Storage Intelligence

Storage Intelligence is a subscription for analyzing and acting on Cloud Storage data at scale.

• Analysis features: Storage Insights datasets, data insights with Gemini Cloud Assist, inventory reports.
• Action features: storage batch operations, bucket relocation.

Use it for organization-wide visibility (cost, security, governance) and for operations too large to script (billions of objects, whole-bucket moves).

[!NOTE]

Datasets, batch operations, and bucket relocation require the subscription. Inventory reports work without it (the subscription covers their scan fees). Gemini Cloud Assist answers general GCS questions without it, but prompts about your buckets need a subscription plus a dataset.

Choosing the Right Feature

1. Configuration

Configure on a project, folder, or organization. Children inherit the configuration, and you can override it at lower levels. Each resource has one edition configuration: INHERIT (default when unset), STANDARD (all features, set by enable), DISABLED, or TRIAL. Bucket filters scope by location or name regex. Requires roles/storage.admin (storage.intelligenceConfigs.update). See Configure and manage Storage Intelligence.

# Exactly one of --project, --sub-folder, --organization:
gcloud storage intelligence-configs enable --project=my-project

# Org-wide with filters:
gcloud storage intelligence-configs enable --organization=123456789 \
    --exclude-bucket-id-regexes="colddata.*" --include-locations=us-east1

gcloud storage intelligence-configs describe --project=my-project
gcloud storage intelligence-configs disable  --project=my-project

# update takes exactly one settings flag:
gcloud storage intelligence-configs update --project=my-project \
    --include-locations=us-east1

30-day trial: enables all STANDARD features and waives the object management fee (other charges, e.g. BigQuery, still apply). Eligible once per org/folder/project. Auto-converts to paid STANDARD after 30 days, so disable within the window to avoid charges. Datasets created during the trial persist (and keep billing BigQuery storage) until deleted.

2. Storage Insights Datasets

A queryable index of metadata and activity for buckets/objects in scope, delivered as a BigQuery linked dataset: metadata snapshots (projects, buckets, objects), activity views (mutations, errors, bucket/project/regional activity), and processing events/errors. See Configure datasets.

Key properties and limits:

• Scope: one org, or up to 10,000 projects/folders, with bucket name-regex and location filters. --auto-add-new-buckets covers future buckets.
• Retention: a rolling window of up to 90 days for metadata. Activity data can be set separately, up to 365 days (0 excludes it).
• Locations: BigQuery locations EU, US, asia-south1, asia-south2, asia-southeast1, europe-west1, us-central1, us-east1, us-east4 only.
• Freshness: the initial load takes 24–48h, activity data lands in ~4h, and metadata snapshots refresh every 24h.

gcloud storage insights dataset-configs create my_dataset \
    --location=us-central1 --organization=123456789 \
    --retention-period-days=30 --source-projects=987654321,123123123

# Must link to BigQuery before querying:
gcloud storage insights dataset-configs create-link my_dataset --location=us-central1

After creation, grant the Storage Insights service agent (service-PROJECT_NUMBER@gcp-sa-storageinsights.iam.gserviceaccount.com) the required permissions. Without them, no data flows. Service agents can be per-config (default) or per-project (--identity=IDENTITY_TYPE_PER_PROJECT).

Use cases:

• Estate analysis: find duplicates, temp data, and data in unexpected regions, or extract prefix lists to feed batch operations.
• Activity: identify inactive buckets and map the hottest projects/prefixes. The regional activity view (request/response bytes per region) informs bucket relocation decisions.
• Security: object securityInsights computes public access status (evaluates PAP, UBLA, ACLs, IAM, org policies, and shows where the grant originates). Audit encryption (encryptionType) and retention (retentionExpirationTime, softDeletePolicy).
• Troubleshooting: object_events_view records errored operations with reasons (e.g., find buckets with high 429 rates).
• Content analysis: join metadata to object data via BigQuery ObjectRef functions (ref column).

Dashboards: connect the linked dataset to Looker Studio, or start from the dashboard template. Dashboard queries consume BigQuery compute, so evaluate on a small dataset first.

Limitations: public access status skips objects in managed folders and ignores VPC-SC and IP filtering. CRC32C/MD5 checksums are missing for CMEK objects, and renaming an HNS folder makes its objects reappear as new entries.

3. Data Insights with Gemini Cloud Assist (Preview)

With a linked dataset, the Cloud Assist panel on the console's Storage Insights page answers natural-language prompts about your metadata and returns the underlying SQL. Examples: "5 largest buckets without Autoclass enabled", "objects with a retention expiration date within the next 30 days", "buckets with a high volume of small files". Including "Cloud Storage" in the prompt improves quality.

Setup: enable Gemini Cloud Assist and Storage Intelligence, create and link a dataset, grant the service agent roles/bigquery.dataViewer, and give users roles/bigquery.jobUser, roles/bigquery.dataViewer, roles/storageinsights.viewer.

Quotas and limits:

• Prompts needing ≥ 800 GB of processing return SQL only, for you to run yourself. Processing is capped at 50 TiB/month/org.
• Returns at most the top 5 matching resources per prompt.
• Reads only the latest snapshot, so no time-series ("how much did my bucket grow"). Cost data, activity data ("last access time"), and some configs (e.g., soft delete) aren't in the dataset at all.
• Still in Preview, so validate responses before acting.

