How to design data storage and access for cost-effective DynamoDB pricing?

 In the context of AWS, here are the steps given:-

Provisioned throughput capacity optimization

You can use the DynamoDB’s auto-scaling for automatically adjust the provisioned read and write capacity automatically based on the demand.

You can also implement a caching mechanism to reduce the number of read operations.

demands capacity usage

You can use the on-demand capacity model for workloads with unpredictable traffic patterns if you are unsure about the required throughput capacity.

You can monitor and analyze the use of the pattern by using the AWS cloud watch metrics to identify the opportunities for switching between provisioned and on-demand capacity modes.

Storage optimization

You should choose the right data types and the data model to minimise storage costs.

You can also implement data retention policies and archival strategies for moving the infrequently accessed data transfer storage solution like Amazon S3 using tools such as AWS glue or AWS data pipeline.

Here Is the example code given in Python programming language by using the AWS SDK to illustrate how you can configure the DynamoDB auto scaling:-

Import boto3

# Initialize DynamoDB client

Dynamodb = boto3.client(‘dynamodb’)

# Configure auto scaling for a table

Table_name = ‘YourTableName’

Read_capacity_units = 5  # Initial provisioned read capacity

Write_capacity_units = 5  # Initial provisioned write capacity

# Configure auto scaling policies

Read_scaling_policy = {

    ‘TargetTrackingScalingPolicyConfiguration’: {

        ‘TargetValue’: 50,  # Target utilization percentage

        ‘PredefinedMetricSpecification’: {

            ‘PredefinedMetricType’: ‘DynamoDBReadCapacityUtilization’

        }

    }

}

Write_scaling_policy = {

    ‘TargetTrackingScalingPolicyConfiguration’: {

        ‘TargetValue’: 50,  # Target utilization percentage

        ‘PredefinedMetricSpecification’: {

            ‘PredefinedMetricType’: ‘DynamoDBWriteCapacityUtilization’

        }

    }

}

# Enable auto scaling for read and write capacity

Dynamodb.update_table(

    TableName=table_name,

    ProvisionedThroughput={

        ‘ReadCapacityUnits’: read_capacity_units,

        ‘WriteCapacityUnits’: write_capacity_units

    },

    BillingMode=’PROVISIONED’,  # Ensure provisioned mode is used

    GlobalSecondaryIndexUpdates=[],  # Update if applicable

    StreamSpecification={},  # Configure streams if needed

    SSESpecification={},  # Configure encryption if needed

    # Add Scaling Policies

    ScalingPolicies=[

        {

            ‘PolicyName’: ‘ReadScalingPolicy’,

            ‘TargetTrackingScalingPolicyConfiguration’: read_scaling_policy

        },

        {

            ‘PolicyName’: ‘WriteScalingPolicy’,

            ‘TargetTrackingScalingPolicyConfiguration’: write_scaling_policy

        }

    ]

)

Here is the same example given by using the java programming language:-

Import com.amazonaws.services.dynamodbv2.AmazonDynamoDB;

Import com.amazonaws.services.dynamodbv2.AmazonDynamoDBClientBuilder;

Import com.amazonaws.services.dynamodbv2.model.*;

Public class DynamoDBAutoScalingExample {

    Public static void main(String[] args) {

        // Initialize DynamoDB client

        AmazonDynamoDB dynamoDBClient = AmazonDynamoDBClientBuilder.standard().build();

        // Configure auto scaling policies

        AutoScalingPolicy readScalingPolicy = new AutoScalingPolicy()

                .withTargetTrackingScalingPolicyConfiguration(new AutoScalingTargetTrackingScalingPolicyConfiguration()

                        .withTargetValue(50.0)  // Target utilization percentage

                        .withPredefinedMetricSpecification(new PredefinedMetricSpecification()

                                .withPredefinedMetricType(“DynamoDBReadCapacityUtilization”)))

                .withPolicyName(“ReadScalingPolicy”);

        AutoScalingPolicy writeScalingPolicy = new AutoScalingPolicy()

                .withTargetTrackingScalingPolicyConfiguration(new AutoScalingTargetTrackingScalingPolicyConfiguration()

                        .withTargetValue(50.0)  // Target utilization percentage

                        .withPredefinedMetricSpecification(new PredefinedMetricSpecification()

                                .withPredefinedMetricType(“DynamoDBWriteCapacityUtilization”)))

                .withPolicyName(“WriteScalingPolicy”);

        // Enable auto scaling for a DynamoDB table

        String tableName = “YourTableName”;

        UpdateTableRequest updateTableRequest = new UpdateTableRequest()

                .withTableName(tableName)

                .withProvisionedThroughput(new ProvisionedThroughput()

                        .withReadCapacityUnits(5L)  // Initial provisioned read capacity

                        .withWriteCapacityUnits(5L))  // Initial provisioned write capacity

                .withBillingMode(BillingMode.PROVISIONED)  // Ensure provisioned mode is used

                .withScalingPolicy(new AutoScalingSettings()

                        .withScalingRoleArn(“YourScalingRoleARN”)  // Specify the IAM role ARN for auto scaling

                        .withTargetTrackingScalingPolicies(readScalingPolicy, writeScalingPolicy));

        dynamoDBClient.updateTable(updateTableRequest);

    }

}