Kevin Leahy is the group general manager for the Data Center Business Unit at Dimension Data with expertise in the areas of cloud, service management, virtualization and IT optimization.
It’s one thing to handle simple test and development or to move non-mission critical data to the cloud. When the data is sensitive or mission critical, enterprises are right to be concerned about the ongoing security and reliability of their data. They should carefully consider how to migrate their data into and out of the cloud environment whenever necessary.
For starters, companies need to know what tools are available to automate the process of moving data into the cloud. They should also establish controls and policies around what happens once the data is outside their network, and will need answers to the following questions before getting started:
- Who should have access to the data?
- How do you scale resources to support the data or applications?
- How will scalability work from an integration perspective?
Automation, control and integration are the three important areas enterprise architects need to understand before migrating applications or data into the cloud. By focusing on these, enterprises can address and set the groundwork for many of the other high-level concerns around data migration that are common, such as security, performance, privacy and data ownership.
Key Element: Automation
Automation is first about orchestration. Understanding how to move applications into the cloud, how orchestration works, and how all these stack up against enterprise and architectural requirements is what makes automation possible. In order for enterprise IT to truly serve the needs of end users and reduce rogue usage of public cloud services, CIOs must embrace automation and orchestration that extends self-service provisioning down to those end users. While that is the goal, the first step is usually the hardest, defining the policies that can be automated.
For many organizations, those policies do not exist, and rogue IT may or may not be an issue without those policies in place. Automation of the policies, while complex, with modern DevOps tools and API’s currently available can usually start with basic policies that can become more complex with event triggers and real time information analysis in the future. The ideal end result is to fully leverage a self-provisioning model to autoscale and create efficiencies in cloud resource usage. Ultimately, only the applications and data that the company wants, and the rules under which it operates, should be moved to the cloud.
Key Element: Control
Control of various resources, such as servers, storage and networking gear, is key to ensuring security no matter where the data is located. This includes an understanding of role-based access controls (RBAC) for each person that dictates what they can control and touch within a cloud environment, separate from administrators, and what type of control an enterprise has over its resources. Control is about gaining visibility into, and the monitoring of, usage and activities. This can be achieved through authentication including multi-user and identity-based access management and depends on how you enable single sign-on, for example, using SAML and/or LDAP.
Control must enforce the policies the company has defined, and the more automated it is, the fewer escapes and the easier it is to demonstrate compliance. A simple example is ensuring private data is removed (i.e. privatized) or encrypted before it is moved to the cloud. Equally, a backup or recovery copy or even archival storage is part of the overall data architecture, and ensuring those copies are protected in the right places, and deleted when required is all part of the control.
Key Element: Intergration
Integration is a complicated and often an underestimated element of data migration. Enabling APIs and enterprise data, applications and systems to seamlessly work together with the existing network takes expertise that is not always available within the IT department. In fact, as cloud maturity has advanced beyond simple web facing application or development and test to complex interdependent applications, integration has become the biggest cost and time factor in implementing hybrid clouds. While tools have advanced, the application management rules in place are usually built assuming all on premise response times and security handling issues are resolved.
Consider what consulting and professional services, as well as managed services, may be required to speed the time it takes to successfully migrate data to the cloud. Integration tools to be explored could include Chef and Puppet configuration management tools and DevOps tools to integrate the application needs with the infrastructure. Cloud management platforms that balance resources across several cloud providers can be implemented as a way of stitching together disparate platforms, but standards adoption is not at the point where that approach can perform as well as a well-architected hybrid platform.
The Result: Business Agility
Migrating data and applications into the cloud can provide better data access and availability and—depending on the types of services you implement—can deliver added protection, security and reliability for your sensitive and mission critical data. The three key elements of automation, control and integration required to successfully migrate your data, mission critical or otherwise, to the cloud can result in one significant overall benefit--business agility.
It is well-known that the cloud delivers flexibility, scalability, a pay-as-you-go consumption model, and the ability to outsource some or all infrastructure and IT functions for improved efficiencies with typically increased ROI. However, migrating to the cloud also frees up critical and valuable resources from day-to-day IT management and maintenance to focus on more strategic business goals. This manifests itself in a number of positive outcomes besides reducing upfront Capex and ongoing Opex.
IT and engineering can instead focus on strategic goals like speeding time to market by reducing test and dev production cycles, delivering more robust services, improving products, and creating new products. This results in satisfied customers and, ultimately, increasing growth and profitability for your enterprise.
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