Understanding the ‘shared responsibility model’ is one of the most important keys for getting to the cloud and staying there.  Successful ‘Infrastructure as a Service’ (IaaS) cloud adoption cases can be likened to a stool with three legs -

Leg #1 – The Infrastructure: scalable, pay-as you-go, on-demand compute and storage services, typically provided by an IaaS vendor like Amazon Web Services (AWS) clou.d

Leg #2 – The Application: The ‘business logic’, which can be developed internally by the enterprise team or can be enterprise software developed by a third party vendor.

Leg #3 – The Operations: The securing, automating, orchestrating, monitoring and managing of the the other two legs.  This involves ensuring the application and underlying infrastructure are highly available and efficiently scaling on-demand in a cost-effective manner.

The team needs to understand which legs it is responsible for and define the fine lines of shared responsibility. For example, in developing a continuous release process, developers need to make sure that they are pushing new features quickly and easily to production while the operations teams are in a position where they can govern the new code as it goes in. In the cloud, the operations teams can now be more oriented towards using the cloud infrastructure API to automate and orchestrate the underlying infrastructure, thereby delivering “infrastructure as code”.  With the emergence of this interdependence, we are seeing the growing importance of the DevOps function.

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As was the case with a recent engagement with a Fortune 100 CIO, a $30M enterprise software purchase came with a $150M infrastructure tab.  In addition, the time frame for that infrastructure to go online was almost 3 years. The CIO wanted the systems online in days or weeks, not months and years.  The only viable option was the cloud.  In such circumstances, cloud agility and fast delivery might just be the most important incentive for the billion dollar enterprise CIO to look for in the cloud. Although the operations team takes charge of the service wrappers (that ensure SLA, security, etc.), the application developers, as well as the operations team members, need to coordinate the development and deployment when utilizing the IaaS platform building blocks.

From an application developer’s perspective, there are several best-practices for developing applications that can scale horizontally. By incorporating these practices, developers can take advantage of flexible, automatable, highly scalable IaaS solutions.  Decoupling the various tiers of the application and making these tiers stateless allows the operations team to provision and de-provision additional resources transparently and ‘on demand’.  Other best practices include separating static data from dynamic data and segregating ‘reads’ from ‘writes’.  This allows for separate, use-case-specific scaling policies which can, on cloud platforms, be automated.  By ‘designing for failure so nothing fails’, the application developer can build an application that is highly available.

While these are simply some best-practices, not all legacy applications account for them.  As a result, operating and scaling these applications often times requires additional work

Despite some of these challenges, benefits like on-demand provisioning, no up-front capital expenditure requirements and pay-as-you-go business models make the cloud a very attractive option for several applications.  A rich ecosystem of vendors who service the infrastructure, application and operations needs is already forming, and these empower the IT and business executives to truly leverage the potential of this paradigm.

About the Author

Arjun Chopra is the CTO at smartShift Technologies. smartShift Technologies is a Cloud Transformation Company with experience in transforming 100s of mission critical applications for market-leading Fortune 500 customers and startups alike. smartShift’s highly automated, multi-patented products predictably, rapidly and cost-effectively transform and modernize enterprise systems (legacy, SAP, Oracle and others) to state-of-the-art, cloud-ready systems. smartShift’s 24/7, SLA-driven managed services secure, monitor and manage cloud infrastructure, with over 25 million hours of uptime supported in public and private clouds. 

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Keywords: Amazon Cloud, Shared Responsibility Model, The Enterprise Cloud, Cloud Computing, SLA, Cloud Security, High Availability, Cloud Costs, Cloud Opeartions

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