Cloud Application Management - Agile, Lean, Lightweight
The acquisition of Hyperic by SpringSource got me thinking about the next generation of application delivery and management for cloud applications. At first, I was cynical about this combination – two small companies with common investors combining resources to soldier on in a tough capital environment. While this cynical thinking probably has a kernel of truth to it, the more I thought about the combination the more I thought that it makes sense beyond the balance sheet implications. Indeed, I believe the future of application delivery and management will combine agile development with lean resource allocation and lightweight management. This new approach to application delivery and management is one that complements the emerging cloud architecture for infrastructure.
Agile development, with its focus on rapid releases of new application functionality, requires a programming approach that is not overly burdened with the structure of J2EE and EJB. Spring, Rails, Grails, Groovy, Python all represent the new approach – placing a premium on quick delivery of new application functionality. Application functionality takes center stage, displacing the IT infrastructure dominance of the legacy application server oriented approach. Developers will use what works to deliver the application functionality instead of using what works for the IT organization's management framework. The new approach does have implications for scalability, but we will get to that issue in a moment.
Lean is one of the newer terms emerging to describe the future of application delivery. I first referenced lean as an IT concept by relating it to the lean approach for manufacturing operations in a blog post about a year ago. With lean application delivery, applications scale horizontally to consume the infrastructure resources that they require based upon the actual demand that they are experiencing. The corollary is that they also contract to release resources to other applications as demand subsides. This “lean” approach to resource allocation with dynamic scaling and de-scaling is what a cloud architecture is all about – elasticity. Rather than optimizing the code to “scale up” on an ever bigger host, the code remains un-optimized but simple – scaling out with cheap, variable cost compute cycles when the peaks in demand require more capacity. Giving back the capacity when the peaks subside.
With the lean approach for resource allocation, a lightweight management approach that measures only a few things replaces the old frameworks that attempt to measure and optimize every layer in an ever more complex infrastructure stack. If the service is under stress due to demand, add more instances until the stress level subsides. If the service is under extremely light load, eliminate resources until a more economical balance is struck between supply and demand. If an instance of a service disappears, start a new one. In most cases, you don't even bother figuring out what went wrong. It costs too much to know everything. This lightweight approach for management makes sense when you have architected your applications and data to be loosely coupled to the physical infrastructure. Managing application availability is dramatically simplified. Managing the physical hosts becomes a separate matter, unrelated to the applications, and is handled by the emerging datacenter OS as described by VMware or the cloud provider in the case of services like those provided by Amazon AWS.
Take a look at the rPath video on this topic. I think it reinforces the logic behind the SpringSource and Hyperic combination. It rings true regarding the new approach that will be taken for rapid application delivery and management in a cloud infrastructure environment. Applications and data will be loosely coupled to the underlying infrastructure, and agile development, lean resource allocation, and lightweight management will emerge as the preferred approach for application delivery and management.
Labels: Amazon AWS, application delivery, cloud computing, hyperic, springsource, VMware
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