Goal: Gain a strong working understanding of tools and trends for distributed software system architecture and development, to allow the learner to better design and build software systems at edX.

Intro

Goal: Understand what distributed computing is, and what’s it’s for.

Level of investment: Low (wikipedia / blog posts)

• (TBD)

• IDesign started off as a Microsoft consulting shop but has since branched out to other technologies.  Their “Method” documents and related resources are great references:  http://idesign.net/

• www.infoq.com is a great place to find recordings of pertinent presentations

• www.highscalability.com is also a great resource -- lots of case studies and real-world examples available there. Also lots of blog chaff, so be careful :)

• Udi Dahan used to have a lot more info on his site, but he still has some great stuff: http://udidahan.com/articles/

Distributed architectures

Goal: Become familiar with common distributed computing paradigms

Level of investment: Medium (blog posts / podcasts / talks)

• Client-Server

• N-tier

• Peer-to-peer

• Distributed logs

• https://engineering.linkedin.com/distributed-systems/log-what-every-software-engineer-should-know-about-real-time-datas-unifying

• Message-passing

• RPC

Bonus: a perspective on a few key architecture patterns. http://www.oreilly.com/programming/free/software-architecture-patterns.csp

Tools (Past + Present)

Goal: Become familiar with the concepts of each of these distributed computing tools. Understand why it was created, what it does, what it’s good at, what it’s not good at, and whether it was successful.

Level of investment: Low (wikipedia / blog posts)

• TCP/IP
• HTTP
• DNS
• Web sockets
• REST
• TLS
• Protocol buffers
• Message queuing protocols, reliable messaging, persistent messaging
• Storage
  • SQL and Relational Databases
  • Document stores
  • Object databases
  • Graph databases

Distributed Systems

Goal: Gain familiarity with common distributed tools, with a focus on tools used at edX

Level of investment: Medium (blog posts, at least one practical / lab project)

• Amazon Web Services (esp. SQS, SES, SNS)

• Memcached architecture

• Elasticsearch architecture

• Cassandra architecture

• RabbitMQ architecture

• Hadoop architecture  (there is an edX course on Hadoop)

Services

Goal: Understand what you need to consider when building a service.

Level of investment: Medium (blog posts, at least one practical / lab project)

• AuthZ/AuthN

• Service Discovery + Service Registries

• Distributed Configuration Management

• Continuous integration and delivery

• APIs

• Design

• Publishing

(Eddie still thinks Heroku's "12 Factor App" is a great starting point, even though it’s getting a bit dated…)

Performance

Goal: Understand performance characteristics of a distributed web architecture, including paradigms and tools.

Level of investment: Medium (blog posts, at least one practical / lab project)

• Capacity planning

• Scaling

• Caching and content delivery networks (e.g. CloudFront)

• Network latency

• Serialization

• Testing

High availability

Goal: Understand the concepts and tradeoffs of a highly-available web architecture, including tools and algorithms for creating a HA system.

Level of investment: Medium (blog posts, at least one practical / lab project)

• Concurrency
• Failover
• Circuit breakers
  • https://martinfowler.com/bliki/CircuitBreaker.html
    
  • Netflix on Circuit Breakers
    • https://medium.com/netflix-techblog/making-the-netflix-api-more-resilient-a8ec62159c2d
    • https://medium.com/netflix-techblog/fault-tolerance-in-a-high-volume-distributed-system-91ab4faae74a
  • Hystrix (NetFlix open-source circuit breaker library): https://github.com/Netflix/Hystrix/wiki
• Eric Brewer’s CAP Theorem
  • http://www.julianbrowne.com/article/viewer/brewers-cap-theorem
  • This is a great - if heavy - follow-up written by Brewer earlier this year, on Google Spanner that I’d recommend as supplemental reading: PDF
  • Related themes: eventual consistency, split brain
• Command-Query Responsibility Segregation (aka, write/read, aka, CQRS)
• AWS-specific appendix: elastic load balancers, auto-scaling groups

Future

Goal: Understand how the field is evolving; understand current trends such as containerization and serverless computing.

Level of investment: Low (blog posts)

• Containers (LXC, Docker)

• Serverless computing - reading:

• https://martinfowler.com/articles/serverless.html

• Serverless computing  - course:

• https://cloudacademy.com/learning-paths/getting-started-serverless-computing-25/

Other Materials

• Nimisha has another list: Resources for Large-scale and Distributed Systems. We should combine that list into this one.
• Also, see detailed notes from a 2-day architecture training: Architecture without an End State with Michael Nygard

Reference

• Randy Shoup talk

• https://www.infoq.com/presentations/reactive-services-scale