Abstract: A system allows users to perform analysis of objects processed by systems, for example, requests, traces, logs, and so on. The system allows users to use an object tagging language to categorize objects. Tagging rules specified using the object tagging language are executed to tag the objects processed. The system created a tagging metadata index based on the tagged objects. The tagging metadata index allows efficient execution of queries used for analyzing the objects. The system may be used for analyzing execution of systems, for example, to compare execution of replicas of a system to determine whether there are differences in the execution of different replicas.

Abstract: System and methods are described for automated recovery from errors occurring during replication of a database. The method includes getting text from one or more log files generated during database replication processing in a cloud computing environment, transforming the text into a structured language form represented by vectors, and identifying patterns in the vectors. The method further includes classifying one or more errors based on the identified patterns using supervised learning as either a recoverable error or an unrecoverable error, analyzing the one or more errors to determine one or more recovery jobs associated with database replication processing in the cloud computing environment for each of the recoverable errors, and invoking the one or more recovery jobs.

Abstract: Systems and methods are provided for retrieving a source database replication configuration profile that is used to determine one or more databases of a plurality of target databases to store selected tenant data of a source database to be replicated, retrieving from each the plurality of target databases a target database replication configuration profile and transforming the profiles to persist in a management platform database, comparing the retrieved source database replication configuration profile and the target database replication configuration profiles to determine which target databases are usable to replicate the selected tenant data to, classifying the target database replication configuration profiles based on results of the comparison, and generating a list of one or more target databases of the plurality of target databases for the selected tenant data of the source database to be replicated to based on the classification of the target database replication configuration profiles.

Abstract: System and methods are described for specifying, deploying, and using plugins during replication of a database. The method includes receiving a replication plugin service configuration specifying a plurality of plugins, getting a first database plugin specified by the replication plugin service configuration, getting one or more reader plugins specified by the replication plugin service configuration, deploying the first database plugin and the one or more reader plugins to a relay communicating with a source database, and getting data from the source database using the first database plugin and the one or more reader plugins.

Abstract: System and methods are described for creating an instance of a database in a cloud computing environment. One method includes receiving a request to deploy an instance of a database in a cloud computing environment, the request including a database deployment model defining deployment of the database instance, building a deployment model decision tree based on the database deployment model, and initializing a cloud deployment strategy using the database deployment model for enabling one or more cloud service providers of the cloud computing environment to deploy the database instance. The method further includes provisioning cloud computing resources for the database instance according to the cloud deployment strategy, initializing sets of services for the database instance according to the deployment model decision tree, creating the database instance, and indicating the database instance as active in the cloud computing environment.

Abstract: System and methods are described for automated recovery from errors occurring during replication of a database. The method includes getting text from one or more log files generated during database replication processing in a cloud computing environment, transforming the text into a structured language form represented by vectors, and identifying patterns in the vectors. The method further includes classifying one or more errors based on the identified patterns using supervised learning as either a recoverable error or an unrecoverable error, analyzing the one or more errors to determine one or more recovery jobs associated with database replication processing in the cloud computing environment for each of the recoverable errors, and invoking the one or more recovery jobs.

Abstract: System and methods are described for specifying, deploying, and using plugins during replication of a database. The method includes receiving a replication plugin service configuration specifying a plurality of plugins, getting a first database plugin specified by the replication plugin service configuration, getting one or more reader plugins specified by the replication plugin service configuration, deploying the first database plugin and the one or more reader plugins to a relay communicating with a source database, and getting data from the source database using the first database plugin and the one or more reader plugins.

Abstract: System and methods are described for creating an instance of a database in a cloud computing environment. One method includes receiving a request to deploy an instance of a database in a cloud computing environment, the request including a database deployment model defining deployment of the database instance, building a deployment model decision tree based on the database deployment model, and initializing a cloud deployment strategy using the database deployment model for enabling one or more cloud service providers of the cloud computing environment to deploy the database instance. The method further includes provisioning cloud computing resources for the database instance according to the cloud deployment strategy, initializing sets of services for the database instance according to the deployment model decision tree, creating the database instance, and indicating the database instance as active in the cloud computing environment.

Abstract: Techniques are disclosed relating to generating code that is executable to implement a data replication policy. In various embodiments, a computer system provides, to a client device, code that is usable to generate a GUI that enables a user of the client device to define a data replication policy, via the GUI, to be implemented during a data replication operation. The computer system may then receive, from the client device, user input provide via the GUI that defines a first data replication policy, where the user input indicates a series of transformations to be performed, as part of the first data replication policy, on a first database object from a source database to replicate a transformed version of the first database object to a target database. Based on the user input, the computer system may generate code that is executable to implement the first data replication policy.

Abstract: System and methods are described for automated replication of a database. The method includes generating a replication decision tree (RDT) for a database replication, deploying a database installation according to the RDT, and identifying a replication topology for the database replication according to the RDT. The method further includes loading schemas for one or more source databases and one or more target databases according to the replication topology and the RDT, validating a replication policy, and cloning the one or more source databases to the one or more target databases according to the replication policy.

