Oracle International Corporation

Microsoft Technology Licensing, LLC

Arsalan Ahmad

Girish Nagaraja

Nikhil Yograj Vaishnavi

Gregg Alan Wilson

Lokesh Gupta

Martinus Petrus Lambertus Van Den Dungen

Ashwin Kumar Vajantri

Pradyumna Reddy Vajja

Dharma Kiritkumar Shukla

Karthik Raman

Momin Mahmoud Al-Ghosien

Ji Huang

Alain Franck Gefflaut

Shireesh Kumar Thota

Pankaj Sharma

Alain Gefflaut

Alexandre De Baynast

Tony Long

Sujit Vattathil Kuruvilla

Andreas Steinmetzler

Girish Yashawant Mande

Arun Upadhyaya Kishan

Todd R Manion

Sandeep Singhal

David Bradley Probert, Jr

Jonathan E Lange

Madhan Gajendran

Atul Katiyar

Thomas James Andrews

Gregory John Colombo

Ankur Savailal Shah

Hari Sudan Sundar

Hemant Kumar

Shreshth Singhal

Liang Li

Rajeev Sudhakar Bhopi

Karthik Venkatesh

Ovidiu Constantin Platon

Zhou Wang

Philip James Ramsey

Padma Priya Aradhyula Bhavani

William Dunlap

Satnam Singh

Kiran Kumar Kolli

Jeff Engel

Junyan Guo

Thomas Santen

Venkata Sivaramakrishna Ramadugu

Robert Lee Tesch, Ii

Mohammad Derakhshani

Vijay Kumar Agrawal

Krishna Sai Veera Reddy

Denis Rystsov

Swarnim Vyas

Mark Livschitz

An approach of performing data center failover using an address that indicates a backup data center. The address includes common names indicating a data center with a domain and a backup datacenter with a replica of the domain. A cloud service provider can receive the address, establish a connection with an available data center, and failover to the backup data center if the data center with the connection becomes unavailable.

Failover of domains

A system executes an authorization process for initiating a session with a computing entity. Executing the authorization process includes determining an identity associated with the computing entity, identifying a current set of access policies associated with the identity, and determining, based on the current set of access policies, a first set of actions that the computing entity is authorized to perform. While executing the session, the system executes a first action in accordance with the current set of access policies. Subsequent to executing the first action, the set of access policies is modified. The system detects an occurrence of a trigger condition, and in response, re-executes the authorization process for the session, including determining, based on the modified set of access policies, a second set of actions the computing entity is authorized to perform that differs from the first set of actions.

Re-executing an authorization process to determine an updated set of authorized actions that may be initiated by a computing entity during a session

A system receives a replication credential associated with a request to replicate a dataset to a destination partition of a cloud environment. The replication credential includes a destination identifier that identifies the destination partition as a destination for replicating the dataset. The system accesses a replication tag associated with the dataset that defines a replication policy for the dataset. The replication tag includes a destination key that identifies the destination as being a permissible destination for replicating the dataset in accordance with the replication policy. The system determines that replication is permissible based on successfully validating that the destination key corresponds to the destination partition identified by the destination identifier of the replication credential. Responsive to determining that replication is permissible, the system initiates a set of one or more operations to replicate the dataset to the destination partition.

Evaluating replication credentials against replication tags to determine whether to grant replication requests

Approaches of reassigning a home region from a first data center to a second data center as requested by a customer are described herein. The home region is able to implement write operations to a domain, whereas other data centers cannot implement write operations to the domain. The customer can request the home region being reassigned to another data center such that the customer can utilize the other data center to implement write operations to the domain.

Home region switch

A server can receive a request to subscribe to a data tenancy in an extended region. The server can determine a size of stored data records associated with the data tenancy in a home region to be replicated in the extended region. Based in part on the size of the stored data records, the server can open a new communication channel dedicated to replicating the stored data records from the first server in the home region to the second server in the extended region. The server can pull the stored data records from the first server in the home region, store the pulled data records on the second sever in the extended region. The server can receive updated data records over an established communication channel between the first server in the home region and the second server in the extended region and store the updated data records on the second server.

Dedicated replication channels for replicating records between regions

The present embodiments relate to a CI replication service that can replicate domain data from IDCS control plane to data plane and to all subscribed regions of a domain. For instance, the CI replication service can provide replication of required resources of a domain for AuthN and AuthZ from an IDCS local region to other regions for high availability (e.g., to improve latency). The CI replication service can replicate the resources from a domain's home region to all subscribed regions for local availability of data for workloads running in those regions. Further, when a new region is subscribed for a domain, then the service can bootstrap that domain's data from home region before enabling that region for the domain.

