Abstract: The present disclosure provides dynamic routing for data flows to a customer network hosted in the cloud. A plurality of compute instances may share a common virtual IP address. Each of the plurality of compute instances may advertise information to a respective network virtualization device (NVD). The information may include the IP address, cost, and/or active/standby status of the compute instance. The NVD may then provide the information to the control plane of a virtual cloud network (VCN), which may aggregate the information from the plurality of compute instances and generate a forwarding table, which may be sent to the NVDs. These techniques may allow a customer to automatically remove a compute instance whose service host has failed. These techniques may also allow a customer to add compute instances and to route data flows according to an active-standby operation, an equal cost active-active operation, or an unequal cost active-active operation.

Abstract: Embodiments relate to improving efficiency of data analytics performed on sets of entity data in which different entity properties having very different update frequencies. Time-based analytical queries track the entity states at each moment within a given time window. Analytical queries are executed over a massive number of entity states while using a reasonable memory footprint. The technique partitions the entity properties into partial historical snapshots of data and combines the partial snapshots on demand only as needed to execute analytical queries over business entities. A complete entity state having values for all entity properties is not required to execute most queries. Only partial snapshots including values referenced by the query need to be combined to satisfy the query. Using partial snapshots minimizes data replication, and the snapshots can be efficiently combined into entity states sufficient for query execution.

Abstract: A system is provided that processes supply chain events. The system defines a supply chain event type. The system further configures a supply chain event of the supply chain event type as a task generating event, where the task generating event indicates that one or more tasks that are defined for a supply chain financial orchestration flow are to be executed, and where the supply chain financial orchestration flow defines a trade relationship between a first entity and a second entity. The system further receives a supply chain event associated with the supply chain financial orchestration flow. The system further determines whether the supply chain event is a task generating event. The system further executes the one or more tasks that are defined for the supply chain financial orchestration flow where the supply chain event is a task generating event.

Abstract: In some aspects, an aggregation system of a cloud system may receive, by an aggregation system of a cloud system and from a data catalog, one or more events from one or more data sources of the cloud system, the one or more data sources having one or more resource types. The aggregation system may store event data to a message queue. The aggregation system of a cloud system may process, by one or more workers of the cloud system, a subset of events from the message queue at a time. The aggregation system may for each event in the subset of events: determine whether an event source has been updated based on information in the event. The aggregation system may in accordance with a determination that the event source has been updated, send an updated status to a dashboard, the dashboard configured to be displayed on a user device.

Abstract: 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.

Abstract: Embodiments determine an eligibility of a request for an operation event from a client using a distributed ledger that comprises a plurality of nodes. Embodiments send the request from the client to a primary node of the distributed ledger, the request comprising a first token. Embodiments validate the node at the primary node with a token provider, broadcast the request to all secondary nodes of the distributed ledger and perform a service by the primary node and the secondary nodes in response to the request. Embodiments send a reply to the client from each of the primary node and the secondary nodes when the service is performed successfully by the respective node, the reply comprising a second token. Embodiments then determine an eligibility of the client for the request based on a count of a number of second tokens received by the client.

Abstract: Systems, devices, and methods of the present invention detect deceptive or fake content in text. In an example, a computer system generates, from text a discourse tree that represents rhetorical relationships between fragments of the text. The computer system generates a communicative discourse tree from the discourse tree. The computer system identifies a number of non-trivial rhetorical relations associated with the nonterminal nodes in the communicated discourse tree and, for each terminal edge having a communicative action, a level of nesting of the communicative action. The computer system derives, from the number of non-trivial rhetorical relations and the levels of nesting of the identified communicative actions, a complexity score that is indicative of a level of deception in the text.

Abstract: Resource allocation limitations include resource limits and resource guarantees. A consumer is vulnerable to interruption by other consumers if using more resources than guaranteed. Resources are designated and/or assigned consumers based on resource limits and resource guarantees. A constraint programming (CP) solver determines resource limits and resource guarantees that minimize vulnerability and/or vulnerability cost based on resource usage data. A CP data model includes limit elements, guarantee elements, and vulnerability elements. The CP data model further includes guarantee-vulnerability constraints, which relies on exceedance distributions generated from resource usage data for the consumers. The CP data model declaratively expresses combinatorial properties of a problem in terms of constraints. CP is a form of declarative programming.

