Servicenow, Inc.

Shay Herzog

Asaf Garty

Hail Tal

Robert Bitterfeld

Shiri Hameiri

Bary Solomon

Boris Erblat

Tom Bar Oz

Daniel Badyan

Alexandra Feiguine

Sreenevas Subramaniam

Aviya Aron

Aakash Umeshbhai Bhagat

Shimon Sant

Aviya Aharon

Olga Zateikin

A computing system includes persistent storage configured to store representations of software applications installed on computing devices, and a software application configured to perform operations, including retrieving, from the persistent storage, a first plurality of representations of a first plurality of software applications installed on a particular computing device and a second plurality of representations of a second plurality of software applications installed on a reference computing device. The operations also include determining a device fingerprint of the particular computing device based on the first plurality of representations and a reference device fingerprint of the reference computing device based on the second plurality of representations, and comparing the device fingerprint to the reference device fingerprint. The operations further include, based on the comparing, determining a disparity between software applications installed on the particular computing device and the reference computing device, and storing, in the persistent storage, a representation of the disparity.

Determining application security and correctness using machine learning based clustering and similarity

A method includes obtaining a discovery pattern that indicates a plurality of operations associated with a corresponding computing resource type of a plurality of computing resource types. The method also includes identifying a variable parameter value associated with execution of the discovery pattern with respect to a computing resource of the corresponding computing resource type, and determining an error value by using a machine learning model to process the variable parameter value. The error value indicates a likelihood that execution of the discovery pattern, when associated with the variable parameter value, with respect to the particular computing resource results in a corresponding error type. The method further includes receiving, based on the error value, an input comprising one or more of (i) an instruction to execute the discovery pattern or (ii) a modification applicable to the variable parameter value.

Discovery troubleshooting based on machine learning

A discovery application on a computing system is provided. The discovery application executes a discovery pattern comprising a sequence of operations for discovery of resources within a load balancing system, wherein execution of the discovery pattern corresponds to making one or more application programming interface (API) calls to an API associated with a network address of the load balancing system; receives a response to the one or more API calls from the load balancing system, wherein the response comprises a payload of information associated with the resources; and updates, based on the response and in a configuration management database (CMDB), one or more configuration items (CIs) associated with the resources.

Discovery of network load balancers

A discovery computing system may receive an account identifier (ID) and a set of credentials required to access a first service account. The discovery computing system may transmit a first API query to a remote computing system. The discovery computing system may receive an organization identifier (ID) of the organization from the remote computing system. The discovery computing system may further transmit a second API query to the remote computing system. The discovery computing system may be further configured to receive information about a set of projects, in the organization, from the remote computing system. The discovery computing system may further generate a set of service accounts and further determine the set of resources, in the remote computing system, associated with each of the generated set of service accounts. The discovery computing system may further store the determined set of resources, as configuration items in a persistent storage.

Automatic discovery of cloud-based infrastructure and resources

A discovery application on a computing system is provided. The discovery application receives a user input, which is for discovery of resources associated with a cloud operating system of a cloud computing system. The user input includes an authentication credential and account information associated with the cloud operating system. Based on the received input, the discovery application executes a discovery pattern comprising operations for the discovery of resources. The cloud operating system includes a group of services to access such resources. At least one of the operations corresponds to an API call to an API endpoint associated with a service of the group of services. The discovery application receives a response to the API call from the cloud operating system. The response includes a payload of information associated with the resources. The discovery application updates, based on the received response, one or more configuration items in a configuration management database.

The present disclosure is directed to a discovery process that enables discovery of database management systems (DBMSs) hosted by at least one client device of a client network. The disclosed discovery process involves a discovery server disposed on the client network accessing the client device hosting the DBMS to collect configuration item (CI) data on the configuration and operation of management, extraction, and replication processes of the DBMS. More specifically, this discovery process involves the discovery server requesting and receiving certain CI data from the management process of the DBMS, requesting and receiving certain CI data from an operating system (OS) of the client devices, as well as parsing and retrieving certain CI data from configuration and report files of the DBMS. Additionally, the disclosed discovery process is designed to be performed without being granted special or additional privileges within the DBMS itself.

