Salesforce Com, Inc.

Aaron Zhang

Yogesh Patel

Percy Dara Mehta

Shaahin Mehdinezhad Rushan

Mahalaxmi Sanathkumar

Shan-Cheng Ho

Zhidong Ke

Mattia Padovani

Utsavi Benani

Heng Zhang

Johannes Kienzle

Birva Joshi

Mugdha Choudhari

Clinton Tran

Mechanisms and techniques for providing continuous integration and continuous deployment (CI/CD) for data lake applications are disclosed. Assembly of code for an app is managed with a CI platform to create a container within a shared environment within which the app runs. The container is isolated from other containers and bundles software, libraries and configuration files and can communicate with other containers through defined channels. The shared environment provides a platform for running the app. The app writes to one or more tables maintained in the shared environment. Assembly of subsequent versions of code for the app is managed by the CI platform. Deployment of the assembled subsequent version of the code to the container is managed by the CI platform. Integration tests are run on the deployed subsequent version of the code with the CI platform. The subsequent version of the code replaces the app in the shared environment when integration testing is complete.

Techniques and architectures for providing continuous integration (CI) and/or continuous delivery (CD) in a data lake environment

Techniques are disclosed for generating metrics for a stream of interaction data. In some embodiments, a computing system receives a stream of interaction data that is based on user interactions with one or more computing systems, where the stream of interaction data includes information for multiple interaction characteristics including an interaction category. In response to receiving additional interaction information in the stream of interaction data, the computing system may generate cumulative metric values for one or more interaction categories. Generating cumulative metric values may include: sharding the additional interaction information based on multiple characteristics including interaction category, storing the sharded information in a non-relational database, determining respective metric values for shards modified by the storing, storing the respective metric values and shard information for each of the modified shards in a relational database, querying the relational database using one or more interaction categories corresponding to the modified shards, and determining the cumulative metric values based on the results of the querying.

Metric determination for an interaction data stream using multiple databases

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Richmond Hill, Canada

Aaron Zhang