How to Cut Cloud Logging and Log Router Costs on GCP

To cut Cloud Logging cost on GCP, rank your biggest log sources, add exclusion filters at the Log Router so high-volume low-value logs are dropped before ingestion, reduce verbose logs at the source, shorten retention to what compliance requires, and route rarely-queried logs to cheaper storage. The charge is on ingestion at 0.50 US dollars per GiB beyond the first 50 GiB free per project per month, so the cheapest log is one excluded before it is ingested. Health checks, successful requests, and debug noise usually dominate volume and are safe to drop.

Last updated: June 2026. Written by Fredrik Filipsson and reviewed by Morten Andersen, built on our See, Cut, Lock, Run method.

This guide sits in our complete guide to Google Cloud cost optimization, the cluster pillar it links up to, and connects to the broader cloud cost optimization playbook. Logging often travels with messaging spend, so read it alongside our companion guide on how to reduce Pub/Sub and Eventarc costs on Google Cloud. Trimming log ingestion is a Cut step move against a bill that grows by default.

How is Cloud Logging priced on GCP?

Cloud Logging charges for log ingestion at 0.50 US dollars per GiB beyond a free allotment of the first 50 GiB per project per month, and that ingestion price includes default storage for 30 days. Per the Google Cloud Observability pricing documentation, retention beyond the included 30 days in custom buckets is billed separately per GiB per month. The key structural fact is that the charge is on ingestion, so once a log is ingested you have already paid the main cost. That is why exclusion at the Log Router beats every other lever: it removes volume before the billable event. Verify the current per-GiB rate and free allotment in the linked pricing page before modeling, because Google Cloud prices change.

What is the Log Router and how does it save money?

The Log Router is the component that receives every log entry in a project and routes it to destinations through sinks, applying inclusion and exclusion filters along the way. It saves money because an exclusion filter on a sink drops matching entries before they are ingested into a billable bucket, so the excluded volume never incurs the ingestion charge. It also lets you send logs you must keep but rarely query to cheaper destinations such as Cloud Storage or BigQuery instead of paid log buckets. In short, the Log Router is both the cost gate and the routing layer, which is why all the high-leverage moves happen there.

How do I cut logging cost, step by step?

Cut it by finding the volume, excluding the noise, and right-sizing what remains. Five steps:

1. Find your biggest log sources. Rank volume by resource, log name, and severity in the Logs Dashboard. Result: the largest contributors to cut first.
2. Add exclusion filters at the Log Router. Drop high-volume, low-value logs on the _Default sink before ingestion. Result: excluded volume is never billed.
3. Drop noisy log lines at the source. Reduce health check, debug, and successful-request logging in the app. Result: less volume reaches the router at all.
4. Shorten retention. Lower custom bucket retention to what compliance requires. Result: no paying to store logs longer than needed.
5. Route low-value logs cheaply. Sink rarely-queried logs to Cloud Storage or BigQuery. Result: compliance retention without paid bucket cost.

What is the cheapest way to keep logs I rarely query?

The cheapest way to keep rarely-queried logs is to route them with a Log Router sink to Cloud Storage or BigQuery rather than holding them in a paid log bucket. Cloud Storage with a nearline or coldline class costs a fraction of log bucket retention per GB and suits archival logs you must keep for compliance but seldom read; BigQuery suits logs you analyze in bulk rather than tail in real time. Reserve Cloud Logging buckets for the logs you actively search, and send everything else to the storage tier that matches how often you touch it. This separates the must-keep requirement from the must-search requirement, and only the latter belongs in expensive logging storage.

Frequently asked questions

How is Cloud Logging priced on GCP?

Cloud Logging charges for log ingestion at 0.50 US dollars per GiB beyond a free allotment of the first 50 GiB per project per month, and that ingestion price includes default storage for 30 days. Retention beyond 30 days in custom buckets is billed separately per GiB per month. Because the charge is on ingestion, the cheapest log is one that is excluded before it is ingested. Verify current rates in the Google Cloud Observability pricing page.

What is the Log Router and how does it save money?

The Log Router is the component that receives every log entry and decides where it goes through sinks and filters. It saves money because exclusion filters applied at the Log Router drop logs before they are ingested into a billable bucket, so excluded volume is never charged. It also lets you route logs you must retain but rarely query to cheaper destinations like Cloud Storage instead of paid log buckets.

What is the cheapest way to keep logs I rarely query?

Route them with a Log Router sink to Cloud Storage or BigQuery rather than keeping them in a paid log bucket. Cloud Storage with a nearline or coldline class is far cheaper per GB for archival logs you must retain for compliance but seldom read, and BigQuery suits logs you analyze in bulk. Keep only the logs you actively search in Cloud Logging buckets.

Do exclusion filters lose data I might need?

Exclusion filters drop matching logs at ingestion, so the excluded entries are not stored in that bucket. To avoid losing data you might need, scope filters tightly to genuinely low-value logs such as health checks and successful load balancer requests, and route anything with compliance value to cheaper storage with a sink instead of excluding it outright. Test filters against recent logs before enforcing them.

The short version

Cloud Logging bills on ingestion, so cut cost at the Log Router: exclude high-volume noise before it is ingested, reduce verbose logging at the source, shorten retention, and route must-keep logs to cheap storage. That removes the charge at the front door instead of managing it at the back. When you want log volume ranked and filtered safely across your projects, that is what our Google Cloud cost optimization service delivers.