Domain replication across regions

Distributed transactions are performed over a collection of servers operating as replicas of a data set, where a successful transaction involves meeting a quorum count of replicas that locally commit the transaction. However, performance constraints of data sets and consuming applications may vary (e.g., sensitivity to latency, scalability, and/or consistency), and the performance characteristics of the server set may be partly determined by the transactional commitment and quorum selection. The distributed transaction may be applied by designating the replicas as a set of followers and a leader that initiates the transaction and receives acknowledgments of local commits by each follower. On condition of the acknowledgments meeting a quorum count for the data set according to the performance characteristics of the application, the leader locally commits the transaction and delivers a result. The transaction may also be applied over collections of replica sets using a second-level quorum to achieve nested consensus.

Resource-governed protocol and runtime for distributed databases with consistency models

Data services are often provided with consistency guarantees of either strong consistency models, comprising uniform wall-clock consistency, or eventual consistency models, where temporary logical inconsistency is guaranteed to be resolved only after full data propagation. However, the performance characteristics of contemporary services often require an intermediate consistency model, where some aspects of the service have specific consistency expectations and other aspects of the service are flexible, such as bounded staleness (e.g., a maximum delay in reaching consistency); session consistency (e.g., individual sessions remain logically consistent, but ordering may vary across sessions); and prefix consistency (e.g., each view during a session is logically consistent, but ordering may vary between session views). Service guarantees may involve a selection within a range of consistency models that includes one or more intermediate consistency levels, and server configurations may be selected and applied to fulfill the intermediate consistency level selected in the service level agreement.

Intermediate consistency levels for database configuration

A service control manager manages one or more services on a computing device, such as creating processes that host the services, stopping the processes that host the services, and so forth. The service control manager also provides a request to a resource manager to reserve, monitor, and/or place limitations on resources for each of the one or more services. For example, the service control manager can request to be notified when resource usage by a service exceeds a resource usage threshold value. These resources are various resources of the computing device, such as a processor (CPU), memory, storage device input/output (I/O), network usage, and so forth. If the usage of a resource by a service satisfies the resource usage threshold value for that resource for that service, then the resource manager notifies the service control manager so the service control manager can take an appropriate remedial action.

Resource management for services

Various embodiments provide techniques and devices for protecting application secrets from operating system attacks. In some examples, applications execute with an isolated user mode of a secure execution environment, while relying on an operating system executing within a separate execution environment for resource management and system services. A proxy kernel can control access by the operating system to data associated with the secure execution environment. Further, the proxy kernel can act as a transparent interface between isolated user mode applications and the operating system during the provision of resource management and system services.

Protecting application secrets from operating system attacks

A stream processing execution engine evaluates development-time performance characteristic estimates in combination with run-time parameters to schedule execution of stream processing software components in a stack of a stream processing application that satisfy a defined performance criterion in a heterogeneous hardware device. A stream processing application includes a stack of interdependent stream processing software components. A stream processing execution engine evaluates one or more performance characteristics of multiple computational resources in the heterogeneous hardware device. Each performance characteristic is associated with performance of a computational resource in executing a computational-resource-dependent instance of a stream processing software component. The stream processing execution engine schedules within the run-time environment a computational resource on which to execute a computational-resource-dependent instance of one of the stream processing software components. The computational-resource-dependent instance is targeted for execution on the computational resource that satisfies a performance policy attributed to the stream processing software component.

Stream processing on heterogeneous hardware devices

Architecture for exposing a virtual private network of peer devices into the public domain via an overlay network. Computing devices, peripheral devices, as well as mobile devices can be physically distributed, but appear to belong to the same virtual private (or home) network, and be accessible from anywhere. Benefits include access to user media/documents from anywhere, searching of all connected devices from one location, multicast and broadcast connectivity, management of the private network and the associated policies, and device discovery on the private network from across public networks. P2P networks and ad-hoc networks can be exposed as a virtual interface, as well as the utilization of client operating systems to create the virtual network, grouping, graphing, the integration with relay services and other NAT/firewall traversal schemes, and the creation of a P2P overlay manager on a physical NIC (network interface card) address rather than a virtual address.

Private virtual LAN spanning a public network for connection of arbitrary hosts

A framework capable of providing transparent handling of network traffic in close proximity networks such as home networks is provided. A single virtual network interface is exposed to users/applications on connected devices. A virtual network interface manager determines available physical network interfaces and switches to a different physical network interface or a different configuration on the same physical network interface in a transparent manner to the communicating application(s). This enables the framework to optimize network communications for the communicating applications, devices, and users based on predefined criteria, application requirements such as different data throughput, or changing environment conditions such as interference. Network communication operations are also simplified for users since they are no longer required to have the necessary knowledge for configuring physical network interfaces manually in response to changing conditions.

Framework for optimizing and simplifying network communication in close proximity networks

Growing community of inventors

Redmond, WA, United States of America

Arsalan Ahmad