Computer systems, devices, and associated methods of loading a bundle component, comprising a bundle of scripts and a manifest including metadata for the bundle, that is compatible with a dependent bundle component are disclosed herein. In one embodiment, a method includes identifying a bundle component identifier and a version identifier for the bundle component that the dependent bundle component depends on in a manifest associated with the dependent bundle component. The method then includes retrieving a manifest for a bundle component that includes the bundle component identifier and is a most recent compatible version of the bundle component. The method includes loading the most recent compatible bundle component based on a URL in the retrieved manifest for the bundle component.

Computer systems, devices, and associated methods of serializing a web page that is of a first format and includes a plug-in including properties of a second format are disclosed herein. In one embodiment, a method includes identifying, in a manifest for the plug-in, properties for inclusion in the first format in a serialized web page. The manifest may also include metadata associated with the properties in the list of properties. The method includes formatting the properties, including associated property values and metadata, in the first format and adding the formatted properties to the serialized web page. The plug-in properties not included in the manifest can be added to the serialized web page in the second format.

A computer system receives an account creation request for a social media platform created and sent using a frontend component. An application programming interface (API) call sequence associated with the account creation request is received from the frontend component. The API call sequence can reflect API calls registered by the frontend component in connection with creation of the account creation request, and timings of the registered API calls. An API call sequence model is applied to the API call sequence. The API call sequence model can be generated by providing training API call sequences to a machine learning component. At least one action is taken in response to the application of the API call sequence model indicating that the API call sequence is anomalous. The action can be taken with regard to the account creation request, or with regard to an account created in response to the account creation request.

An example system includes a memory store of aggregate definitions. Each aggregate definition specifies a key value, an output store, a feature, a half-life value, and an aggregate operation metric to apply to a cross of the feature and the half-life value to generate aggregate metrics. The system also includes an aggregation engine that generates aggregate feature records from the input source based on the aggregate definitions and stores the aggregate feature records in the output store. An aggregate feature record includes an aggregate of the metric for the feature decayed over time using the half-life. The system also includes a query service that identifies, using the aggregate definitions, responsive aggregate feature records that satisfy parameters of a received request, applies the half-life to the responsive feature records, and provides the responsive feature records to a requester, the requester using the responsive feature records as input for a neural network.

A system for providing dynamic code deployment and versioning is provided. The system may be configured to receive a first request to execute a newer program code on a virtual compute system, determine, based on the first request, that the newer program code is a newer version of an older program code loaded onto an existing container on a virtual machine instance on the virtual compute system, initiate a download of the newer program code onto a second container on the same virtual machine instance, and causing the first request to be processed with the older program code in the existing container.

Methods and systems for automatically identifying an application that is experiencing performance problems caused by a resource utilization event may include receiving an indication that an application is experiencing a performance issue. It may be determined that the performance issue is caused by a resource utilization event on a device. The resource utilization event may include the application and one or more other applications running simultaneously, use of one or more functions of the device simultaneously by at least one of the first application and one or more other applications, and/or a resource utilization overload based on simultaneous use of a plurality of sensors on the device. Next, action may be taken to correct the performance issue of the application.

Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: examining image layers of a container image and generating, in dependence on the examining, layer dependency relationship data that specifies layer dependency relationships of the container image; storing in a container repository the layer dependency relationship data that specifies layer dependency relationships of the container image; in response to receipt of a download request that specifies a targeted layer of the container image, analyzing relationship data of the layer dependency relationship data; in dependence on the analyzing, identifying a subset of image layers of the container image preceding the targeted layer; and establishing a deployment container image in dependence on the identified subset of image layers.

This document describes techniques and systems that enable face authentication embedding migration and drift-compensation. The techniques and systems include a user device that is updated to include both a current version of firmware and an updated version of the firmware. Then, an indication of a face-authentication attempt is received along with image data associated with a user's face. After successful authentication, using the current version of firmware on the image data, the user device uses the updated version of the firmware on the same image data to generate a new embedding. The new embedding is stored as part of a migration profile for the user. Additional new embeddings are collected over a series of subsequent face-authentication attempts until a complete set of new embeddings is stored for the migration profile. Then, the old profile is deleted and the migration profile becomes the enrollment profile used for face authentication.

An operationally monolithic application is provided, where the application resides in a first program address space of an application server. The application calls to an application component residing in a second program address space of the application server, the application component being built upon a framework of the operationally monolithic application. The operationally monolithic application loads at least a first library upon which it depends to invoke a first method, and the application component loads at least a second library upon which it depends to invoke a second method. The first and second libraries can co-exist on the application server despite being different versions of the same libraries.

A system for providing dynamic code deployment and versioning is provided. The system may be configured to receive a first request to execute a newer program code on a virtual compute system, determine, based on the first request, that the newer program code is a newer version of an older program code loaded onto an existing container on a virtual machine instance on the virtual compute system, initiate a download of the newer program code onto a second container on the same virtual machine instance, and causing the first request to be processed with the older program code in the existing container.