Abstract: Aspects of the present disclosure relate to watermarks and watermarking techniques for data streaming pipelines. Time stamp and offset timeline data is shared by computing instances along the pipeline to enable improved watermarking of the data stream through the pipeline. The improved watermarks enable better determination of completeness for the data stream and improve materialization of the results. The watermarking techniques can include periodically publishing watermark data by processing units of a vertex, fetching a merged watermark for a vertex by a vertex, and/or watching a data storage for the watermark data for events. Consensus algorithms can be used to maintain consensus among vertices for the watermark data.

Abstract: Aspects of the present disclosure relate to watermarks and watermarking techniques for data streaming pipelines. Time stamp and offset timeline data is shared by computing instances along the pipeline to enable improved watermarking of the data stream through the pipeline. The improved watermarks enable better determination of completeness for the data stream and improve materialization of the results. The watermarking techniques can include periodically publishing watermark data by processing units of a vertex, fetching a merged watermark for a vertex by a vertex, and/or watching a data storage for the watermark data for events. Consensus algorithms can be used to maintain consensus among vertices for the watermark data.

Abstract: Aspects of the present disclosure relate to watermarks and watermarking techniques for data streaming pipelines. Time stamp and offset timeline data is shared by computing instances along the pipeline to enable improved watermarking of the data stream through the pipeline. The improved watermarks enable better determination of completeness for the data stream and improve materialization of the results. The watermarking techniques can include periodically publishing watermark data by processing units of a vertex, fetching a merged watermark for a vertex by a vertex, and/or watching a data storage for the watermark data for events. Consensus algorithms can be used to maintain consensus among vertices for the watermark data.

Abstract: A method implements a streaming machine learning platform. The method includes processing event data with a preprocessing application to generate model input data and cardinality data in response to receiving the event data from a streaming application. The method further includes forwarding, using the cardinality data, the model input data to a machine learning model. The method further includes processing the model input data with the machine learning model to generate model output data stored to an output record. The method further includes processing the model output data from the output record with a post processing application to generate post data stored to a post record. The method further includes generating notification data using the post data of the post record and transmitting a notification of the notification data.

Abstract: A method for generating a software container includes receiving a software application and a containerization file. The method also includes building an image file using the containerization file, the image file containing the software application. The method also includes recording, in the image file, an image lineage. The method also includes performing a security scan of the image file to obtain a result, the security scan comprising checking the image file for inadequacies. The method also includes assigning, to the image file, a security level selected from among a plurality of different predetermined security levels. Assigning is based on a combination of the image lineage and the result of the security scan. The method also includes signing the image file with the security level to create a signed image file. The method also includes storing the signed image file as the software container.

Abstract: A method and system generates extended patterns from base patterns with an automatic pattern generation engine. The method and system tests the extended patterns with an automatic pattern testing engine. The patterns correspond to configurations for implementing cloud-based applications. The patterns are extendable to make additional extended patterns. Extended patterns carry the characteristics of the patterns from which they were extended. Updating a base pattern with new security measures causes a cascade effect that updates all extended patterns that descend from the base pattern.

Abstract: A method and system provides automatic patterns for implementing cloud based applications. The automatic patterns are extendable to make additional extended patterns. Extended patterns carry the characteristics of the patterns from which they were extended. Updating a base pattern with new security measures causes a cascade effect that updates all extended patterns that descend from the base pattern.

Abstract: A method and system generates extended patterns from base patterns with an automatic pattern generation engine. The patterns correspond to configurations for implementing cloud-based applications. The patterns are extendable to make additional extended patterns. Extended patterns carry the characteristics of the patterns from which they were extended. Updating a base pattern with new security measures causes a cascade effect that updates all extended patterns that descend from the base pattern.

Abstract: A method and system generates extended patterns from base patterns and tests the extended patterns. The patterns correspond to configurations for implementing cloud-based applications. The patterns are extendable to make additional extended patterns. Extended patterns carry the characteristics of the patterns from which they were extended. Updating a base pattern with new security measures causes a cascade effect that updates all extended patterns that descend from the base pattern. The method and system automatically stacks and launches applications according to the extended patterns.