Selecting the appropriate discovery tool for your cloud migration

Cloud migrations invariably require the coordination of multiple stakeholders, such as business and technical teams, partners, and third-party providers. As a stakeholder, understanding your portfolio is crucial to determine which workloads to migrate, and their requirements and interdependencies. But manually gathering these insights can be a daunting task. You can inform your decision by provisioning a discovery tool.

Given the variety of choices available, choosing the appropriate discovery tool for your use case can also be challenging. In this blog post, we explain a proven three-step technique to successfully filter and prioritize a list of discovery tools based on the essential features needed for your business.

Figure 1. Steps to determine your migration discovery tool

Step 1: Review

Review the outcomes that your migration journey should deliver. These will drive your discovery requirements and baseline the features needed. Compare the baseline features with existing tools within your organization such as Configuration Management Databases (CMDBs) or Application Performance Management (APM) tooling. By the end of this Review step, you should establish if your in-house tools are sufficient for your objectives. Here is a list of questions to support your migration analysis.

You may need to collect high-level data or complete datasets depending on your stage in the migration process. You may be exploring migration costs to assess the lift-and-shift migration threshold of a benefit program such as AWS Migration Acceleration Program (MAP). In this case, you probably only need a snapshot of your on-premises environment with a list of servers, their configurations, and attached licenses. You may be evaluating the Total Cost of Ownership (TCO) between your on-premises infrastructure and an elastic deployment model on the cloud. In this case, you’ll want to be able to estimate the cost of a right-sized cloud infrastructure. For that, you will want to run a discovery tool for the duration of a business cycle.

Finally, to decide how and when applications are going to migrate, you will need a complete and accurate dataset with the application and database features to be migrated. This must include network dependencies, non-functional requirements (NFRs), disaster recovery (DR) plans, and third-party licensing terms and conditions (T&C).

Conclude this step by baselining the features that you require in the discovery tool.

Step 2: Refine

This step is an elimination process. One of the resources you can use to compile a list of candidate discovery tools is the Discovery migration tool comparison page. Filter and sort the list using the following criteria categories:

1. Core features
2. Common features
3. Special features
4. Tool provisioning
5. Operation

By the end of this step, you should have a prioritized list of the discovery tools that optimally match your requirements.

Core features

Following are the basic set of features that you should expect from any discovery tool. Analysis of the data captured by these features will support your high-level business case.

• Automatic inventory collection. Reports on the infrastructure profile, such as CPU family, CPU cores, memory size, disk size and speed, and operating system.
• Utilization. Shows peak and average utilization of CPU, memory, and disk.
• Network storage discovery. Detects and profiles network shares from network-attached storage (NAS).
• Software. Identifies running processes and installed software, pinpointing database engines and their versions.
• Network scanning. Scans network subnets to discover unknown infrastructure assets.

Common features

Here are some common features of discovery tools. With this data, you will be able to create a more detailed TCO analysis and migration plan.

• Lift-and-shift cost estimation. Maps a recommended target AWS infrastructure for the rehost of the source infrastructure, and calculates the AWS cost.
• Target sizing recommendation. Maps and calculates the cost for alternative target AWS infrastructures based on the peak and average utilization.
• TCO analysis. Provides a cost comparison between current on-premises cost and projected AWS cost.
• Dependency mapping. Collects network connection information and builds inbound and outbound dependency maps of the servers and running applications. Infers applications from groups of infrastructure resources based on communication patterns.
• Application prioritization. Assigns weight or relevance to application and infrastructure attributes to create prioritization criteria for migration.
• Wave planning. Recommends groups of applications and the ability to create migration wave plans.

Special features

Special features map to less common requirements, or to a specific set of the workloads you want to migrate. For example, you may require your tools to collect database dependency information if databases form a significant part of your workloads. If you have strict regulatory compliance to follow (HIPAA, GDPR), you’ll need tools that comply with these regulations. Other examples are:

• Licensing analysis. Provides optimization recommendations for Microsoft SQL Server and Oracle systems in rehosting and replatforming scenarios.
• Enterprise platforms. Includes the ability to collect details from proprietary operating systems like AIX and Solaris, or infrastructure such as AS/400 and mainframe.

When evaluating each feature, consider how much of your environment it applies to, and how important it is for the overall objective. It’s a good practice to deprioritize rather than completely eliminating tools that don’t provide a specific feature.

Provisioning

Once you run through the minimum, common, and special feature requirements, further refine the tool list by evaluating the challenges associated with the provisioning process of each tool. For example, consider aspects like data residency and the cost model. Read Evaluating the need for discovery tooling for a detailed list of provisioning criteria.

Operations

Finally, refine your tool list further by evaluating the requirements to operate the tool. This includes considerations like the running cost and the support model.

Step 3: Select

At this stage, you should have a shortlist of preferred discovery tools, with only one or two tools remaining for final evaluation.

All of these shortlisted tools should fulfill your requirements. You can further refine your selection by choosing the tool that best fits your priorities. For example, if only two tools remain in your shortlist and ease of installation and operation are paramount, then select the tool with the highest levels of deployment automation. If cost is your main constraint, then select the least expensive tool to acquire and operate.

Conclusion

Tools from AWS and AWS Partners can help accelerate your migration to the AWS Cloud. To select the relevant discovery tool for your specific use case, we recommend the following proven three-step approach:

1. Review – Start by reviewing existing in-house capabilities, tools, and data sources. By the end of this step, you should establish if your in-house tools are sufficient for your cloud migration objectives.
2. Refine – Narrow down a list of candidate discovery tools by filtering and prioritizing them based on the requirements from the previous step.
3. Select – Filter the final list of suitable discovery tools by selecting the tool that best addresses your priorities.