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.

Dozent: Edureka

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3 Module

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Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

3 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Anfänger

Empfohlene Erfahrung

7 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

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.

Kompetenzen, die Sie erwerben

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

Werkzeuge, die Sie lernen werden

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

Wichtige Details

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Juni 2026

Bewertungen

6 Aufgaben

Unterrichtet in Englisch

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In diesem Kurs gibt es 3 Module

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.

Das ist alles enthalten

11 Videos5 Lektüren2 Aufgaben

11 VideosInsgesamt 45 Minuten

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

5 LektürenInsgesamt 50 Minuten

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

2 AufgabenInsgesamt 21 Minuten

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

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.

Das ist alles enthalten

10 Videos4 Lektüren2 Aufgaben

10 VideosInsgesamt 35 Minuten

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

4 LektürenInsgesamt 40 Minuten

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

2 AufgabenInsgesamt 21 Minuten

Serverless Data Ingestion and Transformation 15 Minuten
Serverless Data Ingestion and Transformation 6 Minuten

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.

Das ist alles enthalten

11 Videos5 Lektüren2 Aufgaben

11 VideosInsgesamt 41 Minuten

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

5 LektürenInsgesamt 70 Minuten

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

2 AufgabenInsgesamt 36 Minuten

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

Dozent

Edureka

234 Kurse209.927 Lernende

von

Edureka

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Häufig gestellte Fragen

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.