Step-by-Step: Sanity Check for Cascading Replication in PostgreSQL

Cascading replication allows PostgreSQL replicas to stream data not just from the primary, but from other replicas as well. This setup is ideal for scaling read operations and distributing replication load.

In this guide, we’ll walk through a simple sanity check to ensure your 4-node cascading replication setup is working as expected.

🧩 Assumptions
We’re working with a 4-node setup:

Node 1 is the Primary
Node 2 replicates from Node 1
Node 3 replicates from Node 2
Node 4 replicates from Node 3

Replication is already configured and running, and you have access to psql on all nodes.

Step 1: Create reptest Database on Primary (Node 1)

Open a terminal and connect to PostgreSQL:

psql -U postgres

Create the database and switch to it:

sql

CREATE DATABASE reptest;

\c reptest

Step 2: Create a Sample Table

Inside the reptest database, create a simple table:

sql

CREATE TABLE sanity_check (id SERIAL PRIMARY KEY,message TEXT,created_at TIMESTAMP DEFAULT now());

Step 3: Insert Sample Data

Add a few rows to test replication:

sql

INSERT INTO sanity_check (message) VALUES ('Hello from Node 1'), ('Replication test'), ('Cascading is cool!');

Step 4: Wait a Few Seconds

Give replication a moment to propagate. Cascading replication may introduce slight delays, especially for downstream nodes like Node 4.

Step 5: Verify Data on Nodes 2, 3, and 4

On each replica node, connect to the reptest database:
psql -U postgres -d reptest

Then run:
sql
SELECT * FROM sanity_check;

You should see the same rows that were inserted on the primary.

✅ Conclusion

If the data appears correctly on all replicas, your cascading replication setup is working as expected. This simple sanity check can be repeated periodically or automated to ensure ongoing replication health.

PostgreSQL Cascading Replication: Full 4-Node Setup Guide

Cascading replication allows PostgreSQL replicas to stream data not only from the primary node but also from other replicas. This setup is ideal for scaling read operations and distributing replication load across multiple servers.

🗂️ Node Architecture and Port Assignment

Node 1 (Primary) — Port 5432 — Accepts read/write operations and streams to Node 2
Node 2 (Standby 1) — Port 5433 — Receives from Node 1 and streams to Node 3.
Node 3 (Standby 2) — Port 5434 — Receives from Node 2 and streams to Node 4.
Node 4 (Standby 3) — Port 5435 — Receives from Node 3.

IP assignments:

Node 1 → 172.19.0.21
Node 2 → 172.19.0.22
Node 3 → 172.19.0.23
Node 4 → 172.19.0.24

⚙️ Prerequisites

PostgreSQL installed on all four nodes (same version recommended).
Network connectivity between nodes.
A replication user (repuser) with REPLICATION privilege created on the primary.
PostgreSQL data directories initialized for each node.

Step 1: Configure the Primary Server (Node 1, Port 5432)

🔹 Modify postgresql.conf

listen_addresses = '*'
port = 5432
wal_level = replica
max_wal_senders = 10
wal_keep_size = 512MB
hot_standby = on

🔹 Update pg_hba.conf to allow replication from Node 2

Generic:
host replication repuser <Node2_IP>/32 trust

Actual:
host replication repuser 172.19.0.22/32 trust

🔹 Reload PostgreSQL Configuration

pg_ctl reload
Or from SQL:
sql
SELECT pg_reload_conf();

🔹 Start Node 1

pg_ctl -D /path/to/node1_data -o '-p 5432' -l logfile start

Actual:
pg_ctl -D /u01/postgres/pgdata_15/data -o '-p 5432' -l logfile start

🔹 Create Replication User

sql
CREATE USER repuser WITH REPLICATION ENCRYPTED PASSWORD 'your_password';

🔹 Verify Node 1 is Not in Recovery

sql
SELECT pg_is_in_recovery();

Step 2: Set Up Standby 1 (Node 2, Port 5433)

