying something that supports portability between the private and public computing domain, and across different vendor platforms.

In early cloud solutions, mainly the ones focussing on Infrastructure-as-a-service, this portability has been heavily debated (remember the ‘Open Cloud Manifesto’?) and in the end we concluded that server virtualization solved a lot of the portability issues (I am simplifying of course).

We also had Software-as-a-service and some publications showed that the portability could be addressed by looking at standardized business process definitions and data normalisation (again, I am simplifying).
Now the Atos Scientific Community has published a whitepaper that looks at the most complex form of cloud computing; Platform-as-a-service.

PaaS offerings today are diverse, but they share a vendor lock-in characteristic. As in any market for an emerging technology, there is a truly diverse array of capabilities being offered by PaaS providers, from supported programming tools (languages, frameworks, runtime environments, and databases) to various types of underlying infrastructure, even within the capabilities available for each PaaS

So a common characteristic that can be extracted of all this diversity is the fact of PaaS users currently are being bound to the specific platform they use, making the portability of their software (and data) created on top of these platforms difficult.

As a result we see a slow adoption of PaaS in the enterprise; only those groups that have a very well defined end-user group are looking at PaaS – and mostly for the wrong reason: ‘just’ cost saving through standardization.

In the Atos Scientific Community whitepaper they are identified as:

Two primary user groups which benefit from using Cloud at the Platform as a Service level: Enterprises with their own internal software development activities and ISVs interested in selling SaaS services on top of a hosted PaaS.”

The current situation where PaaS is mostly resulting in a vendor lock-in scenarios is holding back the full potential for applications on a PaaS.

By introducing a general purpose PaaS, we would allow a comprehensive, open, flexible, and interoperable solution that simplifies the process of developing, deploying, integrating, and managing applications both in public and private clouds.

Such an architecture is proposed and explained in detail in the whitepaper; it describes the desired capabilities and building blocks that need to be established and it also offers an analysis of market trends and existing solutions, in order to establish a future vision and direction for PaaS, as well as outlining the business potential of such a solution.

We can all continue to feel positive about the power and the business potential of cloud computing.

Changing your cost base from capex to opex, increasing your speed in your go-to-market strategies and the flexibility in capacity and location are very important for your business.

We should not however confuse vendor specific solutions with cloud solutions only because they promise flexibility in cost and easy deployment; being able to shift and shop around is always better – also in cloud computing.

This blog post is a repost of