Capture Postgres Create

Create PostgreSQL Capture

Create a PostgreSQL CDC capture that continuously streams changes from Postgres tables into Estuary collections.

Applies to: source-postgres, source-amazon-aurora-postgres, source-amazon-rds-postgres, source-google-cloud-sql-postgres, source-supabase-postgres, source-neon-postgres

Step 0: Load Connector Documentation

Before proceeding, fetch the official connector docs for prerequisites, config reference, and cloud-specific setup.

Always load the main page: https://docs.estuary.dev/reference/Connectors/capture-connectors/PostgreSQL/

Then load the variant subpage based on the user's Postgres type:

| Variant | Docs URL | |---------|----------| | Self-hosted / Vanilla | Main page covers this | | Amazon Aurora | Main page covers this | | Azure Database | Main page covers this | | Amazon RDS | https://docs.estuary.dev/reference/Connectors/capture-connectors/PostgreSQL/amazon-rds-postgres/ | | Google Cloud SQL | https://docs.estuary.dev/reference/Connectors/capture-connectors/PostgreSQL/google-cloud-sql-postgres/ | | Supabase | https://docs.estuary.dev/reference/Connectors/capture-connectors/PostgreSQL/Supabase/ | | Neon | https://docs.estuary.dev/reference/Connectors/capture-connectors/PostgreSQL/neon-postgres/ |

Use WebFetch to load these pages. Together they cover:

• Prerequisites (WAL level, user creation, publication setup, watermarks table)
• Full config property reference
• Cloud-specific setup instructions
• SSH tunnel configuration
• Network access / IP allowlisting

This skill provides the flowctl workflow and troubleshooting that docs don't cover.

Step 1: Gather Requirements

Before writing any YAML, ask the user:

1. Postgres variant? — Vanilla, Amazon RDS, Aurora, Google Cloud SQL, Supabase, Neon
2. Network path? — Direct connection (cloud-hosted with IP allowlist), SSH tunnel (private network/on-prem), Private Link (AWS/Azure/GCP), or ngrok (local dev)
3. Non-default data plane? — Most users use the default. Ask if they need a non-default data plane.
4. Tables to capture? — All standard tables in the publication is the default. A specific subset, partitioned tables (must capture child partitions, not the parent), views (require batch connector instead of CDC), or tables not yet in the publication all require additional configuration.
5. History mode? — Standard CDC (false) or full event history (true)

Step 2: Find the Correct Connector Version

Always use the latest numbered version tag. Query the connector registry to find it:

# For standard Postgres
flowctl raw get --table connector_tags \
  --query 'documentation_url=eq.https://go.estuary.dev/source-postgres' \
  --query 'select=image_tag,documentation_url' \
  --output yaml

To find any Postgres variant version:

flowctl raw get --table connector_tags \
  --query 'documentation_url=ilike.**' \
  --query 'select=image_tag,documentation_url' \
  --output yaml

Choose the connector image based on the user's Postgres variant: | Variant | Connector Image | |---------|----------------| | Vanilla / self-hosted | ghcr.io/estuary/source-postgres | | Amazon RDS | ghcr.io/estuary/source-amazon-rds-postgres | | Amazon Aurora | ghcr.io/estuary/source-amazon-aurora-postgres | | Google Cloud SQL | ghcr.io/estuary/source-google-cloud-sql-postgres | | Supabase | ghcr.io/estuary/source-supabase-postgres | | Neon | ghcr.io/estuary/source-neon-postgres |

Step 3: Help User Complete Prerequisites

Walk the user through the prerequisites from the docs page loaded in Step 0. Key items:

1. Logical replication — SHOW wal_level; must return logical
2. WAL retention safety — Recommend setting max_slot_wal_keep_size (50GB is a good starting point, more for high-change-rate databases). Without this, Postgres retains unbounded WAL if the capture ever stalls, which can fill the disk and crash the database. The connector does not check this — it's a safety net for the source database, not a replication prerequisite.
3. Capture user — needs REPLICATION permission and SELECT access
4. Publication — CREATE PUBLICATION flow_publication FOR ALL TABLES;
5. Watermarks table — recommended for backfill accuracy

If the user is on a managed service (RDS, Cloud SQL, Supabase), refer to the cloud-specific section in the docs.

Step 4: Create the Capture Spec File

Build flow.yaml using the config reference from the docs. Minimal required config:

captures:
  //source-postgres:
    endpoint:
      connector:
        image: ghcr.io/estuary/source-postgres:
        config:
          address: ":"
          database: ""
          user: ""
          credentials:
            auth_type: "UserPassword"
            password: ""
          historyMode: false
    bindings: []

For SSH tunnel, add networkTunnel.sshForwarding block — see docs for full config.

