Datadog Observability Pipelines is a tool that helps organizations manage and optimize their log data to stay within budget while extracting valuable insights from it. By pre-processing logs, organizations can focus on sending valuable log data to premium storage tiers, reducing the overall cost of indexed storage solutions. This is achieved through various processing functions such as filtering, sampling, editing, and deduplication, which allow teams to be selective about the logs they send to higher-cost destinations. Observability Pipelines also provides granular control over logs, enabling organizations to implement daily quotas for logging sources, ensuring that unexpected events do not compromise cost predictability. The tool offers five processor types, including filter, sample, quota, and dedupe processors, which can be combined to remove noise and irrelevant data from logs before routing them to premium storage. By using Observability Pipelines, organizations can optimize their log spend, reduce costs, and gain valuable insights from their log data.