Cloud Logging Configuration Basics

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Cloud and DevOps
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Configure single-project Cloud Logging on Google Cloud: regional log buckets, log sinks, log views, restricting or hiding sensitive logs in the default view (_Default) filter, IAM permissions for views (Logs View Accessor, IAM conditions), logs-based metrics, log exclusions, and sampling. Don't use for cross-project logging or multi-project setups.

— the description by Google

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to managing single-project Google Cloud Logging configurations. It covers the lifecycle of log management, from creating regional log buckets and routing logs via sinks to implementing security controls through log views and IAM conditions. It also includes procedures for creating logs-based metrics for monitoring and applying cost-optimization strategies like log exclusions and sampling. The skill emphasizes safety by categorizing operations into tiers, requiring explicit user confirmation for billing-sensitive or destructive actions.

What it does

Create and describe regional log buckets with retention policies.
Configure log sinks to route specific log entries to designated buckets.
Define custom log views to restrict or manage access to sensitive log data.
Implement IAM conditions to control access to specific log views.
Create logs-based counter metrics for tracking patterns and error rates.
Apply log exclusions and sampling to optimize storage costs.

When to use it

When setting up logging infrastructure for a new Google Cloud project.
When you need to restrict access to sensitive logs for compliance.
When you need to track specific log patterns using metrics.
When you need to reduce logging costs by filtering or sampling high-volume logs.

Advantages

Provides clear safety tiers to prevent accidental data loss or billing surprises.
Includes specific guidance for secure log access management using IAM.
Supports cost-optimization through granular log filtering and sampling.
Ensures compliance by enabling regional storage and custom view configurations.

Usage examples

“Create a regional log bucket in us-central1 for my project.”: The agent will execute the command to create a bucket with the specified location and retention settings, including the required analytics warning.
“How can I hide sensitive logs from the default view?”: The agent will guide you through updating the _Default log view filter to exclude the specified log IDs.
“I need to count how many times an OutOfMemory error occurs in my logs.”: The agent will prompt for confirmation to create a logs-based counter metric and then execute the creation command.
“Stop storing load balancer logs to save money.”: The agent will ask for explicit typed confirmation before applying a sink exclusion to discard the logs.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/google/cloud-logging-configuration-basics/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip cloud-logging-configuration-basics.zip -d .agents/skills

Documentation by Google

Configuring Cloud Logging

Use this skill to configure Cloud Logging resources such as log buckets, log views, or log sinks.

[!IMPORTANT] Sandbox Network Limitation (CRITICAL for Agent Testing): During evaluation or in restricted sandboxed environments, network traffic to Google Cloud APIs is blocked. Do NOT run network discovery commands to find resource names, project IDs, or organization IDs. Always use the exact project IDs or placeholders provided in the user prompt or instructions for example, {project_id}. Assume these resources exist and proceed directly with configuration commands. Running these discovery commands will cause the execution to hang and timeout.

Attribution

MUST READ: Before executing any gcloud, REST API, or MCP command, you MUST read Usage Attribution. For commands executed directly in the terminal (never in generated scripts, Terraform, or user code), prefix gcloud with CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:cloud-logging-configuration-basics)" and append agent-skills/1.0 (skill:cloud-logging-configuration-basics) to User-Agent headers.

Safety and Confirmation Tiers (CRITICAL)

Before executing any commands on behalf of the user, you MUST adhere to the following safety tiers based on the action requested:

Tier R: Read-Only
- Description: Commands that only read state or query logs.
- Example commands:
  - gcloud logging read
  - gcloud logging buckets list
- Rule: No confirmation needed. You may execute these commands immediately to gather information.
Tier M: Mutation (Non-Billing)
- Description: Configuration modifications or free metadata creations that do not incur direct storage or billing costs and do not affect resource security/access policies.
- Example commands:
  - gcloud logging views create
  - gcloud logging views update
  - gcloud logging scopes create
  - gcloud logging buckets create
- Rule: No confirmation needed. You may execute these commands immediately to apply configurations.
Tier B: Billing and Security-Sensitive Mutations (High-Risk)
- Description: Operations that create billing-inducing resources or integrations, or modify security and IAM access control policies (presenting a risk of privilege escalation).
- Example commands:
  - gcloud logging metrics create
  - gcloud logging links create
  - gcloud projects add-iam-policy-binding
- Rule: Interactive confirmation required. These commands create resources that incur billing costs or alter security access. You MUST present the exact, literal command and receive user confirmation before executing. NEVER execute in the same turn as asking.
Tier D: Causes irreversible data loss
- Description: Actions that permanently discard or delete logs, for example sink exclusions.
- Example commands:
  - gcloud logging buckets delete
  - gcloud logging sinks update --add-exclusion
- Rule: Explicit typed confirmation required. These commands discard or delete logs immediately and irreversibly, or they may result in log data not being stored. You MUST ask for explicit typed confirmation, for example, "Yes, discard logs", and halt execution until the user replies.