Abstract: Systems and methods of interface-based ACLs in a virtual Layer-2 network. The method can include sending a packet from source compute instance in a virtual network to a destination compute instance via a destination virtual network interface card (destination VNIC) within a first virtual layer 2 network and evaluating an access control list (ACL) for the packet with a source virtual network interface card (source VNIC). ACL information relevant to the packet can be embedded in the packet. The VSRS can receive the packet and can identify the destination VNIC within the first virtual layer 2 network for delivery of the packet based on information received with the packet and mapping information contained within a mapping table. The VSRS can access ACL information from the packet and can apply the ACL information to the packet.

Abstract: A global state associated with a garbage collection (GC) process is a state assumed by a reference after GC operations for a current GC phase are performed for the reference. A frame state of a frame on a call stack of an application thread tracks a progress of GC operations for references therein. A color watermark is added after a global state change. The frame originally marked by a stack watermark is now marked by the new color watermark. The new color watermark marks a deepest frame on the call stack having the old global state. A color watermark is deleted when the stack watermark meets the color watermark. If the stack watermark is shifted in the call stack to mark the same frame as a color watermark, then the color watermark is deleted. The marked frame is a deepest frame on the call stack having the current global state.

Abstract: Techniques for data augmentation for training chatbot systems in natural language processing. In one particular aspect, a method is provided that includes generating a list of values to cover for an entity, selecting utterances from a set of data that have context for the entity, converting the utterances into templates, where each template of the templates comprises a slot that maps to the list of values for the entity, selecting a template from the templates, selecting a value from the list of values based on the mapping between the slot within the selected template and the list of values for the entity; and creating an artificial utterance based on the selected template and the selected value, where the creating the artificial utterance comprises inserting the selected value into the slot of the selected template that maps to the list of values for the entity.

Abstract: Discussed herein is a technique for replication of keys across regions of a cloud infrastructure. A first vault is created in a first region. The first vault stores a plurality of records, each of which is associated with a key and corresponding metadata. A second region, different from the first region, is selected where replication of the plurality of records is desired. A second vault is created in the second region. The plurality of records are relayed from the first vault to the second vault, so that each of the plurality of records is replicated in the second vault based on an entropy value of the record. A mutation operation executed with respect to the first vault is stored as a new record in the first vault. The new record is transmitted to the second vault, which is updated to reflect the mutation operation performed on the first vault.

Abstract: Techniques for transitioning between memory segment views include: instantiating a first memory segment view that confines access to a memory segment to a first thread; receiving a request to transition ownership of the memory segment to a second thread; responsive to receiving the request to transition ownership of the memory segment to the second thread: instantiating a second memory segment view that permits access to the memory segment by the second thread; copying metadata from the first memory segment view to the second memory segment view; terminating the first memory segment view, to prevent access to the memory segment via the first memory segment view.

Abstract: Techniques for initiating system actions based on text content are disclosed. A system applies a semantic analysis model at run-time to human-understandable text to identify actionable content within the human-understandable text. The system analyzes metadata associated with the text to identify a mapping between one or more data objects associated and the semantic content in the text. The system identifies one or more contact lists associated, respectively, with the one or more data objects. Using a database schema, the system analyzes the contact lists to determine whether to modify the contact lists.

Abstract: Techniques for transitioning between memory segment views include: instantiating a first memory segment view that confines access to a memory segment to a first thread; receiving a request to transition ownership of the memory segment to a second thread; responsive to receiving the request to transition ownership of the memory segment to the second thread: instantiating a second memory segment view that permits access to the memory segment by the second thread; copying metadata from the first memory segment view to the second memory segment view; terminating the first memory segment view, to prevent access to the memory segment via the first memory segment view.

Abstract: Techniques for governing access to third-party application programming interfaces (API's) are disclosed. A proxy service exposes an API configured to receive requests, from user-facing services, to perform functions of backend services. The proxy service stores a usage policy that defines a criterion that is (a) different from any authorization criterion and (b) associated with using a function of a backend service. The proxy service receives a request to perform the function of the first backend service for a user-facing service and determines that the request does not satisfy the usage policy. Based on determining that the request does not satisfy the usage policy, the proxy service refrains from accessing the backend service to perform the function responsive to the request, and transmits an alert to the user-facing service indicating that the request does not satisfy the usage policy.

Abstract: The present is directed to systems, methods, and devices for holistic rendering of cloud network configuration. The method can include receiving data characterizing a plurality of devices in a computing network. The method can include generating with the inventory processor a data file characterizing each of the plurality of devices in the computing network. This data file can be generated based on the received data and on a set of static overrides. The method can include generating a configuration file for each of the plurality of devices in the computing network via iterative selection and application of templates to portions of the data file.

