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Introduction to Distributed Systems for Dummies
Gain insights into distributed systems, learn architectural patterns like replication and sharding, and explore Apache Spark and Druid to design and develop effective distributed applications.
4.7
53 Lessons
14h
Join 2.9 million developers at
Join 2.9 million developers at
LEARNING OBJECTIVES
- Mastery over the nature of and the need for distributed systems
- An understanding of the core problems in developing distributed systems
- Appreciation of the challenges in distributed systems related to storage, communication, and processing
- Familiarity with key architectural patterns in distributed system design
- In-depth knowledge through case studies of some popular distributed systems
Learning Roadmap
1.
Introduction
Introduction
Step through the essentials of distributed systems and their significance for modern applications.
2.
What Distributed Systems Achieve for Us
What Distributed Systems Achieve for Us
Unpack the core of fault tolerance, reliability, availability, scalability, load balancing, and maintainability in distributed systems.
Fault ToleranceReliabilityHandling Hardware and Software FaultsQuick Quiz #2: Fault Tolerance and ReliabilityAvailabilityAchieving AvailabilityQuick Quiz #3: Availability in Distributed SystemsScalabilityLoad Balancing in Distributed SystemsLoad Balancing AlgorithmsMeasuring Load and PerformanceQuick Quiz #4: Scalability and Load BalancersMaintainabilityQuick Quiz #5: Maintainability
3.
Data in Distributed Systems
Data in Distributed Systems
16 Lessons
16 Lessons
Examine key concepts of data management, replication, partitioning, consistency, and caching in distributed systems.
4.
Communication Between Nodes
Communication Between Nodes
4 Lessons
4 Lessons
Grasp the fundamentals of database communication, microservice protocols, and asynchronous messaging in distributed systems.
5.
Data Processing in Large Scale
Data Processing in Large Scale
4 Lessons
4 Lessons
Solve problems in large-scale data processing using batch and stream processing techniques.
6.
Distributed System Architectural Patterns
Distributed System Architectural Patterns
5 Lessons
5 Lessons
Follow the process of implementing replicated, sharded, lambda, and CQRS patterns in distributed systems.
7.
Case Study 1: Apache Spark
Case Study 1: Apache Spark
2 Lessons
2 Lessons
Master the steps to efficiently handle and analyze big data using Apache Spark.
8.
Case Study 2: Apache Druid
Case Study 2: Apache Druid
2 Lessons
2 Lessons
Learn how to use Apache Druid and understand its distinct OLAP database architecture.
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Developed by MAANG Engineers
ABOUT THIS COURSE
Gone are the days when monolithic applications were the norm. Most applications that we use today are too complex for that type of construction. Instead, most applications that appear as a single unit are actually built as a collection of inter-operating but independent computational components. Developers are expected to have mastery over a programming language or two. Moreover, they should also know the basics of distributed systems in order to succeed.
In this course, you’ll learn what a distributed system is, followed by the challenges unique to distributed systems. You’ll cover popular architectural patterns for achieving targets like replication and sharding. You’ll finish with a study of two popular distributed systems: Apache Spark and Apache Druid.
With the knowledge gained through this course, you’ll be able to design and develop distributed systems. You’ll be able to make optimal design and architectural choices based on the application requirements.
ABOUT THE AUTHOR
Mottakin Chowdhury
It has been a few years in backend engineering. Loving the experience so far!
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