Abstract: Improving program execution using interprocedural escape analysis with inlining includes expanding a call graph of a target program to obtain an expanded call graph, performing, using the expanded call graph, an interprocedural escape analysis (IEA) to generate a materialization map, and calculating an inlining benefit value for a callee using the materialization map. Improving program execution further includes inlining, using the expanded call graph and in the target program, the callee according to the inlining benefit value, updating, after inlining the callee, an allocation in the target program, and completing, after updating the allocation, compilation of the target program.

Abstract: The present disclosure relates to techniques for using variant inconsistency attack (VIA) as a simple and effective adversarial attack method to create useful adversarial examples for adversarial training of machine-learning models. In one particular aspect, a method is provided that includes obtaining a set of input examples for attacking a machine-learning model (the set of examples do not have corresponding labels), modifying an example from the set of examples in a utility preserving manner to generate a pair of modified examples, attacking the machine-learning model with the pair of modified examples in order generate a pair of predictions for the pair of modified examples, comparing the pair of predictions to determine whether the pair of predictions are the same or different, and in response to the pair of predictions being different, adding the pair of modified examples to a set of adversarial examples.

Abstract: Systems and methods implement partial evaluation of single execution methods. A native image is built from a build image compiled from source code. At image build time, a single execution method of the build image is executed to update an image heap of the native image. The single execution method is executed with a single execution for a native instance. The image heap is stored to the native image built from the build image.

Abstract: A computing device may access a target code for implementing an application. The device may identify addresses for one or more functions or one or more variables associated with the target code. The device may generate an interval tree comprising a root node and one or more function nodes. The device may in response to the target code invoking a function or variable: generate an intercept function configured to intercept communication between the target code and a call address for the at least one of the one or more functions or the one or more variables invoked by the target code. The device may intercept data communicated between the target code and the call address. The device may store the intercepted data as a function node in the interval tree. The device may transmit the interval tree to a user device.

Abstract: Techniques for machine-learning of long-term seasonal patterns are disclosed. In some embodiments, a network service receives a set of time-series data that tracks metric values of at least one computing resource over time. Responsive to receiving the time-series data, the network service detects a subset of metric values that are outliers and associated with a plurality of timestamps. The network service maps the plurality of timestamps to one or more encodings of at least one encoding space that defines a plurality of encodings for different seasonal patterns. Based on the mapped encodings, the network service generates a representation of a seasonal pattern. Based on the representation of the seasonal pattern, the network service may perform one or more operations in association with the at least one computing resource.

Abstract: In some implementations, the techniques disclosed herein may include monitoring, by a robotic device, a physical space, the physical space having a portion of a datacenter. In addition, the techniques may include detecting, by the robotic device, a person within the physical space. The techniques may include attempting to authenticate the detected person by an authentication process that includes: prompting, by the robotic device, the detected person to authenticate themselves; receiving, by the robotic device, an authentication credential from the detected person; and determining, by the robotic device, whether the authentication of the detected person has passed. Moreover, the techniques may include in accordance with a determination that the authentication of the detected person has failed, performing an action commensurate with the determination that the authentication has failed.

Abstract: Techniques for extracting data from conversations across different types of communication channels are disclosed. A system applies a set of rules to extract data from conversations based, at least in part, on a type of communication channel used for conducting the conversation. The system applies a machine learning model to recognize semantic content in conversations. The system divides conversations into conversation segments and classifies the conversation segments based on the semantic content. The system selects conversation segments to be extracted based on the semantic content and the type of communication channel over which a conversation is conducted. The system maps conversation segments from different conversations conducted on different types of communication channels to a same set of transactions.

Abstract: Techniques for determining and displaying error messages including a cause of an error generated because two types are not members of the same nest are disclosed. The system detects, at runtime, an instruction in a first type that attempts to access a private member of a second type. The system evaluates one or more nestmate criteria to determine whether the first type and the second type are within a same nest. A nest host corresponding to the nest specifies each nest member of the nest, and each nest member specifies an association with the nest. Responsive to determining that a particular nestmate criterion is not met, the system determines that the first type and the second type are not within the same nest and records or displays data identifying the particular nestmate criterion that has not been met, and throws an access error.

