Amazon Technologies, Inc.

Roland Mesde

Alex Bessonov

Vivek Chawda

Samartha Chandrashekar

Sophia Yeemei Tsang

Nitin Giri

Sushil Ravoori

Brian Ewanchuk

Javier Arturo Thiele-Ruiz

Kyle Daniel Halbach

Paolo Gruenberg Hilario

George Sherif Kamal Hanna

Jiangtao Zhang

Brett Francis

Edwin Ricardo Mendez Rodriguez

Sriram Venkatadri

Matthew Jonathan Narksusook

Koushik Rajagopal

Indraneel Mitra

Divya Balasubramanian

Stefano Marzani

Roie Hodara

Shailaja Yadav

Daniel John Scholl

Raviprasad V Mummidi

Nikhil Kumar Jadhav

Frederick Lee Von Wurden

Madhur Pyasi

Nikhilkumar Jadhav

Sebastian Hochmuth

A vehicle information system maintains a street shadow representing attributes of an environment in which a vehicle is located or travels through. The attributes may include objects or events in the surrounding environment. In some embodiments, cloud-based computing devices maintain a primary street shadow, and roadside resources maintain information about short-lived objects or events that may be added to the primary street shadow to augment it. Additionally, a vehicle may further augment the street shadow representation with locally detected events and/or objects. Also, events and objects detected by a vehicle are provided to the roadside resource. The roadside resource may infer an estimated lifetime of the events and objects, and cache short-lived events and objects for distribution to other vehicles, and also provide long-lived events and objects to the cloud-computing devices for use in updating the primary street shadow.

Composite street shadows for vehicles

Systems and methods of determining and providing optimized deployment plans for deploying software to vehicles are disclosed. In some embodiments, a vehicle software deployment system evaluates one or more cost functions to determine relative costs of different deployment configuration options for deploying software to a vehicle, such as resource costs (e.g., bandwidth, compute, memory, etc.), isolation costs (e.g., limited access to input information, limited connectivity to other ECUs, etc.), performance costs, etc. Based on the evaluation of the one or more cost functions, the vehicle software deployment system determines an optimized deployment plan. Also, the vehicle software deployment system receives telemetry data from the vehicle and automatically determines updated optimized deployment plans in response to changes in configuration of the vehicle indicated in the telemetry data.

Vehicle application deployment system with optimized placement

A vehicle data streaming service may receive requests to register plug-ins to generate synthetic vehicle attribute data streams. A plug-in service of the vehicle data streaming service may configure a given plug-in in an internal containerized environment in a fully automated manner and/or configure the plug-in in an external compute service environment. The vehicle data streaming service may configure the plug-ins to receive input streams to generate synthetic attribute output streams. The vehicle data streaming service and the plug-in service may allow the synthetic attribute output streams to be associated with synthetic vehicle attributes included, or to be included, in a curated catalog of vehicle attributes. The vehicle data streaming service furthermore allows one or more vehicle data stream destinations to subscribe to the synthetic vehicle attributes included in the catalog.

Plug-in orchestrator for vehicle data stream subscription system

A vehicle software release management system enables receipt of a vehicle software package and an associated test plan to generate a versioned software artifact set. The vehicle software release management system may initiate a workflow to manage testing, certification, and deployment of the software package based on the versioned software artifact set. The vehicle software release management system may facilitate testing of the vehicle software package, including generating test scripts and configuring the testing environment according to test configurations. The vehicle software release management system may facilitate certification of the vehicle software package according to the versioned software artifact set and manage the deployment/rollback to software package destinations.

Vehicle software change control system

A vehicle data streaming service provides a curated catalog of vehicle attributes and allows a vehicle data stream source to register to the vehicle data streaming system and associate its data stream to a vehicle attribute of the attribute catalog. The vehicle data streaming service also allows vehicle data stream destinations to subscribe to the vehicle attribute in the vehicle catalog, receives streamed vehicle data from the data stream source, and sends streamed vehicle data conforming to registration requirements to the data stream destinations. Additionally, the vehicle data streaming service may allow management of the vehicle attribute catalog and may further manage the registration one or more sources and the subscriptions of one or more destinations.

Vehicle data stream subscription system

Systems and methods for providing vehicle software deployment plans that include one or more fallback deployment plans are disclosed. In some embodiments, a vehicle software deployment system determines a deployment plan for deploying one or more software applications one or more electronic control units (ECUs) of a vehicle. Additionally, for one or more failure scenarios, the vehicle software deployment system determines one or more respective fallback deployment plans, such as a deployment plan that assumes one of the ECUs of the vehicle has failed. A deployment plan bundle is provided to the vehicle, comprising a primary deployment plan as well as the one or more fallback deployment plans. In the event that one of the failure scenarios takes place with respect to the vehicle, a deployment agent of the vehicle automatically deploys one of the fallback deployment plans that was provided with the deployment bundle.

Vehicle application deployment system with pre-determined fallback deployments

A vehicle signal relay system enables a relay agent in a first zone of a vehicle to send sensor signals having a first link-layer communication protocol to a software application deployed on a compute unit in another zone of the vehicle that is connected using another link-layer communication protocol. The vehicle signal relay system allows the software application to identify target relay agents with access to needed sensor signals. The vehicle signal relay system may further enable one way or mutual attestation. The vehicle signal relay system may also allow filters to be applied to the subscribed vehicle sensor signals, and may allow the software application to determine a communication protocol to be used between the software application and the relay agent.

