Method and system for executing a containerized stateful application on a stateless computing platform using machine learning
A technique for executing a containerized stateful application that is deployed on a stateless computing platform is disclosed. The technique involves deploying a containerized stateful application on a stateless computing platform and executing the stateful application on the stateless computing platform. The technique also involves during execution of the stateful application, evaluating, in an application virtualization layer, events that are generated during execution of the stateful application to identify events that may trigger a change in state of the stateful application and during execution of the stateful application, updating a set of storage objects in response to the evaluations, and during execution of the stateful application, comparing events that are generated by the stateful application to the set of storage objects and redirecting a storage object that corresponds to an event to a persistent data store if the storage object matches a storage object in the set of storage objects.
1. A method for executing a containerized stateful application that is deployed on a stateless computing platform, the method comprising:
deploying a containerized stateful application on a stateless computing platform;
executing the stateful application on the stateless computing platform;
during execution of the stateful application, evaluating, in an application virtualization layer, events that are generated during execution of the stateful application to identify events that may trigger a change in state of the stateful application, wherein events that may trigger a change in state of the stateful application are events from a predefined set of events, and wherein the predefined set of events includes file-related events, wherein the file-related events include CreateFile, WriteFile, DeleteFile, and CloseFile;
during execution of the stateful application, automatically updating a monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer in response to identifying an event from the predefined set of events, wherein file paths of the monitored set of file paths are defined by a drive identifier, a directory name, and a file name; and
during execution of the stateful application, comparing, in the application virtualization layer, events that are generated by the stateful application to the automatically updated monitored set of file paths and redirecting, to a persistent data store, state information that corresponds to an event that matches a file path in the automatically updated monitored set of file paths;
wherein automatically updating the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer during execution of the stateful application comprises applying machine learning to add a file path to the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer for use in subsequent event comparisons during execution of the stateful application for an event that is identified by a monitored set update engine as an event that may trigger a change in state of the stateful application and the file path for the event is not already in the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer;
and
storing the automatically updated monitored set of file paths in the persistent data store.
2. The method of claim 1 , wherein events that may trigger a change in state of the stateful application include events that have a desired access of write.
3. The method of claim 1 , wherein events that may trigger a change in state of the stateful application include file-related events that have a desired access of write.
4. A non-transitory computer readable medium that stores computer-executable code, which when executed by one or more processors implements a method, the method comprising:
deploying a containerized stateful application on a stateless computing platform;
executing the stateful application on the stateless computing platform;
during execution of the stateful application, evaluating, in an application virtualization layer, events that are generated during execution of the stateful application to identify events that may trigger a change in state of the stateful application, wherein events that may trigger a change in state of the stateful application are events from a predefined set of events, and wherein the predefined set of events includes file-related events, wherein the file-related events include CreateFile, WriteFile, DeleteFile, and CloseFile;
during execution of the stateful application, automatically updating a monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer in response to identifying an event from the predefined set of events, wherein file paths of the monitored set of file paths are defined by a drive identifier, a directory name, and a file name; and
during execution of the stateful application, comparing, in the application virtualization layer, events that are generated by the stateful application to the automatically updated monitored set of file paths and redirecting, to a persistent data store, state information that corresponds to an event that matches a file path in the automatically updated monitored set of file paths;
wherein automatically updating the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer during execution of the stateless application comprises applying machine learning to add a file path to the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer for use in subsequent event comparisons during execution of the stateful application for an event that is identified by a monitored set update engine as an event that may trigger a change in state of the stateful application and the file path for the event is not already in the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer;
and
storing the automatically updated monitored set of file paths in the persistent data store.
5. The method of claim 1 , wherein automatically updating the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer comprises determining if a file path is included on an exclusion list and not adding the file path to the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer if the file path is on the exclusion list.
6. The method of claim 1 , wherein automatically updating the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer comprises adding a file path to a search tree that is held in the in-process volatile memory of the application virtualization layer.
7. The non-transitory computer readable medium of claim 4 that stores computer-executable code, which when executed by one or more processors implements a method, wherein to automatically updating a monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer comprises determining if a file path is included on an exclusion list and not adding the file path to the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer if the file path is on the exclusion list.
8. The non-transitory computer readable medium of claim 4 that stores computer-executable code, which when executed by one or more processors implements a method, wherein to automatically updating the monitored set of file paths that is stored in in-process volatile memory of the application virtualization layer comprises adding a file path to a search tree that is held in the in-process volatile memory of the application virtualization layer.