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The written record of what your systems did, and one of the sneakiest line items on the bill.
Quick Definition
Logging is the practice of recording events, requests, and errors produced by applications and infrastructure. Logs are essential for debugging, security, and observability, but high-volume log ingestion and retention can themselves become a significant cloud cost to manage.
Logging is the practice of recording events as software runs: requests handled, errors thrown, decisions made. Logs are the primary evidence when something breaks, the raw material for audits, and one third of the observability triad alongside metrics and traces.
Logs are also a notorious cost trap. Every log line is written, shipped, indexed, stored, and eventually queried, and each step bills. Verbose debug logging left on in production, logs retained for years by default, and high-cardinality noise nobody reads can push logging platforms into a company's top five cloud expenses without anyone deciding that should happen.
Example. A team discovers one chatty service produces 40 percent of total log volume, mostly a debug line firing on every request. One configuration change cuts the monthly observability bill by thousands.
The disciplines are sampling, log levels enforced in production, retention tiers that move old logs to cheap storage, and regular top-talker reviews. The monitoring tools roundup and the Datadog pricing guide explain where logging charges come from.
Hot and searchable for days to weeks, cheap archive for whatever compliance requires. Keeping everything searchable forever is the expensive default.
Keeping a representative fraction of high-volume, low-value logs, such as routine success lines, while retaining all errors.
Usually a few services produce most volume. Find the top talkers, fix levels and noise, then tier retention.