Cloud Logging Cross Project Configuration
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a structured approach to managing logs across multiple Google Cloud projects. It covers two primary architectures: Centralized Storage, which routes logs to a single bucket for unified analysis, and Read-Time Aggregation, which uses log scopes to query distributed logs. The skill includes specific procedures for creating log sinks, configuring log buckets, managing IAM permissions for cross-project access, and troubleshooting common routing failures.
What it does
- Sets up centralized log routing from multiple projects to a single log bucket.
- Configures read-time aggregation using log scopes for distributed querying.
- Creates and manages custom log views to partition or restrict access to log data.
- Provides commands to verify log routing and troubleshoot sink permission issues.
- Adheres to strict safety tiers for read-only, mutation, and security-sensitive operations.
- Includes mandatory usage attribution for all executed gcloud commands.
When to use it
- When you need to aggregate logs from multiple projects, folders, or organizations into one central location.
- When you require unified SQL-based log analytics across a large-scale GCP environment.
- When you need to query logs stored in different projects without moving them.
- When troubleshooting why logs are not appearing in a central destination bucket.
Advantages
- Enables centralized management and auditing of logs across thousands of projects.
- Supports advanced SQL analytics via Log Analytics on centralized buckets.
- Allows for granular access control using custom log views.
- Provides a cost-effective alternative for smaller environments via read-time aggregation.
- Includes clear safety protocols to prevent accidental data loss or security misconfigurations.
Usage examples
- “Set up a central log bucket in project central-logs-123 in the us-central1 region.”
- The agent will execute the gcloud logging buckets create command with the specified parameters and enable analytics.
- “How do I troubleshoot why logs from source-project-abc are not reaching my central bucket?”
- The agent will guide you through verifying the sink filter and checking the writer identity permissions on the central project.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/google/cloud-logging-cross-project-configuration/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip cloud-logging-cross-project-configuration.zip -d .agents/skills
Documentation by Google
Configuring Cross-Project Logging
This skill describes how to use gcloud commands to configure Cloud Logging so
that you store log data in a central location, regardless of the point of
origin. The skill also describes how to query log data when that data is stored
in multiple projects.
[!IMPORTANT] Sandbox Network Limitation (CRITICAL for Agent Testing): During evaluation or in restricted sandboxed environments, network traffic to GCP 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},{source_project_id},{central_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-cross-project-configuration)"
and append agent-skills/1.0 (skill:cloud-logging-cross-project-configuration) 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 readgcloud 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 creategcloud logging views updategcloud logging scopes creategcloud 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 creategcloud logging links creategcloud 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 deletegcloud 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.
Decision Matrix: Centralized Storage vs. Distributed Storage with Read-Time Aggregation
Use this decision matrix to evaluate and choose between Centralized Storage and Read-Time Aggregation. With centralized storage, log data is routed to one log bucket, regardless of where the data originates. You write queries against the centralized log bucket. With read-time aggregation, log data is stored by the resource where it originates. However, a single query aggregates the data by querying all resources.
After you have determined the optimal architecture for handling cross-project logs, follow the corresponding configuration steps detailed below.
| Criterion | Centralized Storage | Read-Time Aggregation |
|---|---|---|
| GCP Project Scale | Scales to thousands of | Best for < 375 projects. |
| : : projects. : : | ||
| Log Storage | Consolidated in a single | Resides in originating |
| : : log bucket. : resources. : | ||
| SQL Analytics | Easy; unified querying | Hard; requires querying |
| : : via Observability : multiple log buckets. : | ||
| : : Analytics. : : | ||
| Access Control | Scoped access via log | Requires IAM access to |
| : : views on the centralized : all views on resources : | ||
| : : log bucket. : that store log data. : | ||
| Configuration | Options vary based on | Will not interfere with |
| : Complexity : Project, Folder, : bucket-based log-based : | ||
| : : Organization structure. : metrics. : | ||
| Cost | Potential for duplicate | Cost-effective; no data |
| : : storage of log buckets : replication. : | ||
| : : if exclusions aren't : : | ||
| : : set. : : |
Architecture
Centralized Storage (Log Routing)
graph LR
subgraph "Source Project(s)"
Log[Resource Logs] --> Sink["Sink: route-to-central-project"]
end
subgraph "Central Project"
Sink --> Bucket["Bucket: central-logs-bucket (us-central1)"]
endRead-Time Aggregation (Log Scopes)
graph LR
subgraph "Source Project 1"
Log1[Resource Logs] --> Bucket1["Bucket: _Default"]
end
subgraph "Source Project 2"
Log2[Resource Logs] --> Bucket2["Bucket: _Default"]
end
subgraph "Scoping Project (No Log Storage)"
Scope["Log scope: central-query-scope"]
Scope -.-> View1["_AllLogs View on Bucket1"]
Scope -.-> View2["_AllLogs View on Bucket2"]
endSetup Steps: Centralized Storage (Log Routing)
Use these steps to route logs from one or more source projects to a central log bucket in a project. Create or select the Google Cloud project that you will use for storing your log data. This is the central project.
