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Cloud Logging Pricing Factors

The pricing for cloud logging is determined by two main factors: log ingestion and log storage.

  • Log ingestion costs are based on the amount of data ingested into the service and are calculated on a per-gigabyte basis.
  • Log storage costs are based on the amount of log data stored in the service and are calculated on a per-gigabyte per-month basis.

The pricing for cloud logging varies depending on the location of the log data, with logs stored in regional locations being less expensive than logs stored in multi-regional locations.

Is Cloud Logging Free or Paid?

Google Cloud offers a free tier for Cloud logging that allows users to get started with the service without incurring any costs. The free tier includes up to 50 GB of log data ingestion per month and up to 30 days of log data retention.

Beyond the free tier, users are charged based on the amount of log data ingested and stored in the service. Additionally, users may incur charges for network egress if they choose to export their log data to another service or location.

The table above outlines the pricing factors and their associated costs for Cloud logging.

Note that pricing may vary based on the location and type of storage used.

How to Estimate Cloud Logging Costs

BigQuery offers two main pricing tiers: flat rate and on-demand. Each pricing tier has its own unique To estimate the cost of Cloud Logging for your project, you need to consider several factors, including the amount of log data generated by your resources, the retention period for your logs, and the location of your log data. Here are some tips for estimating your Cloud Logging costs:

  1. Estimate Log Ingestion Volume: Use the Google Cloud Pricing Calculator to estimate the cost of log ingestion based on the volume of log data generated by your resources. You can also use the Stackdriver Logging API to retrieve your project's ingestion data.
  2. Determine Log Retention Time: Determine the retention time for your logs based on your data retention policies or regulatory requirements. Consider exporting your logs to long-term storage options such as Google Cloud Storage to reduce your log storage costs.
  3. Choose Log Storage Locations: Choose the most cost-effective storage location for your log data. Regional storage is less expensive than multi-regional storage.
  4. Use Advanced Filters: Use advanced filters to reduce the amount of log data that you need to process. By using advanced filters, you can reduce your log ingestion costs.
  5. Consider Export Destinations: Consider exporting your log data to cost-effective storage options such as Google Cloud Storage or using Pub/Sub to process your log data in real-time.

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