|By Mike Maciag||
|June 2, 2011 04:45 PM EDT||
It's an age-old struggle. IT works hard to provide top-of-the-line infrastructure, while developers juggle the build-test-deploy cycle. Somewhere in the middle things get lost in translation and the two find themselves at odds. Developers vie for control of resources and access to tools, while IT struggles to provide resources that are standardized and can be managed in a secure and consistent way.
Sound familiar? We see it all the time in the enterprises we work with. It really boils down to seemingly disparate goals. Even though they're working for the same organization, IT and developers are trying to achieve different things. IT strives for efficient use of resources to get a better return on infrastructure investment. Software developers, on the other hand, are concerned mainly with efficient development. They demand ready access to infrastructure and need a wide range of tools at their fingertips. The constantly fluctuating demands and hodgepodge of tools make it difficult for IT to keep up with their resource needs, and maintain security and consistency within the organization. It's no wonder they always seem to be butting heads.
A New Approach
With the advent of cloud computing, there's new hope of bridging the gap between IT and development. The processes that benefit most from moving to the cloud are those that are resource-intensive or "bursty" in compute demand - exactly the kinds of processes that abound in the build-test-deploy cycle. Great examples include compiling and building source code, testing on several different operating systems, and load testing.
But is a basic cloud implementation enough to address the Dev - IT divide?
Most cloud implementations leverage virtualization and user self-service as their two cornerstone technologies. Virtualization dramatically improves the utilization of the underlying resource; now your underutilized physical servers can be loaded up with many virtual machines (VM), improving your asset utilization. Virtualization also allows IT to provide standardized resources as templates s servers, applications, databases, etc., to users, which enables fast setup and consistent management of the resources. Self-service gives users IT resources on demand: they can request a new server and voila - a new virtual machine is provided instantaneously. Because they don't have to wait for hours or days to get the compute services they need, productivity and time-to-market can be improved.
While cloud provides a lot of value, it still doesn't address the way development wants to interact with IT. Most development teams today have a software production process, a workflow that starts with developers writing software code, building and testing the software, and culminates with the release/deployment of the customer-ready software. This process, complex to begin with, is becoming even more complex with the adoption of Agile development methodologies that encourage faster and more iterative development of software applications. To improve the productivity and efficiency of development in this fast-evolving landscape, cloud infrastructure and services need to be tightly integrated to the process. The necessary ingredients of this integration include:
- Automated, but seamless, self-service: Developers want self-service, but not in the typical Web interface sense that limits them to setting up one resource at a time. In today's fast-paced and Agile software production process, developers need the ability to set up resources instantaneously and in-context of the software production process. For example, developers want build systems to be automatically provisioned upon start of a build process, and torn down upon successful completion of the process. It is imperative that this process is seamless so it can be iterated multiple times a day; it's also important to automate the process so IT doesn't have to deal with VM sprawl or orphaned VM issues.
- Customized resource and environment: While the cloud provides standard IT compute resources, developers typically want to customize the resources to the requirements of the software production process. This may involve configuring the standard IT-instantiated resources deploying new dev/test-specific applications. Just as important, developers want these changes to be done automatically without manual interventions
- Automatic resource management: Developers want the cloud solution to automatically manage the cloud resource, whether it means creation, deletion or active management of the cloud workload and resources. This lets them focus on what they do best and, more important, it enables the IT organization to manage cloud resources in an optimal and efficient manner and achieve shared service economies.
- Visibility: Developers want their solution to provide them with end-to-end visibility into the software production process and the resources that these processes run on. Whether the process is running on physical, virtual or cloud resources, developers are looking for good analytics to quickly triage software production process errors (which build was broken, what software version passed the tests, etc.).
- Flexibility: Finally, while developers want to leverage the cloud, they don't want to be locked in to any one resource choice. The development team wants to retain the option of using physical, virtual or cloud services (private or public) to best fit their production process.
Today's cloud solutions do a great job of managing the cloud resources from an infrastructure perspective:
- Lab management solutions, such as VMWare's Lab Manager or Citrix VMlogix, manage the VMs and standardized templates that are used by development teams
- Cloud Infrastructure as a Service (IaaS) solutions such as Eucalyptus provision and manage the infrastructure that's used by the development team
- Amazon EC2 and Rightscale provide capabilities to use the public cloud to build and test software applications.
Many of these solutions, however, don't understand the development process /tasks that are run on cloud resources, and it is precisely the lack of these types of integrations that is preventing development teams from widespread adoption of cloud technology. One piece that fills the self-service gap to enable development on the private cloud is a software workflow automation system like Electric Cloud ElectricCommander.
Let's talk about how this looks in practice. Say I need to do some system testing. I'm going to need a bunch of machines. If my IT organization supports virtualization technologies, such as VMware Vsphere or Microsoft HyperV, I can get a number of virtual machines with a specific software configuration on them. This is a big improvement over the old days when I would need to secure physical machines, but it's still the virtual equivalent of a blank rack of servers. I've provisioned the resources, but I haven't provisioned the actual test applications. At this point, I have self-service compute resources, but I don't have a system in place that determines what needs to happen, what workflows it needs to go through, how I'm going to load the software or how I'm going to integrate the tools.
By implementing a software production automation system that is optimized for use on the cloud, I now have a platform that lets me define the steps, the workflow between them, tool integration and resource management.
This solution would provide workflow automation (automating, parallelizing and distributing steps within the workflow), seamless services (automatically setting up and tearing down resources as tasks demand), dev tool integration and end-to-end visibility and reporting (aggregating data from multiple apps to quickly identify software errors).
How It Plays It Out in the "Real World"
One of our customers, a large financial institution, has a development team of more than 5,000 developers spread around the world. They've long employed Agile practices, including continuous integration and test processes, but as the development team grew, its demands overwhelmed the script- and open source-based software build and test system they had relied on. Because individual teams were allowed the discretion to choose development methods and tools that worked best for them, the organization was dealing with a wide variety of tools that had become difficult to manage.
A private development cloud turned out to be an essential part of the solution for this organization. It allowed them to offer software build and test as a service to developers, while staying behind their firewall to maintain the tight security the financial industry demands. They now have a common pool of resources to support build, test and deploy procedures that are always accessible on-demand. Teams are still using the tools they prefer, but the organization can now easily allocate resources as they are needed, while supporting parallel builds across multiple computers with varied operating systems and languages.
This customer implemented the private development cloud as an opt-in service, letting teams choose whether to use it or continue to run builds and tests locally. But as teams began to see the benefits, they were eager to move to the cloud. IT is happier too: managing resources while accommodating development's varied tools is now easier, and they have much better visibility into the development process, which is invaluable for a financial company that has to be ready for audits.
At a macro level, implementing a private development cloud has allowed this organization to increase their productivity and save money. The developers, though, aren't thinking of it as an ROI - they're just glad to have a system that helps them do their jobs as efficiently and easily as possible.
Moving development to the cloud and enabling self-service allows developers and IT to work together more easily, with the end result they're all ultimately looking for: better software that's built, tested and deployed cheaper and faster. It seems the cloud holds the key to ending that age-old struggle once and for all.
The essence of data analysis involves setting up data pipelines that consist of several operations that are chained together – starting from data collection, data quality checks, data integration, data analysis and data visualization (including the setting up of interaction paths in that visualization). In our opinion, the challenges stem from the technology diversity at each stage of the data pipeline as well as the lack of process around the analysis.
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