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1. parallelism
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2. fault tolerance
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3. transactions across sites eg banks
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4. security, isolation, contain it.
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1. too many moving parts, concurrent programming
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2. unexpected failure patterns.
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3. partial failures
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4. actual vs ideal performance
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lab 1
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mapreduce
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lab 2
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raft
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lab 3
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k/v server
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lab 4
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sharted key value service
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@ -15,37 +15,29 @@ Features
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========
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- The feature set
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Make note of the specs carefully. Feel free to annotate a bit
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- Define APIs and Endpoints.
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Knowing what routes will be hit by the public and what sort of auth is being used is essential
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- Availability
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What to do if a host goes down, what to do if the entire data centre goes down. If already exists then enquire about the current plans and also ascertain the amount of availability cared about
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- Latency Performance
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Public facing services require snappy responses. This may be kept track of with monitoring tools.
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- Scalability
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- Durability
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At times data can be stored in a db securely without loss and compromises what sort of dbs am I working with.
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- Class Diagrams
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OOP diagrams basically, they may ask to design some parking lot or elevator systems
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- Security and Privacy
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TLDR: When users and auth are required these practices will become sacrosanct
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- Cost Effective
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Lean systems are not only cost effective but easier to maintain. KISS. Check Pros and Cons for current and alt flows
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@ -132,7 +124,6 @@ Types of NoSQL
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Note current conf
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---
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Caching
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-------
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@ -146,7 +137,7 @@ Points of Concern:
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- cannot be accepted as source of truth
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Data Centers/Racks/Hosts
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-----------------------
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------------------------
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Key points of interest may be:
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@ -188,6 +179,7 @@ IPV4 vs IPV6
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- runnin out of ipv4 addys
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- ipv4 = 32 bits vs ipv6 = 128bits (remember go-discord-irc conundrum)
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- Some power systems
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TCP vs UDP
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@ -220,8 +212,7 @@ PKI and CAs
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- We know that CAs verify that the certs or pubkeys are actually good to go ie they are recognized and authorized.
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- Prevents MITM
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- See ``Georg`` for more info.
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- See ``Georg`` for more if- eg avao;
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Symmetric vs Asymmetric Encryption
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----------------------------------
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@ -249,3 +240,19 @@ Bloom Filters and Count-min sketch
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- Space efficient probablisitic based data structures.
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- BF - Used to decide to an element is a part of a set or not. May have false positives but never false negatives. Very Space Efficient (READ MORE)
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- CMS - Frequency event counter. fraction of space used to probablistically arrive at close to the accurate answer.
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Paxos
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-----
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VMS and Containers
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-------------------
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- vm is system on system, containers self contained
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Map Reduce
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------------
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Concurrency, threading
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-----------------------
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@ -0,0 +1,79 @@
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========
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Toolkit
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========
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list
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=========
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cassandra
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---------
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- wide column
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- time series Data
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- consistent hash Sharding
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- eventual consistency, gossipping
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mongodb
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-------
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- json??
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memcached
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---------
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- distrib cache key value storage
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Apache kafka
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------------
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zookeeper
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---------
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mysql
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-----
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- master slave architecture
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redis
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-----
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- memcache on steroids
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- can be clustered
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HAPROXY
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-------
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Nginx
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-----
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kafka
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-----
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solr
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----
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elasticsearch
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-------------
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blobstore
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----------
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docker
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------
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kube and mesos
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--------------
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spark (map reduce)
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-------------------
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hdfs
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----
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java based fs
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