Abstract: An automated, dynamic system and method of testing infrastructure-as-code (IaC). The system is configured to validate infrastructure provisioned in multi-cloud environments and is able to accommodate any cloud provider. Implementation of such as system can eliminate manual errors, as well as enable early detection of errors (i.e., before production deployment), thus empowering early ‘go live’. Furthermore, the proposed embodiments are configured to integrate with already existing devOps pipelines for rapid test execution and can run as many times as needed with minimal configuration, allowing for creation and execution of complex scenarios to test low-level validation upon cloud infrastructure setup.

Abstract: A compiler-implemented technique for performing a storage allocation is described. Computer code to be converted into machine instructions for execution on an integrated circuit device is received. The integrated circuit device includes a memory having a set of memory locations. Based on the computer code, a set of values that are to be stored on the integrated circuit device are determined. An interference graph that includes the set of values and a set of interferences is constructed. While traversing the interference graph, a set of memory location assignments are generated by assigning the set of values to the set of memory locations in accordance with one or more color selection schemes.

Abstract: A concurrency-restricting lock may divide a set of threads waiting to acquire the lock into an active circulating set (ACS) that contends for the lock, and a passive set (PS) that awaits an opportunity to contend for the lock. The lock, which may include multiple constituent lock types, lists, or queues, may be unfair over the short term, but improve throughput of the underlying multithreaded application. Culling and long-term fairness policies may be applied to the lock to move excess threads from the ACS to the PS or promote threads from the PS to the ACS. These policies may constraint the size or distribution of threads in the ACS (which may be NUMA-aware). A waiting policy may avoid aggressive promotion from the PS to the ACS, and a short-term fairness policy may move a thread from the tail of a list or queue to its head.

Abstract: A virtual machine controller service of a service provider network may provide a virtual machine controller environment where applications associated with machine controllers (e.g., programmable logic controllers (PLCs), programmable automation controllers (PACs), etc.) can execute and data can be provided as input to the executing applications. An example process may include receiving a request to create a virtual controller instance, and creating the virtual controller instance in a service provider network based at least in part on the request. The example process may further include executing, on the virtual controller instance, an application that is associated with a machine controller that is operable within a facility, and sending data as input to the application to elicit a response from the application. This example process can be used for training personnel and/or for validating machine controller applications prior to their deployment on a physical machine controller in a facility.

Abstract: A computer-implemented method, in accordance with one aspect of the present invention, includes collecting data existing in a development system that relates to the code change request, in response to receiving a code change request to merge new code with existing code. Factors from the collected data are computed for assessing a risk of promoting the new code, the factors including at least: a developer information factor, a developer availability factor, and an environment health analysis factor. The factors are processed to compute a confidence score for the code change request. If the confidence score is in a first predefined range, the new code corresponding to the code change request is promoted for merging with the existing code, without human intervention. If the confidence score is in a second predefined range, an indication that human intervention is needed before promoting the code is output.

Abstract: A processing system allows external systems to customize and extend services without increasing system intricacy. The processing platform maintains cloud containers that support virtual machines for external systems. An external system provides code for execution on a virtual machine that is supported by a cloud container. Cloud containers provide a boundary for executing code such that the processing platform may limit types of code an external system can run at a cloud container. The external system code can provide new services or may build upon existing public services, and external systems may designate their services as being available to other external systems by publishing the access information in a global application programming interface (API) maintained by the processing platform. Since the external systems submit instructions for execution within their assigned cloud containers, the services and applications are developed without affecting the underlying functionality of the processing platform.

Abstract: A new approach is proposed to support correlating high-level code with low-level instructions of an application running on a hardware. A compiler that compiles a high-level function in the high-level code of the application into a set of low-level instructions to be executed on the hardware is configured to utilize one or more reserved fields of the set of low-level instructions to incorporate one or more IDs and an actionable item. The IDs are mapped to the high-level function, wherein such mapping is programmable by the compiler. Based on the mapped IDs and the actionable item incorporated in the set of the low-level instructions, the runtime performance of the application on the hardware can be monitored and profiled and issues related to the high-level code of the application can be identified for debugging purposes.

Abstract: A method, system, and non-transitory processor-readable medium for optimizing lifecycle rule computer processing including: selecting a set of lifecycle rules to apply to interactions, finding a set of interactions satisfying criteria associated with the lifecycle rule; calculating an associated rule occupancy score based on the number of executed interactions associated with the rule, and executing the rule based on the rule occupancy score associated with the rule.

Abstract: Systems and methods that enable the efficient and adaptive allocation of resources dedicated to a container-based computation (e.g., one or more information processing tasks) are provided. A container controller is employed to launch and dynamically update (e.g., manage) the resource allocation (e.g., indicated by a selected configuration) for a set of containers. The container controller implements a Markov Decision Process (MDP)-based control loop to adaptively configure (e.g., allocate resources for) and reconfigure the set of containers. In some embodiments, the MDP of the control loop is a single-state MDP (e.g., a multi-armed bandit decision process). In such embodiments, each possible configuration for the set of containers is an arm on the multi-armed bandit.

Abstract: In computer-implemented method, computer system, and/or computer program product, a processor(s) obtains a test (of steps(s)) to verify program code for deployment in distributed computing system. The processor(s) determines pre-defined operations correlating to the step(s). The processor(s) automatically distributes the pre-defined operations to a resources of a distributed computing system, for execution. The processor(s) monitors the execution and saves at least one screenshot as each step. The processor(s) generates a user interface with a status indicator. The processor(s) continuously update the user interface, based on the monitoring, to reflect a progression of the portion of the one or more resources through the step(s).

