The Cloud Migration Tool Kit

05 February 2015 | By John Merryman

Most enterprise migration projects start with the leveraging of incumbent enterprise tools. It’s not unlike the majority of home improvement projects where an existing toolkit is adapted to the job at hand, and regardless of the requirements, the toolkit is adapted to meet some version of the requirements. As is often the case, many discovery phases of enterprise migrations are ongoing with no clearly defined endpoint.

The reality is that the majority of mid-sized migrations function on the back of GANTT schedules, spreadsheets, and ‘grunt'. If you’re in the market of moving less than 500 assets (virtual, physical, etc.), you very well may benefit from not using tools to deliver your DC migration project. The time, upskilling, investment, management, and patience to properly learn and implement these tools are prerequisites to obtaining value from their deployment, and the ROI may never be realised.

However, if you’re facing an enterprise migration project comprising multiple locations, many 100’s of applications, and 100’s to 1000’s of assets, a well-planned and deployed toolkit is essential.

The following is the scope of tools required for an enterprise migration project:


Discovery tools function to collect all data regarding the applications and infrastructure within the source environment. Typically, a CMDB is regarded as the ‘partial’ source of truth, and discovery tools are used to inventory the physical and virtual environment to help compile a complete view of the infrastructure topology.

Traditional tools include client agent installs which perform a variety of client side query activity. TADDM (IBM), ADM (EMC), ADDM (BMC) are good examples of these tools designed for ongoing discovery and inventory of a customer source environment.Often, information overload can result from feature-rich tools in this space, so a common challenge includes lengthy integration times followed by massive data analysis and parsing efforts.

Discovery newcomers include RISC Networks & NetBrain, who deploy less invasive network based discovery methods. Both address host interdependency mapping, which is often required to design migration move groups in the migration planning process. We see a lot of merit in this improved approach.

Ultimately, the sources for the discovery data will include operational data, data from deployed tools, and manually input source files such as questionnaires and workshop outputs. The latter are often employed to extract institutional knowledge into a coherent view of ‘what’s running’. Organising and maintaining this information into an actionable state is another challenge, addressed below with migration management & governance.


Increasingly for enterprise migrations, the business wants to rationalise the application portfolio before moving it into the cloud. For cloud migrations, the common question is ‘will my application work in the cloud?’. The combined themes trend towards simplifying the legacy application environment in parallel to modernising the compute stack. Two levels of analysis are required for this activity: business application analysis & technical application analysis.

Business application analysis is traditionally performed with workshops and enterprise architects, a process both expensive and time consuming. An emerging set of tools works to address business application analysis, through online decision trees and workflows. The main benefit of employing these tools is to create a consistent set of outputs that can be used to drive the application modernisation strategy. Examples include CloudConveyor, CloudGenera, & Gravitant. These tools provide a rational view of your application portfolio, at a business and high-level architecture level.

Technical application analysis targets the lower level challenge of mapping application binary characteristics from a source environment to determine if they will work in a target environment. This is a major task and often a significant problem in terms of the migration analysis and decision making for application modernisation. In the desktop virtualisation arena, AppDNA from Citrix has provided considerable value in mapping remediation requirements, providing estimations of effort for application packaging, and has started to show application of this technology to the AWS cloud migration use-case. Consulting company tools such as Cloud Technology Partners have also entered this space with bold and smart new products.

Migration Management / Governance

Once the discovery data collection and analysis phase of the migration is underway, keeping it organised and linked to the migration planning process is the next challenge. Again, for small to medium scale projects, it’s likely that you would be better off with worksheets and standard project management tools, but on scale, the data volumes and linkage to migration planning becomes unwieldy. Taken to the extreme of what not to do, we’ve seen programmes running with GANTT charts of 100,000 rows and dedicated teams administering the GANTT data.

Migration management and governance tools, which have been mostly built for consultants in migration boutique consultancies or SI’s, provide a central repository for migration metadata, along with migration governance and planning functionality. This allows the discovery data to be linked to migration move groups, schedules, and coherently maintained throughout the process of migration planning and execution.

To obtain these tools, you usually have to work with the consulting group who built them, or with a clever boutique consultancy that has setup OEM agreements with the tool’s creators. Bell Microsystems (UK), Transitional Data Systems (US), along with the major SI’s who have invested in this space (Accenture, Dell, HP, etc.) are firms to look out for in the area of migration management and governance tooling.

Migration Automation

Today, a cumbersome medley of work-around scripts, manual copy methods, third party tools, and field engineering drive cloud migrations for enterprise application workloads. As previously discussed in this forum, the cloud migration automation tools market is a hotbed for investment and development.

An eye should be kept on merging toolsets from key market entries including RiverMeadow, Racemi, Ravello Systems, Atadata, to name a few.Traditional enterprise migration tools such as Double-Take (Vision Solutions) and PlateSpin (NetIQ) are also updating toolsets to provide cloud workload and data migration automation.

For more information or to discuss this further, feel free to contact the GlassHouse Technologies team.

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