🔹 Take a Base Backup from Node 1

Generic:
pg_basebackup -h <Node1_IP> -p 5432 -D /path/to/node2_data -U repuser -Fp -Xs -P -R

Actual:
pg_basebackup -h 172.19.0.21 -p 5432 -D /u01/postgres/pgdata_15/data -U repuser -Fp -Xs -P -R

If you get an error:
pg_basebackup: error: directory "/u01/postgres/pgdata_15/data" exists but is not empty

Clear the directory:
rm -rf /u01/postgres/pgdata_15/data/*

🔹 Modify postgresql.conf on Node 2

listen_addresses = '*'
port = 5433
hot_standby = on
primary_conninfo = 'host=172.19.0.21 port=5432 user=repuser password=your_password application_name=node2'

🔹 Start Node 2

Generic:
pg_ctl -D /path/to/node2_data -o '-p 5433' -l logfile start

Actual:
pg_ctl -D /u01/postgres/pgdata_15/data -o '-p 5433' -l logfile start

🔹 Verify Replication on Node 1

sql
SELECT * FROM pg_stat_replication WHERE application_name = 'node2';

Step 3: Set Up Standby 2 (Node 3, Port 5434)

🔹 Allow Replication from Node 3 in Node 2’s pg_hba.conf

Generic:
host replication repuser <Node3_IP>/32 trust

Actual:
host replication repuser 172.19.0.23/32 trust

🔹 Reload Node 2

pg_ctl -D /u01/postgres/pgdata_15/data reload

🔹 Take a Base Backup from Node 2

Generic:
pg_basebackup -h <Node2_IP> -p 5433 -D /path/to/node3_data -U repuser -Fp -Xs -P -R

Actual:
pg_basebackup -h 172.19.0.22 -p 5433 -D /u01/postgres/pgdata_15/data -U repuser -Fp -Xs -P -R

🔹 Modify postgresql.conf on Node 3

listen_addresses = '*'
port = 5434
hot_standby = on
primary_conninfo = 'host=172.19.0.22 port=5433 user=repuser password=your_password application_name=node3'

🔹 Start Node 3

Generic:
pg_ctl -D /path/to/node3_data -o '-p 5434' -l logfile start

Actual:
pg_ctl -D /u01/postgres/pgdata_15/data -o '-p 5434' -l logfile start

🔹 Verify Replication on Node 2

sql
SELECT * FROM pg_stat_replication;

Step 4: Set Up Standby 3 (Node 4, Port 5435)

🔹 Allow Replication from Node 4 in Node 3’s pg_hba.conf

Generic:
host replication repuser <Node4_IP>/32 trust

Actual:
host replication repuser 172.19.0.24/32 trust

🔹 Reload Node 3

pg_ctl -D /u01/postgres/pgdata_15/data reload

🔹 Take a Base Backup from Node 3

Generic:
pg_basebackup -h <Node3_IP> -p 5434 -D /path/to/node4_data -U repuser -Fp -Xs -P -R

Actual:
pg_basebackup -h 172.19.0.23 -p 5434 -D /u01/postgres/pgdata_15/data -U repuser -Fp -Xs -P -R

🔹 Modify postgresql.conf on Node 4

listen_addresses = '*'
port = 5435
hot_standby = on
primary_conninfo = 'host=172.19.0.23 port=5434 user=repuser password=your_password application_name=node4'

🔹 Start Node 4

Generic:
pg_ctl -D /path/to/node4_data -o '-p 5435' -l logfile start

Actual:
pg_ctl -D /u01/postgres/pgdata_15/data -o '-p 5435' -l logfile start

🔹 Verify Replication on Node 3

sql
SELECT * FROM pg_stat_replication;

✅ Final Verification & Monitoring

🔹 Check Replication Status

On Node 1:
sql
SELECT * FROM pg_stat_replication;

On Nodes 2 and 3:
sql

SELECT * FROM pg_stat_wal_receiver;
SELECT * FROM pg_stat_replication;

On Node 4:

sql
SELECT pg_is_in_recovery();
SELECT pg_wal_lsn_diff(pg_last_wal_receive_lsn(), pg_last_wal_replay_lsn()) AS byte_lag;

🔹 Confirm Listening Ports

bash
sudo netstat -plnt | grep postgres
You should see ports 5432, 5433, 5434, and 5435 active.