Abstract: Systems, methods, and other embodiments associated with acoustic fingerprint identification of devices are described. In one embodiment, a method includes generating a target acoustic fingerprint from acoustic output of a target device. A similarity metric is generated that quantifies similarity of the target acoustic fingerprint to a reference acoustic fingerprint of a reference device. The similarity metric is compared to a threshold. In response to a first comparison result of the comparing of the similarity metric to the threshold, the target device is indicated to match the reference device. In response to a second comparison result of the comparing of the similarity metric to the threshold, it is indicated that the target device does not match the reference device.

Abstract: Provided are systems and methods for analyzing actions performed by users in using a cloud service, and adjusting the configuration of a security management and control system based on the analysis. In various examples, the analysis can include generating a weighted directed graph that reflects a user's use of the cloud service, and/or reflects the tenant's overall use of the cloud service. When the security monitoring and control system generates security alerts, the actions that resulted in the alerts can be compared to the graph to determine whether the actions are in accordance with prior behavior of the users. When the actions do correspond to the graph, the system can recommend that the security control or security policy that triggered the alert be modified. In various examples, the graphs can also be used to determine whether any user's actions are anomalous as compared to earlier behavior.

Abstract: In an embodiment, before modifying a persistent ORL (ORL), a database management system (DBMS) persists redo for a transaction and acknowledges that the transaction is committed. Later, the redo is appended onto the ORL. The DBMS stores first redo for a first transaction into a first PRB and second redo for a second transaction into a second PRB. Later, both redo are appended onto an ORL. The DBMS stores redo of first transactions in volatile SRBs (SLBs) respectively of database sessions. That redo is stored in a volatile shared buffer that is shared by the database sessions. Redo of second transactions is stored in the volatile shared buffer, but not in the SLBs. During re-silvering and recovery, the DBMS retrieves redo from fast persistent storage and then appends the redo onto an ORL in slow persistent storage. After re-silvering, during recovery, the redo from the ORL is applied to a persistent database block.

Abstract: A method for providing call intelligence to a signaling firewall in a communications network includes collecting, by a network security service component, call session data from incoming and outgoing calls involving a mobile device and providing, by the network security service component, the call session data to a signaling firewall via an application programming interface (API). The method further includes receiving, by the signaling firewall, an update location request message associated with the mobile device, extracting signaling message information that includes current location data and timestamp data from the received update location request message, and utilizing the current location data and the timestamp data to identify a correlated portion of the call session data.

Abstract: An example system and method facilitate enabling precise answers to technical support questions pertaining to a given computing environment, e.g., a cloud-based enterprise computing environment. The example method includes using an overtrained recurrent neural network employing Long Short-Term Memory (LSTM) cells to selectively answer specific questions by providing precise answers to technical support questions. A second neural network that is not overtrained can provide more generalized answers when a confidence measurement of an answer of the first neural network falls below a predetermined threshold. Furthermore, expert staff, e.g., developers and/or engineers that may be able to more precisely answer a specific question may be shown the answer. Subsequent expert answers or modifications to existing answers may be used to further refine the neural networks, e.g., via periodic supervised learning.

Abstract: When a coordinator of a sharded DBMS receives from a client a query that has an XML operator that references a column in a sharded table and returns an XML image having an XML image type, then the coordinator issues a remote query that uses a new operator to ensure that the shard returns a TBX BLOB having a TBX type. In response to receiving the remote query with the new operator, each shard extracts a binary large object (BLOB) out of the XML image at the shard and returns the TBX BLOB data to the coordinator. In addition, the sharded DBMS provides a make-XML operator that the coordinator uses to work with the TBX BLOB received from each shard and recreate an XML type image, which is the result that the client expects.

Abstract: Systems and methods provide tiered assessment of use of services in a cloud environment. An operator cloud environment running on computers including microprocessors, wherein the operator cloud environment is deployed within a first realm owned by an operator tenant of the realm, a set of software products provided to the first realm from a cloud infrastructure provider of the cloud environment for access via the first realm by a plurality of end users as vendor cloud services, and a metering service. Usage data that records usage of services in a realm includes identification data associating user entities with their usage of the services is provided to the operator tenant associated with control of the realm. A second set of data is generated by processing the usage data to remove or convert the identification data and is provided to the cloud infrastructure provider associated with control of the cloud environment.

