What is a serverless data pipeline?

A serverless data pipeline is a cloud-native workflow that ingests, processes, transforms, and stores data using managed cloud services without managing servers.

How is serverless different from traditional ETL?

Traditional ETL often uses scheduled batch jobs and managed infrastructure, while serverless pipelines respond to events and scale automatically.

What is event-driven processing?

Event-driven processing means pipeline actions begin when an event occurs, such as a file upload to Amazon S3 or a message arriving in Amazon SQS.

Will I learn how to process files?

Yes. You will learn how to process uploaded JSON and CSV files using AWS Lambda and Python.

Why are queues important in serverless pipelines?

Queues help decouple services, buffer messages, support asynchronous processing, and improve reliability when downstream systems are slow or unavailable.

What is a dead letter queue?

A dead letter queue stores messages that fail processing after retry attempts, helping teams inspect failures and prevent message loss.

Will this course cover monitoring and reliability?

Yes. You will learn about CloudWatch logs, alarms, retries, failure recovery, FIFO queues, deduplication, and observability in serverless systems.

How will this course help my career?

This course helps you build practical skills for cloud data engineering, serverless development, data pipeline operations, and cloud architecture roles.

What will I get if I purchase the Certificate?

When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Serverless Data Pipelines

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Serverless Data Pipelines

Q: What AWS services are covered in this course?

The course covers AWS Lambda, Amazon S3, Amazon SQS, Amazon CloudWatch, AWS Step Functions, and Amazon DynamoDB.

Instructeur : Edureka

Inclus avec En savoir plus

Demander à Coursera

3 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Débutant

Expérience recommandée

7 heures à compléter

Planning flexible

Apprenez à votre propre rythme

3 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Débutant

Expérience recommandée

7 heures à compléter

Planning flexible

Apprenez à votre propre rythme

Ce que vous apprendrez

Design Event-Driven Serverless Pipelines using AWS Lambda, Amazon S3, and Amazon SQS for scalable data processing.
Build Data Ingestion Workflows to collect and process file-based and event-based data in cloud-native systems.
Transform JSON and CSV Data using AWS Lambda and Python to generate clean, processed output files.
Monitor and Optimize Serverless Pipelines using retries, DLQs, CloudWatch alarms, Step Functions, and DynamoDB.

Compétences que vous acquerrez

Catégorie : Performance Metric
Catégorie : Extract, Transform, Load
Catégorie : Cloud Security
Catégorie : Serverless Computing
Catégorie : Continuous Monitoring
Catégorie : Site Reliability Engineering
Catégorie : Data Processing
Catégorie : Data Transformation
Catégorie : Data Pipelines
Catégorie : Cloud Computing
Catégorie : Event Monitoring
Catégorie : Security Management
Catégorie : Data Preprocessing
Catégorie : Data Engineering

Outils que vous découvrirez

Catégorie : Amazon Web Services
Catégorie : Amazon CloudWatch
Catégorie : Cloud Storage
Catégorie : AWS Identity and Access Management (IAM)
Catégorie : Amazon DynamoDB
Catégorie : Amazon S3

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Il y a 3 modules dans ce cours

Build practical skills to design, deploy, and operate cloud-native data pipelines using serverless services and event-driven architectures. In this course, you will learn how modern organizations process data without managing servers, using scalable services such as AWS Lambda, Amazon S3, Amazon SQS, Amazon CloudWatch, AWS Step Functions, and Amazon DynamoDB.

You will begin by exploring the foundations of serverless computing and event-driven data pipelines. You will understand how serverless systems differ from traditional ETL workflows, how events trigger processing, and how queues support asynchronous communication between services. Next, you will learn how to build serverless ingestion and transformation workflows. You will process uploaded JSON and CSV files, apply lightweight ETL logic using Python, generate processed outputs, and address common challenges such as validation errors, inconsistent records, and schema changes. The course then focuses on reliability, monitoring, and production deployment. You will explore retry handling, dead letter queues, FIFO queues, deduplication, CloudWatch alarms, workflow orchestration, persistent storage, cost optimization, and operational best practices. Finally, you will apply your learning through hands-on demonstrations and assessments that help you design reliable, scalable, and production-ready serverless data pipelines. By the end of this course, you will be able to: -Design event-driven serverless data pipeline architectures -Build ingestion workflows using AWS Lambda, Amazon S3, and Amazon SQS -Process and transform JSON and CSV data using Python -Implement retry handling, dead letter queues, and failure recovery patterns -Monitor, optimize, and deploy production-ready serverless pipelines This course is ideal for learners who want to build practical cloud data engineering skills and understand how serverless services support scalable, reliable, and cost-efficient data processing. Join us to develop the technical and architectural skills required to build modern serverless data pipelines for real-world cloud environments.

Build a foundation in serverless computing and event-driven architectures by understanding how modern data pipelines operate. This module focuses on core components, asynchronous processing, and queue-based systems—enabling scalable and reliable data workflows.