Abstract: Techniques are described herein for prediction of an buffer pool size (BPS). Before performing BPS prediction, gathered data are used to determine whether a target workload is in a steady state. Historical utilization data gathered while the workload is in a steady state are used to predict object-specific BPS components for database objects, accessed by the target workload, that are identified for BPS analysis based on shares of the total disk I/O requests, for the workload, that are attributed to the respective objects. Preference of analysis is given to objects that are associated with larger shares of disk I/O activity. An object-specific BPS component is determined based on a coverage function that returns a percentage of the database object size (on disk) that should be available in the buffer pool for that database object. The percentage is determined using either a heuristic-based or a machine learning-based approach.

Abstract: The present invention relates to join acceleration. In an embodiment, a computer receives a request for a relational join of build data rows with probe data rows. Based on the request for the relational join, a particular kind of data map from many kinds of data map that can implement the relational join is dynamically selected. Based on the build data rows, an instance of the particular kind of data map is populated. A response is sent for the request for the relational join that is based on the probe data rows and the instance of the particular kind of data map.

Abstract: The present disclosure generally relates to systems and methods for efficiently and dynamically integrating a chatbot into an application service. More specifically, the present disclosure relates to systems and methods that dynamically build custom components that enable the chatbot to communicate and facilitate the use of the application service directly from the chatbot application. Accordingly, the systems and methods described herein provide the benefit of integrating the chatbot application into an application service without having the application developer write code for the integration, thereby enhancing the computational efficiency of the integration and the reliability of the application service when new services or service functionality are added or modified.

Abstract: Aspects of the present disclosure include implementing fabric availability and synchronization (FAS) agents within a fabric network. In one example, a first FAS agent executing on a first network device may receive, from a second network device, a command to modify a configuration of a second network device. The first FAS may upgrade the configuration of the first network device based on the command from a current configuration to a new configuration. The first FAS agent increment a state identifier associated with the configuration of the first network device to a new state identifier associated with the new configuration. The first FAS agent may then transmit a control packet that includes the new state identifier. A second FAS agent executing on the second network device may receive the control packet and execute the command to update the configuration of the second network device to the new configuration.

Abstract: Systems, computer-implemented methods, and computer-readable media for facilitating resource balancing based on resource capacities and resource assignments are disclosed. Electronic communications, received via interfaces, from monitoring devices to identify resource descriptions of resources may be monitored. A resource descriptions data store may be updated to associate each entity of the entities and resource capacities of each resource type of resource types. A first electronic communication, from resource-controlling systems, may be detected. Model data from a model data store may be accessed based on the identified resource descriptions. A first model may be identified based on the model data. A resources assessment corresponding may be generated based on whether a threshold is satisfied based on the first model, a first resource capacity of a first resource type, and the first electronic communication.

Abstract: A hardware-assisted Distributed Memory System may include software configurable shared memory regions in the local memory of each of multiple processor cores. Accesses to these shared memory regions may be made through a network of on-chip atomic transaction engine (ATE) instances, one per core, over a private interconnect matrix that connects them together. For example, each ATE instance may issue Remote Procedure Calls (RPCs), with or without responses, to an ATE instance associated with a remote processor core in order to perform operations that target memory locations controlled by the remote processor core. Each ATE instance may process RPCs (atomically) that are received from other ATE instances or that are generated locally. For some operation types, an ATE instance may execute the operations identified in the RPCs itself using dedicated hardware. For other operation types, the ATE instance may interrupt its local processor core to perform the operations.

Abstract: Techniques are provided for using context tags in named-entity recognition (NER) models. In one particular aspect, a method is provided that includes receiving an utterance, generating embeddings for words of the utterance, generating a regular expression and gazetteer feature vector for the utterance, generating a context tag distribution feature vector for the utterance, concatenating or interpolating the embeddings with the regular expression and gazetteer feature vector and the context tag distribution feature vector to generate a set of feature vectors, generating an encoded form of the utterance based on the set of feature vectors, generating log-probabilities based on the encoded form of the utterance, and identifying one or more constraints for the utterance.

Abstract: Techniques to create zone maps automatically and efficiently for database query processing are disclosed. The techniques comprise creating a sample dataset to represent an original dataset, building a query workload modeler to characterize a full workload of queries, constructing a clustering quality evaluator to evaluate query performance on a dataset with a certain clustering on the columns, finding a clustering solution by evaluating different applications of the workload to the sample dataset corresponding to different clusterings, and determining which columns of the clustering solution could benefit from zone maps.

