Burst capacity in DynamoDB - Mini Project: Build & Apply

Understanding Burst Capacity in DynamoDB

📖 Scenario: You are managing a DynamoDB table for a small online store. The store experiences sudden spikes in traffic during sales events. To handle these spikes smoothly, you want to understand and simulate how DynamoDB's burst capacity works.

🎯 Goal: Build a simple DynamoDB table setup and simulate read capacity usage to observe burst capacity behavior.

📋 What You'll Learn

Create a DynamoDB table named SalesData with a primary key OrderID of type string.

Set the provisioned read capacity units to 5.

Create a variable read_requests to simulate the number of read requests during a spike.

Write a query or logic to check if the read_requests exceed the provisioned capacity and simulate burst capacity usage.

💡 Why This Matters

🌍 Real World

Online stores and applications often face sudden traffic spikes. Understanding burst capacity helps maintain performance during these spikes.

💼 Career

Database administrators and cloud engineers need to manage capacity and optimize costs by leveraging burst capacity in DynamoDB.

1

Create DynamoDB Table

Create a DynamoDB table named SalesData with a primary key called OrderID of type string and set the provisioned read capacity units to 5.

DynamoDB

TableName: 'SalesData',
KeySchema: [{ AttributeName: 'OrderID', KeyType: 'HASH' }],
AttributeDefinitions: [{ AttributeName: 'OrderID', AttributeType: 'S' }],
ProvisionedThroughput: { ReadCapacityUnits: 5, WriteCapacityUnits: 5 }
// Your code here

Hint

Use the TableName, KeySchema, and ProvisionedThroughput properties to define the table.

2

Simulate Read Requests

Create a variable called read_requests and set it to 10 to simulate a spike in read requests.

DynamoDB

const params = {
  TableName: 'SalesData',
  KeySchema: [
    { AttributeName: 'OrderID', KeyType: 'HASH' }
  ],
  AttributeDefinitions: [
    { AttributeName: 'OrderID', AttributeType: 'S' }
  ],
  ProvisionedThroughput: {
    ReadCapacityUnits: 5,
    WriteCapacityUnits: 5
  }
};

// Your code here

Hint

Use const read_requests = 10; to simulate the spike.

3

Check Burst Capacity Usage

Write an if statement that checks if read_requests is greater than the provisioned read capacity units 5. Inside the if, create a variable burst_used and set it to true. Otherwise, set burst_used to false.

DynamoDB

const params = {
  TableName: 'SalesData',
  KeySchema: [
    { AttributeName: 'OrderID', KeyType: 'HASH' }
  ],
  AttributeDefinitions: [
    { AttributeName: 'OrderID', AttributeType: 'S' }
  ],
  ProvisionedThroughput: {
    ReadCapacityUnits: 5,
    WriteCapacityUnits: 5
  }
};

const read_requests = 10;

// Your code here

Hint

Use if (read_requests > 5) to check the condition and set burst_used accordingly.

4

Add Burst Capacity Explanation Comment

Add a comment explaining that burst_used indicates if the table is using burst capacity due to high read requests.

DynamoDB

const params = {
  TableName: 'SalesData',
  KeySchema: [
    { AttributeName: 'OrderID', KeyType: 'HASH' }
  ],
  AttributeDefinitions: [
    { AttributeName: 'OrderID', AttributeType: 'S' }
  ],
  ProvisionedThroughput: {
    ReadCapacityUnits: 5,
    WriteCapacityUnits: 5
  }
};

const read_requests = 10;

let burst_used;
if (read_requests > 5) {
  burst_used = true;
} else {
  burst_used = false;
}

// Your code here

Hint

Add a clear comment above or below the burst_used variable explaining its meaning.

Practice

1. What is the main purpose of burst capacity in DynamoDB?

easy

A. To backup data automatically

B. To permanently increase table throughput

C. To handle sudden spikes in traffic smoothly

D. To reduce storage costs

Solution

1. Step 1: Understand burst capacity concept

   Burst capacity allows DynamoDB to use unused capacity from earlier low traffic periods.

2. Step 2: Identify its main use

   This helps handle sudden traffic spikes smoothly without extra setup.