🔹 Monitor WAL Activity

sql
SELECT * FROM pg_stat_wal;

🔹 Measure Replication Lag

On Primary:
sql

SELECT application_name, client_addr,pg_wal_lsn_diff(pg_current_wal_lsn(), replay_lsn) AS byte_lag FROM pg_stat_replication;

The Docker Copy Machine: How to Clone a Container and Save Hours of Setup Time

Have you ever spent precious time meticulously setting up a Docker container—installing packages, configuring software, and tuning the system—only to need an identical copy and dread starting from scratch?

If you’ve found yourself in this situation, there's a faster way. Docker provides a straightforward method to "clone" or "template" a fully configured container. This is perfect for creating development, staging, and testing environments that are perfectly identical, or for rapidly scaling out services like PostgreSQL without reinstalling everything each time.

In this guide, I’ll show you the simple, practical commands to create a master copy of your container and spin up duplicates in minutes, not hours.

The Problem: Why Not Just Use a Dockerfile?

A Dockerfile is fantastic for reproducible, version-controlled builds. But sometimes, you’ve already done the work inside a running container. You've installed software, run complex configuration scripts, or set up a database schema. Manually translating every step back into a Dockerfile can be tedious and error-prone.

The solution? Treat your perfectly configured container as a gold master image.

Our Practical, Command-Line Approach

Let's walk through the process. Imagine your initial container, named BOX01, is a CentOS system with PostgreSQL already installed and configured.

Step 1: Create Your Master Image with docker commit

The magic command is docker commit. It takes a running (or stopped) container and saves its current state—all the changes made to the filesystem—as a new, reusable Docker image.

# Format: docker commit [CONTAINER_NAME] [NEW_IMAGE_NAME]

docker commit BOX01 centos-postgres-master

What this does: It packages up everything inside BOX01 (except the volumes, more on that later) and creates a new local Docker image named centos-postgres-master.

Verify it worked:

docker images

You should see centos-postgres-master listed among your images.

Step 2: Spin Up Your Clones

Now, you can create as many copies as you need from your new master image. The key is to give each new container a unique name, hostname, and volume to avoid conflicts.

# Create your first clone

docker run -it -d --privileged=true --restart=always --network MQMNTRK -v my-vol102:/u01 --ip 172.19.0.21 -h HOST02 --name BOX02 centos-postgres-master /usr/sbin/init

# Create a second clone

docker run -it -d --privileged=true --restart=always --network MQMNTRK -v my-vol103:/u01 --ip 172.19.0.22 -h HOST03 --name BOX03 centos-postgres-master /usr/sbin/init

Repeat this pattern for as many copies as you need (BOX04, HOST04, etc.). In under a minute, you'll have multiple identical containers running.

⚠️ Important Consideration: Handling Data Volumes

This is the most critical caveat. The docker commit command does not capture data stored in named volumes (like my-vol101).

The Good: Your PostgreSQL software and configuration are baked into the image.

The Gotcha: The actual database data lives in the volume, which is separate.

Your options for data:

Fresh Data: Use a new, empty volume for each clone (as shown above). This is ideal for creating new, independent database instances.

Copy Data: If you need to duplicate the data from the original container, you must copy the volume contents. Here's a quick way to do it:

# Backup data from the original volume (my-vol101)

docker run --rm -v my-vol101:/source -v $(pwd):/backup alpine tar cvf /backup/backup.tar -C /source .

# Restore that data into a new volume (e.g., my-vol102)

docker run --rm -v my-vol102:/target -v $(pwd):/backup alpine bash -c "tar xvf /backup/backup.tar -C /target"

When Should You Use This Method?

Rapid Prototyping: Quickly duplicate a complex environment for testing.
Legacy or Complex Setups: When the installation process is complicated and not easily scripted in a Dockerfile.
Learning and Experimentation: Easily roll back to a known good state by committing before you try something risky.