Inclus

11 vidéos5 lectures2 devoirs

11 vidéosTotal 45 minutes

Course Introduction4 minutes
Exploring the Fundamentals of Serverless Computing3 minutes
Understanding Components of Modern Data Pipelines 5 minutes
Comparing Traditional ETL and Serverless Pipelines 3 minutes
Demonstration: Deploying a Basic AWS Lambda Function Using Python 6 minutes
Demonstration: Triggering Lambda Through S3 File Upload Events 5 minutes
Understanding Event-Driven Architecture Patterns4 minutes
Managing Asynchronous Processing with Queues 3 minutes
Evaluating Reliability in Distributed Event Systems 3 minutes
Demonstration: Sending and Processing Events with Amazon SQS 5 minutes
Demonstration: Building a Queue-Based Event Processing Pipeline 5 minutes

5 lecturesTotal 50 minutes

Course Overview10 minutes
Understanding Failure Cascades in Serverless Pipelines10 minutes
Analyzing Real-World Applications of Serverless Data Pipelines10 minutes
Examining Failure Handling in Event-Driven Architectures 10 minutes
Navigating Scalability Bottlenecks in Distributed Pipeline Systems10 minutes

2 devoirsTotal 21 minutes

Foundations of Serverless and Event-Driven Pipelines 15 minutes
Introduction to Serverless Data Pipelines 6 minutes

Develop skills in data ingestion and transformation workflows using serverless technologies. This module covers scalable pipeline design, structured data processing, and lightweight ETL—ensuring efficient and consistent data handling.

Inclus

10 vidéos4 lectures2 devoirs

10 vidéosTotal 35 minutes

Designing Scalable Data Ingestion Architectures4 minutes
Processing File-Based and Event-Based Data3 minutes
Analyzing Common Failures in Data Ingestion Pipelines 3 minutes
Demonstration: Building an S3-Based Data Ingestion Pipeline4 minutes
Demonstration: Processing Uploaded JSON Data Using Lambda5 minutes
Transforming Data in Cloud Pipelines3 minutes
Processing Structured and Semi-Structured Data3 minutes
Optimizing Lightweight ETL with Python3 minutes
Demonstration: Cleaning and Transforming CSV Data Using Lambda4 minutes
Demonstration: Generating Processed Output Files from Raw Data5 minutes

4 lecturesTotal 40 minutes

Exploring Reliability Patterns in Data Ingestion Pipelines10 minutes
Optimizing Structured Collection in Modern Pipelines10 minutes
Controlling Data Consistency in Distributed Systems 10 minutes
Managing Schema Evolution in Modern Data Pipelines10 minutes

2 devoirsTotal 21 minutes

Serverless Data Ingestion and Transformation 15 minutes
Serverless Data Ingestion and Transformation 6 minutes

Strengthen your ability to build reliable serverless pipelines by focusing on monitoring, failure handling, and deployment. This module covers observability, retry mechanisms, and end-to-end workflows—ensuring scalable and resilient systems.

Inclus

11 vidéos5 lectures2 devoirs

11 vidéosTotal 41 minutes

Investigating Reliability Challenges in Serverless Systems3 minutes
Managing Retry and Failure Recovery Mechanisms4 minutes
Evaluating Observability in Event-Driven Pipelines3 minutes
Demonstration: Understanding FIFO Queues and Deduplication4 minutes
Demonstration: Creating CloudWatch Alarms for Pipeline Failure Detection 4 minutes
Building End-to-End Pipeline Architectures5 minutes
Managing Data Flow Across Serverless Services3 minutes
Optimizing Cost and Performance in Cloud Pipelines3 minutes
Demonstration: Orchestrating Multi-Step Workflows with AWS Step Functions 5 minutes
Demonstration: Persisting Pipeline Results Using Amazon DynamoDB 5 minutes
Course Summary3 minutes

5 lecturesTotal 70 minutes

Exploring Failure Handling in Data Ingestion Pipelines 10 minutes
Handling Failed Events with Dead Letter Queues10 minutes
Analyzing Operational Complexity in Serverless Data Systems10 minutes
Investigating Performance and Security Practices in Serverless Pipelines10 minutes
Practice Project: Serverless Data Pipeline Design and Implementation Strategy30 minutes

2 devoirsTotal 36 minutes

End Course Knowledge Check: Serverless Data Pipelines30 minutes
Monitoring and Queue Reliability 6 minutes

Instructeur

Edureka

234 Cours213 247 apprenants

Offert par

Edureka

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Foire Aux Questions

This course is designed for aspiring cloud data engineers, data engineers, cloud engineers, backend developers, and IT professionals who want to build serverless data pipelines.

Basic familiarity with cloud computing is helpful, but the course introduces the key AWS services and serverless concepts step by step.

Basic Python knowledge is recommended because the hands-on demos use Python for AWS Lambda functions and lightweight data processing.

To access course materials, assignments, and earn a Certificate, you'll need to purchase the Certificate experience when you enroll in a course. Eligible learners may also have the option to start with a Free Trial. Some courses may also offer a Full Course, No Certificate option. This lets you access course materials, submit required assessments, and receive a final grade, but you won't be able to earn or purchase a Certificate.