Discovery and migration planning techniques optimized by environmental analysis and criticality

A computer-implemented method for discovery of computing nodes of a source infrastructure at a source location and for planning migration of the computing nodes to a target infrastructure at a target destination, the method comprising:

• deploying a collector node at a network of the source location;
• discovering, with the collector node, data associated with computing nodes of the source infrastructure;
• transmitting, with the collector node, the discovered data from the network of the source location to a staging application programming interface (API) at a remote server;
• receiving, with the staging API, the discovered data transmitted by the collector node;
• applying, with the staging API, an access control measure to the discovered data;
• satisfying, with a migration processing API, the access control measure applied by the staging API;
• retrieving, with the migration processing API, the discovered data from the staging API after satisfying the access control measure;
• writing, with the migration processing API, the discovered data to a migration database;
• analyzing, with a migration planning API, the discovered data written to the migration database by:
• filtering, with the migration planning API, the discovered data stored in the migration database to filter out common connection data from the discovered data, the common connection data including data relating to at least one of infrastructure services, link local IP addresses, or self-traffic, and
• applying, with the migration planning API, a criticality algorithm to the discovered data to determine a criticality parameter associated with each of the discovered computing nodes based on a number of occurrences of the computing node, a number of systems that depend on the computing node according to the filtered discovered data, and a user-entered weight assigned to the computing node that indicates a relative importance of the computing node, wherein the criticality parameter identifies a potential impact that each discovered computing node has to migration;
• automatically grouping, with the migration planning API, the discovered computing nodes of the source infrastructure into migration pods based on dependency of the computing nodes according to the filtered discovered data, the criticality parameters associated with the computing nodes, and predictive analytics based on past discovered data associated with computing nodes from past planned migrations that are similar to the discovered computing nodes that suggest one or more of the discovered computing nodes to include in one of the migration pods and suggest one or more of the discovered computing nodes to exclude from one of the migration pods, and with each migration pod defining a group of discovered computing nodes that depend on one another for network communication at the source infrastructure;
• prioritizing, with the migration planning API, the migration pods based on the criticality parameters of the discovered computing nodes of each migration pod;
• and
• generating, with the migration planning API, a plan for migrating the migration pods to the target infrastructure based on the prioritization of the migration pods.