When Should You Stick to a Dockerfile?

Production Builds: Dockerfiles are transparent, reproducible, and version-controlled.
CI/CD Pipelines: Automated builds from a Dockerfile are a standard best practice.
When Size Matters: Each commit can create a large image layer. Dockerfiles can be optimized to produce smaller images.

Conclusion

The docker commit command is Docker's built-in "copy machine." It’s an incredibly useful tool for developers who need to work quickly and avoid repetitive setup tasks. While it doesn't replace the need for well-defined Dockerfiles in a production workflow, it solves a very real problem for day-to-day development and testing.

So next time you find yourself with a perfectly configured container, don't rebuild—clone it!

Next Steps: Try creating your master image and a clone. For an even more manageable setup, look into writing a simple docker-compose.yml file to define all your container parameters in one place.

Simplifying PostgreSQL Restarts: How to Choose the Right Mode for Your Needs

Three Restart Modes in PostgreSQL

1. smart mode (-m smart) - Gentle & Safe

Waits patiently for all clients to disconnect on their own
Completes all transactions normally before shutting down
No data loss - everything commits properly
Best for production during active hours
Slowest method but most graceful

2. fast mode (-m fast) - Quick & Controlled

Rolls back active transactions immediately
Disconnects all clients abruptly but safely
Restarts quickly without waiting
No data corruption - maintains database integrity
Perfect for maintenance windows
Medium risk - some transactions get aborted

3. immediate mode (-m immediate) - Emergency Only

Forceful shutdown like a crash
No waiting - kills everything immediately
May require recovery on next startup
Risk of temporary inconsistencies
Only for emergencies when nothing else works
PostgreSQL will automatically recover using WAL logs

💡 Key Points to Remember:

All three modes are safe for the database itself
Data integrity is maintained through WAL (Write-Ahead Logging)
Choose based on your situation: gentle vs fast vs emergency
Fast mode is completely normal for planned maintenance
Always warn users before using fast or immediate modes

🚀 When to Use Each:

Use smart mode when:
Database is in production use
You can afford to wait
No transactions should be interrupted

Use fast mode when:
You need to restart quickly
During maintenance windows
Some transaction rollback is acceptable

Use immediate mode when:
Database is unresponsive
Emergency situations only
You have no other choice

All modes will bring your database back safely - they just differ in how gently they treat connected clients and active transactions!

Step-by-Step: Converting Postgre Sync Replication to Async in Production

Simple Steps

📋 Prerequisites

Postgre 9.1 or higher.
Superuser access to the primary database.
Existing replication setup.

🚀 Quick Change Steps (No Restart Required)

Step 1: Connect to Primary Database
p -U postgres -h your-primary-server

Step 2: Check Current Sync Status
SELECT name, setting FROM pg_settings WHERE name IN ('synchronous_commit', 'synchronous_standby_names');

Step 3: Change to Asynchronous Mode
-- Disable synchronous commit
ALTER SYSTEM SET synchronous_commit = 'off';

-- Clear synchronous standby names
ALTER SYSTEM SET synchronous_standby_names = '';

-- Reload configuration (no restart needed)

SELECT pg_reload_conf();

Step 4: Verify the Change
-- Confirm settings changed

SELECT name, setting FROM pg_settings WHERE name IN ('synchronous_commit', 'synchronous_standby_names');

-- Check replication status (should show 'async')

SELECT application_name, sync_state, state FROM pg_stat_replication;

📝 Configuration File Method (Alternative)

Edit postgre.conf on Primary:
sudo nano /etc/postgre/14/main/postgre.conf
Change these lines:
conf
synchronous_commit = off
synchronous_standby_names = ''

Reload Configuration:
sudo systemctl reload postgres
# or
sudo pg_ctl reload

🧪 Testing the Change

Test 1: Performance Check
-- Time an insert operation
\timing on
INSERT INTO test_table (data) VALUES ('async test');
\timing off

