Abstract: A system and method for blocking path detection is provided. A job comprises tasks with at least some of the tasks dependent on other task(s). Each task is assigned to an ownership team. At a particular point in execution of the job, states of tasks of the job are identified. The states include one of three mutually exclusive states: waiting for another task/finished, in progress, and, blocked. When all the tasks with identified states of in progress or blocked are assigned to a particular ownership team, the particular ownership team is identified as on a blocking path. An action can be performed regarding the blocking path, for example, selected in accordance with policy-defined response actions such as generating an incident, escalating an existing incident, and/or sending a notification (e.g., an accumulated time on the blocking path can be calculated for each team with team(s) notified when certain threshold(s) are exceeded).

Abstract: To improve the reliability of nodes that are utilized by a cloud computing provider, information about the entire lifecycle of nodes can be collected and used to predict when nodes are likely to experience failures based at least in part on early lifecycle errors. In one aspect, a plurality of failure issues experienced by a plurality of production nodes in a cloud computing system during a pre-production phase can be identified. A subset of the plurality of failure issues can be selected based at least in part on correlation with service outages for the plurality of production nodes during a production phase. A comparison can be performed between the subset of the plurality of failure issues and a set of failure issues experienced by a pre-production node during the pre-production phase. A risk score for the pre-production node can be calculated based at least in part on the comparison.

Abstract: An automated root-cause analysis (RCA) system may provide a fully automated platform that provides dependency and execution order modeling for tasks included in a capacity provisioning process, anomaly detection, ticket correlation, root-cause analysis, monitoring and feedback, and data visualization. The automated RCA system may continuously collect and store data for use in determining a root cause of a blockage on a capacity provisioning process. The blockage may be identified in a ticket generated by a cloud-computing system. The automated RCA system may receive the ticket and attempt to determine the root cause of the blockage based on root causes associated with previous tickets generated by the cloud-computing system. The automated RCA system may identify a true root cause, recommend repair items based on the true root cause, identify one or more responsible teams to drive a fix, and provide an estimated time for completion.

Abstract: To improve the reliability of nodes that are utilized by a cloud computing provider, information about the entire lifecycle of nodes can be collected and used to predict when nodes are likely to experience failures based at least in part on early lifecycle errors. In one aspect, a plurality of failure issues experienced by a plurality of production nodes in a cloud computing system during a pre-production phase can be identified. A subset of the plurality of failure issues can be selected based at least in part on correlation with service outages for the plurality of production nodes during a production phase. A comparison can be performed between the subset of the plurality of failure issues and a set of failure issues experienced by a pre-production node during the pre-production phase. A risk score for the pre-production node can be calculated based at least in part on the comparison.

Abstract: An automated root-cause analysis (RCA) system may provide a fully automated platform that provides dependency and execution order modeling for tasks included in a capacity provisioning process, anomaly detection, ticket correlation, root-cause analysis, monitoring and feedback, and data visualization. The automated RCA system may continuously collect and store data for use in determining a root cause of a blockage on a capacity provisioning process. The blockage may be identified in a ticket generated by a cloud-computing system. The automated RCA system may receive the ticket and attempt to determine the root cause of the blockage based on root causes associated with previous tickets generated by the cloud-computing system. The automated RCA system may identify a true root cause, recommend repair items based on the true root cause, identify one or more responsible teams to drive a fix, and provide an estimated time for completion.

Abstract: To improve the reliability of nodes that are utilized by a cloud computing provider, information about the entire lifecycle of nodes can be collected and used to predict when nodes are likely to experience failures based at least in part on early lifecycle errors. In one aspect, a plurality of failure issues experienced by a plurality of production nodes in a cloud computing system during a pre-production phase can be identified. A subset of the plurality of failure issues can be selected based at least in part on correlation with service outages for the plurality of production nodes during a production phase. A comparison can be performed between the subset of the plurality of failure issues and a set of failure issues experienced by a pre-production node during the pre-production phase. A risk score for the pre-production node can be calculated based at least in part on the comparison.

Abstract: A system and method for blocking path detection is provided. A job comprises tasks with at least some of the tasks dependent on other task(s). Each task is assigned to an ownership team. At a particular point in execution of the job, states of tasks of the job are identified. The states include one of three mutually exclusive states: waiting for another task/finished, in progress, and, blocked. When all the tasks with identified states of in progress or blocked are assigned to a particular ownership team, the particular ownership team is identified as on a blocking path. An action can be performed regarding the blocking path, for example, selected in accordance with policy-defined response actions such as generating an incident, escalating an existing incident, and/or sending a notification (e.g., an accumulated time on the blocking path can be calculated for each team with team(s) notified when certain threshold(s) are exceeded).

Abstract: Described herein is a system and method for dependency version conflict auto-resolution for executing job(s). During execution of a particular version of a workflow comprising tasks, information regarding a particular task to be executed is received. The particular task is dependent on another task. Information regarding the dependency is retrieved from a global dependency data structure (e.g., graph) that stores current dependency information regarding the tasks. When it is determined that the conflict exists with respect to the dependency of the particular task on the another task, information regarding the dependency and workflows is retrieved, information regarding a dependency change history regarding at least one of the plurality of tasks, information regarding the particular version of the workflow and a different version of the workflow. A resolution to the conflict can be identified based, at least in part, upon the retrieved information, and, a correct action performed.