Reserved capacity in DynamoDB - Mini Project: Build & Apply

Reserved Capacity Management in DynamoDB

📖 Scenario: You are managing a DynamoDB table for an online store. To save costs and improve performance, you want to reserve capacity units for your table.

🎯 Goal: Build a simple DynamoDB reserved capacity setup by defining a table with provisioned throughput and then configuring reserved capacity units.

📋 What You'll Learn

Create a DynamoDB table named Products with a primary key ProductID of type string

Set the provisioned throughput with ReadCapacityUnits as 5 and WriteCapacityUnits as 5

Create a reserved capacity configuration with ReservedReadCapacityUnits as 10 and ReservedWriteCapacityUnits as 10

Add a tag Environment with value Production to the table

💡 Why This Matters

🌍 Real World

Reserved capacity is used in real businesses to reduce costs by committing to a certain level of database throughput, ensuring predictable performance and pricing.

💼 Career

Understanding reserved capacity is important for cloud database administrators and developers to optimize costs and performance in AWS DynamoDB.

1

Create the DynamoDB table with primary key

Create a DynamoDB table named Products with a primary key called ProductID of type string.

DynamoDB

# Define the DynamoDB table with primary key
# Your code here

Hint

Use TableName to name the table and define AttributeDefinitions and KeySchema for the primary key.

2

Set provisioned throughput for the table

Add provisioned throughput to the Products table with ReadCapacityUnits set to 5 and WriteCapacityUnits set to 5.

DynamoDB

TableName: Products
AttributeDefinitions:
  - AttributeName: ProductID
    AttributeType: S
KeySchema:
  - AttributeName: ProductID
    KeyType: HASH
ProvisionedThroughput:
  # Set read and write capacity units here
  # Your code here

Hint

Provisioned throughput controls how many reads and writes your table can handle per second.

3

Configure reserved capacity units

Add reserved capacity configuration with ReservedReadCapacityUnits set to 10 and ReservedWriteCapacityUnits set to 10 for the Products table.

DynamoDB

TableName: Products
AttributeDefinitions:
  - AttributeName: ProductID
    AttributeType: S
KeySchema:
  - AttributeName: ProductID
    KeyType: HASH
ProvisionedThroughput:
  ReadCapacityUnits: 5
  WriteCapacityUnits: 5
ReservedCapacity:
  # Add reserved read and write capacity units here
  # Your code here

Hint

Reserved capacity helps you save money by committing to a certain level of throughput.

4

Add a tag to the table

Add a tag to the Products table with key Environment and value Production.

DynamoDB

TableName: Products
AttributeDefinitions:
  - AttributeName: ProductID
    AttributeType: S
KeySchema:
  - AttributeName: ProductID
    KeyType: HASH
ProvisionedThroughput:
  ReadCapacityUnits: 5
  WriteCapacityUnits: 5
ReservedCapacity:
  ReservedReadCapacityUnits: 10
  ReservedWriteCapacityUnits: 10
Tags:
  # Add the Environment tag here
  # Your code here

Hint

Tags help you organize and identify your AWS resources.

Practice

1. What is the main benefit of using Reserved Capacity in DynamoDB?

easy

A. It automatically scales the database up and down.

B. It backs up data to another region.

C. It saves money by pre-paying for database capacity.

D. It encrypts data at rest.

Solution

1. Step 1: Understand Reserved Capacity purpose

   Reserved Capacity allows you to pay upfront for a set amount of database throughput, which reduces costs compared to on-demand pricing.

2. Step 2: Compare with other options

   Scaling, backup, and encryption are separate features and not related to Reserved Capacity.

3. Final Answer:

   It saves money by pre-paying for database capacity. -> Option C

4. Quick Check:

   Reserved Capacity = Cost saving by pre-payment [OK]

Hint: Reserved Capacity means paying upfront to save money [OK]

Common Mistakes:

• Confusing Reserved Capacity with auto-scaling
• Thinking it manages backups or encryption
• Assuming it is a query or API feature

2. Which of the following is the correct way to purchase Reserved Capacity for DynamoDB?

easy

A. Through AWS Management Console or AWS CLI

B. Using a SQL query in DynamoDB console

C. By calling a DynamoDB API operation

D. By enabling a setting in the table properties

Solution

1. Step 1: Identify how Reserved Capacity is bought

   Reserved Capacity is purchased via the AWS Management Console or AWS CLI, not through database queries or API calls.

