roam/20210323005824-distributed_systems.org

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:PROPERTIES:
:ID: 9de8fa16-17f9-4877-a24f-a0df7a88c53e
:END:
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#+title: Distributed Systems
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A [[id:1a74e6c8-023d-4a04-aae7-74d4428f6de5][Software Architecture]] consisting of multiple independant pieces of software
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coordinating via message passing.
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* A "Monolithic" Web application as a distributed system
A monolith presents itself as a single black box with no external dependencies or race conditions to contend with. But, is it?
- There's probably some sort of database to store state.
- If it's a web application, its clients are distributed!
#+begin_src plantuml :file distributed-web-application.svg :exports results
actor Browser
participant WebApp
database Database
Browser -> WebApp : Request Page
WebApp -> Database : Load Data
Database -> WebApp : Return Data
WebApp -> Browser : Render Page
...
Browser -> WebApp : Save Form
WebApp -> Database : Write Data
Database -> WebApp : Data Stored
WebApp -> Browser : Done!
#+end_src
#+RESULTS:
[[file:distributed-web-application.svg]]
- Myths
+ The database is local, therefore the connection is guaranteed to be fast and
stable.
+ Data is isolated to the user accessing it, there's no possibility for race
conditions / having to merge data.
+ The behavior of one user won't affect the experience of another.
- Any one of those lines of communication could fail for some reason
+ Bad request :: Something the user sent could cause an error
+ Bad state :: A service could be in a bad state and fail to react as
expected. The web server or database may be overloaded. Invalid data could
be persisted, breaking further requests.
+ Network issues :: Even on the same host, the other service could be down or
inaccessible.
- Any of those activities could occur /concurrently/
+ What happens when two different users try to save changes to the same data?
Or the same user, from two different clients or browser tabs?
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* [[id:6f95b295-d872-4ba6-affc-19b8ad5e4717][Process Isolation]]
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- Monolith vs. Services
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* [[id:8ad5f29c-f967-4e36-b37a-22c309988df7][Concurrent and Parallel Programming]]
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#+begin_quote
A system is said to be concurrent if it can support two or more actions in
progress at the same time. A system is said to be parallel if it can support two
or more actions executing simultaneously.
-- Clay Breshears, The Art Of Concurrency
#+end_quote
- Parallel :: Occurring at the same time
- Concurrent :: Occuring independently
Python threads are concurrent, but not parallel (execution is serialized,
contending for access to the Global Interpreter Lock).
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* [[id:de3ac4c8-2648-410a-b8ed-088f33890781][CAP Theorem]]
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[[file:data/e3/98cb62-2f26-46e5-ae00-64260adc4c43/Visualization-of-CAP-theorem.png]]
#+begin_quote
CAP is frequently misunderstood as if one has to choose to abandon one of the
three guarantees at all times. In fact, the choice is really between consistency
and availability only when a network partition or failure happens; at all other
times, no trade-off has to be made.
#+end_quote
Not absolutist, there are trade-offs that can be made to achieve a best possible
outcome.
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* [[id:1ef99d1b-618b-41dd-afb7-0023d4e4481c][CRDTs]]