Abstract: The disclosed embodiments provide a system for testing machine learning workflows. During operation, the system obtains a configuration for a staging test of a machine learning model, wherein the configuration includes a model name for the machine learning model, a duration of the staging test, and a use case associated with the machine learning model. Next, the system selects a staging test host for the staging test. The system then deploys the staging test on the staging test host in a staging environment, wherein the deployed staging test executes the machine learning model based on live traffic received from a production environment. After the staging test has completed, the system outputs a set of metrics representing a system impact of the machine learning model on the staging test host.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system stores a conversation containing a series of messages exchanged among a number of participants in a first document containing metadata for the conversation; a second document containing message content for the series of messages, wherein the message content includes a fixed position gap between starting or ending positions in consecutive messages in the series of messages; and one or more additional documents storing message metadata for individual messages in the conversation. Next, the system processes a first search across the series of messages in the conversation using an index of the set of documents. The system also processes, using the index, a second search within individual messages in the series of messages as a span query with a distance that is shorter than the fixed position gap.

Abstract: The disclosed embodiments provide a system for testing machine learning workflows. During operation, the system obtains a configuration for a staging test of a machine learning model, wherein the configuration includes a model name for the machine learning model, a duration of the staging test, and a use case associated with the machine learning model. Next, the system selects a staging test host for the staging test. The system then deploys the staging test on the staging test host in a staging environment, wherein the deployed staging test executes the machine learning model based on live traffic received from a production environment. After the staging test has completed, the system outputs a set of metrics representing a system impact of the machine learning model on the staging test host.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system stores a conversation containing a series of messages exchanged among a number of participants in a first document containing metadata for the conversation; a second document containing message content for the series of messages, wherein the message content includes a fixed position gap between starting or ending positions in consecutive messages in the series of messages; and one or more additional documents storing message metadata for individual messages in the conversation. Next, the system processes a first search across the series of messages in the conversation using an index of the set of documents. The system also processes, using the index, a second search within individual messages in the series of messages as a span query with a distance that is shorter than the fixed position gap.