Scalable Web Application Architecture
Title: Web Architecture Study Notes Notebook: Evernote Tags: EVND Tags: Architecture, Study, Web, Design, System
[TOC]
Scalable Web Architecture and Distributed Systems
Principles of Web Distributed Systems Design
Availability
Performance
Reliability
Scalability
Manageability
Cost
Basics
Services
Service Oriented Architecture (SOA)
Redundancy
Redundancy of its services and data
Creating redundancy in a system can remove single points of failure and provide a backup or spare functionality if needed in a crisis
Another key part of service redundancy is creating a shared-nothing architecture.
Partitions
Scaling: scale vertically or horizontally
Scaling vertically means adding more resources to an individual server. To scale horizontally, on the other hand, is to add more nodes.
When it comes to horizontal scaling, one of the more common techniques is to break up your services into partitions, or shards. The partitions can be distributed such that each logical set of functionality is separate; this could be done by geographic boundaries, or by another criteria like non-paying versus paying users. The advantage of these schemes is that they provide a service or data store with added capacity.
Fast and Scalable Data Access
scalability of storage and fast access of data
Caches
Caches take advantage of the locality of reference principle: recently requested data is likely to be requested again.
Caches can exist at all levels in architecture, but are often found at the level nearest to the front end
Cache misses -> Two choices
Global Cache
Distributed Cache
Global Cache
A global cache is just as it sounds: all the nodes use the same single cache space.
Global cache where cache is responsible for retrieval
Global cache where request nodes are responsible for retrieval
Distributed Cache
In a distributed cache, each of its nodes own part of the cached data
One of the advantages of a distributed cache is the increased cache space that can be had just by adding nodes to the request pool.
A disadvantage of distributed caching is remedying a missing node
Proxies
At a basic level, a proxy server is an intermediate piece of hardware/software that receives requests from clients and relays them to the backend origin servers.
Proxies are also immensely helpful when coordinating requests from multiple servers, providing opportunities to optimize request traffic from a system-wide perspective.
One way to use a proxy to speed up data access is to collapse the same (or similar) requests together into one request, and then return the single result to the requesting clients. This is known as collapsed forwarding.
Indexes
Using an index to access your data quickly is a well-known strategy for optimizing data access performance; probably the most well known when it comes to databases.
An index makes the trade-offs of increased storage overhead and slower writes (since you must both write the data and update the index) for the benefit of faster reads.
Load Balancers
Load balancers are a principal part of any architecture, as their role is to distribute load across a set of nodes responsible for servicing requests.
Their main purpose is to handle a lot of simultaneous connections and route those connections to one of the request nodes, allowing the system to scale to service more requests by just adding nodes.
Queues
Another important part of scaling the data layer is effective management of writes.
Queues are fundamental in managing distributed communication between different parts of any large-scale distributed system.
Queues enable clients to work in an asynchronous manner, providing a strategic abstraction of a client's request and its response.
Queues also provide some protection from service outages and failures.
Reference
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