Simplifying Data Management and Onboarding in the Elastic Stack and Elastic Cloud
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Delivering faster data ingestion with Google Cloud Dataflow
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Giving users new ways to explore their data with the flexibility of schema on read and schema on write
Elastic, the company behind Elasticsearch and the Elastic Stack, announces new capabilities and updates to the Elastic Stack and Elastic Cloud to simplify data management and onboarding for customers and enable them to achieve faster data insights.
New capabilities include a native Google Cloud data source integration with Google Cloud Dataflow, providing customers with faster data ingestion in Elastic Cloud and a simplified data architecture. Using Google Cloud’s native serverless ETL service, this integration allows users to quickly and securely ingest Pub/Sub, Big Query, and Cloud Storage data directly into their Elastic Cloud deployments.
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Support for Google Private Service Connect, now generally available, provides private connectivity from Google Cloud virtual private clouds to Elastic Cloud deployments. Customers can now privately and securely connect their Elastic Cloud deployments to their Google Cloud environments using Private Service Connect endpoints, ensuring their data is not exposed on the open internet.
Updates to Elasticsearch and Kibana include enhancements to runtime fields, giving users new ways to explore their data with the flexibility of schema on read and schema on write for onboarding and searching new data and delving into ad hoc analysis.
Composite runtime fields enables users to streamline field creation using one script to output multiple fields, making it easier and more intuitive for users to ingest new data for faster insights. Additionally, a new preview pane in the runtime fields editor enables users to test and preview new fields before they are created and also includes better error handling for the editor to streamline and accelerate the field creation process.
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