1. Create log bucket in central project (Tier M)
Create a custom log bucket with Log Analytics enabled.
[Tip] Use regional log buckets, for example, set the location to
us-central1. Don't use thegloballocation. This approach ensures compatibility with Observability Analytics and SQL querying.
gcloud logging buckets create {bucket_id} \
--project={central_project_id} \
--location={region} \
--retention-days={retention_days} \
--enable-analytics2. Create log sink in central project (Tier M)
Create a project-level sink in the central project pointing to the central log bucket. This sink routes logs that land in the central project's Log Router into the central log bucket.
Assuming the newly created bucket is specifically for centralizing data from
other projects (and the central project is not one of the source projects), the
central sink should exclude the central project's own logs. Include the
_Required audit log exclusions on this central sink to avoid redundancy
between {bucket_id} and the _Required bucket.
gcloud logging sinks create {sink_name} \
logging.googleapis.com/projects/{central_project_id}/locations/{region}/buckets/{bucket_id} \
--project={central_project_id} \
--exclusion=filter='logName:"projects/{central_project_id}/"' \
--exclusion=filter='LOG_ID("cloudaudit.googleapis.com/activity")' \
--exclusion=filter='LOG_ID("externalaudit.googleapis.com/activity")' \
--exclusion=filter='LOG_ID("cloudaudit.googleapis.com/system_event")' \
--exclusion=filter='LOG_ID("externalaudit.googleapis.com/system_event")' \
--exclusion=filter='LOG_ID("cloudaudit.googleapis.com/access_transparency")' \
--exclusion=filter='LOG_ID("externalaudit.googleapis.com/access_transparency")'3. Create log sink in source resource (Tier M)
To route logs to the central project, you must create a log sink in each source
organization, folder, or project. While you can configure a sink to route only a
subset of logs using the --log-filter argument, recommended practice is to
route all non-audit logs, and then restrict access or partition logs at the
destination using custom Log Views on the centralized log bucket.
For an organization-level log sink
gcloud logging sinks create {sink_name} \ logging.googleapis.com/projects/{central_project_id} \ --organization={source_organization_id} \ --include-children \ --exclusion=filter='LOG_ID("cloudaudit.googleapis.com/activity")' \ --exclusion=filter='LOG_ID("externalaudit.googleapis.com/activity")' \ --exclusion=filter='LOG_ID("cloudaudit.googleapis.com/system_event")' \ --exclusion=filter='LOG_ID("externalaudit.googleapis.com/system_event")' \ --exclusion=filter='LOG_ID("cloudaudit.googleapis.com/access_transparency")' \ --exclusion=filter='LOG_ID("externalaudit.googleapis.com/access_transparency")'For project-level log sinks
gcloud logging sinks create {sink_name} \ logging.googleapis.com/projects/{central_project_id} \ --project={source_project_id} \ --exclusion=filter='LOG_ID("cloudaudit.googleapis.com/activity")' \ --exclusion=filter='LOG_ID("externalaudit.googleapis.com/activity")' \ --exclusion=filter='LOG_ID("cloudaudit.googleapis.com/system_event")' \ --exclusion=filter='LOG_ID("externalaudit.googleapis.com/system_event")' \ --exclusion=filter='LOG_ID("cloudaudit.googleapis.com/access_transparency")' \ --exclusion=filter='LOG_ID("externalaudit.googleapis.com/access_transparency")'
4. Grant IAM permissions to sink writers (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 allow the source sinks to route logs to the central project's router, and to allow the central sink to write logs to the central bucket:
Grant Logs Writer permission to the source sink: Retrieve the
writerIdentityof the source log sink and grant itroles/logging.logWriteron the central project.# Get the writer identity of the source sink gcloud logging sinks describe {sink_name} \ --project={source_project_id} \ --format="value(writerIdentity)"The output is the
{source_writer_identity}value (for exampleserviceAccount:...) for the following command:# Grant Logs Writer permissions on the central project gcloud projects add-iam-policy-binding {central_project_id} \ --member={source_writer_identity} \ --role=roles/logging.logWriterGrant Bucket Writer permission to the central sink: Retrieve the
writerIdentityof the central log sink and grant itroles/logging.bucketWriteron the central project.# Get the writer identity of the central sink gcloud logging sinks describe {central_sink_name} \ --project={central_project_id} \ --format="value(writerIdentity)"The output is the
{central_writer_identity}value for the following command:# Grant Bucket Writer permissions on the central project gcloud projects add-iam-policy-binding {central_project_id} \ --member={central_writer_identity} \ --role=roles/logging.bucketWriter
5. Create custom Log Views on the central bucket (Tier M)
To partition logs or restrict access by log ID or project (since all logs were routed to the same central bucket), create custom Log Views on the central bucket.