Test 2: Verify Async Operation
-- Check replication lag
SELECT application_name, sync_state, pg_wal_lsn_diff(pg_current_wal_lsn(), replay_lsn) AS bytes_lag FROM pg_stat_replication;

Test 3: Data Consistency Check

# On primary:
p -c "SELECT COUNT(*) FROM your_table;"

# On standby:
p -h standby-server -c "SELECT COUNT(*) FROM your_table;"

⚠️ Important Considerations

Before Changing:

Understand the risks: Async replication may cause data loss during failover
Check business requirements: Ensure async meets your data consistency needs
Monitor performance: Async should improve write performance but may increase replication lag

After Changing:

Monitor replication lag regularly
Set up alerts for significant lag increases
Test failover procedures to understand potential data loss scenarios
Review application behavior - some apps may need adjustments

🔄 Reverting to Synchronous Mode

If you need to switch back:

ALTER SYSTEM SET synchronous_commit = 'on';
ALTER SYSTEM SET synchronous_standby_names = 'your_standby_name';

SELECT pg_reload_conf();

🎯 When to Use This Change

Good candidates for Async:

Read-heavy workloads where write performance matters
Non-critical data that can tolerate minor data loss
High-volume logging or analytics data
Geographically distributed systems with high latency

Keep Synchronous For:

Financial transactions.
User account data.
Critical business operations.
Systems requiring zero data loss.

💡 Pro Tips

Use a hybrid approach: Some systems support both sync and async simultaneously.
Monitor continuously: Use tools like pg_stat_replication to watch lag times.
Test thoroughly: Always test replication changes in a staging environment first.
Document the change: Keep records of why and when you changed replication modes.
The change from sync to async takes effect immediately and requires no downtime, making it a relatively low-risk operation that can significantly improve write performance for appropriate use cases.

The Real-Time Database Dilemma: When to Use Synchronous vs Asynchronous Replication in PostgreSQL

Synchronous Replication

✅ Benefits:

Zero Data Loss: Guarantees that data is safely written to both primary and standby before confirming success.
Strong Consistency: All servers have exactly the same data at all times.
Automatic Failover: Standby servers are always up-to-date and ready to take over instantly.
Perfect for Critical Data: Ideal for financial transactions, user accounts, and mission-critical information.

❌ Drawbacks:

Slower Performance: Write operations wait for standby confirmation, increasing latency.
Availability Risk: If standby goes down, primary may become unavailable or slow.
Higher Resource Usage: Requires more network bandwidth and standby server resources.
Complex Setup: More configuration and maintenance required.

⚡ Asynchronous Replication

✅ Benefits:

Faster Performance: Write operations complete immediately without waiting for standby.
Better Availability: Primary continues working even if standby servers disconnect.
Long-Distance Friendly: Works well across geographical distances with higher latency.
Simpler Management: Easier to configure and maintain.

❌ Drawbacks:

Potential Data Loss: Recent transactions may be lost if primary fails before replication completes.
Data Lag: Standby servers might be slightly behind the primary.
Weaker Consistency: Temporary mismatches between primary and standby possible.
Failover Complexity: May require manual intervention to ensure data consistency.

🏭 Production Environment Preferences

📊 For Most Production Systems:

Mixed Approach: Use synchronous for critical data, asynchronous for less critical data.
Tiered Architecture: Synchronous for primary standby, asynchronous for additional read replicas.
Monitoring Essential: Track replication lag and performance metrics continuously.

⚡ For Real-Time Systems:

Synchronous Preferred: When data consistency is more important than raw speed.
Financial Systems: Banking, payments, and transactions require synchronous replication.
E-commerce: Order processing and inventory management often need synchronous guarantees.

🚀 When to Choose Async:

High-Write Systems: Applications with heavy write workloads (logging, analytics).
Read-Heavy Applications: When you need multiple read replicas for performance.
Geographic Distribution: Systems spanning multiple regions with higher latency.
Non-Critical Data: Caching, session data, or temporary information.

