Infrastructure as code transforms how DynamoDB tables are provisioned, versioned, and operated. Terraform provides a complete configuration harness for DynamoDB tables alongside Lambda functions, API gateways, and other AWS resources. Using Terraform for DynamoDB is common both as a standalone NoSQL database and as a state-locking backend for the S3 remote backend.
DynamoDB is a fully managed, serverless NoSQL database service from Amazon Web Services that provides high-performance, scalable, and flexible data storage. It offers features such as automatic scaling, built-in security, and global tables for multi-region, multi-active database capabilities, while eliminating the need for manual server provisioning and management. DynamoDB is a fully managed service, meaning Amazon handles administrative tasks such as hardware provisioning, setup, configuration, and maintenance.
Why Manage DynamoDB with Terraform
Terraform lets you define your DynamoDB tables and configurations alongside other resources like Lambda functions and API gateways, creating a complete configuration harnessing all the benefits of infrastructure as code for your application.
State locking is a primary reason DynamoDB is used with Terraform. DynamoDB provides an effective mechanism for state locking in Terraform, which is crucial for preventing concurrent access to the same Terraform state file by multiple users or processes.
Scalability and performance matter for state management. DynamoDB offers high availability, scalability, and low-latency performance, making it an excellent choice for managing Terraform state.
Integration with AWS services is native. DynamoDB is an AWS service, so it integrates seamlessly with other AWS resources that may be part of your infrastructure.
Operational overhead is reduced because DynamoDB is a fully managed service, which means you don’t have to worry about provisioning, patching, or managing the underlying infrastructure.
Data model flexibility is provided. DynamoDB supports document and key-value data models, providing flexibility in how you store and retrieve data related to your Terraform state.
Automatic scaling applies to Terraform operations. DynamoDB can automatically scale to meet the demands of your Terraform operations without manual intervention.
What Terraform Brings to DynamoDB Provisioning
Terraform is an Infrastructure management tool. It facilitates automatically creating cloud resources through resource definition in the files. In the past, I would log into my cloud provider's console and click around to set up things like servers or databases. Doing it manually like that can be tedious and error-prone though. The terraform helps in overcoming this issue by automating the manual setups by defining the tasks and configuring the resources.
Features Of Terraform that facilitate:
- Terraform Simplifying Infrastructure Deployment: With Terraform, instead of clicking through a UI, you simply write down what you want to build in a description file
- It figures out how to make the necessary changes incrementally
- Manual mistakes are avoided. When doing things by hand, it's easy to misconfigure something. But Terraform won't deploy anything that doesn't match what's in the definition files
- It's collaborative. The files can be shared and tracked with version control, so the whole team knows exactly what infrastructure is being used for a project
Using Terraform for infrastructure as code seems like a huge improvement over manual setup and management.
Understanding DynamoDB Core Concepts
DynamoDB is a fully managed NoSQL database from Amazon Web Services. As a non-relational database, it allows for high scalability and performance without the complexity of running your own large database. DynamoDB supports document and key-value data models, providing flexibility in data storage and retrieval.
A major benefit of DynamoDB is automatic scaling capabilities. Based on configured throughput, DynamoDB will scale underlying resources up or down to meet demand. This removes overhead of managing infrastructure and ensures applications have needed throughput.
DynamoDB also supports in-memory caching and expiration of items to improve performance. By caching frequently accessed data in memory, read times are faster. Expiring outdated items reduces storage usage and cost.
What we will cover:
- What is DynamoDB?
- DynamoDB is a fully managed, serverless NoSQL database service from Amazon Web Services that provides high-performance, scalable, and flexible data storage. It offers features such as automatic scaling, built-in security, and global tables for multi-region, multi-active database capabilities, while eliminating the need for manual server provisioning and management.
Prerequisites and File Structure
Your file structure should be as shown below. We will use this file to define the provider and connect Terraform to our AWS Account.
Open your main.tf file and the code shown below.
The terraform {} ensures that the current Terraform configuration will use the AWS Provider from the Terraform Registry to manage infrastructure.
The provider {} ensures helps configure the specified provider. In this case, we configure the AWS Provider to use the configuration file created by the AWS CLI and to host resources in the Virginia region.
After adding this snippet, launch a terminal in the active directory and run terraform init. It will initialize the configuration directory and install the required provider on your device.
Step 1 - Set up AWS credentials
Follow these steps to create a DynamoDB table using Terraform:
- Set up AWS credentials
- Create a Terraform configuration file
- Configure AWS provider
Configuring the AWS Provider
In your Terraform configuration file, specify the AWS provider and the region you want to work with:
hcl
provider "aws" {
region = "us-west-2"
}
The provider block configures the specified provider. In this case, we configure the AWS Provider to use the configuration file created by the AWS CLI and to host resources in the Virginia region.
hcl
terraform {
required_providers {
aws = {
source = "hashicorp/aws"
version = "~> 5.0"
}
}
}
After adding this snippet, launch a terminal in the active directory and run terraform init. It will initialize the configuration directory and install the required provider.
