In the discovery phase of your migration project, you discover and capture detailed data about your cloud migration portfolio, for example, the scope of your migration project. You identify servers and applications in your portfolio, as well as their interdependencies and current baseline performance metrics. Then, you analyze the gathered information to determine application connectivity and capacity requirements, which can guide you in designing and architecting the target cloud environment and identifying the cost.

A detailed discovery can also help in identifying any issues in the current state of the application that might need mitigation before you migrate to the cloud. While analyzing the discovery data, you will also determine an appropriate migration method for your application. Portfolio discovery is the process of identifying all the IT assets that are involved in your cloud migration project, including servers and applications, their dependencies, and performance metrics.

You will also need to gather business details about your resources, such as the Net Present Value (NPV) of the resource, the refresh cycle of the application, the roadmap of the application, and the business criticality of the server or application. These details will help you determine your migration strategy and create a migration plan. In most organizations, these details are maintained across multiple business units and teams. Therefore, during the process of discovery, you may have to interact with various teams, such as business, development, data center, network, and finance.

It is essential to understand that your discovery landscape will depend on various factors:

• What has already been migrated to the cloud?
• What application dependencies are there, along with resources and assets?
• What are the business drivers for cloud migration?
• What is the estimated duration for the entire migration project?
• How many phases is the migration process going to happen in?

One of the top challenges of a migration project is determining interdependencies among applications, particularly since they pertain to Input/Output (I/O) operations and communications. Cloud migration becomes even more challenging as organizations expand due to mergers, acquisitions, and growth. Organizations often do not have complete information about the following:

• The inventory of the number of servers
• Server specifications such as the type and version of OS, RAM, CPU, and disk
• Server utilization and performance metrics
• Server dependencies
• Overall networking details

Performing a thorough portfolio discovery helps in answering questions such as the following:

• Which applications, business units, and data centers are good candidates for migration?
• How suitable are the applications for migrating to the cloud?
• What known or unknown risks are associated with migrating an application to the cloud?
• How should the applications be prioritized for migration?

• Which other IT assets is the application dependent on?
• What is the best migration strategy for the application?
• Is it better to have some downtime for the application than to perform a live migration due to its dependencies and risks?

Several tools are available in the market that can help automate the discovery process and provide more detailed information in a variety of formats. These tools can be classified based on various characteristics, such as deployment type, operation, support, and type of data discovered and reported.

Most of the available solutions can be broadly classified into two categories:

• Agent-based solutions: They require their software client to be installed on a server to gather the necessary details.
• Agentless solutions: They may be able to capture this information without any additional installations.

Some solutions perform port scanning to probe a server or host for open ports, while others perform packet scanning, which often involves capturing and analyzing network packets to decode the information. The tools also vary based on the granularity of the data that's discovered, the storage types, and the reporting options. For example, some tools can provide a higher stack of intelligence beyond the network and can also determine the type of applications running.

The complexity of the discovery process depends on the organization's workload and if they already have a well-maintained inventory in place. Discovery processes are typically run for at least a couple of weeks to gather more holistic information about your environment. Once you discover all the necessary information, you need to analyze it. Let's look at the analysis step in more detail.