Abstract: A system uses a machine learning model to identify anomalies and modify parameters of a computing environment. The system modifies parameters of a computing environment based on the presence and absence of anomalies in the computing system while avoiding modifying parameters as a result of brief spikes in computing environment attributes. The system uses a machine learning model to generate predictions of anomalies for data points of computing environment attributes. The system compiles sets of predictions into batches. The system determines whether each batch includes enough anomalous-labeled data points to be considered an anomalous batch. The system compiles the batches into sets. The system determines whether the sets of batches include enough anomalous batches to be considered an anomalous set of batches. The system modifies the parameters of the computing environment based on determining whether or not the sets of batches are anomalous.

Abstract: Embodiments govern cloud environments using a policy engine. A plurality of policy definitions for governing a plurality of managed environments can be received at a policy engine, each policy definition including one or more conditions and one or more actions, where the managed environments implement cloud based virtual machines that host cloud based applications. Events that relate to one or more of the managed environments can be received at the policy engine. Conditions for the policy definitions can be evaluated by the policy engine, where conditions for a first policy definition are triggered based on one or more of the received events. Based on the evaluating, one or more actions of the first policy definition can be performed, the one or more actions changing a first managed environment that is governed by the first policy definition.

Abstract: Embodiments govern cloud environments using a policy engine. A plurality of policy definitions for governing a plurality of managed environments can be received at a policy engine, each policy definition including one or more conditions and one or more actions, where the managed environments implement cloud based virtual machines that host cloud based applications. Events that relate to one or more of the managed environments can be received at the policy engine. Conditions for the policy definitions can be evaluated by the policy engine, where conditions for a first policy definition are triggered based on one or more of the received events. Based on the evaluating, one or more actions of the first policy definition can be performed, the one or more actions changing a first managed environment that is governed by the first policy definition.

Abstract: Embodiments govern cloud environments using a policy engine. A plurality of policy definitions for governing a plurality of managed environments can be received at a policy engine, each policy definition including one or more conditions and one or more actions, where the managed environments implement cloud based virtual machines that host cloud based applications. Events that relate to one or more of the managed environments can be received at the policy engine. Conditions for the policy definitions can be evaluated by the policy engine, where conditions for a first policy definition are triggered based on one or more of the received events. Based on the evaluating, one or more actions of the first policy definition can be performed, the one or more actions changing a first managed environment that is governed by the first policy definition.

Abstract: A cloud manager restores a backup of a distributed environment by comparing a stack of a current distributed environment to a backup stack of the backup of the distributed environment. The cloud manager identifies a difference between a first number of nodes in the first set of nodes specified in the first stack and a second number of nodes in the second set of nodes specified in the second stack. The cloud manager restores the backup of the distributed environment by modifying a number of nodes in the current distributed environment based on the identified difference between the first number of nodes and the number of nodes in the second stack.

Abstract: A system uses a machine learning model to identify anomalies and modify parameters of a computing environment. The system modifies parameters of a computing environment based on the presence and absence of anomalies in the computing system while avoiding modifying parameters as a result of brief spikes in computing environment attributes. The system uses a machine learning model to generate predictions of anomalies for data points of computing environment attributes. The system compiles sets of predictions into batches. The system determines whether each batch includes enough anomalous-labeled data points to be considered an anomalous batch. The system compiles the batches into sets. The system determines whether the sets of batches include enough anomalous batches to be considered an anomalous set of batches. The system modifies the parameters of the computing environment based on determining whether or not the sets of batches are anomalous.

Abstract: A cloud manager restores a backup of a distributed environment by comparing a stack of a current distributed environment to a backup stack of the backup of the distributed environment. The cloud manager identifies a difference between a first number of nodes in the first set of nodes specified in the first stack and a second number of nodes in the second set of nodes specified in the second stack. The cloud manager restores the backup of the distributed environment by modifying a number of nodes in the current distributed environment based on the identified difference between the first number of nodes and the number of nodes in the second stack.