Creating a DynamoDB Table with Terraform
Next, you can define your DynamoDB table. With Terraform, declaring resources is easy. The convention for declaring resources is shown below.
To get the AWS resource name, visit the Terraform AWS Registry. Your DynamoDB table can be set up by adding the configuration below to your main.tf file.
The snippet above shows a simple DynamoDB table declaration. It is defined in the provisioned billing mode, indicating that the table will be provisioned with a pre-defined read, write capacity.
Include DynamoDB table resource
Next, add the new DynamoDB table resource to the configuration file.
In this example, we will create one called ‘UsersTable’, using the resource awsdynamodbtable.
hcl
resource "aws_dynamodb_table" "users" {
name = "UsersTable"
billing_mode = "PROVISIONED"
read_capacity = 10
write_capacity = 5
hash_key = "userId"
attribute {
name = "userId"
type = "S"
}
tags = {
Name = "UsersTable"
}
}
Let's take a look at this basic DynamoDB table in more detail:
- billing_mode is set to PROVISIONED, with read and write capacity units defined
- readcapacity and writecapacity specify the initial read and write throughput for the table
- hash_key defines the primary key for the table. Here, it's userId which will be a string type
- The attribute block defines the schema for the table. Here, we have only the userId attribute
- The tags block assigns a tag named Name to the table for easier identification
We’ve created our first DynamoDB table in Terraform.
Table Configuration Options
| Attribute | Description | Example |
|---|---|---|
| name | Logical name of the DynamoDB table | UsersTable |
| billing_mode | Billing mode for the table | PROVISIONED or PAYPERREQUEST |
| read_capacity | Read capacity units for provisioned mode | 10 |
| write_capacity | Write capacity units for provisioned mode | 5 |
| hash_key | Primary partition key name | userId |
| attribute | Schema definition for key attributes | name = "userId", type = "S" |
Billing mode comparison:
| Mode | Provisioning | Use Case |
|---|---|---|
| PROVISIONED | Pre-defined read, write capacity | Predictable workloads, cost control |
| PAYPERREQUEST | On-demand scaling | Variable workloads, low latency |
Managing Tables and Items
How to manage tables and items using Terraform?
To add items to your existing DynamoDB table, you can use the awsdynamodbtable_item resource.
Terraform lets you define infrastructure like databases as code. This makes it easy to version control and share with others. In this article, I'll walk through the steps to set up a Terraform file and define a DynamoDB table in it. Then I'll apply the plan to create the real table in AWS. Following along will show you a hands-on example of using Terraform to manage infrastructure as code. The end result will be a DynamoDB table defined in a Terraform config that can be reused and shared.
Scaling and Updates in Practice
Terraform used the selected providers to generate the following execution plan. Resource actions are indicated with the following symbols:
~ update in-place
Terraform will perform the following actions:
```hcl
awsdynamodbtable.environment will be updated in-place
~ resource "awsdynamodbtable" "environment" {
~ billingmode = "PAYPERREQUEST" -> "PROVISIONED"
id = "environmentpartiallyclearlypolishedmoth"
name = "environmentpartiallyclearlypolishedmoth"
~ readcapacity = 0 -> 5
tags = {}
~ write_capacity = 0 -> 2
# (5 unchanged attributes hidden)
# (4 unchanged blocks hidden)
}
```
Plan: 0 to add, 1 to change, 0 to destroy.
Do you want to perform these actions in workspace "learn-terraform-aws-dynamodb-scale"?
Terraform will perform the actions described above. Only 'yes' will be accepted to approve.
Enter a value: yes
awsdynamodbtable.environment: Modifying..
This demonstrates in-place updates for billing mode changes from PAYPERREQUEST to PROVISIONED with new read and write capacity.
Production Best Practices
DynamoDB is one of the most common AWS services managed with Terraform, both as a standalone NoSQL database and as a state-locking backend for the S3 remote backend.
In this article, you will learn how to create and manage DynamoDB tables with Terraform, configure Global Secondary Indexes and streams, set up state locking with an S3 backend, and apply production best practices. We will discuss why you might want to use Terraform to manage DynamoDB in the first place.
State locking with DynamoDB ensures concurrent Terraform runs do not corrupt state. The managed nature of DynamoDB eliminates manual server provisioning and maintenance. Automatic scaling removes manual capacity planning for both application tables and state tables.
Conclusion
Terraform AWS DynamoDB workflows combine declarative infrastructure with a fully managed serverless NoSQL service. The provider configuration establishes a secure connection to AWS, while the awsdynamodbtable resource defines schema, billing mode, throughput, and tags as code. Provisioned billing mode with explicit readcapacity and writecapacity offers predictable cost control, while PAYPERREQUEST provides elasticity for variable demand. State locking via DynamoDB protects Terraform state when used with an S3 remote backend, leveraging DynamoDB’s high availability, low latency, and automatic scaling. Managing items through awsdynamodbtableitem extends the as-code model to data seeding. The incremental planning engine shows precise in-place updates for billingmode and capacity changes, enabling safe production scaling. Together, these capabilities deliver version-controlled, collaborative, and repeatable DynamoDB deployments without manual console operations.