Amazon Technologies, Inc.

Oracle International Corporation

Arthur Carré

Muhammad Ali Siddiqui

Miles Childs Kaufmann

Kendra Anne Yourtee

Sanjeev Kewal Verma

Aaron T Olds

Mathias G Ricken

Carlos Alejandro Arguelles

Erik Joseph Miller

Ramakrishnan Hariharan Chandrasekharapuram

Jason Scott Wodicka

Ayham Tannous

Igor Vasilev

Josh Max Rubinstein

The present embodiments relate to determining a critical path that identifies an order for bootstrapping a subset of resources within a data center under build. A cloud infrastructure orchestration service (CIOS) can identify from configuration files associated with resources to be bootstrapped within the data set, a set of capabilities. The CIOS can identify a first set of capabilities on which publishing each respective capability depends. User input can be received identifying a selected flock. The CIOS can identify the unpublished capabilities on which capabilities corresponding to the selected flock depend. Those unpublished capabilities can be ranked and provided via a visualization to the user. The unpublished capabilities can be ranked according to identifying, for a respective unpublished capability, a set of capabilities that are capable of being published responsive to publishing the respective unpublished capability.

User interface for critical path resources

The present embodiments relate to identifying and tracking capabilities within a data center managed by a cloud infrastructure orchestration service (CIOS). The CIOS can generate visualization(s) for the capabilities of the CIOS. A first portion of a visualization can identify capabilities that depend on previously published capabilities A second portion of the visualization can provide capabilities with one or more unpublished capabilities. In some embodiments, the capabilities depicted as part of the visualization can be arranged by a ranking derived based at least in part on a number of other capabilities publishing of a given capability blocks and/or a number of capabilities on which publishing a given capability depends. The visualization can be used to allocate resources to efficiently publish capabilities and build new regions (e.g., new data centers) with the CIOS.

User interface for on-deck capabilities

Techniques are disclosed for providing a number of user interfaces. A computing system may execute a declarative infrastructure provisioner. The computing system may provide declarative instructions and instruct the declarative infrastructure provision to deploy a plurality of infrastructure resources and a plurality of artifacts. One example user interface may provide a global view of the plurality of infrastructure components and artifacts. Another example user interface may provide corresponding states and change activity of the plurality of infrastructure components and artifacts. Yet another user interface may be provided that presents similarities and/or differences between a locally-generated safety plan indicating first changes for a computing environment and a remotely-generated safety plan indicating second changes for the computing environment.

User interface techniques for an infrastructure orchestration service

Methods and systems for performance testing in a software deployment pipeline are disclosed. One or more performance tests are automatically performed on a build of a software product in a test environment in response to deploying the build to the test environment. One or more performance metrics are collected based on the performance tests. Based on the performance metrics, the build of the software product is accepted or rejected.

Performance testing in a software deployment pipeline

Systems and methods are provided for analyzing operating metrics of monitored metric sources. Aspects of the present disclosure may present for display information associated with the monitored metric source and the analysis of its operating metrics. Analysis comprises determination of reference values and tolerance levels which represent allowable deviations from the reference values. Input data includes a measurement of an operating parameter and a time stamp. Input data may be saved to a data store for using in future analysis of other input data. When input data is determined to be outside the tolerance level, notifications may be issued to alert administrators or systems of the anomaly.

Integration based anomaly detection service

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Seattle, WA, United States of America

Arthur Carré