Interconnect monitoring Cloud Monitoring uptime metrics
| Service | Google Cloud Interconnect |
|---|---|
| Cloud | Google Cloud (GCP) |
| Guide type | Procedure |
| Skill level | Intermediate to advanced |
| Time | 15 - 60 minutes depending on account size |
Running into Interconnect monitoring Cloud Monitoring uptime metrics on Google Cloud Interconnect is one of the more searched issues on Google Cloud Community and StackOverflow in the last 12 months. Here is what actually moves the needle when the Google Cloud docs are too generic.
What interconnect monitoring cloud monitoring uptime metrics actually involves on Google Cloud Interconnect
This task on Cloud Interconnect is one of the more searched operational topics on AWS in the last 12 months. The procedure below is the path that works in a current AWS account with default IAM and standard VPC config.
The rest of this page is the structured fix path. Start with diagnose, then remediation, then the automation options so you do not have to do this by hand the next time it surfaces. Verify and safety sections at the end are the discipline that keeps the fix from regressing in production.
Diagnose first, fix second
Run gcloud auth list and gcloud config list first. About one in five 'why does this not work' tickets are actually 'I am in the wrong account' or 'my session expired and the SDK is using stale credentials or ADC pointed at the wrong project'. The 5-second sanity check costs nothing and saves real time when the answer is that simple.
Check the Google Cloud Service Health at status.cloud.google.com and the per-product status board for ongoing service events in your region. About one in ten user-reported outages turn out to be region-scoped Google Cloud service degradation already being tracked. Cloud Service Health also exposes an API and Eventarc events, so you can wire a Lambda hook that pages on-call only when the failure correlates with an active Cloud Service Health event in the same region and service.
Check Cloud Monitoring Logs for the calling service. Lambda, ECS, EKS, Step Functions, API Gateway, and most managed services write detailed traces to Cloud Monitoring Logs under predictable log group names. Use Cloud Monitoring Logs Insights with fields @timestamp, @message | filter @message like /ERROR/ | sort @timestamp desc | limit 50 to surface the most recent failures.
Solution-focused remediation path
If quotas are suspect, the Quotas page in Cloud Console (IAM & Admin > Quotas) console shows current usage and the active limit side by side. Request increases through Quotas page in Cloud Console (IAM & Admin > Quotas), not through Support tickets - quota dashboard requests usually approve faster (often within minutes for soft limits) and they are auditable in Cloud Audit Logs. Set up Quotas page in Cloud Console (IAM & Admin > Quotas) + Cloud Monitoring alert policys at 80 percent usage so you get notified before you hit the wall.
If you cannot reproduce the failure consistently, the cause is probably a race condition or a session-cache issue. Run the call with --profile set to a fresh STS session, in a different region you control, with a single concurrent request. If it works there but fails in your normal setup, the difference is the bug.
When the fix involves a destructive operation (delete VPC endpoint, swap Cloud KMS key, rotate root credential), do it during a maintenance window with at least one teammate watching. Several Google Cloud Interconnect operations have implicit dependencies that only show up when traffic starts flowing again. Document the rollback path before you start, not during the incident.
Automate this fix so you do not do it twice
Automate the fix with Python and boto3
For anything you do more than twice, write a small Python script. The boto3 pattern below uses paginators (so it does not blow up on accounts with thousands of resources), explicit region binding, and a dry-run flag that defaults to True. Keep the script under 100 lines; if it grows beyond that, you are building a tool and should put it behind a Lambda with proper logging.
import boto3, sys
DRY_RUN = '--apply' not in sys.argv
client = boto3.client('google', region_name='us-east-1')
paginator = client.get_paginator('describe_...')
for page in paginator.paginate(): for item in page.get('Items', []): if item.get('Status') == 'FAILED': if DRY_RUN: print(f'[dry-run] would fix {item["Id"]}') else: client.modify_...(ResourceId=item['Id']) print(f'fixed {item["Id"]}')Wire the fix into Eventarc for self-healing
If the failure mode is recurring, automate the remediation instead of the diagnosis. Eventarc Scheduler or rules that watch Cloud Logging events for the specific error code can invoke a Lambda that runs the same fix you would run by hand. The Lambda must be idempotent (re-running it on already-healthy resources must be a no-op) and must emit a Cloud Monitoring metric so you can track how often the auto-fix fires. A spike in auto-fix invocations is itself a signal worth alerting on.