Abstract: Systems that analyze the performance of a computing resource based on a usage information timeline are disclosed. A system detects peak activity periods occurring in the usage information of the computer resource and scores the individual peak activity periods. Based on the respective scores, the system identifies an anchor period from the peak activity periods. Using the anchor period, the system aggregates the peak activity periods around the anchor period. The aggregating include incrementally sliding a window through the usage information around the anchor period, wherein increments represent candidate activity period. The system selects a candidate activity period including peak activities periods with the greatest workload. The system allocates capacity to the computer resource based on characteristic of the selected candidate activity period.

Abstract: Techniques for improving the convenience of activating different computing applications on a mobile computing device are disclosed. Sensors associated with a mobile computing device (e.g., accelerometers, gyroscopes, light sensors, microphones, image capture sensors) may receive inputs of various physical conditions to which the mobile computing device is being subjected. Based on one or more of these inputs, the mobile computing device may automatically select a content presentation mode that is likely to improve the consumption of the content by the user. In other embodiments, image analysis may be used to access different mobile computing applications.

Abstract: Techniques are described that include receiving, by a computing system, a request to create a restored block volume using a first manifest, the first manifest comprising: (i) a block identifier for a block and (ii) a first block sequence number corresponding to the block identifier and associated with a first snapshot, and (iii) a manifest identifier. The techniques further include receiving, by the computing system, the request to create the restored block volume using a second manifest, the second manifest comprising: (i) the block identifier for the block, (ii) a second block sequence number corresponding to the block identifier and associated with a second snapshot. The techniques further include determining, by the computing system, whether the second block sequence number is indicative of the block having been altered after the first manifest was generated, and responsive to the determination by the computing system, creating the restored block volume.

Abstract: A technique is disclosed for creating a GraphQL Application Programing Interface (API) schema by introspecting various different types of backend datasources. The technique includes receiving a selection of a datasource type to create a GraphQL API schema and introspecting the selected datasource type to determine a set of individual elements associated with the selected datasource type. The technique involves outputting the set of individual elements associated with the selected datasource type via a User Interface (UI) screen of a computer system. The technique further includes receiving a selection of one more individual elements associated with the selected datasource type via a UI screen of the computer system. The technique includes generating a GraphQL API schema comprising a set of objects and a set of resolver functions based on the selected elements and presenting the GraphQL API schema via a UI screen associated with the computer system.

Abstract: Techniques are disclosed for creating an attachment between two compute instances. An infrastructure and a generalized method is described for attaching two or more cloud resources (e.g., two compute instances) in spite of the compute resources being provisioned by two different services from different cloud tenancies. An automated process is described that is executed for wiring the compute instances. The automated process can be generally applied to attach any two compute instances providing two different services and provisioned from two different service tenancies.

Abstract: Techniques for keyword data augmentation for training chatbot systems in natural language processing. In one particular aspect, a method is provided that includes receiving a training set of utterances for training a machine-learning model to identify one or more intents for one or more utterances, augmenting the training set of utterances with out-of-domain (OOD) examples. The augmenting includes: identifying keywords within utterances of the training set of utterances, generating a set of OOD examples with the identified keywords, filtering out OOD examples from the set of OOD examples that have a context substantially similar to context of the utterances of the training set of utterances, and incorporating the set of OOD examples without the filtered OOD examples into the training set of utterances to generate an augmented training set of utterances. Thereafter, the machine-learning model is trained using the augmented training set of utterances.

Abstract: Disclosed techniques relate to orchestrating power consumption reductions across a number of hosts. A number of response levels may be utilized, each having an association to a corresponding set of reduction actions. The impact to customers, hosts, and/or workloads can be computed at run time based on current and/or predicted conditions and workloads, and a particular response level can be selected based on the computed impact. These techniques enable a sufficient, but least impactful response to be employed.

