Abstract: Various embodiments for customizing a dynamic navigation system are described herein. An embodiment operates by receiving a request from a support user device for debug access to an application. A predetermined time period for which to provision a set of computing resources is identified and the set of computing resources are provisioned for a pod on a server. Both a first container including access to a new instance of the application and a second container providing access to a debugger program are generated for the pod. Upon determining that the predetermined time period has expired, access to the provisioned set of computing resources of the pod is revoked, and the provisioned set of computing resources to be made available for other processes of the server.

Abstract: Various examples are directed to systems and methods for operating an application for use with an enterprise database system. A common format process may receive, from a user device, a first request directed to the enterprise database system, convert the first request into a common protocol, and send a first common protocol request to the application logic code. The application logic code may generate a second request in the common protocol and send the second request to the common format process. The common format process may convert the second request from the common protocol to a database query protocol to generate at least one database query and send the at least one database query to the enterprise database system.

Abstract: Disclosed herein are various embodiments for training and enriching a natural language processing system. An embodiment operates by identifying a natural language processor (NLP) trained on a first set of documents, wherein the NLP is trained to perform a set of functionality based on the first set of documents. An industry, set of words corresponding to the industry, and set of sentences including at least a subset of the set of words in which the NLP is to be configured to perform the set of functionality are identified. A set of sentences that exceed a similarity threshold are identified. The NLP is trained with the subset of the set of sentences that exceed the similarity threshold, wherein the trained NLP with the subset is configured to perform the set of functionality within the industry with a greater accuracy than NLP trained on only the first set of documents.

Abstract: Methods and systems may be associated with a cloud computing environment. A proxy platform data store may contain node data associated with nodes of the cloud computing environment. Each node might, for example, store multi-party computation information. A proxy platform, able to access the proxy platform data store, may detect that a first node needs to access a cloud application secret key and determine, based on information in the proxy platform data store, a set of nodes associated with the secret key that the first node needs to access. The proxy platform may then use a multi-party computation algorithm and information received from the set of nodes to generate the secret key.

Abstract: Mechanisms are disclosed for applying one or more heuristics to collected server configurations to detect anomalous configurations. A collection system requests configuration data, including one or more configuration values, from a plurality of configuration agents running on a plurality of hosted servers. The one or more configuration values are received from the plurality of configuration agents at the collection system. The one or more configuration values are stored in one or more databases, organized based on one or more server identifiers. The one or more configuration values are accessed, by an analysis system, from the one or more databases. One or more heuristics are applied to the one or more configuration values based on the one or more server identifiers. In response to detecting the presence of one or more anomalous server configurations, a notification of one or more server configuration issues is provided.

Abstract: A system and method to query, update, and reduce a size of locking data for a dataset including a fixed plurality of dimensions each having a fixed plurality of members comprising index tables for the dimensions and a locks table specifying one of a fixed plurality of lock states for the plurality of members, where the fixed plurality of members each have an associated index.

Abstract: A system to manage database management system backup objects may include an external storage component storing a first database management system backup object. A database management system node (e.g., associated with a database as a service cluster of a hyper-scalar infrastructure) may be configured to write information to and read information from the external storage component without being able to delete information in the external storage component. A backup housekeeping component, independent of the database management system node, may trigger a request to retrieve backup requirement information (e.g., associated with a maximum backup age, a latest backup identifier, an indication of a newest backup to be deleted, etc.) from the database management system node.

Abstract: Computer-readable media, methods, and systems are disclosed for scheduling a start time and a shutdown time of one or more online resources associated with a multi-cloud resource scheduler. A request from a first user is received to access a multi-cloud resource scheduler associated with one or more online resources. Responsive to the request from the first user, credentials of the first user are validated prior to providing access to the multi-cloud resource scheduler. Based upon validating the credentials of the first user, access to the multi-cloud resource scheduler is provided. Instructions are received from the first user to schedule a start time and a shutdown time of at least one online cloud resource connected to the multi-cloud resource scheduler. An availability of the at least one online cloud resource is established for access by a second user based on the instructions.

Abstract: Data is received that specifies a bound for an adversarial posterior belief ?c that corresponds to a likelihood to re-identify data points from the dataset based on a differentially private function output. Privacy parameters ?, ? are then calculated based on the received data that govern a differential privacy (DP) algorithm to be applied to a function to be evaluated over a dataset. The calculating is based on a ratio of probabilities distributions of different observations, which are bound by the posterior belief ?c as applied to a dataset. The calculated privacy parameters are then used to apply the DP algorithm to the function over the dataset. Related apparatus, systems, techniques and articles are also described.

Abstract: In an example embodiment, an efficient, automated method to generate password guesses is provided by leveraging online text sources along with natural language processing techniques. Specifically, semantic structures in passwords are exploited to aid system in generating better guesses. This not only helps cover instances where traditional password meters would indicate a password is safe when it is not, but also makes the solution robust against fast-evolving domains such as new slang in natural languages or new vocabulary arising from new products, product updates, and services.

