From 476dd1c5d99884000e2c3a7d243e8dace2fcf117 Mon Sep 17 00:00:00 2001 From: Vu Date: Sun, 14 Mar 2021 17:26:49 +0700 Subject: [PATCH] fixed issue preview --- resources/noat.cards/Application layer.md | 6 +++--- resources/noat.cards/Asynchronism.md | 15 ++++++--------- resources/noat.cards/Availability patterns.md | 18 +++++++++--------- 3 files changed, 18 insertions(+), 21 deletions(-) diff --git a/resources/noat.cards/Application layer.md b/resources/noat.cards/Application layer.md index ac1fcf4d..188645b8 100644 --- a/resources/noat.cards/Application layer.md +++ b/resources/noat.cards/Application layer.md @@ -18,17 +18,17 @@ The single responsibility principle advocates for small and autonomous service Workers in the application layer also help enable [asynchronism](https://github.com/donnemartin/system-design-primer#asynchronism) . -### [](https://github.com/donnemartin/system-design-primer#microservices) Microservices +### Microservices Related to this discussion are [microservices](https://en.wikipedia.org/wiki/Microservices) , which can be described as a suite of independently deployable, small, modular services. Each service runs a unique process and communicates through a well-definied, lightweight mechanism to serve a business goal. [1](https://smartbear.com/learn/api-design/what-are-microservices) Pinterest, for example, could have the following microservices: user profile, follower, feed, search, photo upload, etc. -### [](https://github.com/donnemartin/system-design-primer#service-discovery) Service Discovery +### Service Discovery Systems such as [Zookeeper](http://www.slideshare.net/sauravhaloi/introduction-to-apache-zookeeper)  can help services find each other by keeping track of registered names, addresses, ports, etc. -### [](https://github.com/donnemartin/system-design-primer#disadvantages-application-layer) Disadvantage(s) : application layer +### Disadvantage(s) : application layer * Adding an application layer with loosely coupled services requires a different approach from an architectural, operations, and process viewpoint (vs a monolithic system) . * Microservices can add complexity in terms of deployments and operations. diff --git a/resources/noat.cards/Asynchronism.md b/resources/noat.cards/Asynchronism.md index 946768d5..bfdae42c 100644 --- a/resources/noat.cards/Asynchronism.md +++ b/resources/noat.cards/Asynchronism.md @@ -10,7 +10,7 @@ _[Source: Intro to architecting systems for scale](http://lethain.com/introducti Asynchronous workflows help reduce request times for expensive operations that would otherwise be performed in-line. They can also help by doing time-consuming work in advance, such as periodic aggregation of data. -### [](https://github.com/donnemartin/system-design-primer#message-queues) Message queues +### Message queues Message queues receive, hold, and deliver messages. If an operation is too slow to perform inline, you can use a message queue with the following workflow: @@ -25,26 +25,23 @@ RabbitMQ is popular but requires you to adapt to the 'AMQP' protocol and manage Amazon SQS, is hosted but can have high latency and has the possibility of messages being delivered twice. -### [](https://github.com/donnemartin/system-design-primer#task-queues) Task queues +### Task queues Tasks queues receive tasks and their related data, runs them, then delivers their results. They can support scheduling and can be used to run computationally-intensive jobs in the background. Celery has support for scheduling and primarily has python support. -### [](https://github.com/donnemartin/system-design-primer#back-pressure) Back pressure +### Back pressure If queues start to grow significantly, the queue size can become larger than memory, resulting in cache misses, disk reads, and even slower performance. [Back pressure](http://mechanical-sympathy.blogspot.com/2012/05/apply-back-pressure-when-overloaded.html)  can help by limiting the queue size, thereby maintaining a high throughput rate and good response times for jobs already in the queue. Once the queue fills up, clients get a server busy or HTTP 503 status code to try again later. Clients can retry the request at a later time, perhaps with [exponential backoff](https://en.wikipedia.org/wiki/Exponential_backoff) . -### [](https://github.com/donnemartin/system-design-primer#disadvantages-asynchronism) Disadvantage(s) : asynchronism +### Disadvantage(s) : asynchronism * Use cases such as inexpensive calculations and realtime workflows might be better suited for synchronous operations, as introducing queues can add delays and complexity. -### [](https://github.com/donnemartin/system-design-primer#sources-and-further-reading-11) Source(s) and further reading +### Source(s) and further reading * [It's all a numbers game](https://www.youtube.com/watch?v=1KRYH75wgy4) * [Applying back pressure when overloaded](http://mechanical-sympathy.blogspot.com/2012/05/apply-back-pressure-when-overloaded.html) * [Little's law](https://en.wikipedia.org/wiki/Little%27s_law) -* [What is the difference between a message queue and a task queue?](https://www.quora.com/What-is-the-difference-between-a-message-queue-and-a-task-queue-Why-would-a-task-queue-require-a-message-broker-like-RabbitMQ-Redis-Celery-or-IronMQ-to-function) - -[](https://github.com/donnemartin/system-design-primer#communication) ---------------------------------------------------------------------- \ No newline at end of file +* [What is the difference between a message queue and a task queue?](https://www.quora.com/What-is-the-difference-between-a-message-queue-and-a-task-queue-Why-would-a-task-queue-require-a-message-broker-like-RabbitMQ-Redis-Celery-or-IronMQ-to-function) \ No newline at end of file diff --git a/resources/noat.cards/Availability patterns.md b/resources/noat.cards/Availability patterns.md index 3cce966d..5f79527a 100644 --- a/resources/noat.cards/Availability patterns.md +++ b/resources/noat.cards/Availability patterns.md @@ -7,7 +7,7 @@ isdraft = False There are two main patterns to support high availability:fail-over and replication. -### [](https://github.com/donnemartin/system-design-primer#active-passive) Active-passive (Fail-Over) +### Active-passive (Fail-Over) With active-passive fail-over, heartbeats are sent between the active and the passive server on standby. If the heartbeat is interrupted, the passive server takes over the active's IP address and resumes service. @@ -15,7 +15,7 @@ The length of downtime is determined by whether the passive server is already ru Active-passive failover can also be referred to as master-slave failover. -### [](https://github.com/donnemartin/system-design-primer#active-active) Active-active (Fail-Over) +### Active-active (Fail-Over) In active-active, both servers are managing traffic, spreading the load between them. @@ -23,39 +23,39 @@ If the servers are public-facing, the DNS would need to know about the public IP Active-active failover can also be referred to as master-master failover. -### [](https://github.com/donnemartin/system-design-primer#disadvantages-failover) Disadvantage(s) : failover +### Disadvantage(s) : failover * Fail-over adds more hardware and additional complexity. * There is a potential for loss of data if the active system fails before any newly written data can be replicated to the passive. -### [](https://github.com/donnemartin/system-design-primer#master-slave-and-master-master) Master-slave replication +### Master-slave replication The master serves reads and writes, replicating writes to one or more slaves, which serve only reads. Slaves can also replicate to additional slaves in a tree-like fashion. If the master goes offline, the system can continue to operate in read-only mode until a slave is promoted to a master or a new master is provisioned. [![](https://camo.githubusercontent.com/6a097809b9690236258747d969b1d3e0d93bb8ca/687474703a2f2f692e696d6775722e636f6d2f4339696f47746e2e706e67) ](https://camo.githubusercontent.com/6a097809b9690236258747d969b1d3e0d93bb8ca/687474703a2f2f692e696d6775722e636f6d2f4339696f47746e2e706e67) _[Source: Scalability, availability, stability, patterns](http://www.slideshare.net/jboner/scalability-availability-stability-patterns/) _ -### [](https://github.com/donnemartin/system-design-primer#disadvantages-master-slave-replication) Disadvantage(s) : master-slave replication +### Disadvantage(s) : master-slave replication * Additional logic is needed to promote a slave to a master. * See [Disadvantage(s) : replication](https://github.com/donnemartin/system-design-primer#disadvantages-replication)  for points related to both master-slave and master-master. -### [](https://github.com/donnemartin/system-design-primer#master-master-replication) Master-master replication +### Master-master replication Both masters serve reads and writes and coordinate with each other on writes. If either master goes down, the system can continue to operate with both reads and writes. [![](https://camo.githubusercontent.com/5862604b102ee97d85f86f89edda44bde85a5b7f/687474703a2f2f692e696d6775722e636f6d2f6b7241484c47672e706e67) ](https://camo.githubusercontent.com/5862604b102ee97d85f86f89edda44bde85a5b7f/687474703a2f2f692e696d6775722e636f6d2f6b7241484c47672e706e67) _[Source: Scalability, availability, stability, patterns](http://www.slideshare.net/jboner/scalability-availability-stability-patterns/) _ -### [](https://github.com/donnemartin/system-design-primer#disadvantages-master-master-replication) Disadvantage(s) : master-master replication +### Disadvantage(s) : master-master replication * You'll need a load balancer or you'll need to make changes to your application logic to determine where to write. * Most master-master systems are either loosely consistent (violating ACID) or have increased write latency due to synchronization. * Conflict resolution comes more into play as more write nodes are added and as latency increases. * See [Disadvantage(s) : replication](https://github.com/donnemartin/system-design-primer#disadvantages-replication)  for points related to both master-slave and master-master. -### [](https://github.com/donnemartin/system-design-primer#disadvantages-replication) Disadvantage(s) : replication +### Disadvantage(s) : replication * There is a potential for loss of data if the master fails before any newly written data can be replicated to other nodes. * Writes are replayed to the read replicas. If there are a lot of writes, the read replicas can get bogged down with replaying writes and can't do as many reads. @@ -63,7 +63,7 @@ _[Source: Scalability, availability, stability, patterns](http://www.slideshare. * On some systems, writing to the master can spawn multiple threads to write in parallel, whereas read replicas only support writing sequentially with a single thread. * Replication adds more hardware and additional complexity. -### [](https://github.com/donnemartin/system-design-primer#sources-and-further-reading-replication) Source(s) and further reading: replication +### Source(s) and further reading: replication * [Scalability, availability, stability, patterns](http://www.slideshare.net/jboner/scalability-availability-stability-patterns/) * [Multi-master replication](https://en.wikipedia.org/wiki/Multi-master_replication) \ No newline at end of file