A method and apparatus for automatically deploying artifacts are disclosed. In one embodiment, the method comprises generating a trusted configuration artifact with a forward immutable continuous integration (CI) implemented as a build pipeline; accessing, by an orchestration system, the trusted configuration artifact from the IAC repository; and automatically deploying the configuration to change a state of the cluster, according to an orchestration type associated with the trusted configuration artifact, including determining the orchestration type.

A method for determining an efficacy of an application includes identifying a plurality of application components deliverable within the application, identifying a component from the plurality of application components to execute to perform the step based upon a profile; providing the particular component; detecting an interaction with the provided component; and determining an efficacy of the application. A system for determining an efficacy of an application includes a processor and a memory storing computer-executable instructions that, when executed by the one or more processors, cause the computing system to identify a plurality of application components deliverable within the application, identify, from the plurality of application components, a component to execute to perform the step, based upon a profile; provide the particular component; detect an interaction with the provided component; and determine an efficacy of the application, based at least in part upon the detected interaction.

A method for determining an efficacy of an application includes identifying a plurality of application components deliverable within the application, identifying a component from the plurality of application components to execute to perform the step based upon a profile; providing the particular component; detecting an interaction with the provided component; and determining an efficacy of the application. A system for determining an efficacy of an application includes a processor and a memory storing computer-executable instructions that, when executed by the one or more processors, cause the computing system to identify a plurality of application components deliverable within the application, identify, from the plurality of application components, a component to execute to perform the step, based upon a profile; provide the particular component; detect an interaction with the provided component; and determine an efficacy of the application, based at least in part upon the detected interaction.

Intelligent selection of optimization methods in heterogeneous environments is described. In some embodiments, an Information Handling System (IHS) may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: identify a context; rank a plurality of optimization methods based upon the context; and execute at least a subset of the ranked optimization methods.

A docker image is received. The docker image is for a container. The container contains files that allow for virtualization of applications that run within the container. The docker image is parsed to identify layer files in the docker image. Installed software components (e.g., installed files) and/or hardware components in the layer files are identified. Software application index calls are made to generate information that identifies relationships between the installed software components and/or hardware components. The relationships between the installed software components and/or hardware components are then displayed to a user.

Computing systems, for example, multi-tenant systems deploy software artifacts in data centers created in a cloud platform using a cloud platform infrastructure language that is cloud platform independent. The system receives an artifact version map that identifies versions of software artifacts for data center entities of the data center and a cloud platform independent master pipeline that includes instructions for performing operations related to services on the data center, for example, deploying software artifacts, provisioning computing resources, and so on. The system receives a deployment manifest that provides declarative specification of deployment strategies for deploying software artifacts in data centers. The system implements a deployment operator that executes on a cluster of computing systems of the cloud platform to implement the deployment strategies.

Computing systems, for example, multi-tenant systems deploy software artifacts in data centers created in a cloud platform using a cloud platform infrastructure language that is cloud platform independent. The system receives an artifact version map that identifies versions of software artifacts for data center entities of the data center and a cloud platform independent master pipeline that includes instructions for performing operations related to services on the data center, for example, deploying software artifacts, provisioning computing resources, and so on. The system receives a deployment manifest that provides declarative specification of deployment strategies for deploying software artifacts in data centers. The system implements a deployment operator that executes on a cluster of computing systems of the cloud platform to implement the deployment strategies.

Disclosed are various embodiments for anti-pattern detection in extraction and deployment of a microservice. A software modernization service is executed to analyze a computing application to identify various applications. When one or more of the application components are specified to be extracted as an independently deployable subunit, anti-patterns associated with deployment of the independently deployable subunit are determined prior to extraction. Anti-patterns may include increases in execution time, bandwidth, network latency, central processing unit (CPU) usage, and memory usage among other anti-patterns. The independently deployable subunit is selectively deployed separate from the computing application based on the identified anti-patterns.

Disclosed are various embodiments for anti-pattern detection in extraction and deployment of a microservice. A software modernization service is executed to analyze a computing application to identify various applications. When one or more of the application components are specified to be extracted as an independently deployable subunit, anti-patterns associated with deployment of the independently deployable subunit are determined prior to extraction. Anti-patterns may include increases in execution time, bandwidth, network latency, central processing unit (CPU) usage, and memory usage among other anti-patterns. The independently deployable subunit is selectively deployed separate from the computing application based on the identified anti-patterns.

A method, apparatus, electronic device, storage medium and program product of code management are provided. In response to a request for building an executable file, corresponding developed code is obtained from a code library. The developed code is compiled into intermediate code to determine security of the intermediate code. In response to determining that the intermediate code is secure, an executable file is generated based on the intermediate code.