Abstract: A first virtual machine executing on a centralized management node provides a first image file to a first computing entity arranged within a first point of delivery. The first image file includes a first boot configuration file or a first ramdisk file. A second virtual machine provides a second image file to a second computing entity arranged within a second point of delivery different from the first point of delivery. The second image file includes a second boot configuration file or a second ramdisk file. The first virtual machine provides a third image file to the first computing entity. The third image file comprises a first operating system installation file. The second virtual machine provides a fourth image file to the second computing entity. The fourth image file comprises a second operating system installation file.

Abstract: Techniques for providing a fencing scheme for cluster systems without inherent hardware fencing. Storage nodes in an HA cluster communicate with one another over communication paths implemented through a variety of mechanisms, including drives and network connections. Each storage node in the HA cluster executes a fencing enforcer component operable to enforce actions or processes for initiating fencing of itself and/or initiating self-fencing of another storage node in the HA cluster determined to be malfunctioning. By providing for richer communications between storage nodes in an HA cluster and a richer set of actions or processes for fencing a malfunctioning storage node including self-fencing, the malfunctioning storage node can be made to exit the HA cluster in a more controlled fashion. In addition, a remaining storage node in the HA cluster can more safely take on the role of primary storage node with reduced risk of data corruption on shared resources.

Abstract: Provided are techniques for enhancing applications based on effectiveness scores. Application functionalities of applications in an application landscape are identified. Application logs for the applications are analyzed to identify how the application functionalities are executing. Groups of application functionalities are formed, where each of the groups includes different application functionalities that perform a similar function. For a group of the groups, an effectiveness score is assigned to each of the different application functionalities in that group. For each application functionality, a corresponding recommendation is identified on how that application functionality is to be modified based on the effectiveness score for that application functionality compared to the effectiveness score of each of the other application functionalities in the group. Each application functionality to be modified is automatically updated based on the corresponding recommendation.

Abstract: An automated system for detecting performance bugs in a program and for providing code recommendations to improve the performance of the program generates a code recommendation table from performance-related pull requests. The performance-related pull requests are identified in part from a classifier trained on semi-supervised data. A code recommendation table is generated from performance-related pull requests and is searched for similarly-improved code based on a set of difference features that includes structural and performance features of the before-code of a pull request that is not in the after-code.

Abstract: A computer-implemented method includes: receiving, by a computing device and from a user device, a request to validate an application program interface (API); validating, by the computing device, the API by performing a fetch analysis using different user profiles; returning, by the computing device and to the user device, a result of the fetch analysis; validating, by the computing device, the API by performing an insert/update analysis using the different user profiles; and returning, by the computing device and to the user device, a result of the insert/update analysis.

Abstract: A computer implemented method determines a placement of an application being added to a network. The method includes determining a logical-physical mapping for the application. Sub-graphs in the logical-physical mapping are identified. A stored application in a catalog of applications previously used in the network is located. The stored application includes one of the sub-graphs in the logical-physical mapping. An experiment is generated, performed by a computing device running a neural network model, using the sub-graphs. The experiment includes inducing a physical node mapping for the sub-graph. A cost function associated with a placement of the application being added to the network to one or more physical nodes in the induced physical node mapping is determined.

Abstract: A request to launch a compute instance is received at a control plane of a provider network. At an outbound command communicator, an indication that a compute instance is to be established at a target host at a client premise is obtained. A first address is associated with the target host at the control plane and also assigned to the communicator. A message with a second address within a first network of the client premise as a destination is transmitted. The message comprises a command to establish the compute instance at the target host. The first address is assigned to the target host within a second network of the client premise. Processing of the command at the target host results in establishment of a compute instance.

Abstract: Analyzing or debugging applications is provided. The system identifies an action for an application provided by a developer. The system determines a first classification score based on historical execution of the action. The system generates a machine generated action for the application based on metadata associated with the application. The system determines a second classification score based on a comparison of the action with the machine generated action. The system selects, via a matching program, a second application that matches the application. The system determines a third classification score based on a comparison of an action approved for the second application with the action provided by the application developer. The system updates a delivery control parameter based on the first classification score, the second classification score and the third classification score. The system controls delivery of the application based on the delivery control parameter.

Abstract: Presented herein are methods, non-transitory computer readable media, and devices for optimizing thread assignment to schedulers, avoid starvation of individual data partitions, and maximize parallelism in the presence of hierarchical data partitioning are disclosed, which include: partitioning, by a network storage server, a scheduler servicing a data partitioned system into a plurality of autonomous schedulers; determining what fraction of thread resources in the data partitioned system at least one of the plurality of autonomous schedulers is to receive; and determining, with minimal synchronization, when it is time to allow the at least one of the plurality of autonomous schedulers servicing a coarse hierarchy to run.

Abstract: A method for automatically modeling a codebase to facilitate management and analytics is provided. The method includes automatically aggregating a data set, the data set including data that correspond to a codebase; identifying, from the data set, entities and corresponding attributes, the entities relating to a component of the codebase; establishing, by using the data set, a relationship for the entities, the relationship corresponding to an interaction between each of the entities; determining a potential owner for each of the entities based on a corresponding change history; defining, by using the data set, an ownership rule for each of the entities, the ownership rule associating the potential owner to the corresponding entities; and computing an actionable item for each of the entities based on the corresponding attributes.