Filter by log ID:
gcloud logging views create {view_id} \ --bucket={bucket_id} \ --location={region} \ --project={central_project_id} \ --log-filter='LOG_ID("{log_id}")'Filter by source project:
gcloud logging views create {view_id} \ --bucket={bucket_id} \ --location={region} \ --project={central_project_id} \ --log-filter='project_id="{source_project_id}"'
Verify Centralized Log Routing (Tier R)
To verify that logs are being routed from the source projects to the central regional log bucket:
Write a test log in the source project:
gcloud logging write {test_log_id} "Test log entry for verification" \ --severity=WARNING \ --project={source_project_id}Read the test log from the central log bucket: For regional log buckets, you must specify the
--viewflag. Because the default view_Defaultonly contains logs matching the default filter, you should query the_AllLogsview or your custom log view on the central bucket:gcloud logging read 'logName:"projects/{source_project_id}/logs/{test_log_id}"' \ --bucket={bucket_id} \ --location={region} \ --view=_AllLogs \ --project={central_project_id}
Setup Steps: Read-Time Aggregation (Log Scopes)
Create or select a Google Cloud project that you will use for querying your log data. This is the scoping project. Use these steps to configure a log scope. Log scopes let you issue a query for log data that is stored in multiple projects.
1. Create a custom Log View (Optional but recommended) (Tier M)
Create a Log View in the source project to restrict which logs are accessible.
[!IMPORTANT] Gotcha: Log View filters can only contain specific restrictions. Refer to https://docs.cloud.google.com/logging/docs/logs-views.md.txt#view-filter
gcloud logging views create {view_id} \
--bucket={bucket_id} \
--location={region} \
--project={source_project_id} \
--log-filter='LOG_ID("{log_id}")'{bucket_id}: for example,_Default{region}: for example,global{view_id}: for example,app-logs-viewIf you want to allow access to all logs in the log bucket, omit the
--log-filterflag.
2. Create a log scope in the scoping project (Tier M)
Create a log scope in the scoping project listing the source resources, which may be projects or specific log views.
gcloud logging scopes create {log_scope_id} \
--project={scoping_project_id} \
--resource-names={resource_names}{log_scope_id}: for example,central-query-scope{resource_names}: Comma-separated list of log views. For example,projects/source-project-1/locations/global/buckets/_Default/views/app-logs-view,projects/source-project-2/locations/global/buckets/_Default/views/app-logs-view. You can include up to 100 views in the scope.
3. Update Default Observability Scope (Optional) (Tier M)
Link the log scope to the project's default observability scope so it is used by default in Logs Explorer.
gcloud observability scopes update _Default \
--project={scoping_project_id} \
--location=global \
--log-scope=//logging.googleapis.com/projects/{scoping_project_id}/locations/global/logScopes/{log_scope_id}4. Grant IAM permissions to users (Tier B)
Unlike centralized routing, permissions are checked at query time on all source projects. Users running queries must have:
roles/logging.viewAccessorgranted on the specific Log View (with IAM conditions) orroles/logging.vieweron the source projects.Access to the scoping project.
Troubleshooting Cross-Project Log Routing and Sink Permission Failures
If logs are not appearing in a central project's bucket after configuring centralized logging:
1. Verify Log Router Sink Filters in Source Resource
Ensure that the log sink's filter matches the logs you expect to route.
[!IMPORTANT] Gotcha: Standard filter expressions like
logName:abcorlogName="projects/{project_id}/logs/abc"can fail to match in log sinks. Always useLOG_ID("abc")for precise matching in log sink filters.Verify that you have not configured an exclusion filter that accidentally discards these logs.
2. Verify and Grant Writer Identity Permissions (Most Common Cause)
The log sink's writer identity service account in the source project must be explicitly granted the necessary permissions on the central resource.
Step A: Get the Writer Identity
gcloud logging sinks describe {sink_name} \ --project={source_project_id} \ --format="value(writerIdentity)"Step B: Grant the Permission in the Central Project (Tier B)
[!IMPORTANT] Security Action (Tier B): Granting IAM permissions changes access control policy and must be explicitly confirmed by the user before execution.
For Cloud Logging Buckets (standard): Grant
roles/logging.bucketWriter:gcloud projects add-iam-policy-binding {central_project_id} \ --member={writer_identity} \ --role=roles/logging.bucketWriterFor GCS Buckets: Grant
roles/storage.objectCreatoron the GCS bucket.For Pub/Sub Topics: Grant
roles/pubsub.publisheron the Pub/Sub topic.For BigQuery Datasets: Grant
roles/bigquery.dataEditoron the BigQuery dataset.
References and Supporting Links
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