Does Long Term Data Retention Matter In Observability? Users Say Yes.

Observability is fundamentally a data problem, with organizations needing the right data at the right time to effectively troubleshoot issues, yet the challenge lies in predicting which data will be needed. As organizations grow, so does their observability data, raising questions about which data to collect, how to manage it, and how long to retain it. While cost is a major inhibitor of long-term data retention, discarding data solely due to cost concerns can be problematic, as longer retention can be crucial for compliance, security investigations, and unforeseen circumstances. A forthcoming State of Observability report indicates that 94% of users consider long-term data retention important, despite the challenges posed by the cost of indexing and storage. Some organizations are addressing these costs by using data pipelines to route telemetry data to cold storage, but this can create data silos. Tools like Observe, built on Snowflake, offer a solution by allowing organizations to retain data for extended periods without incurring additional costs for rehydrating data from cold storage, thus breaking down silos and providing valuable context to the data.

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