3. Final Answer:

   To handle sudden spikes in traffic smoothly -> Option C

4. Quick Check:

   Burst capacity = handle spikes [OK]

Hint: Burst capacity smooths sudden traffic spikes [OK]

Common Mistakes:

• Thinking burst capacity permanently increases throughput
• Confusing burst capacity with backup or storage features
• Assuming manual code is needed to use burst capacity

2. Which of the following statements about DynamoDB burst capacity is syntactically correct?

easy

A. BurstCapacity: enabled

B. ProvisionedThroughput: { ReadCapacityUnits: 5, WriteCapacityUnits: 5 }

C. EnableBurstCapacity = true

D. SetBurstCapacity(5)

Solution

1. Step 1: Check valid DynamoDB syntax

   ProvisionedThroughput with ReadCapacityUnits and WriteCapacityUnits is valid for table setup.

2. Step 2: Identify invalid options

   Options B, C, and D are not valid DynamoDB syntax or parameters.

3. Final Answer:

   <code>ProvisionedThroughput: { ReadCapacityUnits: 5, WriteCapacityUnits: 5 }</code> -> Option B

4. Quick Check:

   Valid syntax = ProvisionedThroughput: { ReadCapacityUnits: 5, WriteCapacityUnits: 5 } [OK]

Hint: Only ProvisionedThroughput syntax is valid here [OK]

Common Mistakes:

• Assuming burst capacity needs explicit enabling syntax
• Using incorrect parameter names
• Confusing configuration with method calls

3. Consider a DynamoDB table with provisioned read capacity of 10 units. The table has been idle for a while, accumulating unused capacity. Suddenly, a spike causes 15 read requests per second. What will happen?

medium

A. The table will reject all requests during the spike

B. The table will throttle all requests above 10 units immediately

C. The table will automatically increase provisioned capacity to 15 units

D. The table will use burst capacity to handle some requests above 10 units

Solution

1. Step 1: Understand idle capacity accumulation

   Unused capacity from idle periods accumulates as burst capacity credits.

2. Step 2: Apply burst capacity during spike

   When requests exceed provisioned units, DynamoDB uses burst capacity to handle some extra requests smoothly.

3. Final Answer:

   The table will use burst capacity to handle some requests above 10 units -> Option D

4. Quick Check:

   Burst capacity handles spikes above provisioned [OK]

Hint: Burst capacity covers temporary spikes above provisioned [OK]

Common Mistakes:

• Thinking DynamoDB instantly throttles above provisioned units
• Assuming automatic permanent capacity increase
• Believing all requests are rejected during spikes

4. You notice your DynamoDB table is throttling requests during a traffic spike, even though it was idle before. What is the most likely cause?

medium

A. Burst capacity credits were already used up before the spike

B. Provisioned throughput is set too high

C. Burst capacity must be manually enabled

D. The table is in on-demand mode

Solution

1. Step 1: Analyze burst capacity usage

   Burst capacity depends on unused capacity credits accumulated during idle times.

2. Step 2: Reason about throttling cause

   If credits are used up, the table cannot handle spikes beyond provisioned throughput, causing throttling.

3. Final Answer:

   Burst capacity credits were already used up before the spike -> Option A

4. Quick Check:

   Throttling = no burst credits left [OK]

Hint: No burst credits means throttling during spikes [OK]

Common Mistakes:

• Thinking burst capacity needs manual enabling
• Assuming high provisioned throughput causes throttling
• Confusing on-demand mode with provisioned burst capacity

5. A DynamoDB table has a provisioned write capacity of 20 units. It was idle for 10 minutes, then suddenly receives 50 write requests per second for 1 minute. How does burst capacity affect this scenario?

hard

A. Burst capacity allows some requests above 20 units to succeed temporarily

B. Burst capacity automatically increases provisioned capacity to 50 units

C. Burst capacity allows all 50 requests to succeed without throttling

D. Burst capacity does not apply to write requests

Solution

1. Step 1: Understand burst capacity accumulation

   Idle time accumulates unused write capacity credits that can be used in bursts.

2. Step 2: Apply burst capacity during spike

   During the spike, burst capacity allows handling some requests above provisioned 20 units temporarily, but not all 50.

3. Final Answer:

   Burst capacity allows some requests above 20 units to succeed temporarily -> Option A

4. Quick Check:

   Burst capacity = temporary extra writes above provisioned [OK]

Hint: Burst capacity helps some writes above provisioned temporarily [OK]

Common Mistakes:

• Assuming burst capacity handles all spike requests fully
• Thinking burst capacity increases provisioned throughput permanently
• Believing burst capacity applies only to reads