Abstract: A method may comprise accessing first data sets associated with a first job of a workflow, each first data set associated with an execution of the first job, each first data set specifying a runtime of the first job and a first plurality of feature values of features associated with the runtime; executing a first plurality of feature weighting analyses utilizing the first data sets to rank the plurality of features with respect to their predictive value on a runtime of the first job; and generating, using at least one data processing apparatus, a predicted runtime of the first job based on a time series analysis of a plurality of runtimes of a plurality of second data sets, the second data sets selected from the first data sets based on the rank and one or more expected feature values associated with a future execution of the first job.

Abstract: According to one aspect of the present disclosure, a telemetry data set, which includes a plurality of data fields associated with application operations, is collected for an application. A request for at least a portion of the telemetry data set is received and processed. Data fields in the telemetry data set that are to be anonymized are identified based on the request, with information in the identified data fields is to be anonymized according to corresponding anonymization rules. The information in each of the identified data fields is masked based on the corresponding anonymization rule for the data field, and an anonymized telemetry data set is generated. The anonymized telemetry data set includes the masked information for the identified data fields and unmasked information for other data fields indicated in the request.

Abstract: Data is received at a release automation system indicating a project opened in an integrated development environment (IDE) on another system. A deployment model of the release automation system is identified as associated with the project, the deployment model including at least a definition of a workflow to be executed to perform automated deployment of applications and a definition of an environment including one or more target computing systems. Data is received at the release automation system indicating a user interaction with the IDE and a particular definition within the deployment model is determined as being relevant to the user interaction and the project. An interface between the IDE and the release automation system is used to cause information from the particular definition to be presented in a graphical user interface of the IDE based on the user interaction.

Abstract: According to at least one embodiment, an application environment is provisioned. In some embodiments, a stack template is accessed in response to a request to provision the application environment, with the stack template defining provider-independent configuration information for a particular stack. A deployment target template corresponding to the stack template is accessed, with the deployment target template defining provider-independent configuration information for middleware. A provisioning workflow is selected based at least on stack provider information indicated by the stack template, with the stack provider information indicating an infrastructure for provisioning the particular stack indicated by the stack template. A stack is provisioned on the infrastructure based on the selected workflow, the stack template, and the stack provider information, and middleware is then on the provisioned stack based on the deployment target template.

Abstract: A workflow to be executed may be identified, the workflow comprising a plurality of jobs linked via relationships. A graph of the jobs of the workflow may be generated based on the relationships. Runtimes for the jobs of the workflow are predicted, wherein for at least some of the predicted runtimes a predicted runtime for a job is based on an analysis of features of the job deemed to be predictive of a runtime for the job. A predicted runtime of a critical path through the workflow is generated based on the graph of the jobs and at least a subset of the predicted runtimes of the jobs of the workflow.

Abstract: A method may comprise accessing first data sets associated with a first job of a workflow, each first data set associated with an execution of the first job, each first data set specifying a runtime of the first job and a first plurality of feature values of features associated with the runtime; executing a first plurality of feature weighting analyses utilizing the first data sets to rank the plurality of features with respect to their predictive value on a runtime of the first job; and generating, using at least one data processing apparatus, a predicted runtime of the first job based on a time series analysis of a plurality of runtimes of a plurality of second data sets, the second data sets selected from the first data sets based on the rank and one or more expected feature values associated with a future execution of the first job.

Abstract: First data sets associated with a job of a workflow are accessed, each first data set specifying a runtime of a job and a first plurality of feature values of a plurality of features. Feature weighting analyses are executed utilizing the first data sets to rank the plurality of features with respect to their predictive value on whether or not execution of the job is to fail. During execution of the workflow, a runtime of the job of the workflow is monitored. During execution of the job, a likelihood of failure of the job is generated based at least in part on the monitored runtime of the job and a plurality of runtimes of second data sets, the second data sets selected from the first data sets based on the rank of the plurality of features and one or more expected feature values associated with the execution of the job.

Abstract: According to at least one embodiment, an interactive graphical user interface (GUI) is presented on a display coupled to a computing device, and the GUI includes a selection field for selection of one or more items. An interaction with the selection field is received, and a selection interface is presented in the GUI based on the interaction with the selection field. The selection interface includes a list of selectable items associated with the selection field and a list of selectable actions to be taken with respect to selection of an item for the selection field. A selection of a particular action in the list of selectable actions is received, and an action interface for performing the particular action is presented in the GUI based on the selection of the particular action.

Abstract: According to one aspect of the present disclosure, a telemetry data set, which includes a plurality of data fields associated with application operations, is collected for an application. A request for at least a portion of the telemetry data set is received and processed. Data fields in the telemetry data set that are to be anonymized are identified based on the request, with information in the identified data fields is to be anonymized according to corresponding anonymization rules. The information in each of the identified data fields is masked based on the corresponding anonymization rule for the data field, and an anonymized telemetry data set is generated. The anonymized telemetry data set includes the masked information for the identified data fields and unmasked information for other data fields indicated in the request.

Abstract: A request to upgrade one or more agents hosted on a particular computing system is received and an upgrade package is identified that includes a set of upgrade files. The upgrade package is determined to include a manager upgrade file for a service manager hosted on the particular computing system, where the one or more agents are child processes of the service manager. The agent upgrade files are accessed from the upgrade package and upgrades of the agents are performed using the agent upgrade files. An upgrade of the service manager is also performed using the manager upgrade file based on the request to upgrade, where the upgrade of the service manager is performed with the upgrades of the one or more agents.

Abstract: A connection request is received from an agent at a particular one of multiple communication processes of an automation engine, for the agent to connect to the automation engine through the particular communication process. The agent is to act as one of multiple agents configured to perform automation actions at the direction of the automation engine system, where communication between the automation engine and the agents is facilitated through the communication processes. A number of connections at each of the communication processes is determined and a threshold value is identified. The particular communication process determines that connecting the particular agent to the particular communication process would cause the number of connections at the particular communication process to violate the threshold. The particular communication process causes the particular agent to instead connect to another one of the communication processes of the automation engine based on the threshold.