Disclosed are embodiments of a installed software program that receive a model from a product management system. The model is trained to select one of a plurality of predefined states based on operational parameter values of the installation of the software program. Each of the plurality of predefined states define configuration values of the installation of the software program. The defined configuration values indicate, in some embodiments, updates to operational parameter values of the installation of the software program.

Requests are received for handling by a cloud computing environment which are then executed by the cloud computing environment. While each request is executing, performance metrics associated with the request are monitored. A vector is subsequently generated that encapsulates information associated with the request including the text within the request and the corresponding monitored performance metrics. Each request is then assigned (after it has been executed) to either a normal request cluster or an abnormal request cluster based on which cluster has a nearest mean relative to the corresponding vector. In addition, data can be provided that characterizes requests assigned to the abnormal request cluster. Related apparatus, systems, techniques and articles are also described.

A patient record gateway of an electronic health record system can be validated using a conformance statement that defines capabilities and characteristics of patient record servers associated with the gateway. Part of validating the patient record gateway includes performing a configuration test of the patient record gateway using the conformance statement.

Techniques are provided for enforcing policies at a sub-logical unit number (LUN) granularity, such as at a virtual disk or virtual machine granularity. A block range of a virtual disk of a virtual machine stored within a LUN is identified. A quality of service policy object is assigned to the block range to create a quality of service workload object. A target block range targeted by an operation is identified. A quality of service policy of the quality of service policy object is enforced upon the operation using the quality of service workload object based upon the target block range being within the block range of the virtual disk.

A request manager analyzes API calls from a client to a host application for state and performance information. If current utilization of host application processing or memory footprint resources exceed predetermined levels, then the incoming API call is not forwarded to the application. If current utilization of the host application processing and memory resources do not exceed the predetermined levels, then the request manager quantifies the processing or memory resources required to report the requested information and determines whether projected utilization of the host application processing or memory resources inclusive of the resources required to report the requested information exceed predetermined levels. If the predetermined levels are not exceeded, then the request manager forwards the API call to the application for processing.

Provided is an anomaly pattern detection system including an anomaly detection device connected to one or more servers. The anomaly detection device may include an anomaly detector configured to model input data by considering all of the input data as normal patterns, and detect an anomaly pattern from the input data based on the modeling result.

A model correction tool automatically detects and corrects model drift in a model for a machine learning application. To detect drift, the tool continuously monitors input data, outputs, and/or technical resources (e.g., processor, memory, network, and input/output resources) used to generate outputs. The tool analyzes changes to input data, outputs, and/or resource usage to determine when drift has occurred. When drift is determined to be occurring, the tool retrains a model for a machine learning application.

An electronic device including an application processor and a communication processor. The communication processor including a resource memory, the communication processor configured to monitor an occupancy rate of the resource memory, determine whether the electronic device is in an idle state, forcibly release a network connection, clear the resource memory, and reconnect the network connection.

Technologies for providing shared memory for accelerator sleds includes an accelerator sled to receive, with a memory controller, a memory access request from an accelerator device to access a region of memory. The request is to identify the region of memory with a logical address. Additionally, the accelerator sled is to determine from a map of logical addresses and associated physical address, the physical address associated with the region of memory. In addition, the accelerator sled is to route the memory access request to a memory device associated with the determined physical address.

Apparatuses and methods are provided to generate customizable databases and/or analyze performance. In an example embodiment, a method of generating customizable databases is provided. The method includes receiving a calculation expression relating to one or more defined characteristics. The calculation expression may be defined by a user. The method also includes loading data into a data warehouse. The data includes at least one of the one or more defined characteristics. The method further includes generating a data cube based on the received calculation expression and the data loaded into the data warehouse. The data cube includes an accessible table. A corresponding apparatus is provided. Additional method and apparatus to analyze performance are also provided.