Abstract: Techniques are disclosed for bootstrapping a secure data center using a cross domain system and a cluster of edge devices. The cross domain system can be implemented at the secure data center to provide one-way ingress and egress channels for network traffic to the target data center. The cross domain system is connected to a host data center and can receive configuration data from the host data center to configure the cluster of edge devices. The cross domain system can include a cluster configuration node that can request bootstrapping data from the host data center on demand, receive the requested bootstrapping data, and use the bootstrapping data to generate a virtual bootstrapping environment on the cluster of edge devices.

Abstract: An append operation is provided for using a plurality of threads on a plurality of streaming multiprocessors of a graphical processing unit. The append operation writes results into a result buffer. Executing the append operation comprises claiming, by each given thread within the plurality of threads having a result to write, a portion of a selected WCB, writing, by the given thread, the result to the portion of the selected WCB, and in response to a flush condition being met for the selected WCB, copying contents of the selected WCB to a result buffer.

Abstract: Techniques are disclosed for managing dependencies in an orchestration service. A computer-implemented method can include operations performed by a declarative infrastructure provisioner (DIP). In some embodiments, the DIP parses configuration data associated with a computing system and generates a directed acyclic graph (DAG) for booting a first resource. The DAG may specify a dependency of the first resource on a capability of a second resource. The DIP may traverse the DAG and determine, based at least in part on the traversal, that the dependency has been reached. The DIP may publish, to a scheduling process, an indication that the first resource is awaiting availability of the capability of the second resource. In some embodiments, the DIP receives a subsequent indication that the capability is available, regenerates the DAG, and recommences traversal of the DAG. Additional operations for booting the first resource may be performed in accordance with the recommenced traversal.

Abstract: Techniques for performing NAT operations to send packets between networks are described. In an example, a network device receives a packet that comprises a header. The header indicates a source address of a first computing resource in a first network and a destination address of a second computing resource in a second network. The network device determines a pool of identifiers allocated for the first network and the second computing resource and identifies a packet flow based on the header. The network device also determines that no identifier from the pool of identifiers has been allocated for the packet flow and determines an identifier available to allocate for the packet flow from the pool of identifiers. The network device performs a NAT operation on the packet based on the identifier.

Abstract: A method for managing NSSAI availability information at an NSSF includes receiving and storing NSSAI availability information from NF service consumers. The method further includes maintaining time values usable to determine expiration times for NSSAI availability information database records, where the time values are updated when a corresponding record is updated. The method further includes auditing the records, and, in response to failing to receive a request to update the NSSAI availability information for one of the NSSAI information database records within an expiration time, marking the record as stale. When a trigger is detected for providing NSSAI availability information from one of the database records that is marked as stale, the NSSF refrains from providing the NSSAI availability information to the NF service consumer.

Abstract: Systems, devices, and methods of the present invention involve discourse trees. In an example, a method involves generating a discourse tree. The method includes identifying, from the discourse tree, a central entity that is associated with a rhetorical relation of type elaboration and corresponds to a topic node that identifies a central entity of the text. The method includes determining a subset of elementary discourse units of the discourse tree that are associated with the central entity. The method includes forming generalized phrases from the subset of elementary discourse units. The method includes forming tuples from the generalized phrases, where a tuple is an ordered set of words in normal form. The method involves responsive to successfully converting an elementary discourse unit associated with an identified tuple into a logical representation, updating the ontology with an entity from the identified tuple.

Abstract: Systems are disclosed for determining contextual segments for targeting contextual advertising in metaverses. The system can deploy an observer avatar in a metaverse to capture information inside a portion of a metaverse from behaviors and interactions of a target user avatar. The observer avatar can capture audio, video, images, and text perceived by the observer avatar in the area of the user avatar, along with metadata describing the captured information. Using the captured observations, the system can determine contextual segments classifying the portion of the metaverse. Using a library of the contextual segments, advertisers can distribute contextually targeted advertisements.

Abstract: Techniques are disclosed for systems including techniques for multi-feature balancing for natural langue processors. In an embodiment, a method includes receiving a natural language query to be processed by a machine learning model, the machine learning model utilizing a dataset of natural language phrases for processing natural language queries, determining, based on the machine learning model and the natural language query, a feature dropout value, generating, and based on the natural language query, one or more contextual features and one or more expressional features that may be input to the machine learning model, modifying at least one or the one or more contextual features and the one or more expressional features based on the feature dropout value to generate a set of input features for the machine learning model, and processing the set of input features to cause generating an output dataset for corresponding to the natural language query.

