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‎.gitignore

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_site/
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.sass-cache/
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.jekyll-metadata
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Gemfile.lock
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Gemfile.lockx
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### Example user template template
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### Example user template
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‎_layouts/default.html

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<head>
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<meta charset="utf-8">
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<link rel="stylesheet" href="/css/main.css"/>
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<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.1.1/jquery.min.js"></script>
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{% for script in page.scripts %}
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<script type="text/javascript" src="{{site.baseurl}}{{script.src}}"></script>
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{% endfor %}
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<title>{{page.title}}</title>
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</head>
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<body class="homepage-body">
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<hr style="clear:both">
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<footer >
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<p class="regular-text">Copyright © 2017 JPCMarques</p>
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<p class="regular-text" style="margin-left: 0">Copyright © 2017 JPCMarques</p>
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</footer>
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</body>
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</html>

‎_study-wiki/PP2.md

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---
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layout: subpage
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title: PP2
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sidebarClass: sidebar
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navbar:
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- Back: study-wiki
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---
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‎_study-wiki/cloud-computing-and-virutalization.md

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layout: subpage
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title: Cloud Computing and Virtualization
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sidebarClass: sidebar
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navbar:
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- Back: study-wiki
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---
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# Cloud computing as an Utility #
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Illusion of infinity resources on demand:
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* 1 CPU x 100h = 100 CPU x 1h
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Removal of any a priori commitment
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* no or very low initial costs
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* reduce CapEx (capital expenditure), convert to OpEx
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Small granularity payments
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* computing paid by CPU hour, web request, storage access, or bandwidth used
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Shared hosting (one server with multiple websites)
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Virtual dedicated server
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* Resource sharing among different websites on same machine
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* Possibly proportional to payment
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Managed dedicating hosting
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* One server per website with partial admin rights
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* For good QoS
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Dedicated hosting: one server per client (simple and flexible)
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Collocated hosting: client owns the machine (provider guarantees network QoS)
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Cluster hosting: multiple rented machines (for scalability)
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Grid hosting: Multiple geographically distributed and replicated machines (for scalability, latency/speed, fault tolerance)
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# Successes of Cloud Computing #
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Scalability, grow as you go along
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* grow the company (start ups with no H/W risk)
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* grow the application
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Utility aspects
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* no system admins
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* low granularity payments
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Varied development paradigms
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* VMs, web apps, etc
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# Problems of Cloud Computing #
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* Availability
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* Lock-in
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* Privacy and auditing
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* Cost of data transfer
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* Performance reliability
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* Scalable storage
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* Large scale bugs
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* Scale-out time
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* Reputation propagation
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* Compatible licensing
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# Abstraction #
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Complexity in computer systems (hw/sw)
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Abstraction hides details
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* key to manage complexity
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* simplified interface to underlying resources
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* approach = levels of abstraction + well-defined interfaces
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## Well-defined interfaces ##
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Examples:
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* Instruction sets
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* OS system calls
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* Libraries
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* Byte-code format
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Advantages:
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* Decoupling
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* Independence from changes in internal details
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* vendor independence
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* parallel development
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* diversity: competing abstractions favour innovation
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Disadvantages:
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* Interfaces are confining
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* may reduce interoperability
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* subsystems designed for one interface do not work with others
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* assumption that oS has full control over hw
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* very restrictive specially in networked environment
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* limited flexibility, lock-in, security and failure isolation
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Solution?
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* keep advantages and avoid disadvantages
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* virtualization: mapping of interfaces
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## Virtualization ##
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Isomorphism
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* virtual guest, real host
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* state mapping
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* emulation
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Virtualization vs abstraction
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* abstraction is also an isomorphism
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* virtualization does not necessarily hide details (maintains similar state size and number of operations)
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Examples:
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* Virtual hard disks
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* VMs
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* VMWware with Linux guest running on Windows host

