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3RD YEAR - SECOND SEM > Web Services 2 > Flashcards

Web Services 2 Flashcards

1
Q

System Architecture

A

client
web server
application server
database server
DMS

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2
Q

Goals and Approaches System Architecture

A
  • Internet-based E-Commerce has made system growth more rapid and dynamic.
  • Improving performance and reliability to provide
    A. Higher throughput
    B. Lower latency (i.e., response time)
    C. Increase availability
  • Approaches
    a. Scaling network and system infrastructure
    b. How performance, redundancy, and reliability are related to scalability
    c. Load balancing
    d. Web caching

  • goals are to make the E-Commerce system faster, more reliable, and always available.
  • The approaches involve strategies like expanding infrastructure, ensuring consistent performance as the system grows, distributing workload evenly, and storing frequently accessed data for quicker access.
  • These efforts ensure that users have a smooth and seamless experience when shopping online.
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3
Q

Restricts traffic based on rules and can “protect” the internal network from intruders

A

Firewall

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4
Q

Directs traffic to a destination based on the “best” path; can communicate between subnets

A

Router

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5
Q

Provides a fast connection between multiple servers on the same subnet

A

Switch

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6
Q

Takes incoming requests for one “virtual” server and redirects them to multiple “real” servers

A

Load Balancer

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7
Q

SPOF meaning

A

single point of failure

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8
Q

Scaling Servers: Two Approaches

A
  1. Multiple smaller servers
  2. Fewer larger servers to add more internal resources
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9
Q

Fewer larger servers to add more internal resources

A
  • Add more processors, memory, and disk space
  • Most commonly done with database servers
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10
Q

Where to Apply Scalability

A
  • To the network
  • To individual servers
  • Make sure the network has capacity before scaling by adding servers
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11
Q
  • People scale because they want better performance
  • But a fast site that goes down because of one component is a Bad Thing
  • Incorporate all three into your design in the beginning - more difficult to do after the eBusiness is live
A

Performance, Redundancy, and Scalability

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12
Q

Application Service Providers (sites) grow by

A
  • scale up: replacing servers with larger servers
  • scale out: adding extra servers
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13
Q

Approaches to Scalability

A
  1. Farming
  2. Clone
  3. RACS
  4. Partitioning
  5. RAPS
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14
Q

the collection of all the servers, applications, and data at a particular site.

A

Farming

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15
Q
  • A service can be cloned on many replica nodes, each having the same software and data.
  • offers both scalability and availability.
A

Cloning

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16
Q

Two Clone Design Styles

A
  1. Shared Nothing
  2. Shared Disc
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17
Q

simpler to implement and scales IO bandwidth as the site grows.

A

Shared Nothing

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18
Q

design is more economical for large or update-intensive databases.

A

Shared Disc

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19
Q
  • grows a service by duplicating the hardware and software; dividing the data among the nodes (by object), e.g., mail servers by mailboxes
  • should be transparent to the application; requests to a partitioned service are routed to the partition with the relevant data
  • does not improve availability
    the data is stored in only one place
  • partitions are implemented as a pack of two or more nodes that provide access to the storage
A

Partition

partitioning helps split up the workload and make sure everything runs smoothly, but it doesn’t make the system invincible to problems, and each piece of data is kept in just one spot

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20
Q

What is the problem with load sharing

A
  • Too much load
  • Need to replicate servers
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21
Q

Load Sharing Strategies

A
  • flat architecture
    (DNS rotation, switch based)
  • hierarchical architecture
22
Q
  • rotates IP addresses of a Web site; treat all nodes equally
  • Hot-standby machine (failover); expensive, inefficient
  • Problem; Not sufficient for dynamic content
A

Flat Architecture - DNS Rotation

DNS rotation helps balance the load among multiple servers and ensures your website stays online even if one server fails. However, it might not be the best solution for websites that change a lot or show different things to different people.

23
Q

Flat Architecture - DNS Rotation Pros

A

A simple clustering strategy

24
Q

Flat Architecture - DNS Rotation Cons

A

Client-side IP caching: load imbalance, connection to down node

25
Q
  • Switching products
  • Cluster servers by one IP
  • Distribute workload (load balancing)
  • typically round-robin
  • Failure detection
  • Cisco, Foundry Networks, and F5Labs
  • Problem
  • Not sufficient for dynamic content
A

Flat Architecture - Switch Based

setup helps manage internet traffic by spreading it out among multiple servers, but it might not be the best for handling content that changes a lot or is personalized for each user

26
Q

Flat Architectures in General Problems

A
  • Not sufficient for dynamic content
  • Adding/Removing nodes is difficult Manual configuration required
  • limited load balancing in switch
27
Q
  • Master/slave architecture
  • Two levels
  • Level I. Master: static and dynamic content
  • Level II. Slave: only dynamic
A

Hierarchical Architecture

ensures that responsibilities are clearly divided and that tasks are handled efficiently at different levels.

