Distributed Systems | Distributed Computing Explained

Summary

This video script offers a concise introduction to distributed systems, explaining their fundamental concepts and components. It clarifies that distributed systems consist of independent nodes linked by a network, working together to achieve a common goal while appearing as a single entity to users. The script discusses the importance of coordination, communication, and middleware in managing system complexities. It also touches on the advantages of distributed computing, such as reliability and scalability, and the challenges, including failure detection and consistency issues, emphasizing the design-for-failure principle.

Takeaways

• 🌐 Distributed systems are a collection of independent nodes that communicate over a network to achieve a common goal, appearing as a single entity to the end-user.
• 🔍 Examples of distributed systems include Google search, Amazon, Netflix, blockchain, online gaming, and banking platforms, which are all part of our daily digital interactions.
• 💡 The client-server model is a simple and common example of a distributed system, where clients request services and servers provide responses.
• 📦 A distributed system's nodes can be either unstructured or highly structured, depending on the system's requirements, and they handle complexities hidden from the end-user.
• ⏰ Distributed systems do not share a clock or memory, meaning they operate independently and manage their own time and data storage.
• 🔄 Concurrency is a key feature of distributed systems, allowing multiple processes to execute tasks in parallel, enhancing performance and efficiency.
• 🔗 Middleware is a critical component in distributed systems, providing a layer that connects nodes, manages resources, and offers communication and security services.
• 🔄 Coordination and synchronization are essential for managing the lack of shared clock and memory, ensuring smooth operation and data consistency across nodes.
• 🏗️ Architectural models in distributed systems, such as layered, object-based, data center, and event-driven, dictate how nodes are organized and interact.
• 🌟 Advantages of distributed systems include reliability, scalability, fault tolerance, resource sharing, and enhanced performance.
• 🚧 Challenges in distributed systems include failure detection, redundancy, consistency issues, and potential performance bottlenecks, necessitating careful design and management.

Q & A

What is a distributed system?

A distributed system is a collection of separate and independent software or hardware components called nodes that are linked together by a network and work together coherently by coordinating and communicating through message passing or events to fulfill a common goal. The complexities of the system are hidden from the end-user, making the whole system appear as a single computer.

Why is nearly all software today considered to some extent distributed or involving distributed computing?

Nearly all software today is considered distributed because many applications, such as Google search engine, Amazon platforms, Netflix, blockchain, online gaming, money transfer, and online banking, inherently involve distributed computing to provide their services effectively and efficiently across different locations and devices.

What is the simplest example of a distributed system?

The simplest example of a distributed system is the client-server model, where the client and server communicate over a network to perform tasks and share resources.

What are the two main conditions for a system to be considered distributed rather than centralized or parallel?

For a system to be considered distributed, there should be no shared clock and no shared memory among the components. Each element in the system must have its own processor, and harmony is achieved through coordination and synchronization.

What is an overlay network in the context of distributed systems?

An overlay network is a virtual network built on top of an underlying network infrastructure. It is a network on top of another network, such as peer-to-peer networks like blockchain and BitTorrent, or voice over IP, which is an overlay network over the Internet.

What is the role of middleware in a distributed system?

Middleware in a distributed system is a layer that connects the nodes together and makes them appear as one single, supercomputer. It is a logical layer on top of the whole system that manages resources, provides communication and security services, and handles barriers and complexities of distributed computing.

What is the difference between concurrency and coordination in distributed systems?

Concurrency refers to the fact that multiple operations and activities are executed in parallel, potentially interacting with each other. Coordination, on the other hand, ensures the smooth collaboration between operations and activities, helping to achieve agreement among them.

What are the main reasons for preferring a distributed system over a single supercomputer?

The main reasons for preferring a distributed system include the need for geographical dispersion, resource sharing, scalability, fault tolerance, increased performance, and the ability to handle large repositories of data and significant computing power requirements.

What are the two main types of distributed computing in terms of scale?

The two main types of distributed computing in terms of scale are cluster computing and grid computing. Cluster computing uses closely connected, identical computers with local and centralized management, while grid computing involves heterogeneous nodes dispersed over a large area with decentralized administration.

What are some of the challenges associated with distributed systems?