Abstract: A client-side load balancer replaces standard name serving functions. An operating system on client machine receives a command to start a client application. The command includes a command line argument (a switch) based on which the operating system also starts the client-side load balancer, which intercepts name service requests. The client-side load balancer controls a cache memory with a list of IP addresses of available servers that are associated with a URL for a particular service request. In response to successive name service requests for the URL, the client-side load balancer provides IP addresses from the list in a strictly repetitive order. The order may be a Round Robin order, or any permutation of a Round Robin order.

Abstract: Embodiments detect stops by an entity on a pre-planned trip that includes a plurality of stops and a planned sequence of stops. Embodiments receive a first geo-location message indicating a first location and corresponding first time for the entity. Embodiments, based on the first geo-location message and a previous geo-location message, generate an enter geofence set and an exit geofence set. When the entity is currently, based on the previous geo-location message, at one of the stops and the current stop is in the exit geofence set, embodiments store the first time as a departure time for the current stop. When the entity is not currently, based on the previous geo-location message, at one of the stops and the enter geofence set is non-empty, embodiments store the first time as an arrival time for a stop corresponding to the first location.

Abstract: A cloud infrastructure orchestration service (CIOS) may track build progress. A service plan may define a first execution order of releases for bootstrapping a service (e.g., provisioning and deploying resources of the service) to an execution target (ET) (e.g., a set of devices of a data center). The first execution order may be defined using transitions between ET checkpoints, with each transition and checkpoint being associated with a corresponding release. A directed acyclic graph (DAG) may be generated from any suitable number of service plans associated with various services to define a second execution order for the releases needed to bootstrap the services. At build time, CIOS may track release execution by updating the state of an ET to correspond to an ET checkpoint when the release is successful. ET states may be used by CIOS to enforce the second execution order.

Abstract: A method of providing access to a hardware security module (HSM) partition may include receiving request for access to the HSM partition from a client device. The request may include a leaf certificate signed with a public key associated with a user and a secret key associated with the client device. The method may include verifying the request using the leaf certificate and a trust anchor certificate signed with a public key associated with the client device. The method may include a first connection between the HSM partition and the client device. The method may include verifying the request using the leaf certificate and an authentication certificate stored on the HSM partition. The method may include establishing a second connection between the client device and the HSM partition such that the computing system is isolated from the second connection.

Abstract: Network entities associated with a virtual cloud network are transitioned through a certificate bundle distribution process for distributing new certificate authority certificates to the network entities. Operations may include executing, in relation to each of the network entities, a first operation associated with a first phase of the process; obtaining, for each particular network entity, individual entity information associated with a progress of a particular network entity in relation to the first phase; computing, based on the individual entity information, an aggregate metric indicative of an aggregate progress of the network entities in relation to the first phase; determining, based on the aggregate metric, that one or more transition criteria are satisfied for transitioning the network entities from the first phase to a second phase of the process; and executing, in relation to each of the network entities, a second operation associated with the second phase of the process.

Abstract: Techniques are described herein for cold-start forecasting datasets using backcasting and composite embedding. An example method can include a system receiving a set of time series and metadata text comprising a first subset of metadata text and a second subset of metadata text. The system can generate a plurality of embeddings, each embedding comprising a numerical representation of a metadata text of the set of metadata text. The system can generate a plurality of vectors, each vector comprising a time series of the set of time series each time series associated with a metadata text of the first subset of metadata text. The system can generate a plurality of composite embeddings based at least in part on combining each embedding with a respective vector of the plurality of vectors. The system can determine a forecasted value associated with the second subset of metadata text based on the composite embeddings.