4. Inventory Reports

Scheduled per-bucket object listings (CSV or Apache Parquet) written to a destination bucket, as a faster alternative to paginated Objects: list. The report config lives on the source bucket (max 100 per bucket) and defines the frequency (daily/weekly), the metadata fields (always project, bucket, and name, plus optional fields like size, timeCreated, updated, storageClass, etag, checksums, generation, contentType, and retentionExpirationTime), and the destination bucket (same project and location as the source, or the source bucket itself). Reports over 1M objects are sharded, with a *_manifest.json written when all shards are complete.

Use for: quick single-bucket analysis, transfer validation, per-bucket audits. Use datasets instead for: multi-bucket/org-wide analysis, trends, activity data.

[!NOTE]

Delivery is best-effort, so reports may skip days or miss objects. For complete daily coverage, use datasets instead. Not compatible with bucket IP filtering, and unavailable in a few locations (e.g., me-central1, me-central2, dual-regions eur5/eur7/eur8).

5. Storage Batch Operations

Serverless jobs that run one transformation across objects in one bucket, scaling to ~1B objects in ~3 hours with concurrent jobs. Jobs are LROs with progress tracking and automatic retries.

Job types:

• delete
• metadata update: custom metadata, or fixed fields like Content-Type, Cache-Control, Custom-Time, and retention config
• object hold set/release
• object rewrite: CMEK key or storage class
• object context updates

Objects are selected either by a manifest (a CSV in GCS with the header bucket,name,generation, where generation is optional and rows for other buckets are ignored) or by up to 1,000 object prefixes (an empty list means the whole bucket). A common pattern is to query a dataset to generate the manifest.

# Bulk metadata update from a manifest:
gcloud storage batch-operations jobs create my-job \
    --bucket=my-bucket \
    --manifest-location=gs://my-bucket/manifest.csv \
    --put-metadata=Content-Language=en

# Always dry-run large deletes first (counts affected objects, no changes):
gcloud storage batch-operations jobs create my-dry-run \
    --bucket=my-bucket --included-object-prefixes=tmp/,staging/ \
    --delete-object --dry-run

gcloud storage batch-operations jobs describe my-job   # also: cancel, delete

[!CAUTION]

Batch deletes are recoverable only via soft delete (7-day default). If soft delete is disabled on the bucket, deleted objects are unrecoverable.

Limits: jobs auto-cancel after 14 days, at most 1,000 prefixes per job, at most ~20 concurrent jobs per bucket recommended, and Requester Pays buckets are unsupported. Pricing adds no fee beyond the subscription, but normal per-operation charges apply: transformations are Class A (skipped if the object is already in the desired state), deletes are free, and listing during jobs and dry runs is Class A.

6. Bucket Relocation

Moves a bucket to a different location without renaming it or manual data copying, preserving object metadata and storage classes, including Autoclass (legacy classes convert to Standard). Reads stay available throughout. Typical drivers: cut inter-region transfer costs, colocate with compute, or move from a region to a dual/multi-region for resilience (use the dataset regional activity view to find candidates).

Two types, determined by source/destination locations:

• With write downtime (most moves: region↔region, region↔dual-region, across multi-region codes): writes are blocked only during the final synchronization step, which you initiate.
• Without write downtime (locations sharing a multi-region code, e.g. configurable dual-region ↔ multi-region): no finalize step, but takes a minimum of 7 days regardless of size, and latency may increase.

# 1. Dry run first to catch incompatibilities early:
gcloud storage buckets relocate gs://my-bucket --location=us-central1 --dry-run

# 2. Initiate. Bucket metadata is write-locked, object reads/writes continue:
gcloud storage buckets relocate gs://my-bucket --location=us-central1

# 3. Finalize (write-downtime moves only). Object writes fail with HTTP 412
#    until complete, then the lock lifts automatically:
gcloud storage buckets relocate --finalize \
    --operation=projects/_/buckets/my-bucket/operations/OPERATION_ID

Copy duration scales with object count, churn, and size (objects over 10 GB move slowly, at roughly a day per TB-sized object). Check the compatibility list before starting: Firebase and appspot buckets can't be relocated at all, multipart uploads and retention policies have restrictions, and with-downtime moves support fewer features. ME-CENTRAL1 and ME-WEST1 aren't supported.

7. Pricing

• Subscription: $2.50 per million objects/month, amortized daily, billed to the bucket's project, only for objects older than 24h. Early termination fee if a bucket leaves STANDARD tier within 30 days (deletions exempt).
• Datasets: no extra SI fee (multiple configs over the same buckets pay once), but BigQuery storage and query charges apply (~300 MB metadata per TB of data daily). Disabling SI stops snapshots but does not delete BigQuery data, so delete dataset configs to stop charges.
• Batch operations: standard Class A/B operation charges per object (deletes free).
• Bucket relocation: $0.04/GB moved, plus inter-region transfer, one Class A op per object, and storage billed in both locations during the move. There are no retrieval or early-deletion fees, and transfer is waived if source and destination overlap in a region.
• Trial: waives the object management fee and the early termination fee.

Details: https://cloud.google.com/storage/pricing#storage-intelligence

Documentation

• Storage Intelligence Overview
• Configure and Manage Storage Intelligence
• 30-Day Introductory Trial
• Storage Insights Datasets / Configure Datasets / Tables and Schemas
• Analyze Data with Gemini Cloud Assist
• Inventory Reports
• Batch Operations / Create and Manage Jobs
• Bucket Relocation / Plan a Relocation