Learn MuleSoft & AWS: a Guide to Cloud Mule ESB Integration

Explore Amazon S3, a serverless data store that stores objects in buckets with unique keys for fast, scalable access from anywhere. Learn about permissions, versioning, and right once read many.

Compare SFTP servers with Amazon S3 to understand durability, high availability, and scalable storage. Use APIs, CLI tools, and webhooks for automation, encryption, access management, and versioning.

Learn how to install and configure the Amazon S3 connector in MuleSoft, create a project, and connect to AWS S3 to store and access data from anywhere.

Learn how to create an Amazon S3 bucket using MuleSoft flows, configure region and bucket name, test with Postman, and understand bucket naming rules for AWS S3.

Create an Amazon S3 object by configuring the bucket name, object key, and ACL in a MuleSoft flow, then test uploading payload via Postman.

Learn how to retrieve Amazon S3 objects by building a flow, configuring bucket name and object key from requests, logging and transforming responses, and returning the object content.

Learn to list objects in an Amazon S3 bucket and delete selected objects using a flow, leveraging object keys and metadata, with logging and a final response payload.

Discover Amazon Simple Queue Service, a managed messaging system that stores and retrieves messages between software components, enabling secure, durable, highly available loosely coupled architecture via standard and FIFO queues.

Explore the main differences between enterprise messaging systems and Amazon SQS, highlighting cloud benefits such as no administrative overhead, scalability, durability, and reduced costs.

Explore how to implement reliable, asynchronous messaging with the MuleSoft AWS SQS connector, enabling queueing, decoupled microservices, one-way and request-response patterns, and scalable batch job distribution.

Learn how to create an Amazon SQS queue within a MuleSoft and AWS integration, configure the connector, test the connection, and troubleshoot region endpoints to enable queue operations.

Learn to send messages to an Amazon SQS queue with a MuleSoft flow, set delay seconds, define message body and attributes, and test with Postman.

Learn to get the approximate number of messages in an Amazon SQS queue using a dedicated flow and Postman to verify the pending message count.

Implement a request‑response messaging pattern using Amazon SQS by configuring the receive messages operation, polling, and logging, then transform and validate message bodies during deployment.

Explore Amazon Simple Notification Service as a publish–subscribe messaging system with topics and subscribers for app-to-app and app-to-person communication, including push notifications and no polling.

Leverage Amazon Simple Notification Service as a fully managed pub/sub that scales automatically. It requires zero infrastructure, supports emails, SMS, mobile push, and Lambda integrations.

Explore Amazon Simple Notification Service's publish-subscribe messaging to topics for app-to-app and end-user notifications, including mobile push and emails, and learn to configure and test the SNS connector in MuleSoft.

Learn to create Amazon SNS topics, configure a test connection, and validate topic creation through a Postman workflow, preparing for subsequent AWS SNS topic operations.

Subscribe a queue to an Amazon SNS topic by configuring topic, protocol, and endpoint in a MuleSoft flow, then test with Postman and confirm via email.

Learn how to publish messages to an Amazon SNS topic using MuleSoft ESB, configuring topic ARN and subject, building the payload, and validating delivery via Postman and console logs.

Explore Amazon DynamoDB, a fully managed sequel database service that delivers performance, scalability, no server provisioning, on-demand backups for retention, and high availability and durability in a cloud native context.

Compare NoSQL options such as Hadoop, MongoDB, and Cassandra with Amazon DynamoDB, a cloud-native managed key-value store optimized for low latency and auto scaling.

Learn to integrate Amazon DynamoDB with MuleSoft using the DynamoDB connector to connect to the DynamoDB API, create scalable tables, and manage access with IAM.

Create Amazon DynamoDB tables by defining attribute definitions and key schemas, including partition and sort keys, set capacity, deploy, and validate creation with a client request.

Create a DynamoDB table with a global secondary index, defining attribute definitions, key schemas, and provisioned throughput to support queries on user id, game title, and top score.

Describe building a MuleSoft flow to describe DynamoDB tables, deploy the app, and use Postman to retrieve attributes, primary key, throughput, and creation date.

Create a mule flow to insert records into an Amazon DynamoDB table named employees by building an insert record path, composing an item object with employee ID, first name, last name, email, country, and role, and performing a put item operation using a partition key and sort key. Deploy and test with Postman, verify in the AWS console, generate random IDs, and troubleshoot region mismatches while extending the approach to a second table using a global secondary index.

Insert records into an Amazon DynamoDB games table using the put item operation, build a payload with user id, title, top score, wins, losses, and validate the insertion via Postman.

Learn to retrieve items from an Amazon DynamoDB table using a MuleSoft flow. Configure the get item operation with a partition key and sort key, and validate results with Postman.

Learn to update existing items in a DynamoDB table using the update item operation. Configure the table name, primary keys, and new email and role values with variable transformers.

Explore deleting items in an Amazon DynamoDB table using a MuleSoft flow, including configuring the delete item operation, table name, and primary key (partition and sort keys).

Learn to get items from an Amazon DynamoDB table using a filter in a MuleSoft flow, configuring table name, filter expression, and query parameters, then deploy and test with Postman.

Create a GitHub repository, initialize a local repo, run git status, commit changes, set remote origin, and push to the remote for your MuleSoft and AWS integration project.