🎯 Key Recommendations

Start with Async for most applications, then move to sync for critical components.
Monitor Replication Lag constantly - anything beyond few seconds needs attention.
Test Failover Regularly - ensure your standby can take over when needed.
Use Connection Pooling to help manage the performance impact of synchronous replication.
Consider Hybrid Approaches - some databases support both modes simultaneously.

🔍 Real-World Example

Social Media Platform:

Synchronous: User accounts, direct messages, financial transactions.
Asynchronous: Activity feeds, notifications, analytics, likes.

E-commerce Site:

Synchronous: Orders, payments, inventory updates.
Asynchronous: Product recommendations, user reviews, search indexing.

Step-by-Step Guide to PostgreSQL Streaming Replication (Primary-Standby Setup)

Here's the properly organized step-by-step guide for setting up PostgreSQL 12/15 streaming replication between Primary (172.19.0.20) and Standby (172.19.0.30):


✅ Pre-Requisites

Two servers with PostgreSQL 12/15.3 installed
Database cluster initialized on both using initdb (service not started yet)

IP configuration:

Primary: 172.19.0.20
Standby: 172.19.0.30

🔧 Primary Server Configuration

Backup config file:

bash

cd /u01/postgres/pgdata_15/data
cp postgresql.conf postgresql.conf_bkp_$(date +%b%d_%Y)


Edit postgresql.conf:

bash

vi postgresql.conf

Set these parameters:

listen_addresses = '*'
port = 5432
wal_level = replica
archive_mode = on
archive_command = 'cp %p /u01/postgres/pgdata_15/data/archive_logs/%f'
max_wal_senders = 10
wal_keep_segments = 50

Start PostgreSQL:

bash

/u01/postgres/pgdata_15/bin/pg_ctl -D /u01/postgres/pgdata_15/data -l logfile start

Create replication user:

sql

CREATE USER repl_user WITH REPLICATION ENCRYPTED PASSWORD 'strongpassword';

Configure pg_hba.conf:

bash

cp pg_hba.conf pg_hba.conf_bkp_$(date +%b%d_%Y)

vi pg_hba.conf

Add:
host replication repl_user 172.19.0.30/32 md5

Reload config:

bash

/u01/postgres/pgdata_15/bin/pg_ctl -D /u01/postgres/pgdata_15/data -l logfile reload

🔄 Standby Server Configuration

Clear data directory:

bash

rm -rf /u01/postgres/pgdata_15/data/*

Run pg_basebackup:

bash

pg_basebackup -h 172.19.0.20 -U repl_user -p 5432 -D /u01/postgres/pgdata_15/data -Fp -Xs -P -R

Start PostgreSQL:

bash

pg_ctl -D /u01/postgres/pgdata_15/data -l logfile start

Verify logs:

bash

tail -f /u01/postgres/pgdata_15/data/logfile

Look for:

text

started streaming WAL from primary at 0/3000000 on timeline 1

🔍 Verification Steps

On Primary:

sql

CREATE DATABASE reptest;

\c reptest

CREATE TABLE test_table (id int);

INSERT INTO test_table VALUES (1);

On Standby:

sql

\c reptest

SELECT * FROM test_table; -- Should return 1 row

Check processes:

Primary:

bash

ps -ef | grep postgres

Look for walsender process

Standby:

Look for walreceiver process

Network test:

bash

nc -zv 172.19.0.20 5432


📌 Key Notes

-Replace paths/versions according to your setup
-Ensure firewall allows port 5432 between servers
For Oracle Linux 6.8, adjust service commands if needed
-Monitor logs (logfile) on both servers for errors


Detailed steps:

✅ Pre-Requisites

Two servers with PostgreSQL 12 or PostgreSQL 15.3 installed.
Database cluster initialized on both using initdb (but do not start the service yet).

IPs configured:

Primary: 172.19.0.20
Standby: 172.19.0.30

Make some necessary changes in postgresql.conf file on the primary server.

