Building Modern Distributed Systems with Java
Significant percentage of large scale enterprises that I have been working with, admitted experiencing performance issues with their business critical applications. Most of production systems have been built on top of legacy, monolith technologies. Recent popularity of micro-services will not fulfill its promise of decoupled, scalable and fault-tolerant systems, unless "done right".
More
While entering the world of micro-services, engineers start building distributed applications, where robust remote procedure calls and cluster coordination are a must.
In this course you will learn about common challenges that appear while designing and implementing large scale distributed systems, and how Big-Tech companies solve those problems.
Technologies, algorithms and design patterns covered in this course:
Service Registry and Discovery, Service Mesh
Apache Cassandra
ETCD (coordinator managing Kubernetes clusters)
Apache Kafka
Idempotent service design, retry logic
Sharding and Consistent Hashing
Client-side Load Balancing, Distributed Tracing, Canary Deployment, Sidecar Pattern, Circuit Breaker
Course will teach you the principles of various distributed systems design, for example master-less vs. with leaders, poll-based vs. push-based, immediate vs. eventual consistency. After completing the course, learning new distributed database technology would be easier, because you will know the common re-used techniques, including their pros and cons.
My intention is to keep course content very practical, with lots of code examples and applied best practices. For example, I will cover Service Registry and Discovery to the detail, that you will know how to implement your own framework on top of ETCD. Throughout the course, we are going to build distributed URL shorten service.
The course may be a good recap for people preparing for systems design interview.
Watch Online Building Modern Distributed Systems with Java
# | Title | Duration |
---|---|---|
1 | Evolution of computer system’s architecture | 04:04 |
2 | Challenges of distributed computing | 04:10 |
3 | Use-case of course application | 04:25 |
4 | Practice 1 | 04:52 |
5 | The need of communication | 06:37 |
6 | Message transport and format | 02:20 |
7 | Synchronous and asynchronous communication patterns | 03:02 |
8 | Traditional load balancers | 02:24 |
9 | Service Registry and Discovery | 02:26 |
10 | Service meshes | 08:37 |
11 | Idempotent service design | 07:34 |
12 | Practice 2 | 08:42 |
13 | Traditional RDBMS systems vs. NoSQL | 06:09 |
14 | Data sharding and consistent hashing | 06:25 |
15 | CAP theorem | 06:46 |
16 | Short introduction to Apache Cassandra | 20:20 |
17 | Practice 3 | 11:46 |
18 | The need of cluster-wide coordination | 07:37 |
19 | RAFT consensus algorithm | 12:36 |
20 | Short introduction to Etcd | 12:35 |
21 | Implementation of distributed mutex | 07:42 |
22 | Leader election design pattern | 02:42 |
23 | Deployment requirements for strongly consistent distributed systems | 05:18 |
24 | ACID properties in distributed system | 04:47 |
25 | Practice 4 | 17:07 |
26 | Asynchronous communication pattern and message-oriented middleware | 05:34 |
27 | Short introduction to Apache Kafka | 05:27 |
28 | Apache Kafka as a distributed system | 29:40 |
29 | Event-driven architecture | 02:29 |
30 | Practice 5 | 09:19 |