28
Q

Hierarchical Architecture Benefits

A
  • Better failover support (Master restarts job if a slave fails)
  • Separate dynamic and static content (resource intensive jobs (CGI scripts) runs by slave)

helps ensure smooth operation and efficiency by distributing tasks among different levels of servers. If one server fails, the others can step in to keep things running, and tasks are divided based on their nature to make the best use of resources.

29
Q

Web performance and scalability issues

A
  • network congestion
  • server overloading
30
Q
  • A large distributed information system
  • Inexpensive and faster accesses to information
  • Rapid growth of WWW (15% per month)
  • Web performance and scalability issues
A

World Wide Web

31
Q

Web Architecture WWW

A

web architecture is about how your browser asks for web pages from a server and how the server sends those pages back for you to see.

32
Q
  • Intermediate between clients and Web servers
  • To implement firewall
  • To improve performance, caching can be placed
A

Web Proxy

33
Q

Web Architecture Web Proxy

A

browser helps you access websites, a proxy can hide your identity or enhance security, a web server stores and serves websites, and a firewall protects your computer or network from threats. Each plays a role in your online experience and keeping you safe while browsing the internet

34
Q
  • Caching popular objects is one way to improve Web performance.
  • Web caching at clients, proxies, and servers
A

Web Caching System

35
Q

Advantages of Web Caching

A
  1. Reduces bandwidth consumption (decrease network traffic)
  2. Reduces access latency in the case of cache hit
  3. Reduces the workload of the Web server
  4. Enhances the robustness of the Web service
  5. Usage history collected by Proxy cache can be used to determine the usage patterns and allow the use of different cache replacement and prefetching policies.
36
Q

Disadvantages of Web Caching

A

1.Stale data can be serviced due to the lack of proper updating
2. Latency may increase in the case of a cache miss
3. A single proxy cache is always a bottleneck.
4. A single proxy is a single point of failure
5. Client-side and proxy cache reduces the hits on the original server.

37
Q

Web Caching Issues

A
  • Cache replacement
  • Prefetching
  • Cache coherency
  • Dynamic data caching
38
Q

Characteristics of Web objects

A

different size, accessing cost, access pattern.

39
Q

There are new replacement policies for Web objects:

A
  • key-based
  • cost-based
40
Q

Traditional replacement policies do not work well

A
  1. LRU (Least Recently Used),
  2. LFU (Least Frequently Used),
  3. FIFO (First In First Out),
41
Q

Two Replacement Schemes

A
  1. Key-based replacement policies
  2. Cost-based replacement policies

key-based replacement policies help decide which items to remove from storage when you need to make room for new ones. They each have their own way of choosing which items to remove based on factors like size, usage history, or download speed.

42
Q

Cost-based replacement policies

A
  • Cost function of factors such as last access time, cache entry time, transfer time cost, and so on
  • Least Normalized Cost Replacement: based on the access frequency, the transfer time cost and the size.
  • Server-assisted scheme: based on fetching cost, size, next request time, and cache prices during request intervals.

help determine which items to keep or remove from storage based on factors like how often they’re used, how long it takes to access them, and any associated costs. Each policy uses different criteria to make these decisions, ultimately aiming to optimize storage efficiency and performance.

43
Q
A
44
Q

Prefetching

A
  • The benefit from caching is limited.
  • Maximum cache hit rate - no more than 40-50%
  • to increase hit rate, anticipate future document requests and prefetch the documents in caches
  • documents to prefetch
  • considered as popular at servers
  • predicted to be accessed by user soon, based on the access pattern
  • It can reduce client latency at the expense of increasing the network traffic.

  • prefetching is like getting ready for a party by preparing snacks before guests arrive.
  • By predicting which documents users will want to access and fetching them in advance, prefetching can help reduce wait times for users, but it also means more data traveling over the network.
45
Q
  • Cache may provide users with stale documents.
  • HTTP commands for cache coherence
  • GET: retrieves a document given its URL
  • Conditional GET: GET combined with the header IF-Modified-Since.
  • Pragma no-cache: this header indicate that the object be reloaded from the server.
  • Last-Modified: returned with every GET message and indicate the last modification time of the document.
    * Two possible semantics*
  • Strong cache consistency
  • Weak cache consistency
A