Abstract: Methods, systems, and computer readable media for network function (NF) discovery using preferred-locality information are disclosed. One example method for NF discovery using preferred-locality information comprises: at a first NF comprising at least one processor: receiving a message relating to a transaction involving a consumer NF; identifying, from the message, an NF instance identifier (ID) corresponding to the consumer NF; determining, using the NF instance ID and a data store including NF related information and corresponding preferred-locality information, a preferred-locality value; including the preferred-locality value in a preferred-locality information element (IE) of an NF discovery request; and transmitting the NF discovery request toward a second NF.

Abstract: Embodiments are directed to a multi-tenant cloud system. Embodiments receive a request for an authentication action for a user and create an authenticate target action. Embodiments register a cache listener to listen for a target action response that is responsive to the authenticate target action and initiate the authentication action for the user at an on-premise active directory (“AD”) via a bridge. Embodiments wait for a cache callback and, at the cache callback, receive a target action response comprising a result of the authentication action.

Abstract: Herein are techniques that train regressor(s) to predict how effective would a machine learning model (MLM) be if trained with new hyperparameters and/or dataset. In an embodiment, for each training dataset, a computer derives, from the dataset, values for dataset metafeatures. The computer performs, for each hyperparameters configuration (HC) of a MLM, including landmark HCs: configuring the MLM based on the HC, training the MLM based on the dataset, and obtaining an empirical quality score that indicates how effective was said training the MLM when configured with the HC. A performance tuple is generated that contains: the HC, the values for the dataset metafeatures, the empirical quality score and, for each landmark configuration, the empirical quality score of the landmark configuration and/or the landmark configuration itself. Based on the performance tuples, a regressor is trained to predict an estimated quality score based on a given dataset and a given HC.

Abstract: In accordance with an embodiment, a system and method for dynamic auto-scaling based on roles is provided. Within a system, a node, based upon a load demand, can be duplicated. Additionally, when duplicating a node, the role of the node can be used to determine various characteristics of the duplicated node, taking into account various factors.

Abstract: Techniques are described herein processing asynchronous power transition events while maintaining a persistent memory state. In some embodiments, a system may proxy asynchronous reset events through system logic, which generates an interrupt to invoke a special persistent flush interrupt handler that performs a persistent cache flush prior to invoking a hardware power transition. Additionally or alternatively, the system may include a hardware backup mechanism to ensure all resets and power-transitions requested in hardware reliably complete within a bounded window of time independent of whether the persistent cache flush handler succeeds.

Abstract: Described are improved systems, computer program products, and methods for adaptively provisioning an ordered sequence in a clustered database environment. The approach includes identifying a cached list of sequence numbers. A request for one or more sequence numbers in a database environment may be received. A determination may be made to decide whether the request pertains to an ordered sequence. The one or more sequence numbers may be adaptively provisioned to fulfill the request based at least in part upon an independent cache implementation or upon a shared cache implementation.

Abstract: A text prediction system for providing personalized text suggestions for different customers is disclosed. For a text message being composed via an application for an intended recipient, the system receives a portion of the text message based upon a current cursor position in the text message. The system identifies a customer associated with the intended recipient and identifies a customer-specific model for the customer. The system predicts text to be suggested for type-ahead insertion at the current cursor position using the customer-specific model and based upon the portion of the text message. The suggested text may include one or more data variables that are replaceable with values determined from data stored for the customer. The data variables provide further customization to the suggested text by presenting suggestions are more personalized for the recipient of the text message. The system causes the suggested text to be output via the application.

Abstract: Aspects if the disclosure are directed towards multi-step forecasting via temporal aggregation. An example embodiment includes a method the includes receiving a time series including a first time step value and a second time step value. The method can further include generating a temporally aggregated time series by summing the first time step value and the second time step value to create a third time step value. The method can further include calculating a first set of input values and a second set of input values from the temporally aggregated time series. The method can further include forecasting a fourth time step value using the first set of input values and the second set of input values, and a fifth time step using the second set of input values from the temporally aggregated time series.

