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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsUpgrade a Google Ads API integration in four controlled stages: inventory the versions and sunset dates, review compatibility, test in a separate account hierarchy, then roll out with change tracking and a recovery plan. A code rollback is only possible while the old API endpoint still exists; it cannot revive an endpoint after Google disables it, and it cannot automatically undo mutations already accepted in an account.
What a Google Ads API upgrade changes
Google distinguishes major releases from minor releases. A major release can introduce backward-incompatible changes and has its own endpoint. A minor release is backward-compatible and updates the corresponding major endpoint in place. That distinction determines whether you need endpoint changes, a new client-library release, or mainly a dependency update.
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Google states that a version is disabled on its sunset date and that all calls to its endpoint then fail. “Deprecated” therefore does not mean “already unavailable”: a deprecated endpoint normally continues to work until the published sunset date. Once sunset occurs, deploying the old application build will not restore service.
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The schedule is version-specific and can change. At the current schedule date of October 17, 2026, Google Ads API v25 is listed with an August 2027 sunset, while v22 has a tentative October 2026 sunset. Treat the month-level v22 date as an operational deadline that needs confirmation on Google’s current schedule before you set a final change freeze.
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Checklist at a glance
| Phase | Required action | Evidence to retain |
|---|---|---|
| Target and deadline | Inventory versions, methods, libraries, credentials, and customer targets; confirm the target version and exact sunset date. | Version-to-method map and approved migration window. |
| Compatibility | For a major release, update the endpoint and use a client library that supports it. Review upgrade guidance, release notes, and proto differences. | Completed breaking-change checklist and code owners’ sign-off. |
| Testing | Use a separate test manager/account hierarchy and test credentials. Exercise each method and request shape your integration uses. | Test results, expected-error cases, and known feature gaps. |
| Validation | Use read-only queries and validate_only=true where the method supports it. |
Validation responses and a list of methods that do not support validation. |
| Rollout | Deploy as a bounded change, verify authentication and responses, then widen according to risk controls. | Baseline snapshots, deployment record, and monitoring results. |
| Recovery | Keep the previous build and library deployable while its endpoint remains available; prepare corrective mutations for account state. | Pause criteria, recovery credentials, and reconciliation plan. |
1. Establish the target version and migration deadline
Inventory what the integration really calls
Start from production behavior rather than from a dependency file. Record every Google Ads API version currently called, the services and methods in use, client-library versions, credentials, and customer accounts or manager hierarchies targeted by each process. Include scheduled jobs, background workers, administrative scripts, and emergency tools; an overlooked worker can keep an old endpoint in production.
Google Cloud Console API metrics can help identify recent methods and versioned method names. Use those observations to check your source-code inventory. The result should be a table mapping each application component to its API version, method, account scope, credential, and owner.
Confirm sunset status before choosing a date
Check Google’s current version schedule immediately before approving the migration deadline. Record whether the source version is active, deprecated, or already sunset, and record the target release and its support window. Do not infer a deadline from a general release cadence: the schedule is version-specific and may contain tentative dates.
Leave time for all of the following before the source version sunsets:
- compatibility changes and code review;
- test-account execution and defect fixes;
- staging or canary deployment;
- production verification;
- a corrective deployment if the first release fails.
For example, v22’s listed October 2026 sunset is close to the current date, so an integration still using v22 should treat the work as urgent and verify the exact sunset day rather than waiting for a convenient release cycle. v25, released July 22, 2026, is listed with an August 2027 sunset, giving more planning room but not eliminating the need to migrate deliberately.
2. Review compatibility before changing code
Major-release review
For a major upgrade, change the endpoint used by the integration and select a client-library release that supports the target major version. Follow Google’s official upgrade guide for each version step between your current and target releases; skipping intermediate release notes can hide a change that affects your code even if the final library installs cleanly.
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Review these breaking-change categories explicitly:
- removed or renamed services, interfaces, fields, methods, and enum values;
- field-type changes and altered nullability or oneof behavior;
- resource-name or URL-format changes;
- different default output fields or response behavior;
- changed error reasons, validation rules, or retry-relevant status details.
Compare generated protos or typed models, not only handwritten wrapper code. Search serializers, deserializers, pagination helpers, query builders, logging filters, and alert rules for names that changed in the target version.
Concrete v25 compatibility work
Google Ads API v25 release notes dated July 22, 2026 describe a customer lifecycle goal schema change: lifecycle goal fields were changed into oneofs, and legacy lifecycle goal resources and settings were removed in favor of a unified schema. Code that assumes the old resources exist, or that writes multiple mutually exclusive fields without oneof handling, needs a targeted update and tests for both valid and invalid combinations.
Version 25.2 has release notes dated September 23, 2026. Treat that minor release as a separate dependency decision: it does not require changing the major endpoint, but newly added definitions may require an updated client library. Review its notes for additions that your integration intends to consume.
Minor-release review
A minor release is backward-compatible and does not require changing the endpoint path. You still need to update the client library if your code uses definitions introduced by that minor release. Regenerate or refresh types, compile all consumers, and run the same response-parsing tests used for a major upgrade.
3. Build a test environment that exposes real risks
Use test accounts and separate credentials
Google recommends test accounts for trying new API implementations or account configurations before production. Create a separate test manager/account hierarchy and use test credentials that cannot accidentally mutate production accounts. Test accounts cannot interact with production accounts, so verify that configuration files, secret references, and account IDs make the separation obvious.
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Test accounts are valuable but incomplete. They do not have serving data and cannot exercise certain features, including billing, conversion uploads, and bid simulations. Plan a controlled production check for any behavior that depends on those capabilities, using the least-privileged suitable credentials and explicit approval.
