Google Cloud Logging

Google Cloud Logging is a service that enables users to monitor, analyze and visualize cloud usage from different platforms and services.

By - Manish Kumar Barnwal
Updated on
August 21, 2023


What is Google Cloud Logging?

Google Cloud Logging collects log data from various platforms and services, including Google Cloud Platform. The data is saved in buckets for a specific time period of your choice, ensuring secure storage and real-time access and analysis.

The Cloud Logging API enables easy search and filtering of log data, saving time and effort. Additionally, Cloud Logging provides advanced search and visualization features for creating custom dashboards that offer insights into your applications, identify trends, and troubleshoot issues.

When to use Cloud Logging?

Google Cloud Logging is great for businesses that need to keep track of and analyze log data from their cloud resources. It manages logs efficiently and affordably, which is perfect for organizations with a lot of logging needs.

Also, Cloud Logging has different types of logs, such as Cloud Platform Logs, Security Logs, and Logging Exports, each with specific purposes. With Cloud Logging, businesses can learn more about their systems, apps, and networks and make better decisions based on that information.

What is the cloud logging process?

Google Cloud Logging is a service that allows organizations to store, search, analyze, and receive alerts from log data and events from GCP and AWS resources. This service collects logs and events from various sources and makes them available for analysis, visualization, and export.

By tracking every user action, system fault, application transaction, and network packet movement, cloud logging allows organizations to resolve bottlenecks, review historical trends, and forecast future occurrences.

Features & Advantages

Cloud Logging Features

Cloud Logging offers a range of features that make it an ideal solution for businesses that require extensive logging and analysis capabilities. Some of the key features of Cloud Logging include:

  • Scalability: Google Cloud Logging can scale up or down automatically, depending on the volume of logs being generated. This ensures that businesses can manage large volumes of logs without worrying about infrastructure costs or capacity planning.
  • Real-time monitoring: Google Cloud Logging provides real-time monitoring of logs, allowing businesses to track the performance and availability of their applications and infrastructure in real-time. This feature enables businesses to identify and troubleshoot issues as they happen, ensuring that their environments are always up and running.
  • Multi-cloud logging: Google Cloud Logging supports logging from multiple cloud providers, making it easy for businesses to manage logs from various sources. This feature enables businesses to consolidate their logs in one place, making it easier to analyze and troubleshoot issues.
  • Integrations: Google Cloud Logging integrates with various services and tools, including Google Cloud Monitoring, Google Cloud Storage, and third-party logging and monitoring tools. This feature makes it easier for businesses to use Google Cloud Logging in conjunction with other services.

Cloud Logging Advantages

  1. Monitoring Using Logging:  Logging provides a comprehensive record of all activities and changes made to resources, including who made the changes and when. This helps organizations detect and troubleshoot issues quickly and efficiently. Cloud logging can also be used for performance monitoring, providing insights into how resources are performing and identifying bottlenecks.
  2. Security Compliance: Most regulatory frameworks require organizations to maintain logs of all activities that occur on their systems, including who accessed what data and when. Cloud logging provides a centralized location for storing logs and ensures that they are tamper-evident and secure. This makes it easier for organizations to demonstrate compliance with regulations such as HIPAA, SOC 2, and PCI DSS.
  3. Security Standards: Cloud logging provides several security features to help organizations keep their data and systems secure. For example, logs can be encrypted both at rest and in transit, ensuring that sensitive information is not compromised. Access to logs can be controlled through fine-grained access control mechanisms, ensuring that only authorized personnel can access them. Cloud logging also provides multi-factor authentication and other security measures to prevent unauthorized access to logs.
  4. Centralized Management: With a centralized management system in place, organizations can quickly identify and troubleshoot issues, track user activity, and monitor system performance. Additionally, cloud logging enables organizations to easily scale their logging capabilities as their needs evolve, ensuring that they always have the necessary resources to support their operations.


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 Calculate Cloud Logging Costs

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.

Cost Optimization

Cloud Logging Cost Optimization

Cloud Logging is a critical component for monitoring and debugging in Google Cloud, and cost optimization is important when using it efficiently.

  1. Logs Expiration and Retention: Cloud Logging allows you to set the expiration time for logs to control the retention period. By default, logs are kept for 30 days. However, for data governance purposes or to comply with industry regulations, you may need to maintain logs for a more extended period. In such cases, you may set a longer retention time, or you may export the logs to cheaper long-term storage options such as Google Cloud Storage.
  2. Log Filtering: Using log filters is an effective way to reduce Cloud Logging costs. Filters help you narrow down the logs that need to be processed, so you only pay for what you need. You can use advanced queries to filter logs based on resource type, severity level, or custom labels. The more filters you use, the more specific the log data you collect, which can significantly reduce logging costs.
  3. Log Export to Different Destinations: Cloud Logging allows you to export logs to various destinations such as Google Cloud Storage, BigQuery, and Pub/Sub. If you only need to store logs for future reference or compliance purposes, exporting logs to Google Cloud Storage may be a more cost-effective option. In contrast, exporting logs to BigQuery allows you to analyze log data in real-time.
  4. Use log-based Metrics: You can create custom metrics from logs to help you analyze and monitor your system's behavior. Log-based metrics are computed based on the log data, which means that you only pay for the logs processed to generate the metrics. This is a cost-effective way to gain insight into your system's performance and behavior.

Remember that cost optimization is an ongoing process, and you should continually monitor and adjust your usage to ensure that you are getting the most value for your investment in Cloud Logging.

Cloud Logging Best Practices

Here are some best practices to help you reduce Cloud Logging costs and optimize queries:

  1. Log-based Alerts: Use log-based alerts to monitor logs for specific events and patterns. Log-based alerts trigger notifications when specific log entries meet certain conditions. By setting up alerts, you can avoid excessive logging, reduce logging costs, and focus only on critical events.
  2. Use Labels to Group Log Entries: Assigning labels to your logs can help you group them based on a specific attribute, such as project, environment, or application. This allows you to filter logs by label, reducing the number of logs processed and ultimately reducing logging costs.
  3. Disable Log Exports for Non-Essential Logs: If you have enabled log exports to destinations such as BigQuery or Pub/Sub, make sure that you only export logs that are essential for your use case. Exporting non-essential logs increases logging costs without providing any significant value.
  4. Use Log Views: Log Views allow you to create a customized view of your logs, displaying only the log entries that meet specific criteria. This can help reduce logging costs by filtering out unnecessary logs.

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