I'm looking for some effective strategies to manage Datadog logging costs, particularly in environments where log volumes and usage patterns can change frequently. I've found that aggressive filtering and minimizing the retention of indexed logs aren't effective solutions. I'm trying to strike a good balance between retaining useful information and keeping costs manageable. Has anyone faced similar challenges, and what solutions did you find?
1 Answer
Have you thought about how crucial logs are for your operations? Do you really need Datadog for this? If logs are vital for your e-commerce setup, you might find it beneficial for quick incident investigations and analytics. However, if those volatile log volumes continue to be a challenge, you might start looking at other tools that integrate but still allow for effective log correlation.
Absolutely, logs are crucial! I’m focused on e-commerce, so a swift incident response is key. Switching tools is on the table, but I really need that log correlation with the other data in Datadog. The challenge is still figuring out how to maintain quality data without ballooning costs.