What you'll learn: How to get a managed PostgreSQL database running on AWS using Terraform. Learn the basics of preparing your environment, locking down credentials, setting up automated backups, and pointing out some performance tips. Pick up essentials for picking a hosting spot, see pros and cons, and get advice for keeping things humming as you scale.

What is PostgreSQL database?

PostgreSQL is an open-source system that stores and manages your data, pulling together features from both classic SQL and modern database designs. Having started at UC Berkeley, it has grown into one of the most trusted options available, whether you're building a simple app or running enterprise workloads.

Developers love PostgreSQL because it's flexible – it handles JSON, arrays, custom types, and lets you write your own functions. You don't have to sacrifice speed while organizing data the way you want.

Standout features include reliable transactions, ACID compliance, built-in replication, and broad extensibility. These add up to give you consistent data, robust uptime, and the ability to adapt as needs shift.

Because it's open source, the global PostgreSQL community is always pushing out updates, new features, code updates and security fixes. Businesses choose PostgreSQL for its transparency and long-term reliability, as well as the cost savings – rom analytics dashboards to global web apps, it can fit projects of every size.

If you're ready to run PostgreSQL, the big cloud providers – AWS, Google Cloud, and Microsoft Azure – offer managed versions that take care of scaling and backups, freeing your team to tackle higher-level improvements and features.

Choosing these services lets you reduce maintenance and improve security and uptime—a big plus for anyone building on the cloud.

Why deploy PostgreSQL database on AWS?

Using PostgreSQL on AWS means you spend less time managing infrastructure and more time building features. With Amazon RDS for PostgreSQL, AWS handles the behind-the-scenes work – like routine maintenance, updates, and scaling – so you can focus on what matters.

AWS doesn't just make life easier, it prioritizes resilience and security, like deployments across multiple zones (Multi-AZ) that keep your data available if something goes wrong. You also get encryption, network isolation, and role-based permissions baked right in, no extra setup needed.

AWS lets you run PostgreSQL in the cloud without expecting you to be a database admin 24/7. It's secure, reliable, flexible, and built to grow alongside your needs.

Where you can host PostgreSQL database

You've got options with PostgreSQL. You can run it on your laptop, keep it in your own data center, or tap into cloud-managed services. Each option has its own benefits: some give you control, others handle the headaches for you.

On-premises hosting gives you complete ownership of the environment
Cloud hosting uses managed services such as Amazon RDS for PostgreSQL, Google Cloud SQL, and Azure Database for PostgreSQL to automate most of the work
You can also deploy PostgreSQL on containerized or hybrid platforms using tools like Kubernetes or Docker, an approach that offers portability

Here are the pros and cons of each:

Hosting option	Pros	Cons
On-premises hosting	Full control over infrastructure and configuration Meets strict compliance or data residency requirements Useful for legacy environments that can't move to the cloud	Higher operational overhead and maintenance costs Scaling requires new hardware and manual setup Limited automation for backups and monitoring
Cloud hosting	Simplifies deployment and scaling Offers built-in backups, monitoring, and failover Lower upfront infrastructure cost	Less direct control over configuration or updates Ongoing service costs may grow with usage Vendor lock-in can make migrations harder
Containerized or hybrid platforms	Portable across cloud and on-premises environments Supports consistent, repeatable deployments Allows greater customization than managed services	More complex setup and orchestration Requires DevOps expertise to maintain and secure Backups and scaling must be configured manually

When you pick your hosting, look past the sticker price and consider your team's expertise and your long-term roadmap. Small dev or test projects might stick with VMs, while production systems get more value from cloud automation.

Preparing your environment for Terraform and AWS RDS

Before you can deploy a PostgreSQL database with Terraform, you need to set up your environment so Terraform can communicate securely with AWS. This preparatory step helps deployment run smoothly and keeps your infrastructure reproducible.

If you're working in a team, consider using a tool like Terrateam to streamline collaboration and automate Terraform workflows.

Terrateam integrates with your version control system to manage Terraform plans and applies, ensuring consistency and reducing the risk of errors in shared environments.

Before rolling out a PostgreSQL database with Terraform, you'll need to have done the groundwork: Terraform running locally (or in your CI tool), plus AWS credentials ready so all the pieces can talk to each other securely.

Install Terraform on your system using Homebrew:

brew tap hashicorp/tap
brew install hashicorp/tap/terraform

Once Terraform is installed, make sure it's working correctly:

terraform -version

Set your AWS credentials to let Terraform manage resources. The AWS CLI is the quickest way to do this:

aws configure

You'll be prompted for keys and default settings, all of which you can find it uyour ~/.aws/credentials file. For production use, you should avoid using the root account. Instead, set up an IAM user or role with just the permissions you need.

Next, make a project folder and your Terraform configuration file. This step tells Terraform what provider you're using and which AWS region to target:

provider "aws" {
  region = "us-east-1"
}

Save the file as main.tf, and then initialize your environment:

terraform init

Terraform init pulls in everything Terraform needs to manage AWS resources. Now you're ready to define your PostgreSQL setup.

Writing Terraform configuration files for a PostgreSQL instance

Now you're ready to lay out the database resource.

Using the aws_db_instance resource in Terraform lets you clarify what your PostgreSQL instance should look like and how AWS should provision it.