‎_study-wiki/data-and-information-systems-administration.md

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layout: subpage
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title: Database Management Systems
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navbar:
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---
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[refs]: c1 silber and ragu
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<div id="Purpose "></div>
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# Purpose of Database Management Systems #
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---
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A DBMS is a collections of interrelated data and set of programs to access the data.
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DB contain relevant information about a particular enterprise/organization
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DBMS provides and environment which is efficient and convenient to use
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## Issues of file systems for data storage ##
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* Data redundancy and inconsistency (multiple formats, duplication of information in diff files)
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* Difficulty in data access (need a new program for each new task)
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* Data isolation (multiple files and formats)
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* Integrity (integrity problems become part of program code, making it hard to add new ones)
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* Atomicity of updates
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* Concurrent access
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* Security
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## Why a DBMS? ##
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* Provides independent data and (much more) efficient access to that data.
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* Since a DBMS removes the need to control data from the application itself, it reduces application development time.
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* Data integrity and security (obviously reducing development time), through usage of mechanisms such as Data Abstraction
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* Uniform data administration ????
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* Concurrent access and crash recovery (namely through atomicity of access)
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## Levels of Data Abstractions ##
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### Physical level ###
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Describes how data is stored
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### Logical level ###
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Describes data stored in the database, and the relationships among the data
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### View level ###
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Application programs may hide details of data types; views can also hide information for security purposes
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## Data models ##
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A collection of conceptual tools for describing data, relationships among them, their semantics and constraints
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## Data Independence ##
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Applications are insulated from how data is structured and stored
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**Logical data independence** - protection from changes in the logical structure of data
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**Physical data independence** - protection from changes in the physical structure of data
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## Instances and Schema ##
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**Schema** - logical structure of the database, the description of a particular collection of data using a given data model
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(analogous to a class in java)
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* *Physical* and *Logical* schemas differ on what level they are designed in (physical or logical)
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**Instance** - the content of the database at a particular point in time (analogous to the value of variable)
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## SQL: Structured Query Language ##
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A relational DBMS provides a DDL and a DML as part of a single DB language (SQL)
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SQL is a declarative query language (user specifies what data is required, without specifying the method of access;
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in procedural languages the method is specified)
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### DDL (Data Definition Language)###
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DDL compiler generates a set of tables stored in a data dictionary, which essentially contains metadata
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### DML (Data Manipulation Language)###
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Language for accessing and manipulating data
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## Transaction Management ##
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A transaction is a collection of operations that perform a single logical function in a database application
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The transaction management component ensures that the database remains in a consistent state despite system and transaction failures
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Transactions must be ACID (Atomic, Consistent, Isolated and Durable/persistent)
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## Database Users ##
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Users are differentiated by the way they expect to interact with the system
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* Application programmers: interact with the system through DML calls
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* Sophisticated users: form requests in a database query language
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* Naïve/end users: invoke one of the permanent application programs that have been written previously
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* Database administrator: coordinate all the activities of the database system, has a good understanding of the enterprise's information
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resources and needs:
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* Schema definition
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* Storage structure and access method definition
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* Schema and physical organization modification
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* Granting user authority to access the database
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* Specifying integrity constraints
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* Acting as liaison with users
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* Monitoring performance, tuning the system and responding to changes in requirements
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## Database Tuning ##
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Activity of making a database application run faster (higher throughput, though it may mean lower response time for time-critical applications)

‎_study-wiki/enterprise-integration.md

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# #
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---
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Development must handle changing needs fast enough to meet demands -> Reduce magnitude of development cycle (smaller phases = higher adaptability, e.g. SCRUM)
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Adapting software is usually better and faster to reach a minimum deliverable product, as opposed to building from scratch.
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Adaptability to change is also important for internal processes, to shorten their duration and increase their efficiency.
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There's an higher and higher need to adapt for any situation, typically with things out of the enterprise's control, to integrate with a larger number of entities
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seamlessly and effortlessly (integration with and in **supply chains**)
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# Elaborate here #
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# Legacy applications #
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