Artificial intelligence optimized cloud migration

A computer system comprising:

• a processor;
• a memory;
• one or more computer program instructions stored on the memory for execution by the processor, the program instructions comprising:
• receive a user input associated with a migrating system comprised of a plurality of assets, wherein the user input comprises information regarding an operating system environment of the migrating system and a plurality of dependencies associated with each asset of the plurality of assets, and a physical location associated with each respective asset;
• generate a constraint portfolio, utilizing an artificial intelligence model trained with a plurality of data from a historical scheduler knowledge base and the user input, wherein the constraint portfolio is a set of rules for transferring the migrating system to a cloud computing system;
• generate a wave plan model based on the constraint portfolio and a cost optimization function, wherein the cost optimization function is based on an equation, wherein the equation is:
• d(t)=wss(t)+wmm(t)+wpp(t)+wrr(t)
• wherein d(t) is the cost optimization function, t is time, s is a subject matter expert cost, ts is time spent by one or more subject matter experts, m is a migration tools cost, tm is time using migration tools, p is a migration process delay cost, tp is migration process delay time, r is a failed migration risk cost, tr is time spent due to failed migration risk, and ws, wm, wp, and wr are assigned weights, and wherein the wave plan model is a schedule to transfer each of the assets of the migrating system in one or more bundles to the cloud computing system;
• create a task portfolio based on the wave plan model, wherein the task portfolio is a date and time dependent schedule for transferring the migrating system to the cloud computing system;
• and
• generate one or more runbooks based on the task portfolio schedule, wherein the one or more runbooks are executable migration instruction applications.

A computer program product comprising a computer readable storage medium and program instructions stored on the computer readable storage medium, the program instructions comprising:

• receive a user input associated with a migrating system comprised of a plurality of assets, wherein the user input comprises information regarding an operating system environment of the migrating system and a plurality of dependencies associated with each asset of the plurality of assets, and a physical location associated with each respective asset;
• generate a constraint portfolio, utilizing an artificial intelligence model trained with a plurality of data from a historical scheduler knowledge base and, wherein the constraint portfolio is a set of rules for transferring the migrating system to a cloud computing system;
• generate a wave plan model based on the constraint portfolio and a cost optimization function, wherein the cost optimization function is based on an equation, wherein the equation is:
• d(t)=wss(t)+wmm(t)+wpp(t)+wrr(t)
• wherein d(t) is the cost optimization function, t is time, s is a subject matter expert cost, ts is time spent by one or more subject matter experts, m is a migration tools cost, tm is time using migration tools, p is a migration process delay cost, tp is migration process delay time, r is a failed migration risk cost, tr is time spent due to failed migration risk, and ws, wm, wp, and wr are assigned weights, and wherein the wave plan model is a schedule to transfer each of the assets of the migrating system in one or more bundles to the cloud computing system;
• create a task portfolio based on the wave plan model, wherein the task portfolio is a date and time dependent schedule for transferring the migrating system to the cloud computing system;
• and
• generate one or more runbooks based on the task portfolio schedule, wherein the one or more runbooks are executable migration instruction applications.