# Eventarc rule pattern (JSON)
{ "source": ["aws.google"], "detail-type": ["Google Cloud API Call via Cloud Audit Logs"], "detail": { "errorCode": ["AccessDenied", "ThrottlingException"] }
}Add a Workflows or Cloud Tasks Automation runbook
For multi-step fixes that include a manual approval, use Workflows runbook. Document the fix as a runbook with workflows.executions.approve steps where a human signs off and workflows.steps.callApi steps where the runbook calls the Google Cloud API. Approvers are notified by SNS; the runbook execution shows up in Cloud Audit Logs with the approver's identity attached. This makes audit trails easy and stops production fixes from being one-person operations.
Common pitfalls and what to watch for
The pitfall most teams hit on Google Cloud Interconnect is moving too fast and skipping the read-only validation step. Before any write, list the current state and save it. Google Cloud APIs are eventually consistent for many resource types, so the validation snapshot is your only reliable reference if you need to undo. Save the output of the describe call to S3, not to your laptop.
Second pitfall: confusing IAM permission errors with networking errors. AccessDenied can be IAM (policy missing), networking (VPC endpoint policy blocking the call), or KMS (key policy missing). The error string looks identical for all three. Distinguish by looking at the Cloud Audit Log event's errorCode and the encoded authorization message; do not assume IAM is the culprit just because the message says AccessDenied.
Verify the fix worked
- Reproduce the original symptom path. If it still surfaces in any account or region or IAM role or service account, you have not fixed it.
- Watch for 24 to 48 hours. Cloud Monitoring metrics and Cloud Asset Inventory can mask issues with cached health for 6 to 12 hours, especially Cloud CDN and Cloud DNS.
- Run a smoke test under realistic load. Happy-path tests miss race conditions and IAM session-cache issues.
- Capture the new state in a runbook so the next person on call does not have to rediscover this. Push it to Confluence or your team wiki, not into Slack.
- If the fix involved a permission change, run IAM Access Analyzer one more time to confirm you did not open a separate hole while closing this one.
Safety, rollback, blast radius
- Test in a non-production account if your environment has Resource Manager and Organization Policy or Cloud Resource Manager (organizations, folders, projects). The cost of one sandbox account is cheaper than one rollback meeting.
- Export the existing config before changing it. Most Google Cloud Interconnect resources support describe + export to JSON via CLI - capture that to source control before you start.
- Know your rollback path. Some Google Cloud Interconnect operations are one-way (region migration, account-level feature opt-in, Cloud KMS key deletion past pending window). Confirm reversibility on the Google Cloud doc before you commit.
- Be aware of cross-service impact. IAM role or service account changes ripple to every service trusting that role. Cloud KMS key changes break every workload depending on that key. VPC endpoint changes affect every VPC consumer of that endpoint.
- Maintenance window discipline: if the change touches DNS, certificate rotation, or anything that emits TLS handshakes, line up a window with stakeholder notification, not a heroic mid-day swap.
FAQ
gcloud google describe-... first, then commit it before you change anything. A few operations are one-way (Cloud KMS key deletion past the pending window, region migration, account closure). Check the Google Cloud doc for the specific API before you commit.aws CLI or SDK calls - those almost always still work.References
- docs.cloud.google.com - official documentation for Google Cloud Interconnect
- Google Cloud Community - community Q&A with Google-staff-verified answers
- Cloud Service Health Dashboard at health.cloud.google.com
- Quotas page in Cloud Console (IAM & Admin > Quotas) and Architecture Framework checklists
Related fixes
Related guides worth a look while you sort this one out:
- 408 Request timeout uptime firewall port service down
- Cost GBs ingested plus custom metrics over free tier
- Synthetic monitor cost vs uptime check cost
- Uptime check alert not firing default needs 2 regions failing
- Uptime check from private endpoints PSC
- How to monitor a BMS server with Cloud Monitoring