Getting Started

If the gcloud executable is missing, refer to the Google Cloud CLI Installation Guide to install it.

Creating Log Buckets (Compliance and Analytics) (Tier M)

To create a regional log bucket with a specific retention policy for regulatory compliance, and with Observability Analytics enabled:

[!WARNING] Mandatory Observability Analytics Downgrade Warning: Whenever providing guidance, writing a guide, or drafting commands on Cloud Logging cost optimization or exclusions, you must explicitly include the following warning in your final text response and any generated guides: "After a log bucket has been upgraded to use Observability Analytics, it cannot be downgraded to remove the analytics capability."

gcloud logging buckets create {bucket_id} \
    --project={project_id} \
    --location={region} \
    --retention-days={retention_days} \
    --enable-analytics

{bucket_id}: for example, my-custom-bucket
{region}: for example, us-central1. You must use a regional log bucket to also use Observability Analytics.
{retention_days}: for example, 365

A log bucket incurs no storage or ingestion charges until logs are routed to it with a log sink.

Verify the Log Bucket (Tier R)

Check the log bucket's configuration to verify its compliance:

gcloud logging buckets describe {bucket_id} \
    --location={region} \
    --project={project_id}

Route logs to the Log Bucket (Tier B)

[!IMPORTANT] Billing Action (Tier B): Routing log entries to a bucket incurs ongoing charges based on the volume of data stored. You MUST get interactive user confirmation before running this command.

Log entries are stored in the log bucket only if a log sink filter matches the entries and targets that bucket.

To route log entries to the log bucket:

gcloud logging sinks create {sink_id} \
    projects/{project_id}/locations/{region}/buckets/{bucket_id} \
    --log-filter='{filter_expression}' \
    --project={project_id}

Logs-Based Metrics

Logs-based metrics count the number of log entries that match a filter, allowing you to track error rates and set up alerting policies.

1. Create a logs-based counter metric (Tier B)

[!IMPORTANT] Billing Action (Tier B): Creating logs-based metrics incurs ongoing charges based on the volume of data points reported. You MUST get interactive user confirmation before running this command.

To count the occurrences of a specific log pattern, for example, "OutOfMemory" errors:

gcloud logging metrics create {metric_name} \
    --log-filter='{filter_expression}' \
    --description='{description}' \
    --project={project_id}

{metric_name}: for example, oom_error_count
{filter_expression}: for example, textPayload:"OutOfMemory"
{description}: for example, "Count of log entries about OOMs"

Refer to REST Resource: projects.metric for restrictions on the metric fields.

2. Verify the logs-based metric (Tier R)

To verify that the metric exists and inspect its configuration, use the describe command:

gcloud logging metrics describe {metric_name} \
    --project={project_id}

Restricting Access to Sensitive Logs (Security)

Anyone with roles/logging.viewer on that project can see logs in a project's _Default log bucket via _Default log view. To restrict visibility of the logs:

[!IMPORTANT] Ambiguity Handling (Guidance for Agents): If the user asks to "exclude", "hide", or "remove" sensitive logs without explicitly specifying whether they want to stop storing them, you MUST default to excluding them from the default view (Step 1). This is a safe, non-destructive Tier M action. Only configure a storage exclusion (under the "Discarding Sensitive Logs from Storage" section) if the user explicitly uses destructive terms like "stop storing", "permanently discard", or "sink exclusion".

