Lake Formation Governance

AWS Lake Formation Governance

When to Use

• Implementing fine-grained access control (table, column, row-level) for a data lake
• Replacing coarse-grained S3 bucket policies with Lake Formation permissions
• Sharing Glue Data Catalog resources across AWS accounts
• Setting up data lake blueprints for automated ingestion
• Governing who can access what data in Athena, Redshift Spectrum, or Glue jobs
• Preparing for AWS Certified Data Engineer Associate (DEA-C01) exam

Core Jobs

1. Lake Formation vs S3 Bucket Policies

Rule: Use S3 bucket policies for coarse access control (which buckets/prefixes are accessible). Use Lake Formation for fine-grained control over which tables, columns, and rows a principal can see.

Both are required: Lake Formation is an additional governance layer OVER IAM and S3. A principal needs both IAM permissions AND Lake Formation permissions to access data.

2. Permissions Model

Permission hierarchy:

Database → Tables → Columns → Row filters

Lake Formation permission types:

• CREATE_DATABASE, CREATE_TABLE — DDL operations
• SELECT, INSERT, DELETE, DROP, ALTER — DML operations
• DESCRIBE — view metadata only (no data access)
• SUPER — all permissions (admin)

Grantable permissions: principals with GRANT OPTION can grant their permissions to others (delegation).

Permission inheritance: granting on a database with GrantOption propagates to future tables created in that database.

3. Column-Level Security

• Grant access to specific columns only in a table
• Excluded columns are invisible to the grantee (not returned in query results)
• Example: grant analyst access to customer_orders table but EXCLUDE ssn, credit_card columns
• Configured via Lake Formation console or API: specify included or excluded columns per grant

Grant SELECT on table customer_orders
  to role analyst_role
  Columns: [order_id, order_date, amount, status]  -- exclude PII

4. Row-Level Security (Data Filters)

• Data filters = filter expressions applied to table rows at query time
• Define filter once, apply to multiple grants
• Filter expression example: region = 'us-east-1' AND status = 'active'
• Use cases:
  • Multi-tenant data lake (each team sees only their tenant's data)
  • Regional data access (EU team sees only EU records)
  • Sensitivity-based filtering (analysts see non-PII rows only)

Create data filter:

Filter name: us_only_orders
Table: orders
Row filter expression: region = 'US'
Column exclusions: [customer_ssn, payment_info]

Apply by granting this filter to specific IAM roles or Lake Formation principals.

5. Cross-Account Data Sharing

• Share Glue Data Catalog databases and tables with other AWS accounts via AWS RAM (Resource Access Manager)
• Recipient account: accepts RAM share → sees shared database in their Data Catalog
• No data is copied — recipient queries data in the originating account's S3 (via Glue/Athena/Redshift Spectrum)
• Lake Formation permissions still apply (originator controls what the recipient can see)
• Cross-region sharing: share across regions (same or different accounts)

Steps:

1. Register S3 data lake location in Lake Formation (originator account)
2. Grant Lake Formation permissions to target account principal
3. Create RAM resource share with Catalog databases/tables
4. Target account accepts RAM share and creates Lake Formation permissions for their principals

6. Blueprints and Automated Ingestion

• Lake Formation blueprints — pre-built templates to automate data ingestion to the data lake
• Available blueprints: Database snapshot, Incremental database, CloudTrail logs, CloudFront logs
• Creates Glue workflows automatically (crawlers + jobs) from blueprint configuration
• Target: S3 location registered with Lake Formation (governance applied automatically)
• Schedule: one-time or periodic (cron-based)

7. Governed Tables (ACID)

• Governed Tables = Lake Formation native table format with ACID transaction support
• Supports concurrent reads/writes with consistent snapshots
• Automatic compaction: Lake Formation compacts small files in background (S3 optimization)
• Row-level transactions: INSERT, DELETE with full ACID guarantees
• Enable via Lake Formation console when creating table; stored in S3 with transaction log

Key Concepts

• Data lake administrator — IAM user/role with Lake Formation admin privileges; can grant/revoke all permissions
• LF-Tags (Lake Formation tags) — attribute-based access control (ABAC); tag resources and grant access by tag values; scales better than explicit grants for large catalogs
• Registered S3 location — S3 path registered with Lake Formation; Lake Formation manages access (IAM passthrough disabled); unregistered paths use IAM only
• IAM passthrough mode — for Athena queries on non-registered S3 locations; Lake Formation not involved
• Governed Tables — ACID transactional tables in Lake Formation (vs standard Glue catalog tables)
• Data Catalog encryption — encrypt Glue Data Catalog metadata at rest using KMS
• CloudTrail integration — all Lake Formation API calls logged; audit who accessed what data

Checklist

• S3 data lake locations registered with Lake Formation (enables fine-grained control)?
• IAM passthrough disabled for registered locations (Lake Formation fully manages access)?
• Column-level grants configured to exclude PII/sensitive columns from non-privileged roles?
• Row-level data filters defined for multi-tenant or regional access requirements?
• LF-Tags used for large catalogs (scales better than explicit grants)?
• Cross-account sharing via RAM (not data copying)?
• Data lake administrator role limited to specific IAM principals?
• CloudTrail logging enabled for Lake Formation API calls (audit)?

Output Format

• 🔴 Critical — Lake Formation registered locations with IAM passthrough still enabled (defeats Lake Formation governance); no column exclusions on tables with PII fields
• 🟡 Warning — explicit grants used at scale without LF-Tags (hard to manage); cross-account sharing done by copying data (inefficient) instead of RAM share
• 🟢 Suggestion — Governed Tables for concurrent ETL workloads; blueprints for automated ingestion from RDS/on-prem databases; LF-Tags for scalable ABAC

Exam Tips

• Lake Formation = governance layer OVER Glue Data Catalog and S3; it does NOT move or copy data
• Column-level security = grant access to SPECIFIC columns; row-level = grant rows matching filter expression; both configurable per principal
• Lake Formation permissions + IAM BOTH required — Lake Formation is an ADDITIONAL layer; having IAM S3 access is not enough if location is registered
• Registered S3 locations = Lake Formation manages access control; unregistered locations = IAM and S3 bucket policies only
• Cross-account sharing via RAM = share Catalog resources (databases, tables) without copying data; recipient queries data in source account's S3
• Governed Tables = ACID transactions and automatic compaction in Lake Formation (similar to Delta Lake/Iceberg transactional tables)
• LF-Tags (ABAC) = scalable permissions for large catalogs; tag-based grants auto-apply to new resources with matching tags
• Data lake administrators can see all Data Catalog resources by default; limit this role to minimum necessary principals