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001 Ai Topological Sort

120-architectures-in-distributed-systems

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Architectural Patterns for Distributed Systems

Source: https://arpitbhayani.me/blogs/architectures-in-distributed-systems Date: 2021-06-22

Explore common architectures in distributed systems, including client-server, 3-tier, n-tier, and peer-to-peer. Understand their characteristics and when to use each one for optimal system design.

While designing a Distributed System, it is essential to pick the right kind of architecture. Usually, architectures are evolving, but picking the right one at the inception could make your system thrive.

So, here are 4 common architectures in Distributed Systems

Client-server

To render some information to the end-user, the client contacts the server (holding the data) with a request; the server sends back the data requested. The client is smart enough to understand how to request the data, post-process it, format it, and then serve it to the end-user.

001-ai-topological-sort.md
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002 Temporal Primer
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003 Rag Production
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004 Structure Of Llm Chat
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005 How Llms Work
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006 Monolith Is Distributed System
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007 Defensive Databases
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008 Bm25
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009 Join Algorithms
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010 Venting At Work
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011 Half Life
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012 Multi Paxos
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013 Mysql Replication Internals
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014 Bloom Filters
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015 Clock Sync Nightmare
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016 Kafka Partitions
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017 Product Quantization
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018 Qkv Matrices
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019 Deleted Production
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020 How Llm Inference Works
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021 Blocking Queues
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022 Heartbeats In Distributed Systems
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023 Cassandra Writes
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024 Redis Replication
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025 Arrogant People At Work
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026 Cdn Content Replication
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027 Cant Fix Everything Day One
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028 Emotions At Work
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029 Grpc Http2
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030 Meetings With No Agenda Are A Waste Of Time
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031 Growth Is Not About Doing Everything
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032 Career Longevity Vs Job Hopping
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033 Stay Relevant At Higher Salary Levels
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034 Why Consensus
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035 Database Deadlocks
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036 Cpu Cache Locality
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037 Eventual Consistency
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038 Dns Udp Tcp
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039 Masters
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040 Empathy Makes Great Engineers Unstoppable
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041 Good Mentors Build People
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042 Always Have Back Burner Projects
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043 Before You Push Back Know What Youre Standing On
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044 Be The One They Can Count On
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045 How Much People Bet On You
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046 How To Get Leadership To Say Yes To Your Project
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047 Dont Let Your Best Ideas Die In Silence
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048 Be Someone Others Want To Work With
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049 Dont Fall For Xy Problem Ask Right Questions
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050 Biggest Lie Startups Tell Engineers
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051 Promotions Are Proactive Not Reactive
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052 Not Enough To Be Right Learn To Be Heard
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053 No One Ships Alone
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054 Not Every Mistake Needs A Correction
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055 Build Influence At Work
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056 Your Soft Skills Arent Soft At All
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057 Experience Before Forming Opinion
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058 Curiosity And High Bias For Action
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059 Worklog
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060 Mistakes And Growth
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061 Own It Instead Of Sweeping It Aside
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062 Dont Wait Step Up
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064 Interview Bias And What Sets You Apart
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065 Saying This Isnt My Problem Is A Problem
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066 Okr
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067 Miscommunication
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068 When In Doubt Code It Out
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070 Lead Projects That Land
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072 We Engineers Suck At Task Estimation
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073 Shiny Object Syndrome In Tech
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074 3p
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075 Leverage The Equilibrium
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076 On Demand Container Loading In Aws Lambda
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077 Sql Has Problems We Can Fix Them Pipe Syntax In Sql
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078 Nanolog A Nanosecond Scale Logging System
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079 Best Resource Is Mythical
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080 Wtf The Who To Follow Service At Twitter
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081 Know A Lot
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082 Out Of Syllabus
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083 Negotiate The Offer
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084 Never Bad Mouth Your Ex Exployer
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085 Culture Fit
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086 Quantification In Resume
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087 Hiring Is Unfair
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088 Questions For Interviewers
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089 Collaboration Communication
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090 Out Of Vicious Interview Cycle
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091 Pitch Projects Not Ideas
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092 Read Design Docs
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093 Read Rca Docs
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094 Start Generalist
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095 Do Not Rely On Summaries
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097 Title Inflation
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098 Find Your Own Project
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100 Keep Yourself Unblocked
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101 Genetic Knapsack
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102 Pseudorandom Number Generation Lfsr
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103 How Indexes Work On Partitioned And Sharded Data
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104 Some Data Partitioning Strategies For Distributed Data Stores
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105 Data Partitioning
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106 Leaderless Replication
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107 Conflict Resolution
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108 Conflict Detection
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109 Multi Master Replication
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110 Monotonic Reads
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111 Read Your Write Consistency
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112 Handling Outages Master Replica
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113 Replication Formats
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114 Replication Strategies
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115 Master Replica Replication
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116 Durability
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117 Isolation
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118 Atomicity
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119 Consistency
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120 Architectures In Distributed Systems
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121 Mistaken Beliefs Of Distributed Systems
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122 Fork Bomb
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123 Chained Operators Python
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124 Taxonomy On Sql
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125 The Weird Walrus
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126 Fully Persistent Arrays
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127 Persistent Data Structures Introduction
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128 Constant Folding Python
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129 String Interning Python
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130 Recursion Visualizer Python
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131 Flajolet Martin
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132 2q Cache
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133 Israeli Queues
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134 1d Terrain
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135 Jaccard Minhash
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136 Ts Smoothing
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146 Inheritance C
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147 Rum
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150 Fractional Cascading
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160 Function Overloading
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This kind of architecture is not common in our day-to-day web applications. Still, it is prevalent when multiple services share a common database (server) and request data directly from the database.

3-tier

This is one of the most widely used topologies out there. Unlike client-server architecture, the clients in a 3-tier architecture are not smart and are stateless. This architecture introduces a middle layer holding the business logic. The client talks to the business layer, and this business layer talk to the server (holding the data).

Most of the web applications are 3-tier applications where your client (browser) talks to the business layer (webserver), which in turn queries the server (database) for the data. The business layer processes and formats the data (optional) and sends it back to the client. The client does not know how the data is being fetched from the server, making it stateless.

n-tier

As an extension to the 3-tier architecture, the n-tier application is where your middle layer (business layer) talks to another service to get information. This is typically seen when there is multiple independent business logic in the system.

A classic example of an n-tier architecture is Microservices based architecture. Each service is responsible for its information, and the service communicates with other services to get the required data. Thus, a 3-tier application typically evolves into an n-tier application.

Peer-to-peer

Peer-to-peer architecture is typically a decentralized system wherein no special machines hold all the responsibilities; instead, the responsibility is split across all the machines equally. The peers act as both clients and servers, and they communicate with each other to serve the request.

A couple of popular examples of P2P architecture are BitTorrent and Bitcoin networks. The n-tier architecture can optionally evolve into a P2P, but this evolution is not that popular. Usually, going P2P is a choice that is made during the inception of the service.

References

  • Distributed Systems - Wikipedia