Create a file named main.tf (or update your existing one) and drop in this code:

resource "aws_db_instance" "postgres" {
  identifier        = "demo-postgres"
  engine            = "postgres"
  engine_version    = "15.4"
  instance_class    = "db.t3.micro"
  allocated_storage = 20
  username          = "admin"
  password          = "examplepassword"
  skip_final_snapshot = true
}

That'll get you a basic RDS PostgreSQL instance.

If this is for production, swap in variables for usernames and passwords, reference your network and security policies, and make sure to turn on automated backups.

Do a final check, and then roll out:

terraform validate

A quick validation helps spot typos or misconfigurations before Terraform starts to affect your AWS account.

Configuring networking and security groups

With the DB resource penned in, you'll want to lock down access. Thankfully, AWS uses security groups to manage who can connect.

Add this to your Terraform file:

resource "aws_security_group" "db_access" {
  name        = "postgres-sg"
  description = "Allow PostgreSQL access"

  ingress {
    from_port   = 5432
    to_port     = 5432
    protocol    = "tcp"
    cidr_blocks = ["0.0.0.0/0"] # Replace with your trusted IP range
  }

  egress {
    from_port   = 0
    to_port     = 0
    protocol    = "-1"
    cidr_blocks = ["0.0.0.0/0"]
  }
}

Don't forget to attach the security group to your RDS instance with vpc_security_group_ids. For real-world use, always narrow down the cidr_blocks to just your trusted network, not open to the entire internet.

Using AWS Secrets Manager to secure database credentials

Putting plain-text DB usernames and passwords directly into Terraform is risky business. AWS Secrets Manager is made to keep those secrets safe, letting you pull them in securely when Terraform runs.

First, stash your DB credentials in a new secret via the Console or CLI. Then, reference it in your Terraform config:

data "aws_secretsmanager_secret_version" "db_credentials" {
  secret_id = "postgres-credentials"
}

You can extract stored values in your RDS configuration:

locals {
  creds = jsondecode(data.aws_secretsmanager_secret_version.db_credentials.secret_string)
}

resource "aws_db_instance" "postgres" {
  identifier = "secure-postgres"
  engine     = "postgres"
  username   = local.creds.username
  password   = local.creds.password
  # Other settings...
}

Making this small change keeps secrets out of your code and repo, making your stack safer without much extra work.

Applying Terraform to deploy and manage your PostgreSQL database

Now your configurations ready, review what Terraform wants to create:

terraform plan

If everything looks good, it's time to apply:

terraform apply

Note: Terrateam can automate these steps by managing Terraform plans and applies directly through your version control system. For example, when a pull request is created, Terrateam can automatically generate a terraform plan and post the results for review. Once approved, it can safely execute the terraform apply, ensuring consistency and reducing the risk of manual errors.

Terraform will launch the RDS instance, hook up the networking, and grab your credentials from Secrets Manager (it might take a few minutes for everything to spin up).

Check your deployed database with:

aws rds describe-db-instances --db-instance-identifier secure-postgres

You'll see connection info like the host and port, plus the status. Try connecting with your favorite PostgreSQL client to make sure it's all online.

Want backups and performance data? Drop these in your resource definition:

backup_retention_period = 7
performance_insights_enabled = true

Now you'll have automatic recovery options and better insight into how your database is performing, without any extra manual setup.

Best practices for maintaining and scaling PostgreSQL on AWS

When your PostgreSQL instance is up, keeping things running smoothly means frequent check-ins and tuning as your needs change.

Here are some best practices to maintain and scale PostgreSQL on AWS:

Monitor performance regularly: Use CloudWatch or Performance Insights for query times, resource spikes, and slowdowns. Solve small problems before they stack up.
Tune-tune and optimize: Dig into query plans, tweak memory settings, add indexes where they matter. Little adjustments can have a big impact under real-world loads.
Automate backups: Schedule them and set clear retention policies. Snapshots, replication, and read replicas all boost your disaster recovery plan.
Keep your software current: Update PostgreSQL versions for fresh security patches, features, updates, and long-term support.
Be smart about scaling: Upgrade your instance size or storage as needed, but sometimes adding a read replica or using Aurora PostgreSQL is your best move.
Reassess as your business evolved: As data grows and usage changes, check your setup – what worked for a small app might not fit once you're scaling up

Exploring alternative cloud providers and databases

AWS RDS is just one path; other clouds or databases might fit your project better.

Google Cloud SQL and Azure Database for PostgreSQL provide similar managed experiences. If your company already relies on one of those clouds, staying there can make integration easier.

Depending on your app, you might look at:

MySQL for simple relational web apps
MongoDB when you need flexible documents
CockroachDB if you want distributed SQL across geographies

Match the database and platform to your current and future needs, not just what feels easy right now, and make sure your team can manage the new tech with confidence.

Conclusion

With Terraform and AWS, you can automate your PostgreSQL setup – cutting busywork and focusing on building, not babysitting servers.

Your setups are versioned and repeatable, AWS keeps the lights on, and you still get to make changes as your needs shift. Whether you're experimenting or running production, this approach gives you security, reliability, and a smooth path to grow. PostgreSQL's flexibility means your database can keep up as your architecture changes.

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