Abstract: A cloud infrastructure orchestration service may maintain a service plan and manifest (SPAM) corresponding to a service to be bootstrapped (e.g., provisioned and deployed) to a cloud computing environment (e.g., to a data center). The service plan may specify a deterministic order of releases for performing a process to fully bootstrap the service using one or more build milestones and one or more execution units, each execution unit specifying ordered steps for transitioning between build milestones Each step may reference one or more execution target checkpoint transitions, which in turn reference an alias of a configuration file that defines a release. A manifest may be used to identify the configuration files and artifacts to be used by the releases and to validate the service plan. A SPAM may be used to reduce/eliminate nondeterministic behavior of previous orchestration systems and to provide visualizations of the bootstrapping process at different granularities.

Abstract: A cloud-computing service (e.g., a “Puffin Service”) is described. The service may maintain backward and forward compatibility between skills and capabilities. Skills may be configured to enable improved tracking of a process for building data center. There may be occasions in which an orchestrator may use both skills and capabilities to drive build operations. To enable both constructs to be utilized, the Puffin Service maintains associations between skills and capabilities. These associations enable skills to be published when published capabilities are identified and corresponding capabilities to be published for published skills, which in turn allows the Orchestrator to drive build operations based on any suitable combination of capabilities and/or skills. Previously published capabilities may be identified and system-generated skills (“shadow skills”) may be used to represent the previously published capabilities, further enabling compatibility between constructs while avoiding burdensome data entry.

Abstract: Techniques are described for data management. An example method can include detecting data from a second data center in a second region, the data stored in an isolated environment of the first data center. The method can further include determining a validation parameter based at least in part on the first region. The method can further include validating the data based at least in part on the validation parameter. The method can further include processing a first message indicating to release the data from the isolated environment of the isolated environment. The method can further include causing the data to be released from the isolated environment based at least in part on the validating, the first message to release the data, and the second message that the first message originated in the first region.

Abstract: A cloud infrastructure orchestration service (CIOS) may track build progress made by any suitable number of regional orchestrators. An orchestrator control plane may be configured to generate a region build plan for bootstrapping a plurality of services within a data center. The orchestrator control plane may instruct a region orchestrator to execute a build according to the build plan. The region orchestrator may be configured to update an execution state corresponding to the execution of the region build plan as it executes steps of the ordered steps of the region build plan. At any suitable time (e.g., when executing one of the steps fails), intervention data may be received with which a new region build plan may be generated. The new region build plan may be used for subsequent execution of the region build. This may enable run-time corrections to be made.

Abstract: A cloud infrastructure orchestration service (CIOS) may track build progress made by any suitable number of regional orchestrators. The cloud infrastructure orchestration system may include any suitable number of regional orchestrators, each regional orchestrator executing in an isolated hosting environment (e.g., a service cell isolated from other service cells). An orchestrator control plane may be configured to generate a build plan for bootstrapping a plurality of services within a data center, the build plan may be generated based at least in part on a service build definition of a plurality of service build definitions, the service build definition specifying a deterministic process for bootstrapping a service of the plurality of services. The orchestrator control plane may instruct a regional orchestrator to perform bootstrapping operations according to the build plan and may track the progress of the bootstrapping operations on an ongoing basis.

Abstract: Techniques are described for data management. An example method can include processing a first message indicating that an intermediate computing system managed by a data center in a first region has received data from a second data center in a second region, the data stored in an isolated environment of the intermediate computing system. The method can further include transmitting first control instructions to the intermediate computing system to validate the data based at least in part on a first criteria. The method can further include processing a second message indicating to release the data from the isolated environment of the intermediate computing system and processing a third message indicating that the second message originated from the first region. The method can further include causing the data to be released from the isolated environment based at least in part on the validation results.

Abstract: Techniques for managing requests to modify a data set at future times are disclosed. The system receives a request to modify the data set at a future time, such as in a future time window. The system generates a representation of the data set at the future time. The system determines the future state of the data set based on the current state of the data set and requested future modifications to the data set. The system determines whether a conflict exists between the request to modify the data set at the future time and another scheduled request to modify the data set at the future time. Based on determining whether a conflict exists, the system performs one or more of scheduling the request to modify the data set at the future time and performing a remediation action to address the conflict.