Abstract: A system is disclosed that includes capabilities for generating a Machine Learning (ML) inference pipeline for deploying an ML model using artifacts received from one or more training stages in an ML training pipeline. The system receives one or more artifacts for one or more training stages in a set of training stages in a ML training pipeline associated with an ML process. The system then identifies one or more inference stages in an ML inference pipeline that correspond to the one or more training stages in the ML training pipeline. For each inference stage that corresponds to a training stage, the system associates the artifact received for the training stage with the inference stage. The system then generates the ML inference pipeline comprising the inference stages and their associated artifacts, where the artifacts include the artifacts received for the training stages in the ML training pipeline.

Abstract: Techniques for de-centralized execution of workflows are disclosed. A system executes a sequence of jobs in a workflow. Each job includes application code to perform a defined set of functions. Each job includes wrapper code at one or both ends of the application code. The system executes the sequence of jobs by iteratively spinning up a virtual machine, loading workflow data to be used by application code, executing the application code, and storing modified workflow data. The virtual machine executing one job triggers the next virtual machine to execute the next job in the workflow, without scheduling the next job by a centralized job scheduler. Upon spinning up the next virtual machine, a virtual machine executing a preceding job shuts itself down.

Abstract: Embodiments described herein are directed towards a synthetic document generation pipeline for training artificial intelligence models. One embodiment includes a method including a device that receives an instruction to generate a document to be used as a training instance for a first machine learning model, the instruction including an element configuration, a document class configuration, a format configuration, an augmentation configuration, and data bias and fairness. The device can receive an element from an interface based at least in part on the element configuration, the element can simulate a real-world image, real-world text, or real-world machine-readable visual code. The device can generate metadata describe a layout for the element on the document based on the document class configuration. The device can generate the document by arranging the element on the document based on the metadata, wherein the document is generated in a format based on the format configuration.

Abstract: Client data corresponding to a single client can be stored. A decision to proceed with a defragmentation of two or more particular core groups can be determined. A destination core group to receive client data can be identified. At least one additional core group can be initiated to manage interim data write requests from the single client. Each of the two or more particular core groups can be closed to data write requests. A defragmentation of the two or more particular core groups can be performed by merging into the destination core group. The destination core group can be availed to data read and delete requests. The two or more fragmented core groups can be reallocated for other uses. The additional core groups continue to receive read and write requests. The destination core groups further can be merged and defragmented further.

Abstract: Operations include determining whether to cache resources accessed by a query based on the execution time of the query. The system identifies a set of executions of a same query. The system determines a cumulative execution time for the set of executions of the same query. If the cumulative execution time exceeds a threshold value, then the system caches a resource used for execution of the query.

Abstract: A system is provided for training an inferential model based on selected training vectors. During operation, the system receives training data comprising observations for a set of time-series signals gathered from sensors in a monitored system during normal fault-free operation. Next, the system divides the observations into N subgroups comprising non-overlapping time windows of observations. The system then selects observations with a local minimum value and a local maximum value for all signals from each subgroup to be training vectors for the inferential model. Finally, the system trains the inferential model using the selected training vectors. Note that by selecting observations with local minimum and maximum values to be training vectors, the system maximizes an operational range for the training vectors, which reduces clipping in estimates subsequently produced by the inferential model and thereby reduces false alarms.

Abstract: Methods and systems are disclosed for automated semantic tagging that include detecting a particular thread executed by a processor and identifying a root process of the particular thread. An object-process link may be by linking an object that executed code that called the particular thread to the root process. A thread list of thread definitions of the object may be identified. A particular thread definition that corresponds to the particular thread can be mapped. Resource types to be consumed upon executing an instance of the thread instantiated from the particular thread definition can be identified and the corresponding values of the resource types can be determined. A process specification can be generated that encapsulates the thread definition, resource types and values so as to reproduce a state of the root process at a point in which the particular thread executed.

Abstract: Improved techniques for dialogue management are disclosed. In particular, disclosed systems facilitate improved autonomous agents that can generate a virtual social dialogue from a corpus of text. A virtual social dialogue is a dialogue between autonomous agents and user devices. For example, a virtual social dialogue can include viewpoints, concerns, or questions of various actors on a particular topic. By presenting textual content in this manner, disclosed techniques improve information comprehension and increase the practicality of autonomous agents.

Abstract: A method for detecting a security vulnerability in code may include obtaining (i) a permitted information flow graph for a permitted query and (ii) a target information flow graph for a target query in the code, determining, by traversing the permitted information flow graph, a permitted information flow including permitted disclosed columns, permitted accessed columns, and a permitted predicate, determining, by traversing the target information flow graph, a target information flow including target disclosed columns, target accessed columns, and a target predicate, comparing the permitted information flow and the target information flow to obtain a comparison result, and determining, based on the comparison result, that the target query includes the security vulnerability.

