Abstract: According to some embodiments, an automated provisioning system may receive a customer demand associated with an application to be executed in a cloud-based computing environment. The automated provisioning system may include a process allocator to communicate with Virtual Machine (“VM”) and container provisioners and determine cluster data. A machine learning based microservice setup platform, coupled to the automated provisioning system, may receive the cluster data and information about the customer demand. The machine learning based microservice setup platform may then execute policy rules based on the cluster data (and information about the customer demand) and generate a recommendation for the customer demand. The automated provisioning system may then assign the customer demand to one of a VM-based infrastructure and a container-based infrastructure in accordance with the recommendation generated by the machine learning based microservice setup platform.

Abstract: According to some embodiments, a centralized resource provisioning system may associated with a plurality of end-user applications in a cloud-based computing environment. The centralized resource provisioning system may include a policy decision maker that generates a centralized recommendation for a computing resource of a first end-user application. An application decision maker may be associated with the first end-user application and generate a decentralized recommendation for the computing resource of the first end-user application. A machine controller of the centralized resource provisioning system may then arrange to adjust the computing resource for the first end-user application when both the centralized recommendation and the decentralized recommendation indicate that the adjustment is appropriate.

Abstract: A host delegates Just-In-Time (JIT) bytecode compilation to a serverless Web Assembly (WASM) runtime. The WASM runtime receives the bytecode, together with any additional arguments (e.g.: offsets of dependent functions, vtable metadata, virtual machine state). The host may include a parser to provide the additional arguments. In response to receiving the bytecode and arguments, the WASM runtime triggers a thread and loads appropriate WASM modules to compile the bytecode. The resulting assembly instructions are sent back to the host for execution in connection with the (frequently requested) method. Only the bytecode of frequently-accessed methods (as determined at the host) may be delegated for compilation. Delegation of bytecodes for compilation according to embodiments, may conserve a significant percentage of CPU cycles at the host, which can then be used for executing code instead.