Cloud Logging API

Name: Cloud Logging API API
Brand: Cloud Logging API
Availability: InStock

✓ Official Vendor SpecDeveloper ToolsMonitoring Observabilityoauth247 EndpointsREST

For Agents

Write log entries from agent runs, query historical logs with advanced filters, and configure sinks that export logs to BigQuery, Pub/Sub, or Cloud Storage for downstream analysis.

Quickstart

Get started with Cloud Logging API in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"write a structured log entry to google cloud logging"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with Cloud Logging API API.

Write structured log entries with severity, resource labels, and trace correlation via entries:write

Query historical log entries across projects and folders with advanced filters via entries:list

Tail live log streams in real time for incident response via entries:tail

Create and manage log-based metrics that count or distribute log content for Cloud Monitoring

GET STARTED

Start building with Cloud Logging API API

Explore with Jentic

View OpenAPI Document

Use for: Write a structured log entry from my agent run with trace and severity, Search for ERROR-level log entries from the last hour in my project, Tail live logs for a Cloud Run service while I reproduce a bug, Create a log-based metric that counts authentication failures

Not supported: Does not handle metric storage, distributed traces, or alert policy management — use for log entry write, query, routing, and retention only.

Cloud Logging is Google Cloud's centralised log management service for writing, storing, searching, and routing log entries from applications, virtual machines, containers, and Google Cloud services. It supports structured and unstructured logs, log-based metrics, exclusion filters, and sinks that route entries to BigQuery, Pub/Sub, or Cloud Storage. Log Buckets and views provide retention control and tenant-level access, while CMEK settings let teams bring their own encryption keys for compliance workloads.

Use Cases

Patterns agents use Cloud Logging API API for, with concrete tasks.

★ Centralised application logging

Write structured log entries from application code, Cloud Run services, GKE workloads, and Compute Engine VMs into a single Cloud Logging project so engineers can search across the entire stack from one console. Severity, resource labels, and trace IDs make it possible to correlate a request as it flows through multiple services. Setup is typically under a day for a single project.

Call entries:write with a structured payload containing severity ERROR, jsonPayload with the exception details, and the trace ID extracted from the incoming request

Log-based metrics and alerting

Convert log content into Cloud Monitoring time series by defining log-based metrics that count matching entries or extract numeric values. Pair these metrics with alerting policies in Cloud Monitoring to page on-call when authentication failures spike or specific error patterns appear. Useful when you need observability signals that only exist in log content.

Create a log-based counter metric named auth_failures with a filter selecting severity=ERROR and jsonPayload.event=login_failed scoped to the auth service

Compliance log retention and routing

Use log buckets, views, and sinks to route audit and security logs into long-term storage in BigQuery for analysis or Cloud Storage for archive while keeping operational logs at shorter retention. CMEK settings allow regulated workloads to encrypt log data with customer-managed keys. Typical compliance-grade configuration takes 1-2 days including IAM scoping.

Create a sink named audit-archive routing logName matching cloudaudit.googleapis.com to a Cloud Storage bucket with 7-year retention

Agent integration via Jentic

AI agents that orchestrate Google Cloud workflows often need to record execution context, query past runs for context, or watch logs while executing remediation steps. Through Jentic the agent can write entries, list past entries by filter, or tail a live stream without holding the underlying OAuth token in its prompt.

Call entries:list with filter resource.type=cloud_run_revision AND severity>=WARNING for the last 30 minutes and summarise the top 3 error patterns

Key Endpoints

47 endpoints — cloud logging is google cloud's centralised log management service for writing, storing, searching, and routing log entries from applications, virtual machines, containers, and google cloud services.

METHOD

PATH

DESCRIPTION

POST

/v2/entries:write

Write structured log entries

POST

/v2/entries:list

Query log entries with advanced filters

POST

/v2/entries:tail

Tail a live stream of log entries

POST

/v2/entries:copy

Copy log entries between buckets

GET

/v2/monitoredResourceDescriptors

List monitored resource descriptors

GET

/v2/{+name}/cmekSettings

Read CMEK encryption settings

GET

/v2/{+name}/locations

List supported logging locations

POST

/v2/entries:write

Write structured log entries

POST

/v2/entries:list

Query log entries with advanced filters

POST

/v2/entries:tail

Tail a live stream of log entries

POST

/v2/entries:copy

Copy log entries between buckets

GET

/v2/monitoredResourceDescriptors

List monitored resource descriptors

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Google Cloud OAuth 2.0 client credentials and refresh tokens are stored encrypted in the Jentic vault. Agents receive scoped, short-lived bearer tokens for each call; the refresh token and client secret never enter the agent's context.

Intent-based discovery

Agents search by intent such as write a log entry or query gcp logs and Jentic returns the matching Cloud Logging operations with their input schemas, so the agent calls the correct endpoint without browsing Google Cloud's discovery documents.

Time to first call

Direct integration with Cloud Logging takes 1-2 days for OAuth setup, scope configuration, and structured payload formatting. Through Jentic the same flow is under an hour: search, load schema, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

Cloud Monitoring API

Time-series metrics, dashboards, and alerting that consume log-based metrics produced from Cloud Logging

Choose Cloud Monitoring when the agent needs to read or write metrics, manage alert policies, or query time-series data; use Cloud Logging when working with raw log entries

Complementary

Error Reporting API

Aggregates and groups production exception data extracted from Cloud Logging entries

Use Error Reporting when the agent specifically needs grouped error events with stack traces; use Cloud Logging for raw log search

Complementary

Cloud Trace API

Distributed trace data that pairs with log entries via shared trace IDs

Choose Cloud Trace when the agent needs span and latency analysis; use Cloud Logging when correlating logs to those traces

Complementary

BigQuery API

Destination warehouse for log sinks routing audit and application logs into SQL-queryable tables

Use BigQuery once logs have been routed via a sink and the agent needs SQL analytics over the exported entries

FAQs

Specific to using Cloud Logging API API through Jentic.

What authentication does the Cloud Logging API use?

Cloud Logging uses Google OAuth 2.0 with scopes including https://www.googleapis.com/auth/logging.write for writing entries and https://www.googleapis.com/auth/logging.read for queries. Through Jentic the OAuth token is held in the encrypted vault and the agent receives only a scoped session, so the raw refresh token never enters the agent's context.

Can I tail live log entries through the Cloud Logging API?

Yes, the entries:tail endpoint streams log entries in real time as they arrive, which is useful for following a deployment or reproducing a bug. It accepts the same filter language as entries:list, so you can scope the stream to a specific service or severity.

What are the rate limits for the Cloud Logging API?

Read requests (entries:list, entries:tail) and write requests (entries:write) have separate per-project quotas published in Google Cloud's Logging quotas documentation, typically several hundred to a few thousand requests per minute. Enable batched writes and exponential backoff on 429 responses to stay under the limits.

How do I write a structured log entry through Jentic?

Search Jentic for write a log entry to cloud logging, load the entries:write operation, and execute it with a payload containing logName, resource, severity, and jsonPayload. Jentic handles the OAuth bearer token automatically so the agent only constructs the entry body.

Is the Cloud Logging API free?

Cloud Logging includes 50 GiB of free log ingestion per project per month, with usage above that billed per GiB. Querying logs via entries:list is free; long-term retention beyond the default 30 days incurs storage charges.

Can I export logs to BigQuery automatically?

Yes, create a sink with a BigQuery dataset destination and a filter expression. All matching entries are streamed into partitioned tables in the dataset, where you can query them with SQL alongside other Cloud data.