Observe is built on Snowflake. We know Snowflake uniquely well. Observe is a cloud-native observability platform that delivers petabyte-level scalability, blazing-fast query performance and a dramatically lower total cost of ownership. Observe natively integrates with Snowflake Trail to give complete visibility into the performance of Snowflake Data Cloud, query execution, Snowpark User-Defined Functions, Snowpark Container Services deployed applications, ML/AI models, and underlying infrastructure.

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Observe uses various Snowflake accounts worldwide, with a focus on cost efficiency and scale. Observe’s Dataset acceleration is somewhat similar to materialized views while workload scheduling that the rest of this article will describe implements an algorithm similar to that underpinning multi-cluster warehouses.

Resource Management and Queries on Snowflake

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Once data is in Observe, it can be turned into a Data Graph, which consists of Datasets curated from the Data Lake to make it easier to navigate and faster to query. Datasets represent “things” that users want to ask questions about. They can be business-related, such as customers and shopping carts, or infrastructure-related, such as pods, containers, and S3 buckets.

Data Modeling and Transformation with Observe and Snowflake

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Observe chose to build the Observability Cloud on Snowflake, because it allowed us to store massive amounts of data, shape, and accelerate it in an efficient, scalable way. Snowflake’s separation of storage and compute allows Observe to scale our offering for the largest customer workloads, with the flexibility of rapidly getting a lot of compute resources on demand.

Strengths of Snowflake Partnership

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