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What and Why

System Design Interviews or not: Why take this course?What is a Distributed System?Why do we need Distributed systems?Fun Stuff: They never thought about Scaling Case Study: Filtragram

Node in a Distributed System

What is a Node in a Distributed System?Node Characteristics: Latency in Distributed Systems Is Node a Single Physical Machine?Nodes are reliable but Edges are not Node failures in distributed systems

Performance and Numbers

Measure Everything: Why Measuring Performance is necessary Performance Metrics for Distributed Systems: Latency, Round-Trip Time & Throughput Averages can mislead: Measure Performance using Percentiles Tail Latencies at Scale: When Percentiles mislead Tail Latencies at Scale SLAs

Fault Tolerance and Availability

There will be Downtime - The horror! The horror!Faults, Errors and Failures - Is there a difference Fault Tolerance and Redundancy Throttling and Exponential Backoffs Retries and Idempotency

Understanding TIME in Distributed Systems

Did this Node Time-Travel into the Past?How do Computer Clocks Work and What's Clock Skew?What is NTP and how it works?Untitled Masterpiece

Data Centers for software engineers

Data Center Economics Data Center for Software Engineers

Scaling Distributed Systems

A DMV Office in a Small town What is Scalability in Distributed Systems?Vertical Scaling Functional Scaling Horizontal Scaling Saving Costs With Elasticity Horizontal Scaling brings its own set of issues

Load Balancers

A Quick overview of Domain Name System (DNS)How to scale Horizontally using Load Balancers What is Network Address Translation & How Load Balancers use it?Layer 4 v.s Layer 7 Load Balancers Routing Algorithms for Load Balancers Stateful vs. Stateless Applications and Session Management DNS Load Balancing and Geo DNS

Structured Storage at Scale

Storing Data: HDDs Structured Storage vs. Blob Storage Data Storage: Durability & Availability

Sharding in Storage Systems

Scaling Data Storage using Data Partitioning Consistent Hashing

SQL vs NO-SQL

Consistency CAP Theorem Idempotency

Blob Storage at Scale

Caching in Distributed Systems

Data Caching: Memcached & Redis File Caching: CDNs

Queues and Asynchronous Processing

Data Analytics and Batch Processing

Logging and Monitoring

Searching at Scale

Conclusion

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