Some of the challenges associated with distributed systems include failure detection, redundancy, achieving consistency among nodes, and performance bottlenecks. These challenges often arise from the complexities of managing a system that is designed to be robust and scalable.

What is the 'design for failure' principle in the context of building distributed systems?

The 'design for failure' principle is a crucial approach in developing distributed systems where developers expect and plan for the worst-case scenarios in every aspect of system operation. This includes anticipating and mitigating potential failures to ensure the system remains robust and reliable.

Outlines

00:00

🌐 Introduction to Distributed Systems

This paragraph introduces the concept of distributed systems, emphasizing their ubiquity in modern technology such as Google, Amazon, and Netflix. It clarifies that distributed systems consist of independent nodes that communicate over a network to achieve a common goal, appearing as a single entity to the user. The importance of understanding that two programs on the same computer do not constitute a distributed system is highlighted, and the necessity for nodes to have their own processors and memory is explained. The paragraph sets the stage for a deeper dive into the topic by outlining the basic characteristics and requirements of distributed systems.

05:01

🔍 Key Concepts of Distributed Computing

The second paragraph delves into the fundamental concepts of distributed computing, which extends beyond the structure of distributed systems to include computing models and algorithms. It introduces cloud computing as a modern example and discusses the basic elements such as nodes, resources, and middleware that facilitate communication and resource management within distributed systems. The paragraph also covers concepts like distribution transparency, concurrency, coordination, synchronization, and architectural models, which are crucial for understanding how distributed systems operate and are organized. The advantages of using distributed systems, such as scalability and reliability, are briefly mentioned, setting up the discussion for the subsequent paragraph.

10:03

🛠 Types and Considerations in Distributed Systems

This paragraph explores the different types of distributed systems based on scale and architecture, such as cluster and grid computing, and architectural styles like layered, object-based, data center, and event-driven. It discusses the advantages of distributed computing, including reliability, scalability, fault tolerance, resource sharing, and performance. The paragraph also addresses the challenges associated with distributed systems, such as failure detection, redundancy, consistency, and performance bottlenecks. The importance of designing for failure is emphasized, highlighting the need to expect and plan for the worst-case scenarios in system operation.

15:05

📚 Conclusion and Final Thoughts

The final paragraph concludes the video script by summarizing the key points discussed in the video and highlighting the difference between a distributed system and a simple network. It emphasizes the robustness and security of distributed systems compared to networks and encourages viewers to subscribe for more content. The paragraph leaves the audience with a comprehensive understanding of distributed systems and their significance in contemporary computing environments.

Keywords

💡Distributed Systems

Distributed Systems refer to a collection of separate and independent software or hardware components, known as nodes, that are linked by a network and work together coherently. They are essential to the video's theme as they form the basis for discussing various concepts like client-server model, nodes, and system architecture. The script mentions examples such as Google, Amazon, and Netflix to illustrate the ubiquity of distributed systems in modern technology.

💡Distributed Computing

Distributed Computing is a broader term that encompasses the building of computing models and algorithms for distributed systems. It is distinguished from the concept of a distributed system by focusing on the computational aspect. The video discusses distributed computing in the context of cloud computing and other services like PaaS and IaaS, emphasizing its importance in modern technology solutions.

💡Nodes

In the context of the video, nodes are the individual software or hardware components of a distributed system that have their own processors and memory. They are key to the operation of distributed systems, as they communicate and coordinate with each other to achieve a common goal. The script explains that nodes can be either part of open or closed groups, with the Internet serving as an example of an open group of nodes.

💡Client-Server Model

The Client-Server Model is a fundamental example of a distributed system architecture where the client makes requests and the server provides responses. The video script uses this model to demonstrate a simple form of distributed systems, highlighting its prevalence and the need for understanding it as a basis for more complex distributed systems.

💡Resource

A resource in distributed systems is any asset that can be accessed remotely by nodes or users of the distributed applications. The script mentions that resources can include files, services, storage facilities, and other networks, emphasizing their importance in the functionality of distributed systems by providing the necessary assets for operations.

💡Middleware

Middleware in distributed systems is a layer that connects nodes together, making the system appear as a single, unified entity. It manages resources, communication, and security services, and handles complexities of distributed computing. The video script describes middleware as an essential component that allows for the development and operation of distributed applications by abstracting the underlying distributed nature of the system.