Abstract: Embodiments govern cloud environments using a policy engine. A plurality of policy definitions for governing a plurality of managed environments can be received at a policy engine, each policy definition including one or more conditions and one or more actions, where the managed environments implement cloud based virtual machines that host cloud based applications. Events that relate to one or more of the managed environments can be received at the policy engine. Conditions for the policy definitions can be evaluated by the policy engine, where conditions for a first policy definition are triggered based on one or more of the received events. Based on the evaluating, one or more actions of the first policy definition can be performed, the one or more actions changing a first managed environment that is governed by the first policy definition.

Abstract: A cloud manager restores a backup of a distributed environment by comparing a stack of a current distributed environment to a backup stack of the backup of the distributed environment. The cloud manager identifies a difference between a first number of nodes in the first set of nodes specified in the first stack and a second number of nodes in the second set of nodes specified in the second stack. The cloud manager restores the backup of the distributed environment by modifying a number of nodes in the current distributed environment based on the identified difference between the first number of nodes and the number of nodes in the second stack.

Abstract: Techniques for cloning a computing environment while modifying components of the computing environment are disclosed. A cloning request specifies a modification to a source environment. A cloning engine determines one or more additional non-requested modifications to be made in a destination environment necessitated by the requested modification. A modified destination specification is generated including the requested modification and the one or more additional non-requested modifications. A destination stack is generated, and the destination environment is provisioned according to the destination stack.

Abstract: A cloud manager restores a backup of a distributed environment by comparing a stack of a current distributed environment to a backup stack of the backup of the distributed environment. The cloud manager identifies a difference between a first number of nodes in the first set of nodes specified in the first stack and a second number of nodes in the second set of nodes specified in the second stack. The cloud manager restores the backup of the distributed environment by modifying a number of nodes in the current distributed environment based on the identified difference between the first number of nodes and the number of nodes in the second stack.

Abstract: Techniques for cloning a computing environment while modifying components of the computing environment are disclosed. A cloning request specifies a modification to a source environment. A cloning engine determines one or more additional non-requested modifications to be made in a destination environment necessitated by the requested modification. A modified destination specification is generated including the requested modification and the one or more additional non-requested modifications. A destination stack is generated, and the destination environment is provisioned according to the destination stack.

Abstract: The present disclosure relates to automatically and periodically updating a multi-tier application stack in a cloud environment. More particularly, the present disclosure relates to systems and methods that access a central server to determine if new updates have been released, and when new updates have been released, automatically apply the new updates to an application environment with minimal network burden and service interruption.

Abstract: The present disclosure relates to exporting local applications to cloud systems and provisioning the exported application on the cloud systems. Additionally, templates can be generated for the provisioned application, and each template can be individually customized and deployed to a destination as an application environment with a defined topology. Rapidly and dynamically generating deployable templates of provisioned applications enables cloud-based distributed versioning of the applications.

Abstract: The present disclosure relates to automatically and periodically updating a multi-tier application stack in a cloud environment. More particularly, the present disclosure relates to systems and methods that access a central server to determine if new updates have been released, and when new updates have been released, automatically apply the new updates to an application environment with minimal network burden and service interruption.

Abstract: The present disclosure relates to exporting local applications to cloud systems and provisioning the exported application on the cloud systems. Additionally, templates can be generated for the provisioned application, and each template can be individually customized and deployed to a destination as an application environment with a defined topology. Rapidly and dynamically generating deployable templates of provisioned applications enables cloud-based distributed versioning of the applications.

Abstract: A web server provided according to aspect of the present disclosure maintains registration data indicating the browsers to be notified upon occurrence of corresponding events. Upon receiving notification of occurrence of an event from an application server, the web server determines the set of browsers registered to receive notification of the occurrence of the event, and pushes the event to each of the set of browsers. By relying on a web server for such operation, each of the applications in the application server can be implemented as stateless applications, thereby providing advantages such as scalability and portability.

Abstract: A web server provided according to aspect of the present disclosure maintains registration data indicating the browsers to be notified upon occurrence of corresponding events. Upon receiving notification of occurrence of an event from an application server, the web server determines the set of browsers registered to receive notification of the occurrence of the event, and pushes the event to each of the set of browsers. By relying on a web server for such operation, each of the applications in the application server can be implemented as stateless applications, thereby providing advantages such as scalability and portability.