程序员考试刷题-COMP90024-CCC-notes:COMP90024-集群和云计算-2020S1-考试复习/总结表[Ric...

# COMP90024-CCC ## Week1 - How we got here 1. What is cloud computing? - In 2013, Cloud computing is a jargon term without a commonly accepted non-ambiguous scientific or technical definition. (Anything that is not on your computer, e.g.: gmail) - In 2016, Proponents claim that cloud computing allows companies to avoid upfront infrastructure costs, and focus on projects that differentiate their businesses instead of on infrastructure. Proponents also claim that cloud computing allows enterprises to get their applications up and running faster, with improved manageability and less maintenance, and enables IT to more rapidly adjust resources to meet fluctuating and unpredictable business demand. Cloud providers typically use a "pay as you go" model. This can lead to unexpectedly high charges if administrators do not adapt to the cloud pricing model. (Everyone has different flavor) 2. Cloud Characteristics (Lecture notes and then my paraphrasing) - On-demand self-service - A consumer can provision computing capabilities as needed without requiring human interaction with each service provider. - Scale computing resources up and down by needs without requiring human interaction with each service provider. - For anyone in any time - infinite availability (key) - Networked access - Capabilities are available over the network and access through standard mechanisms that promote use by heterogeneous client platforms. - Resources can be access through network and adapted to heterogeneous client platforms. - Resource pooling - The provider's computing resources are pooled to serve multiple consumers using a multi-tenant model potentially with different physical and virtual resources that can be dynamically assigned and reassigned according to consumer demand. - Provider’s resources are pooled and can be dynamically assigned and reassigned by need. - Enough resource to scale up & down - Rapid Elasticity - Capabilities can be elastically provisioned and released, in some cases automatically, to scale rapidly upon demand. - Capabilities can scale easily and rapidly upon demand. - Measured Service - Cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service. - Resourcing optimization by measuring usage - monitor for load balance (e.g.: nigix) 3. Flavour - Compute clouds - Amazon Elastic compute cloud - Azure - Data Clouds - Amazon Simple Storage Service - Google docs - iCloud - Dropbox - Application Clouds - App store - Virtual image factories - Public(credit card and pay for using) /Private(Unimelb research cloud)/Hybrid(MRC run out of resource nad buy from Amazon)/Mobile/Health Clouds - complexity arise in: decision about what can we move out/what cost ot stay in/who is allowed this to happen 4. History - tends in computing 1. Computing and Communication Technologies (r)evolution - from centralised to decentralised 2. distributed system history - Once upon a time we had standards - Then we had more standards - mid-90s: focused on computer-computer interaction - internet: peer-to-peer - challenge: sharing data between different organizations - soln: grid computing - Grid: only need access to it no matter it is data or super computer the process to move things - problem: people have different ways to do it - Distributed System - <u>**Transparency**</u> and **<u>heterogeneity</u>** in computer-computer interactions - Finding resources -> Binding resources -> run time type checking -> invoking resources - Dealing with heterogeneous of system - Challenges - Complexity of implementations - Vendor specific solutions - Scalability problem - Sharing data between different organizations - Grid Computing - From computer-computer focus to organisation-organisation focus - Can be thought of as a distributed system with non-interactive workloads. - It is in contrast to the traditional notion of a supercomputer, which has many processors connected by a local high-speed computer bus instead of Ethernet. - Grid computing is distinguished from conventional high-performance computing systems such as cluster computing in that grid computers have each node set to perform a different task/application. Grid computers also tend to be more heterogeneous and geographically dispersed (thus not physically coupled) than cluster computers. - Although a single grid can be dedicated to a particular application, commonly a grid is used for a variety of purposes. Grids are often constructed with general-purpose grid middleware software libraries. Grid sizes can be quite large. - Challenge - What resources are available - To determine the status of resources - Job scheduling - Virtual organization support - Security - Public key infrastructure 5. Comparison between Grid/Cluster/Cloud Computing ``` Clusters "tend" to be tightly coupled, e.g. a bunch of servers in a rack with high speed interconnects - we'll go into some details of this in week 3; Grid is/was more loosely coupled resources that provided single sign-on access to distributed resources that are often hosted by different organisations; Cloud = we'll get to that soon! ;o) ``` - Grid computing - Refer to the top - Cluster Computing - Clusters tend to be tightly coupled, e.g. a bunch of servers in a rack with high speed interconnects - Example - Super computer - Cloud Computing - Refer to week 5 - Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources(networks, servers, storage, applications, services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. ### past exam - > [2013 Q1] A) Explain what is meant by the terms: - > Grid Computing [1] - focus on organizational collaboration, coordination, activity and technologies to doing it - > Cluster Computing [1] - multiple servers rach-mounted which are accessible and you can run jobs across the cluster - > Cloud Computing [1] - is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources(networks, servers, storage, applications, services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. - > [2013 Q1, 2017 Q1 B [5]] B) Current Cloud Computing systems do not solve many key challenges of large-scale distributed systems. Discuss. [7] - by below - > [sample Q2 A] Describe some of the current challenges associated with large-scale distributed systems. [4] - distributed systems didn't solve data heterogeneity. And we have big data challenges. - distributed systems has scalability and issues of fixed hardware system. We have distributed computers running on different hardware system. - fault tolerance not solved - Many diverse faults can happen with distributed systems - , e.g. server failures or partial failures, network outages, overloading of components etc etc. - There is no simple solution to this that has been widely adopted/accepted. - results in software stack - Each system tends to develop its own technical solution - , e.g. using queuing or having back-ups/failovers of system for failures. -