[postgres@HOST01 data]$ pwd

/u01/postgres/pgdata_15/data

[postgres@HOST01 data]$ cp postgresql.conf postgresql.conf_bkp_Aug18_2025

[postgres@HOST01 data]$ vi postgresql.conf


listen_addresses = '*'
port = 5432
wal_level = hot_standby
archive_mode = on
archive_command = 'cp %p /u01/postgres/pgdata_15/data/archive_logs/%f'
max_wal_senders = 10

After making necessary changes in the postgresql.conf file. Let’s start the database server on primary server using below command.

[postgres@HOST01 data]$ /u01/postgres/pgdata_15/bin/pg_ctl -D /u01/postgres/pgdata_15/data -l logfile start

Once the database server is started, invoke psql as super user i.e. postgres and create a role for replication.

CREATE USER repl_user WITH REPLICATION ENCRYPTED PASSWORD 'strongpassword';

Allow connection to created user from Standby Server by seting pg_hba.conf

[postgres@HOST01 data]$ pwd

/u01/postgres/pgdata_15/data

[postgres@HOST01 data]$ ls

archive_logs pg_commit_ts pg_ident.conf pg_replslot pg_stat_tmp PG_VERSION postgresql.conf

base pg_dynshmem pg_logical pg_serial pg_subtrans pg_wal postgresql.conf_old

global pg_hba.conf pg_multixact pg_snapshots pg_tblspc pg_xact postmaster.opts

logfile pg_hba.conf_bkp_Aug18_2025 pg_notify pg_stat pg_twophase postgresql.auto.conf postmaster.pid


[postgres@HOST01 data]$ cp pg_hba.conf pg_hba.conf_bkp_Aug18_2025

[postgres@HOST01 data]$ vi pg_hba.conf

host replication repl_user 172.19.0.30/32 md5

Reload the setting of the cluster.

[postgres@HOST01 data]$ /u01/postgres/pgdata_15/bin/pg_ctl -D /u01/postgres/pgdata_15/data -l logfile stop

[postgres@HOST01 data]$ /u01/postgres/pgdata_15/bin/pg_ctl -D /u01/postgres/pgdata_15/data -l logfile start

(OR)

[postgres@HOST01 data]$ /u01/postgres/pgdata_15/bin/pg_ctl -D /u01/postgres/pgdata_15/data -l logfile reload

We made changes to the configuration of the primary server. Now we’ll use pg_basebackup to get the data directory i.e. /u01/postgres/pgdata_15/data to Standby Server.

Standby Server Configurations.

[postgres@HOST02 ~]$ pg_basebackup -h 172.19.0.20 -U repl_user -p 5432 -D /u01/postgres/pgdata_15/data -Fp -Xs -P -R

Password:

pg_basebackup: error: directory "/u01/postgres/pgdata_15/data" exists but is not empty

Navigate to data directory and empty it.

cd /u01/postgres/pgdata_15/data

rm -rf *

[postgres@HOST02 ~]$ pg_basebackup -h 172.19.0.20 -U repl_user -p 5432 -D /u01/postgres/pgdata_15/data -Fp -Xs -P -R

Password:

38761/38761 kB (100%), 1/1 tablespace

Now start the database server at standby side using below command.


[postgres@HOST02 ~]$ pg_ctl -D /u01/postgres/pgdata_15/data -l logfile start

waiting for server to start.... done

server started

Check the logfile to gather some more information.

[postgres@HOST02 data]$ tail -f logfile

2025-08-18 21:12:09.487 UTC [11349] LOG: listening on IPv4 address "0.0.0.0", port 5432
2025-08-18 21:12:09.487 UTC [11349] LOG: listening on IPv6 address "::", port 5432
2025-08-18 21:12:09.491 UTC [11349] LOG: listening on Unix socket "/tmp/.s.PGSQL.5432"
2025-08-18 21:12:09.498 UTC [11352] LOG: database system was interrupted; last known up at 2025-08-18 21:11:13 UTC
2025-08-18 21:12:09.513 UTC [11352] LOG: entering standby mode
2025-08-18 21:12:09.518 UTC [11352] LOG: redo starts at 0/2000028
2025-08-18 21:12:09.519 UTC [11352] LOG: consistent recovery state reached at 0/2000100
2025-08-18 21:12:09.520 UTC [11349] LOG: database system is ready to accept read-only connections
2025-08-18 21:12:09.557 UTC [11353] LOG: started streaming WAL from primary at 0/3000000 on timeline 1

Let’s now check the replication. Invoke psql and perform some operations.

