Modern cloud environments generate vast amounts of log data, making it costly to index all of it, thus necessitating effective cost management strategies without compromising observability. Logz.io offers solutions like Archive & Restore, Log Patterns, and Drop Filters to manage these costs efficiently. Archive & Restore allows businesses to store logs in inexpensive storage like an S3 bucket, enabling access and reingestion if needed, ensuring that crucial data is not permanently lost. Log Patterns help identify noisy logs by clustering similar logs and organizing them by frequency, which aids in recognizing which logs are using significant resources without frequent use. Drop Filters further optimize cost management by filtering out rarely needed logs before indexing, reducing unnecessary data processing and storage costs. Together, these features enable businesses to maintain a balance between cost efficiency and comprehensive data analysis, providing the flexibility to reingest data if it becomes crucial for troubleshooting future incidents.