Vehicle signal relay service

A vehicle data management system and data jurisdiction system manage vehicle data between multiple jurisdictions and enables a set of jurisdiction rules involving rules of various jurisdictions to be applied consistently. The vehicle data jurisdiction system can detect changes in jurisdiction of a vehicle based on various pieces of received vehicle information and applies appropriate jurisdiction rules from a set of jurisdiction rules. Various jurisdictions may have conflicting jurisdiction rules and, in such circumstances, the data jurisdiction system resolves potential conflicts between the rules using a jurisdiction rules resolution workflow. Based on the resolution of the conflict, the data jurisdiction system can migrate data of the vehicle to one or more other jurisdictions, or otherwise implement the correct rules determined by resolving the conflict.

Vehicle data jurisdiction management

A vehicle information system and an in-vehicle agent implement a system for detecting discrepancies, for example due to drift, between actual real-world conditions in an environment surrounding a vehicle and corresponding conditions as represented in a model used by the vehicle. Additionally, the in-vehicle agent provides the detected discrepancies to a road-side resource and/or cloud-based computing device in order to distribute the detected discrepancies to other vehicles in the area. Also, a model maintained at the cloud-based computing devices may be updated to account for the discrepancies. The roadside resource and/or vehicle may infer estimated lifetimes of the detected discrepancies and intelligently distribute information describing the discrepancies based on their respective estimated lifetimes.

Vehicle environment discrepancy identification and discrepancy distribution to other vehicles

Systems and methods are disclosed for implementing a vehicle shadow service that includes a vehicle and/or vehicle shadow update mechanism. A vehicle shadow management sub-system of the vehicle shadow service includes or interfaces with an interface configured to receive vehicle state change requests. Received requests are stored in an update queue for a vehicle shadow and a validation processor determines whether the received state change requests are valid before sending a given state change request to a vehicle corresponding to the vehicle shadow. In some embodiments, state change requests may be invalidated due to being rendered moot by subsequently received requests, changes in state of the vehicle, expiration, etc. The corresponding vehicle shadow is then updated when a data stream from the vehicle indicates that the requested state change has in fact been implemented at the vehicle.

Vehicle update system

Techniques are described for providing an access control list (ACL) assisted process for filtering the analysis and display of dependency relationships among software application components (e.g., packages, files, classes, etc.), e.g., as part of modernization processes aimed at decomposing monolithic applications, identifying anti-patterns, or otherwise analyzing such applications. A software modernization service of a cloud provider network provides discovery agents and other tools that are capable of creating an inventory of users' software applications and collecting application artifacts (e.g., source code or bytecode files) associated with the software applications in users' computing environments. Various techniques are described for using ACLs containing entries enabling or disabling the analysis or display of various application components to customize various modernization processes and results displays.

Access control list (ACL) based static analysis of software application artifacts

Techniques are described for automatically identifying monolithic software applications in users' computing environments for software modernization purposes. A monolithic patent application typically refers to a single-tiered application with self-contained functionality designed largely without modularity, although many types of applications can have monolithic characteristics. In many cases, modularity in a software application's design is desirable and thus developers may often seek to decompose monolithic applications into more modular 'microservices' or other subunits when possible. A software modernization system includes a software analysis service that obtains, for one or more software applications undergoing evaluation, a collection of application artifacts, application profiling metrics, and other application profile data. A collection of features is extracted from the application artifacts and metrics and used as input to a ML model trained to determine whether a software application likely is monolithic.

Machine learning-based identification of monolithic software application

Disclosed are various embodiments for anti-pattern detection in extraction and deployment of a microservice. A software modernization service is executed to analyze a computing application to identify various applications. When one or more of the application components are specified to be extracted as an independently deployable subunit, anti-patterns associated with deployment of the independently deployable subunit are determined prior to extraction. Anti-patterns may include increases in execution time, bandwidth, network latency, central processing unit (CPU) usage, and memory usage among other anti-patterns. The independently deployable subunit is selectively deployed separate from the computing application based on the identified anti-patterns.

Anti-pattern detection in extraction and deployment of a microservice

Disclosed are various embodiments for isolated code detection from application code analysis. Various application components may be identified from a source code file or a bytecode file of a computing application. A graph model representative of the computing application is generated having nodes and bridges that connect some nodes to other nodes. The graph model is generated such that at least one of the nodes is an isolated node having less than a threshold number of bridges connecting to other nodes, which is indicative that a corresponding one of the application components can be implemented as an independently deployable component of the computing application.

Isolated code detection from application code analysis

Disclosed are various embodiments for the extraction of isolated nodes during source code refactoring. A graph model representative of a computing application is generated having nodes and bridges that connect some nodes to other nodes. An application component corresponding to a selected one of the nodes may be extracted from the computing application. An independently deployable component of the computing application may be generated and deployed on a network service such that the independently deployable component is accessible through a network-based call.

Growing community of inventors

Cupertino, CA, United States of America

Roland Mesde