Cache Coherence

  • ensures everyone accessing the same document gets the most recent version.
  • HTTP commands like GET, Conditional GET, and Pragma no-cache help achieve this by fetching updated versions of documents as needed, and Last-Modified helps track when a document was last updated.
  • There are two approaches to cache consistency: strong, where everyone gets the same version immediately, and weak, where updates might take a bit longer to propagate to everyone
46
Q

HTTP commands for cache coherence

A
  1. GET: retrieves a document given its URL
  2. Conditional GET: GET combined with the header IF-Modified-Since.
  3. Pragma no-cache: this header indicate that the object be reloaded from the server.
  4. Last-Modified: returned with every GET message and indicate the last modification time of the document.
47
Q

Strong cache consistency

A
  • Client validation (polling-every-time)
  • sends an IF-Modified-Since header with each access of the resources
  • server responses with a Not Modified message if the resource does not change
  • Server invalidation
  • whenever a resource changes, the server sends invalidation to all clients that potentially cached the resource.
  • Server should keep track of clients to use.
  • Server may send invalidation to clients who are no longer caching the resource.

  • ensures that clients always have the latest version of a webpage.
  • Clients ask the server if a webpage has changed since the last visit, and if it has, the server sends the updated version. If the webpage hasn’t changed, the server tells the client it’s still the same, saving unnecessary data transfer.
  • If the webpage does change, the server notifies all clients, even those who aren’t currently caching the webpage, to ensure everyone stays up-to-date.
48
Q

Weak Cache Consistency

A
  • Adaptive TTL (time-to-live)
  • adjust a TTL based on a lifetime (age) - if a file has not been modified for a long time, it tends to stay unchanged.
  • This approach can be shown to keep the probability of stale documents within reasonable bounds ( < 5%).
  • Most proxy servers use this mechanism.
  • No strong guarantee as to document staleness
  • Piggyback Invalidation
  • Piggyback Cache Validation (PCV) - whenever a client communicates with a server, it piggybacks a list of cached, but potentially stale, resources from that server for validation.
  • Piggyback Server Invalidation (PSI) - a server piggybacks on a reply to a client, the list of resources that have changed since the last access by the client.
  • If access intervals are small, then the PSI is good. But, if the gaps are long, then the PCV is good.
    *

  • adaptive TTL adjusts how long files stay in the cache based on how often they change.
  • Piggybacking adds extra information to messages sent between clients and servers to help them keep their caches up-to-date.
  • This ensures that even if some files in the cache are outdated, the probability of having stale documents is kept low, and the cache stays relatively fresh.
49
Q

Dynamic Data Caching

A
  • Non-cacheable data
  • authenticated data, server dynamically generated data, etc.
  • how to make more data cacheable
  • how to reduce the latency to access non-cacheable data
  • Active Cache
  • allows servers to supply cache applets to be attached with documents.
  • the cache applets are invoked upon cache hits to finish necessary processing without contacting the server.
  • bandwidth savings at the expense of CPU costs
  • due to significant CPU overhead, user access latencies are much larger than without caching dynamic objects.
  • Web server accelerator
    resides in front of one or more Web servers
    provides an API which allows applications to explicitly add, delete, and update cached data.
    The API allows static/dynamic data to be cached.
    An example - the official Web site for the 1998 Olympic Winter Games
    whenever new content became available, updated Web reflecting these changes were made available within seconds.
  • Data Update Propagation (DUP, IBM Watson) is used for improving performance.
  • Data Update Propagation (DUP)
  • maintains data dependence information between cached objects and the underlying data which affect their values
  • upon any change to underlying data, determines which cached objects are affected by the change.
  • Such affected cached objects are then either invalidated or updated.
  • With DUP, about 100% cache hit rate at the 1998 Olympic Winter Games official Web site.
  • Without DUP, 80% cache hit rate at the 1996 Olympic Games official Web site.
    *

  • dynamic data caching is about finding ways to speed up access to data that changes frequently, like personalized information.
  • Active cache adds little helpers to cached documents to do some processing without contacting the server each time. While this saves on bandwidth, it can also increase user access times due to extra processing overhead.
  • DUP helps spread these updates across the caching system quickly and efficiently. It ensures that everyone who visits your website gets the most up-to-date information without any lag.
50
Q

Web Caching and ReplicationProducts Design Goals

A
  • Performance
  • Minimize document retrieval latency
  • Scalability
  • Reduce the amount of data transferred
  • Balance bandwidth use
  • Manageability: easy to deploy and support
  • Maintain backward compatibility with existing client software
  • Availability
  • Maximize document availability (fault tolerant)
  • Flexibility: run on multiple hardware and OS platforms, support multiple protocols, HTTP, FTP, etc.
  • Retain transparency to user

3RD YEAR - SECOND SEM (25 decks)

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