💡Concurrency

Concurrency in the video is described as the execution of multiple operations and activities in parallel within a distributed system. It is an intrinsic property of distributed systems that allows for efficient task execution and is illustrated in the script with a diagram showing different phases of a distributed program where tasks are performed concurrently.

💡Coordination and Synchronization

Coordination and synchronization are concepts that address the challenges of managing processes in a distributed system without a shared clock. Coordination ensures smooth collaboration between operations, while synchronization controls access to shared resources to prevent data corruption and inconsistency. The script discusses these concepts as essential for maintaining system integrity and performance in distributed computing.

💡Architectural Model

The architectural model in distributed systems defines how nodes are organized and how they communicate and interact. The video script explains different architectural styles such as layered, object-based, data center, and event-driven architectures, each with its own approach to organizing and managing distributed systems for optimal performance and scalability.

💡Global State

Global state in distributed systems represents the collective state of all separate processes, providing a unified view of the system's properties at a specific point in time. The script mentions global state as an important concept that helps in understanding the overall status of a distributed system, akin to a global object containing all the system's global variables.

💡Scalability

Scalability is the ability of a distributed system to handle growth, either by adding more nodes or by expanding existing resources. The video script highlights scalability as one of the main advantages of distributed systems, allowing for horizontal scaling to meet increased demand or workload without significant reconfiguration.

💡Failure Detection

Failure detection in distributed systems is the process of identifying when a node or component has stopped functioning properly. The script points out that failure detection can be challenging, especially in large and evolving systems, and is an important consideration in designing robust distributed systems.

💡Design for Failure

Design for failure is a principle in developing distributed systems that involves anticipating and planning for potential failures in every aspect of system operation. The video script emphasizes this principle as crucial for creating systems that are resilient and can continue to operate reliably even when components fail.

Highlights

Introduction to distributed systems and distributed computing.

Explanation of how nearly all modern software involves some form of distributed computing.

Client-server model as the simplest example of a distributed system.

Detailed definition of a distributed system: a collection of independent nodes coordinated to fulfill a common goal.

Importance of no shared clock and no shared memory in distributed systems.

Discussion on the concepts of concurrency, heterogeneity, and loose coupling in distributed systems.

Overview of open and closed groups in distributed systems, with examples like the Internet and intranets.

Introduction to overlay networks, such as blockchain and BitTorrent, which operate on top of the Internet.

Explanation of the middleware layer that connects nodes and makes them appear as a single supercomputer.

Description of key concepts like nodes, resources, distribution transparency, and global state in distributed computing.

Discussion on the motives for using distributed systems, including resource sharing, scalability, and fault tolerance.

Comparison of cluster computing and grid computing based on scale and coupling.

Overview of architectural styles in distributed systems: layered, object-based, data center, and event-driven.

Advantages of distributed systems, including reliability, scalability, and increased performance.

Challenges of distributed systems, such as failure detection, redundancy, and consistency issues.