Abstract: Techniques for expense report submission are disclosed. An expense report submission system receives, via a graphical user interface, a user query that corresponds to requesting whether a particular expense is allowed. The expense report submission system applies the user query to a machine learning model configured to evaluate data associated with expenses against one or more expense policy rules. The expense report submission system generates a response to the user query based at least on a result of applying the user query to the machine learning model. The response to the user query indicates whether the expense is allowed based at least on the expense reporting rule(s). The expense report submission system presents, in the graphical user interface, the response to the user query.

Abstract: Techniques for predictive system remediation are disclosed. Based on attributes associated with applications of one or more system-selected remedial actions to one or more problematic system behaviors in a system (e.g., a database system), the system determines a predicted effectiveness of one or more future applications of a remedial action to a particular problematic system behavior, as of one or more future times. The system determines that the predicted effectiveness of the one or more future applications of the remedial action is positive but does not satisfy a performance criterion. Responsive to determining that the predicted effectiveness is positive but does not satisfy the performance criterion, the system generates a notification corresponding to the predicted effectiveness not satisfying the performance criterion.

Abstract: A method for communicating delegated NF discovery results between SCPs and using the delegated NF discovery results for alternate SBI service request routing includes receiving, at a first SCP and from a consumer NF instance, an SBI service request. The method further includes determining that delegated NF discovery is required, and, in response, performing delegated NF discovery on behalf of the consumer NF instance. The method further includes receiving an NF discovery response including delegated NF discovery results. The method further includes sending the SBI service request including the delegated NF discovery results to a second SCP.

Abstract: Resource-to-operation pairs are received at a user interface. The resource-to-operation pairs are stored in a model abstraction as a flat structure. The resource-to-operation pairs in the flat structure are converted into Representational State Transfer (REST) connectors. The REST connectors are encoded in a conventional interface description language. The REST connectors are stored in webpage code. A request is received at the webpage code from the client system for a service of a process step of the process-based software application. A REST connector in the webpage code translates the request to a message that conforms with the service. A response from the service is received at the webpage code. The response from the service is processed at the webpage code. Data retrieved by the processing of the response is accessed via a browser located at the client system.

Abstract: A system configured to implement Comprehensive Contention-Based Thread Allocation and Placement, may generate a description of a workload from multiple profiling runs and may combine this workload description with a description of the machine's hardware to model the workload's performance over alternative thread placements. For instance, the system may generate a machine description based on executing stress applications and machine performance counters monitoring various performance indicators during execution of a synthetic workload. Such a system may also generate a workload description based on profiling sessions and the performance counters. Additionally, behavior of a workload with a proposed thread placement may be modeled based on the machine description and workload description and a prediction of the workload's resource demands and/or performance may be generated.

Abstract: The present memory restoration system enables a collection of computing systems to prepare inactive rewritable memory for reserve and future replacement of other memory while the other memory is active and available for access by a user of the computing system. The preparation of the reserved memory part is performed off-line in a manner that is isolated from the current user of the active memory part. Preparation of memory includes erasure of data, reconfiguration, etc. The memory restoration system allows for simple exchange of the reserved memory part, once the active memory part is returned. The previously active memory may be concurrently recycled for future reuse in this same manner to become a reserved memory. This enables the computing collection infrastructure to “swap” to what was previously the inactive memory part when a user vacates a server, speeding up the server wipe process.

Abstract: Techniques are disclosed for deploying a computing resource (e.g., a service) in response to user input. A computer-implemented method can include operations of receiving (e.g., by a gateway computer of a cloud-computing environment) a request comprising an identifier for a computing component of the cloud-computing environment. The computing device receiving the request may determine whether the identifier exists in a routing table that is accessible to the computing device. If so, the request may be forwarded to the computing component. If not, the device may transmit an error code (e.g., to the user device that initiated the request) indicating the computing component is unavailable and a bootstrap request to a deployment orchestrator that is configured to deploy the requested computing component. Once deployed, the computing component may be added to a routing table such that subsequent requests can be properly routed to and processed by the computing component.

Abstract: A first data accessor acquires a lock associated with a critical section. The first data accessor initiates a help session associated with a first operation of the critical section. In the help session, a second data accessor (which has not acquired the first lock) performs one or more sub-operations of the first operation. The first data accessor releases the lock after at least the first operation has been completed.