Abstract: Skills and skills metadata may be used to define a process for building a data center. Skills of one service may depend on skills corresponding to the same or different service. A dependency graph may be generated based on these dependencies. The graph may specify an order by which orchestration operations are to be performed to build the services, thereby building the data center. During execution of the process for building the data center, health states corresponding to the skills may be tracked (based at least in part on alarms and/or namespaces associated with the skills). When an unhealthy skill is identified, the system may traverse the dependency graph to identify a root cause (e.g., failed operations corresponding to a skill on which the unhealthy skill directly/indirectly depends). A notification and/or various options may be provided to address the unhealthy state of one or both skills.

Abstract: A cloud-computing service (e.g., a “Puffin Service”) is described. The service may maintain service and skill catalogs corresponding to various services to be deployed to a region (e.g., during a region build). The service may host numerous user interfaces with which various service and skill metadata may be provided. In some embodiments, such data may include one or more dependencies between skills. The data managed by the cloud-computing service may be utilized to build a dependency graph. Navigation of the dependency graph may be performed via one or more user interfaces hosted by the cloud-computing service. An orchestration service (e.g., a Multi-Flock Orchestrator) may manage bootstrapping efforts for any suitable number of services during a region build based at least in part on dependencies between skills.

Abstract: A variety of testing environments and techniques are disclosed. An orchestrator control plane may generate a build plan comprising a plurality of ordered steps for bootstrapping one or more services. The build plan may be generated based at least in part on one or more service plans and manifests that individually specify a deterministic process for bootstrapping a service. The orchestrator control plan may instruct a region orchestrator executing within an isolated testing environment to execute a test build of the one or more services according to the build plan. The region orchestrator may execute, as part of executing the test build, a subset of steps from the plurality of ordered steps of the build plan utilizing resources of the isolated testing environment and in an order identified by the build plan. At any suitable time, the isolated testing environment may be reset to enable subsequent test build executions.

Abstract: A cloud infrastructure orchestration service (CIOS) may be used to create a service plan and manifest (SPAM) that defines a deterministic order of releases for bootstrapping a service (e.g., provisioning and deploying resources of the service) to a cloud computing environment (e.g., to a data center). A corresponding manifest may be used to identify the configuration files and artifacts to be. The manifest may be used to validate the service plan. The CIOS may be configured to validate the SPAM. If compatible, the SPAM may be added to a SPAM set. A SPAM set (a collection of SPAMs corresponding to respective services) may be used to derive a version set (identifying configuration file and artifact versions) with which a directed acyclic graph may be generated. CIOS may bootstrap various services within the data center based at least in part on traversing the directed acyclic graph.

Abstract: A clustering model is used to partition a set of historical opportunity profiles representing historical opportunities into a plurality of opportunity profile clusters. A target opportunity profile that includes a plurality of target-opportunity parameters is obtained, and an opportunity profile cluster is identified that meets a matching criterion with the target opportunity profile. The plurality of historical opportunity profiles of the identified opportunity profile cluster are partitioned based on an outcome indicator associated respectively with each of the plurality of historical opportunity profiles, providing a first subset of historical opportunity profiles and a second subset of historical opportunity profiles. An insight generation model is applied to the target opportunity profile along with the first subset and/or the second subset to generate one or more insights for the target opportunity profile.

Abstract: A distributed database service can be migrated from a source environment to a destination environment. The distributed database service can be associated with a database and database members. the source environment can include source database members such that each source database member includes a respective image of the database. Migrating the distributed database service can include provisioning a migration gateway in the source environment. Migrating the distributed database service can also include provisioning a domain name system service in the destination environment. Migrating the distributed database service can also include provisioning a first destination database member in the destination environment. While updating the first destination database member with a respective image of the database, the distributed database service can process a database request.

Abstract: Techniques for transferring data to a secure computing region that is isolated from any public networks is disclosed. In some embodiments, one or more artifacts for the secure computing region are packaged. As part of the packaging, one or more data packets and metadata for the one or more artifacts can be generated. The metadata indicates corresponding destination components for the one or more artifacts within the secure computing region. The data packet(s) are received and transmitted by a first data diode endpoint device. The first data diode endpoint device is configured to transmit data to the secure computing region via a second data diode endpoint device, the second data diode endpoint device being configured to restrict data from being transmitted to a destination outside of the secure computing region. The transmission of the one or more data packets may be monitored by the system.