Primary:

create database qadar_reptest;
\c qadar_reptest;
create table mqm_reptst_table (serial int);
insert into mqm_reptst_table values (1);

Standby:

\c qadar_reptest;
select count(*) from mqm_reptst_table;

Check the background process involved in streaming replication:

Primary:

[postgres@HOST01 data]$ ps -ef|grep postgres

root 11329 160 0 19:40 pts/1 00:00:00 su - postgres
postgres 11330 11329 0 19:40 pts/1 00:00:04 -bash
root 11608 11496 0 21:07 pts/2 00:00:00 su - postgres
postgres 11609 11608 0 21:07 pts/2 00:00:00 -bash
postgres 11635 11609 0 21:07 pts/2 00:00:00 /usr/bin/coreutils --coreutils-prog-shebang=tail /usr/bin/tail -f logfile
postgres 11639 1 0 21:08 ? 00:00:00 /u01/postgres/pgdata_15/bin/postgres -D /u01/postgres/pgdata_15/data
postgres 11640 11639 0 21:08 ? 00:00:00 postgres: checkpointer
postgres 11641 11639 0 21:08 ? 00:00:00 postgres: background writer
postgres 11643 11639 0 21:08 ? 00:00:00 postgres: walwriter
postgres 11644 11639 0 21:08 ? 00:00:00 postgres: autovacuum launcher
postgres 11645 11639 0 21:08 ? 00:00:00 postgres: archiver last was 000000010000000000000002.00000028.backup
postgres 11646 11639 0 21:08 ? 00:00:00 postgres: logical replication launcher
postgres 11663 11639 0 21:12 ? 00:00:00 postgres: walsender repl_user 172.19.0.30(38248) streaming 0/3000060
postgres 11671 11330 0 21:15 pts/1 00:00:00 ps -ef
postgres 11672 11330 0 21:15 pts/1 00:00:00 grep --color=auto postgres

Standby:

[postgres@HOST02 ~]$ ps -ef|grep postgres

root 11300 119 0 20:59 pts/1 00:00:00 su - postgres
postgres 11301 11300 0 20:59 pts/1 00:00:00 -bash
postgres 11349 1 0 21:12 ? 00:00:00 /u01/postgres/pgdata_15/bin/postgres -D /u01/postgres/pgdata_15/data
postgres 11350 11349 0 21:12 ? 00:00:00 postgres: checkpointer
postgres 11351 11349 0 21:12 ? 00:00:00 postgres: background writer
postgres 11352 11349 0 21:12 ? 00:00:00 postgres: startup recovering 000000010000000000000003
postgres 11353 11349 0 21:12 ? 00:00:00 postgres: walreceiver streaming 0/3000148
postgres 11356 11301 0 21:16 pts/1 00:00:00 ps -ef
postgres 11357 11301 0 21:16 pts/1 00:00:00 grep --color=auto postgres


Check the network connectivity betweeen the servers.

Standby:

[postgres@HOST02 ~] yum install nc
[postgres@HOST02 ~]$ nc -zv 172.19.0.20 5432
Ncat: Version 7.70 ( https://nmap.org/ncat )
Ncat: Connected to 172.19.0.20:5432.
Ncat: 0 bytes sent, 0 bytes received in 0.02 seconds.

ERROR with "Failed to set locale, defaulting to C" on Centos at the docker environment (yum install)

Fix:

As root user, then do steps:

sed -i 's/mirrorlist/#mirrorlist/g' /etc/yum.repos.d/CentOS-*
sed -i 's|#baseurl=http://mirror.centos.org|baseurl=http://vault.centos.org|g' /etc/yum.repos.d/CentOS-*

yum update -y