Abstract: Systems and methods are provided for retrieving a source database replication configuration profile that is used to determine one or more databases of a plurality of target databases to store selected tenant data of a source database to be replicated, retrieving from each the plurality of target databases a target database replication configuration profile and transforming the profiles to persist in a management platform database, comparing the retrieved source database replication configuration profile and the target database replication configuration profiles to determine which target databases are usable to replicate the selected tenant data to, classifying the target database replication configuration profiles based on results of the comparison, and generating a list of one or more target databases of the plurality of target databases for the selected tenant data of the source database to be replicated to based on the classification of the target database replication configuration profiles.

Abstract: Examples described relate to container images. An example method may include generating a mapping of respective unique identifiers of container images of a software container and respective metadata of the container images, validating the mapping against a rule to identify a unique identifier of a mapped container image that meets the rule, generating a target mapping that includes the unique identifier of the mapped container image that meets the rule and the action specified in the rule, and performing the action specified in the rule on the mapped container image corresponding to the unique identifier in the target mapping.

Abstract: A cloned configuration of a source machine is created by determining a first set of physical location codes for a source machine. A map is generated based on the sorted physical location codes that maps the first set of physical location codes to a first set of generic location codes. A second set of physical location codes associated with a second set of adapter slots in a target machine is generated. A second map is generated based on the sorted second set of physical location codes that maps the second set of physical location codes to a second set of generic location codes. A third set of physical location codes is generated based on the first set of generic location codes and the second map. If an entry in the third set of physical location codes is not present the second set of physical location codes, an error is generated.

Abstract: Techniques of workload deployment in a computing network are described. For example a computing system may receive a workload deployment request for deployment of a workload on resources of the computing network. The computing system may determine unavailability of interoperable resources for deployment of the workload, based on interoperability information associated with each of the resources, and identify at least one set of resources for deployment of the workload, where deploying the workload on each set of resources from amongst the at least one set of resources comprises changing configuration of at least one resource included within corresponding set of resources. The computing system may further rate each of the set of resources based on deployment parameters, and select a first set of resources from amongst the at least one set of resources for deployment of the workload based on the rank of each of the set of resources.

Abstract: A method, system, and program product for hypervisor controlled redundancy for Input/Output (I/O) paths using virtualized I/O adapters is provided. A hypervisor detects a virtual machine exceeding a pre-defined bandwidth threshold. The hypervisor searches a shared pool of free virtual functions (VF) for a free VF. If the shared pool of free VFs is not depleted, a free VF is allocated to the virtual machine (VM). If the shared pool of free VFs is depleted, the active VMs are examined for VF capacity that may be donated to the triggering VM.

Abstract: Examples described relate to validating network parameters of a containerized application. In an example, the current state of a network parameter configured for a containerized application in a cloud computing environment may be determined. The current state of the network parameter may be validated against a container application profile of the containerized application, wherein the container application profile specifies a desired state of the network parameter. In response to a determination that the current state of the network parameter does not meet the desired state of the network parameter specified in the container application profile, a determination may be made whether a network interface that meets the desired state of the network parameter is available in the cloud computing environment. In response to a determination that the network interface is available in the cloud computing environment, the containerized application may be migrated to the available network interface.

Abstract: Examples described relate to container images. In an example, a mapping of respective unique identifiers of container images of a software container and respective metadata of the container images may be generated. The mapping may be validated against a rule to identify a unique identifier of a mapped container image that meets the rule, wherein the rule may specify an action to be performed on the mapped container image in an event the mapped container image meets a condition defined in the rule for performing the action. A target mapping that includes the unique identifier of the mapped container image that meets the rule and the action specified in the rule may be generated. The action specified in the rule may be performed on the mapped container image corresponding to the unique identifier in the target mapping.

Abstract: Methods, devices, and techniques for determining interoperable resources are discussed herein. For example, in one aspect, a resource in a cloud environment may be discovered. Responsive to discovering the resource, an interoperability support matrix associated with the resource can be obtained. The interoperability support matrix may specify another resource that interoperates with the resource. An interoperability record is then stored in an interoperability support matrix repository. The interoperability record can specify that the another resource interoperates with the resource.

Abstract: In one implementation, a system for policy based workload scaler includes a parameters engine to define external factors for a number of resources providing a number of cloud service workloads, a threshold engine to define a threshold value for the cloud service workloads from the number of resources, a priority engine to assign a priority to each of the number of cloud service workloads, and a service engine to reclaim resources from a first portion of cloud service workloads with a first priority and allocate the reclaimed resources to a second portion of cloud service workloads when the threshold value is exceeded and the external factors are exceeded.

Abstract: A cloned configuration of a source machine is created by determining a first set of physical location codes for a source machine. A map is generated based on the sorted physical location codes that maps the first set of physical location codes to a first set of generic location codes. A second set of physical location codes associated with a second set of adapter slots in a target machine is generated. A second map is generated based on the sorted second set of physical location codes that maps the second set of physical location codes to a second set of generic location codes. A third set of physical location codes is generated based on the first set of generic location codes and the second map. If an entry in the third set of physical location codes is not present the second set of physical location codes, an error is generated.