2. Step 2: Eliminate incorrect methods

   SQL queries and table property settings do not handle Reserved Capacity purchases.

3. Final Answer:

   Through AWS Management Console or AWS CLI -> Option A

4. Quick Check:

   Reserved Capacity purchase = Console or CLI [OK]

Hint: Buy Reserved Capacity only via AWS Console or CLI [OK]

Common Mistakes:

• Trying to buy Reserved Capacity with API calls
• Assuming it can be set in table properties
• Confusing it with query commands

3. If a company has a steady workload of 1000 read capacity units and 500 write capacity units, which option best describes the cost benefit of Reserved Capacity?

medium

A. Reserved Capacity saves money by pre-paying for steady usage.

B. Reserved Capacity will cost more than on-demand pricing.

C. Reserved Capacity only applies to burst workloads.

D. Reserved Capacity automatically adjusts capacity units.

Solution

1. Step 1: Understand workload type

   The workload is steady and predictable, which is ideal for Reserved Capacity.

2. Step 2: Match Reserved Capacity benefits

   Reserved Capacity saves money by pre-paying for steady usage, unlike on-demand which is more expensive for constant loads.

3. Final Answer:

   Reserved Capacity saves money by pre-paying for steady usage. -> Option A

4. Quick Check:

   Steady workload + Reserved Capacity = Cost saving [OK]

Hint: Reserved Capacity suits steady workloads to save money [OK]

Common Mistakes:

• Thinking Reserved Capacity is for bursty or variable workloads
• Assuming it auto-scales capacity units
• Believing it costs more than on-demand for steady use

4. A developer tries to buy Reserved Capacity using a DynamoDB API call but gets an error. What is the likely cause?

medium

A. Reserved Capacity requires table to be in on-demand mode.

B. Reserved Capacity cannot be purchased via API calls.

C. The API call syntax is incorrect.

D. Reserved Capacity is only for global tables.

Solution

1. Step 1: Check how Reserved Capacity is purchased

   Reserved Capacity is bought only through AWS Console or CLI, not through DynamoDB API calls.

2. Step 2: Understand error cause

   Trying to buy it via API results in error because the API does not support this operation.

3. Final Answer:

   Reserved Capacity cannot be purchased via API calls. -> Option B

4. Quick Check:

   Reserved Capacity purchase method = Console/CLI only [OK]

Hint: Reserved Capacity purchase via API causes error [OK]

Common Mistakes:

• Assuming API calls can buy Reserved Capacity
• Blaming syntax errors without checking purchase method
• Confusing Reserved Capacity with table modes

5. A company has unpredictable spikes in traffic but wants to save costs using Reserved Capacity. What is the best approach?

hard

A. Reserved Capacity automatically adjusts to spikes, so buy any amount.

B. Buy Reserved Capacity for the peak traffic to cover all spikes.

C. Use only on-demand capacity to handle spikes efficiently.

D. Buy Reserved Capacity for the average baseline and use on-demand for spikes.

Solution

1. Step 1: Analyze workload pattern

   The workload has unpredictable spikes, so buying Reserved Capacity for peak would be costly and wasteful.

2. Step 2: Combine Reserved and on-demand

   Buying Reserved Capacity for the steady baseline and using on-demand for spikes balances cost and flexibility.

3. Final Answer:

   Buy Reserved Capacity for the average baseline and use on-demand for spikes. -> Option D

4. Quick Check:

   Baseline Reserved + on-demand spikes = Cost efficient [OK]

Hint: Reserve baseline, use on-demand for spikes to save money [OK]

Common Mistakes:

• Buying Reserved Capacity for peak traffic wastes money
• Relying only on on-demand increases cost
• Thinking Reserved Capacity auto-scales with spikes