Systems and methods for database management system (DBMS) discovery

An example computing system includes a database disposed within a remote network management platform associated with a managed network that obtains service from a computing cluster that includes one or more worker nodes configured to execute containerized software applications using a containerized orchestration engine. The computing system also includes a computing device configured to identify a namespace associated with the containerized orchestration engine. The computing device is also configured to query a deployment configuration application programming interface (API) associated with a containerized application platform to obtain deployment configuration data. Further, the computing device is configured to query a build configuration API associated with the containerized application platform to obtain build configuration data. In addition, the computing device is configured to store, in the database, the deployment configuration data, the build configuration data, and one or more relationships between the deployment configuration data and the build configuration data.

Discovery of containerized platform and orchestration services

Discovery of resources associated with cloud operating system

A system may contain a computational instance including persistent storage that maintains a discovery pattern and credentials for a cloud-based service, where the cloud-based service provides a remote computing infrastructure. The system may also contain one or more processors configured to: remotely access, using the credentials, the cloud-based service; execute the discovery pattern to obtain copies of tags configured in the cloud-based service, where the tags each include key fields, value fields, and resource identifier fields, and where the resource identifier fields uniquely specify respective computational resources of the cloud-based service; associate the tags that were discovered to configuration item representations of the respective computational resources; and store, in the persistent storage, the tags and their associations to the configuration item representations.

Discovery and storage of resource tags

A system may include persistent storage containing discovery patterns configured to identify computing resources and relationships therebetween, and an application configured to perform operations, including selecting a discovery pattern from the discovery patterns and obtaining, from the persistent storage, source code representing the discovery pattern. The operations may also include parsing the source code to determine therein (i) a plurality of configuration items (CIs) representing the computing resources that the discovery pattern is configured to discover when executed, and (ii) relationships between respective CIs of the plurality of CIs. The operations may additionally include generating a representation of the discovery pattern based on the plurality of CIs and the relationships. The representation may include the plurality of CIs represented by a plurality of nodes and the relationships represented by edges between respective nodes. The representation may be stored in the persistent storage in association with the discovery pattern.

Discovery pattern visualizer

A system includes persistent storage configured to store data on behalf of a managed network and a discovery application configured to perform operations. An application system hosts software applications on behalf of the managed network. The operations include obtaining a service identifier for the application system and, based thereon, determining partitions into which the application system is divided. The operations also include determining, within each respective partition, spaces between which the software applications of the managed network are distributed, and determining, within each respective space, one or more software applications of the software applications of the managed network. The respective space provides an isolated computing environment for execution of the one or more software applications therein. The operations further include determining a mapping that indicates a distribution of (i) the spaces among the partitions and (ii) the software applications among the spaces, and storing, in the persistent storage, the mapping.

Discovery and mapping of a platform-as-a-service environment

A system includes persistent storage configured to store, a mapping of computing resources provided by a remote computing system to a managed network. The system also includes an application that obtains instructions to modify a computing resource provided by the remote computing system and, based on the instructions, generates and transmits, to the remote computing system, a request to modify the computing resource. The application receives, from the remote computing system, a response indicating a modification to the computing resource and selects a discovery pattern configured to verify the modification by obtaining attributes associated therewith. The application obtains, from the remote computing system, the attributes by executing the discovery pattern and determines, based on the attributes, that the modification has been completed according to the instructions. Based on this determination, the application updates the mapping to indicate the modification and stores, in the persistent storage, the mapping as updated.

Discovery and mapping of cloud-based resource modifications

A system includes persistent storage and an application that obtains a service identifier associated with a managed network. The service identifier allows access to a remote computing system that provides computing resources on behalf of the managed network. The application also identifies a geographic region that contains the computing resources. The application additionally identifies, within the geographic region, virtual computing devices allocated to the managed network and attributes thereof. The application further identifies, based on the attributes, (i) load balancers configured to distribute network traffic among the virtual computing devices and (ii) storage volumes used by the virtual computing devices. The application yet further determines a mapping between the virtual computing devices, the load balancers, and the storage volumes to represent a service infrastructure of the remote computing system dedicated to the managed network and stores, in the persistent storage, the mapping as one or more configuration items.

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Raanana, Israel

Shay Herzog