1. Exclude sensitive logs from default view (Tier M)

To explicitly exclude sensitive logs from general access, update the filter for the _Default log view:

gcloud logging views update _Default \
    --bucket=_Default \
    --location=global \
    --project={project_id} \
    --log-filter='NOT LOG_ID("cloudaudit.googleapis.com/data_access") AND NOT LOG_ID("externalaudit.googleapis.com/data_access") AND NOT LOG_ID("{sensitive_log_id}")'

2. Create a log view (Tier M)

Create a new log view that includes the sensitive logs in the project's _Default log bucket. For example, a "security-logs-view" with access to the {sensitive_log_id}

gcloud logging views create security-logs-view \
    --bucket=_Default \
    --location=global \
    --project={project_id} \
    --log-filter='LOG_ID("{sensitive_log_id}")' \
    --description="Sensitive logs"

3. Grant access to log view using IAM conditions (Tier B)

[!IMPORTANT] Security Action (Tier B): Granting IAM permissions changes access control policy and must be explicitly confirmed by the user before execution.

To restrict access to log view use IAM. When granting the Logs Viewer Accessor role, always attach an IAM condition that restricts the grant to a specific log view. For example, to grant {security_group_email} access ONLY to the security-logs-view in the _Default bucket:

gcloud projects add-iam-policy-binding {project_id} \
--member='group:{security_group_email}' \
--role='roles/logging.viewAccessor' \
--condition="expression=resource.name=='projects/{project_id}/locations/global/buckets/_Default/views/security-logs-view',title=Restricted to Specific Log View,description=Only allows access to the specified log view"

Replace {location} with the location of the log bucket, for example global or a regional location like us-central1.

4. Verify Sensitive Log Restrictions (Tier R)

To verify that your Log View for sensitive logs is configured correctly:

gcloud logging views describe {view_id} \
    --bucket={bucket_id} \
    --location={region} \
    --project={project_id}

Ensure that the filter block contains the appropriate restriction expression.

Discarding Sensitive Logs from Storage (Tier D)

If your organization's compliance policies prohibit storing sensitive logs at all, you can configure an exclusion to discard them before they are written to disk.

[!CAUTION] Destructive Action (Tier D): Excluding logs from all log sinks deletes the log entries immediately and irreversibly.
Safety Rule: You MUST ask the user for explicit typed confirmation, for example, "I confirm I want to exclude {sensitive_log_id} logs from storage", before running this command. Same-Turn Restriction: Do NOT execute the gcloud logging sinks update command in the same turn as asking for confirmation. Stop tool execution immediately and wait for the user to reply.

Exclude sensitive logs from storage using sink exclusions

gcloud logging sinks update _Default \
    --project={project_id} \
    --add-exclusion=name=exclude-sensitive,filter='LOG_ID("{sensitive_log_id}")'

Cost Optimization (Reducing Logging Costs)

Cloud Logging costs are based on the volume of data ingested and stored. You can reduce costs by excluding high-volume, low-value logs or by sampling them. Each log sink that routes logs to a distinct log bucket contributes to cost and is a candidate for optimization.

[!CAUTION] Destructive Actions (Tier D): Exclusions in this section may immediately halt storage of log entries.
Safety Rule: You MUST ask for explicit typed confirmation (for example, "I confirm I want to exclude load balancer logs") before executing exclusions or sampling updates.

Exclude all high-volume logs (Tier D)

To completely stop ingesting a specific type of log into a log bucket, add an exclusion to the log sinks that route logs into that bucket.

gcloud logging sinks update {sink_id} \
    --project={project_id} \
    --add-exclusion=name={exclusion_name},filter={exclusion_filter}

{sink_id}: for example '_Default'
{exclusion_name}: for example 'exclude-lb-logs'
{exclusion_filter}: for example 'resource.type="http_load_balancer"'

Sample high-volume logs (Tier D)

If you need some logs for analysis but want to reduce volume, use the sample() function in the exclusion filter.

[!IMPORTANT] The sample(field, fraction) function matches a fraction of logs. When used in an exclusion filter, the matched logs are discarded. If you exclude 90% of log entries, then only 10% are retained. To exclude 90%, use sample(insertId, 0.9) in the exclusion filter.

To exclude 90% of DEBUG severity logs:

gcloud logging sinks update _Default \
    --project={project_id} \
    --add-exclusion=name=sample-debug-logs,filter='severity=DEBUG AND sample(insertId, 0.9)'

Verify Log Exclusions and Cost Optimization (Tier R)

To verify that log exclusions are correct, list the details of the sink and check the exclusions to ensure your filter is present. For example, for the _Default sink:

gcloud logging sinks describe _Default --project={project_id}

References and Supporting Links

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs a command-line tool

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Published by

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google/skills · skills/cloud/cloud-logging-configuration-basics · commit 2194d3b

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2026-11-09

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