For AWS IAM or GCP IAM auth, set credentials.auth_type accordingly — see docs for required fields.

Step 5: Discover Tables

flowctl discover --source flow.yaml

Note: The first discover attempt occasionally fails with a generic error. If this happens, simply retry — it typically succeeds on the second attempt.

What this does:

1. Connects to the database
2. Discovers all tables in the publication
3. Generates JSON schemas from table structures
4. Updates flow.yaml with bindings
5. Creates SOPS-encrypted config file

Generated file structure:

flow.yaml                          # Updated with bindings
source-postgres.config.yaml        # SOPS-encrypted credentials
/
  flow.yaml                        # Import file
  /
    flow.yaml                      # Collection definitions
    public/
      .write.schema.yaml    # Write schema per table
      .read.schema.yaml     # Read schema per table

Step 6: Review and Customize Bindings

After discovery, review the generated bindings in flow.yaml:

• Remove unwanted tables — Delete the binding entry
• Rename target collections — Change the target field

Step 7: Publish

flowctl catalog publish --source flow.yaml --auto-approve

The --auto-approve flag is required for non-interactive use.

Step 8: Verify

# Check status (expect PENDING → Backfilling → OK: Streaming CDC Events)
flowctl catalog status //source-postgres

# View recent logs
flowctl logs --task //source-postgres --since 5m | jq -c '{ts, message}'

# Read captured data
flowctl collections read --collection //public/ --uncommitted | head -20

Status progression:

1. WARNING: waiting for task shards to be ready (PENDING) — normal for ~30 seconds
2. Backfilling Tables (N tables backfilling) — initial data sync
3. OK: Streaming CDC Events — capture is running normally

Step 9: Test Real-Time CDC

Insert a row in the source database and verify it appears in the collection within seconds:

flowctl collections read --collection //public/ --uncommitted | \
  jq 'select(. == "")'

Troubleshooting

"no connector tag found for image"

Cause: Wrong image tag (e.g., :dev)

Fix: Query connector_tags for the correct version (see Step 2).

"Config failed schema validation"

Cause: Config structure is wrong. Common mistakes:

• Password at root level instead of credentials.password
• Missing credentials.auth_type: "UserPassword"
• Missing historyMode: false

"connection refused" or timeout

Cause: Database not reachable from Estuary cloud

Fix:

1. Verify firewall allows Estuary IPs (see docs for current list)
2. Use SSH tunnel for private networks
3. For local dev: ngrok tcp 5432

"permission denied for replication"

Cause: User lacks REPLICATION permission

Fix:

ALTER USER flow_capture WITH REPLICATION;
GRANT pg_read_all_data TO flow_capture;  -- Postgres 14+

"publication does not exist"

Cause: Publication not created or wrong name in advanced config

Fix:

CREATE PUBLICATION flow_publication FOR ALL TABLES;

No tables discovered

Cause: Publication exists but has no tables, or the capture user lacks permissions to see them. This is a very common support issue.

Debug:

-- Check publication has tables (run as admin)
SELECT p.pubname, pt.schemaname, pt.tablename
FROM pg_publication p
JOIN pg_publication_tables pt ON p.oid = pt.pubid
ORDER BY p.pubname, pt.schemaname, pt.tablename;

-- Check capture user can see tables (run as capture user)
SELECT table_schema, table_name, table_type
FROM information_schema.tables
WHERE table_schema NOT IN ('pg_catalog', 'pg_internal', 'information_schema');

If the publication is empty, add tables or recreate with FOR ALL TABLES. If the capture user sees fewer tables than admin, it's a permissions/schema visibility issue.

Capture stuck in PENDING

Wait 30-60 seconds — this is normal during shard assignment. If still stuck:

flowctl logs --task //source-postgres --since 5m | jq 'select(.level == "error" or .level == "warn")'

Watermarks table warning

Warning: relation "public.flow_watermarks" does not exist

Impact: Capture still works, but backfill accuracy may be affected.

Fix: Create the watermarks table per docs prerequisites.

Discover fails on first attempt

This is a known intermittent issue. Simply retry flowctl discover --source flow.yaml — it typically succeeds on the second attempt.

Related Skills

• connector-disable-enable — Pause/restart existing captures
• connector-delete-recreate — Nuclear option for stuck captures
• estuary-logs — Deep log analysis
• estuary-catalog-status — Status checking

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: estuary
• Source: estuary/agent-skills
• License: Apache-2.0
• Homepage: https://estuary.dev

Install and usage instructions live in the source repository linked above.