Abstract: A method for a resilient asynchronous request-reply solution may include initiating, in response to receiving a request from a client device, a process for executing the request using a first service and a second service. The method may include persisting the request as a command in a database accessible to a first instance of the first service and a second instance of the first service. The persisting is performed by a first thread, and the persisting includes storing an association between the first thread and the command. The method also includes sending the command from the first service to the second service, receiving, from the second service, a response to the command, updating, in response to the receiving, the command in the database to include the response, and providing, the response to complete the process. Related systems and articles of manufacture are provided.

Abstract: Techniques and solutions are provided for updating or augmenting consolidated data that is produced using base data. The consolidated data can include data that is aggregated by various grouping criteria. After a set of consolidated data is determined, the base data may change, one or more rules used to calculate the consolidated data may change, or it may be desired to see data that is more granular than that included in the consolidated data. After consolidated data is provided to a user, a user issues a data augmentation request. The data augmentation request causes the base data, which may have been updated, to be processed to provide updated data, where the processing includes grouping operations used in producing the consolidated data. The updated data is provided to a client in response to the data augmentation request.

Abstract: A benchmarking service is engineered to provide computing performance metric benchmarks based on computing performance metrics provided from a variety of providers without being exposed to the underlying computing performance metrics. A homomorphic encryption scheme is used in a threshold cryptography scenario that allows aggregation of the computing performance metrics without decrypting the metrics. An independent decryption service can partially decrypt the benchmark, which can ultimately be decrypted to plaintext for use by the provider. Bitwise operations can be defined to address error problems, and the bitwise operations can be constrained to a smaller bit size to avoid proliferation of gates.

Abstract: In order to address the technical problems encountered with tenant-specific connection pools and global connection pools, in an example embodiment, an efficient connection pool is provided, which restricts the total number of connections per application runtime instance (as with the global connection pool) but at the same time groups and maintains the connections at the tenant level, using tenant-specific sub-pools.

Abstract: A method, a system, and a computer program product for providing a compression service, such as a Compression as a Service (Caas). In some implementations, there is provided a method including receiving, at a compression service, metric information regarding one or more columns of a database server; in response to receiving the metric information, processing, by the compression service, the metric information to identify at least one column as a candidate for compression by the compression service; in response to identifying the at least one column, compressing by the compression service, the at least one column, wherein the compression service uses a hardware accelerator to execution a compression algorithm that compresses the at least one column; and notifying, by the compression service, the database server of the at least one column compressed by the compression service. Related systems, methods, and articles of manufacture are also disclosed.

Abstract: Systems, methods, and computer products are described herein for explainable machine learning predictions. An application receives data including a specification that defines a trained machine learning (ML) model. The application parses a model description of the trained ML model. An engine factory creates an instance of an engine based on the model description. The application generates a user interface (UI) for requesting a prediction and an associated explanation using the engine. The UI receives user input data including a requested prediction having one or more influencers. The engine determines and provides the prediction and the associated explanation based on the user input data.

Abstract: Computer-readable media, methods, and systems are disclosed for linear interval-based dynamic range partitioning in one or more database systems. A request is received by a database management system to insert a new row into a partitioned database table. The partitioned database table may include a plurality of existing partitions and a partition others partition. Based on determining that the new row should be inserted into the partition others partition a series of steps are performed. First, one or more new partitions are added to the partitioned database table. Then, the new row is inserted into the one of the one or more new partitions in the partitioned database table.

Abstract: In some example embodiments, a computer-implemented method may include training a machine learning model in a first database instance using a machine learning algorithm and a training dataset in response to receiving a request to train, serializing the trained machine learning model into a binary file in response to the training of the machine learning model, recreating the trained machine learning model in a second database instance using the binary file in response to receiving a request to apply the machine learning model, and generating an inference result by applying the recreated trained machine learning model on the inference dataset in the second database instance.

Abstract: In an example embodiment, information about an interaction by a user, via the graphical user interface, with an item rendered in the graphical user interface, is obtained from a graphical user interface. The information includes a session identification corresponding to a networking session in which the interaction occurred and an item identification corresponding to the item interacted with. Then k hash functions are applied to a combination of the session identification and the item identification, producing k indexes. Values of bits corresponding to the k indexes in a bloom filter stored in a non-volatile memory are determined. In response to a determination that the values of bits corresponding to the k indexes are all set to one, a session counter corresponding to the item identification is incremented.

Abstract: Provided is a system and method for detecting a SQL command from a natural language input using neural networks which works even when the SQL command has not been seen before by the neural networks. In one example, the method may include storing a candidate set comprising structured query language (SQL) templates paired with respective text values, reducing, via a first predictive network, the candidate set into a subset of candidates based on a natural language input and the text values included in the candidate set, selecting, via a second predictive network, an SQL template from among the subset of candidates based on the natural language input and text values included in the subset of candidates, and determining a SQL command that corresponds to the natural language input based on the selected SQL template and content from the natural language input.