Construct a method-by-method matrix
For every service and method your application calls, include the request shape, expected response fields, resource-name handling, pagination or streaming behavior, retry logic, and expected errors. Include representative accounts and campaigns without copying production secrets into test fixtures.
| Test dimension | What to exercise | Why it matters |
|---|---|---|
| Read-only queries | Queries with empty, normal, and large result sets; pagination and streaming paths. | Detects schema, field, and resource-name changes without writing account state. |
| Mutate validation | Supported mutate requests with valid values, missing required fields, policy violations, and malformed resource names. | Checks request structure and field-level errors before committing a change. |
| Error handling | Authentication failures, permission errors, rate limits, transient failures, and partial-failure responses where applicable. | Verifies retries, alerting, and operator messages against the new error details. |
| Data-dependent features | Serving metrics, billing, conversion uploads, and bid simulations where the application relies on them. | These capabilities are not available in test accounts and need a controlled production check. |
Use validate_only correctly
For methods that support it, set validate_only=true to validate a request without executing the mutation. This is useful for checking field values, request structure, and policy errors while protecting account state. It is not an end-to-end test: a successful validation does not prove that production permissions, serving data, downstream parsing, or account-specific behavior will work.
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Support varies by method. Google Ads API GoogleAdsService.SearchStream does not support validate_only; check each method’s documentation before adding the flag. Keep a matrix column showing whether validation is supported, skipped, or replaced by a read-only test.
4. Roll out with observation and change tracking
Deploy a bounded first release
Package the new endpoint and compatible library as a deployment that can be stopped independently of unrelated application changes. Start with a small, known-safe set of operations or accounts. This is risk-control guidance rather than a Google-mandated percentage: choose the boundary your application can isolate and monitor.
- Verify that the deployed build authenticates with the intended developer token, customer IDs, and manager hierarchy.
- Run read-only operations and compare returned resource names, fields, counts, and parsing results with the pre-deployment baseline.
- Execute a narrowly scoped mutation only after read paths are healthy and approvals are recorded.
- Watch error rates, validation messages, missing fields, retries, latency, and account-state differences.
- Expand coverage in deliberate stages, recording the decision and evidence at each stage.
Capture a baseline and inspect writes
Before deployment, record important resource values and the expected operations for the first release. After deployment, use the Google Ads UI Change History or the API’s change_event and change_status resources to identify modifications and inspect old and new field values. This provides an audit trail for deciding whether a change came from the upgraded client or another actor.
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Review unversioned changes as well. Google notes that incompatible changes cannot always align with version boundaries; announcements appear on its API blog and are summarized on the sunset page. Subscribe to those notices as part of normal ownership, not only during a migration.
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Application rollback
Keep the previous application build and its compatible client library deployable during the migration window. Before relying on that fallback, confirm that its API endpoint has not reached sunset. If the endpoint is disabled, every call to it fails regardless of which binary you deploy.
Define a pause trigger before launch: for example, a sustained authentication failure, unexpected validation-error increase, response parsing failures, or an account-state discrepancy above an approved threshold. Identify the person who can stop the rollout, the deployment artifact to restore, and the credentials and endpoint used by the recovery build.
Remote account-state recovery
Reverting application code does not undo remote mutations already accepted by Google Ads. Use Change History or the change resources to identify the writes, determine the intended prior values, and issue carefully reviewed corrective mutations. Google provides tracking mechanisms, not an automatic universal rollback facility.
Understand mutation semantics before planning recovery. By default, a mutate request with partial_failure=false succeeds only if every operation in that request succeeds. Where the operation supports it, partial_failure=true can commit valid operations while returning errors for failed operations. That behavior is not interchangeable with an all-or-nothing transaction, so your recovery script must know which operations were actually applied.
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Reconcile after correction
After corrective mutations, read the affected resources again and compare them with the approved desired state. Record operation IDs, errors, old and new values, and the operator who approved the correction. Do not assume that restoring one field restores dependent settings or campaign behavior; inspect each affected resource and its relationships.
Common failure modes and fixes
“The old build still fails”
Check whether the old endpoint has reached its sunset date. If it has, code rollback cannot help; complete the upgrade or move traffic to an endpoint that is still supported.
“Validation passed, but production failed”
Confirm that the method supports validate_only, then check production permissions, account state, serving-data dependencies, and response parsing. Validation covers request validation for that method, not complete end-to-end execution.
“Only some operations changed”
Inspect whether the request used partial failure. Review the returned per-operation errors and Change History, then reconcile successful operations before sending any corrective request.
“A field disappeared after the upgrade”
Compare the target proto and release notes for removed fields, changed defaults, or oneof conversion. Update serializers and consumers together; do not silently substitute an empty value until you understand whether the field was removed or merely no longer returned by default.
“Test accounts cannot reproduce the issue”
Check whether the behavior depends on serving metrics, billing, conversion uploads, bid simulations, or another production-only capability. Reproduce the smallest safe case in production with approvals and monitoring rather than treating the test-account result as proof of equivalence.
Quick Recap
Final pre-sunset sign-off
- Every versioned method has an owner, target version, and test result.
- The target client library and endpoint are deployed in a non-production environment.
- Major-version breaking changes, including schema and enum changes, have code-review approval.
- Test-account limitations and required production checks are documented.
- Validation support is recorded per method, with read-only alternatives where needed.
- Baseline snapshots, Change History access, and monitoring alerts are ready.
- The previous build remains deployable only if its endpoint is still active.
- Pause criteria, corrective mutations, and post-correction reconciliation steps are assigned to named operators.
- The sunset date has been rechecked against Google’s current schedule immediately before the production window.
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