Mattias Brunnert's blog post outlines strategies for analyzing and optimizing the storage footprint of an Elastic deployment using the disk usage API. The post emphasizes the importance of proper index mapping configuration to reduce storage consumption, as incorrect or missing mappings can lead to increased storage usage. It guides users on how to use the disk usage API to identify fields that are consuming the most storage and suggests using tools like jq to format API responses for easier analysis in Kibana. The blog also discusses the benefits of adhering to Elastic's best practices, such as using Elastic integrations for automatic field mappings and configuring custom data mappings manually within index templates. Additionally, it recommends using data tiers to manage storage costs effectively, particularly by moving older data to cheaper storage solutions, with Elastic Cloud offering tools to facilitate this process.