Transcripts

hello geeks this is me a year from a

bonus video about distributed systems in

this video I try to provide a concise

overview about distributed systems and

distributed computing as an extra video

listen to the architectural patterns

series so without further ado let's dive

in into the topic first let's explain

and clarify what a distributed system is

and what it's not but before that let me

tell you something that you may not be

aware of nearly all the software we use

today is to an extent distributed or

involve distributed computing how you're

gonna know the answer in a bit for now

let me just give you some examples

distributed systems or distributed

computing is all around us

Google search engine Amazon platforms

Netflix blockchain online gaming money

transfer and online banking and the list

goes on probably the most

straightforward and the simplest example

of distributed systems is the

client-server model which I assume you

are familiar with and if not you can

check my short video about it I'll go

back to this model for the sake of

demonstration later for now let's go

back to the fundamental question and see

what exactly a distributed system is a

distributed system is a collection of

separate and independent software or

hardware components called nodes that

are linked together by means of a

network and work together coherently by

coordinating and communicating through a

message passing or events to fulfill one

and goal nodes of the system could be

unstructured or highly structured

depending on the system requirements in

any case the complexities of the system

remain hidden to the end-user be it a

human being or a computer and the whole

system appeared as a single computer to

its users alright let me repeat with the

written words now a distributed system

is a collection of separate and

independent software or hardware

components called nodes that are

networked hidden work together

coherently by coordinating and

communicating through a message passing

or events to fulfill one and goal nodes

could be instructed or highly structured

depending on the system requirements and

the complexities of the system are

hidden to the end user making the whole

system appear as a single computer to

its users so basically it's just a bunch

of independent computers that cooperate

to solve a problem together I know it

sounds simple but it's a hell of a world

under the hood before we continue though

I just want to say that two programs

communic

with each other on the same computer is

not necessarily a distributed system

even though they work together to

achieve the same goal a client-server

model that uses the same computer is not

a distributed system this is important

to know of course there is the exception

of parallel multiprocessor computers but

for the sake of simplicity in clarity

it's not tackle complicated examples

that's because for systems be called

distributed as opposed to centralized or

parallel the following conditions needs

to be true first no shared clock

computers have clocks also called timers

which are critical electronic devices

that keep track of oscillations and they

help the computer to have its own notion

of time this in turn helps to determine

the order between events and regulates

at the time and speed of the computer

operations if two programs communicate

using the same computer they basically

have the same clock this is as to

another requirement for distribution

systems which is that each element in

this system has to have its own

processor and harmony is achieved

through coordination and synchronization

the second principle is no shared memory

this is another key feature of

distributed systems this means nearly

each process has its own independent

memory to work with and States is

distributed throughout the system

concurrency is another important

characteristic of distributed systems

which means that software and hardware

components of the system also called

processes are autonomous and execute

tasks concurrently and last but not

least heterogeneity and lose copy which

means the processors are independent and

separate from each other and they have

different speeds even though

heterogeneity in loose coupling are not

necessary almost invariably in nodes in

distributed systems run different

operating systems and components can be

built with different technologies and

run on different platforms before moving

on to basic concepts about distributed

computing I just want to mention a

couple of notes first distributed system

is a dynamic system that allows

computers or nodes to join and leave at

well this has many advantages as we'll

see later but also it introduces some

challenges in overhead such as in case

of open distributed systems security

issues and the extra work of managing

the organization and membership of nodes

the second thing I want to say is the

nearly all existing large distributed

systems especially modern ones are

overlaying networks what in the universe

is an overlay network and not real a

network is a virtual network that was

possible to build thanks to an

underlying network infrastructure but

simply an overlay network is just a

network on top of another network for

instance PHP networks such as blockchain

and BitTorrent and overlay networks that

is to say there are networks on top of

the Internet

voice over IP is another network over

the Internet so it's also called an

online network ok I hope by now you have

a fair idea about what a distributed

system is and can tell whether system is

distributed or not good now let's talk

about some important basic concepts

about distributed computing okay so

distributed computing is a type of

computing over distributed systems right

so this means that distributed computing

is more than distributed systems it's a

broader term and it is concerned with

building and establishing computing

models for distributed systems and

working out algorithms to solve problems

related to such systems cloud computing

is a good modern example of distributed

computing other examples of distributed

computing solutions are platform as a

service infrastructure as a service

server LS etc now we will keep things

simple and don't call me about basic

distributed computing concepts all right

so one of the very basic concepts that

you should know about is the notion of a

node and notice the software or hardware

components that has its own processor a

memory and is able to communicate with

the rest of the system nodes form open

groups that is to say a network of nodes

that is open to the external world and

thus join and the network is easy and

also external entities can communicate

with the system easily the internet is

one big giant distributed system that

falls under this category nodes can also

form closed groups which are restricted

in terms of membership authentication

and resource accessibility internets an

example of that of course nodes can

communicate via messaging mechanisms

such as RPC calls brest services etc

another important notion is what is

referred to as a resource a resource is

an asset in the distributed system that

could be accessed remotely by nodes in

the network or users of the distributed

applications that are over the

distributed system resources can be

virtually anything such as files

services storage facilities other

networks etc basically a resource is

anything that a node can take advantage

of or use distribution transparency is

another important concept which denotes

that everything that happens under the

hood should stay invisible to the end

users of the system in other words the

dispersion of resources the failure of

nodes and fail overs migration and

replication operations etc all should be

invisible to users of the system the way

to achieve this is through an important

component called the middleware and

speaking of which a middleware in this

context is a distributed systems layer

that connects the nodes together and

make them appear as one single

supercomputer it is a logical layer on

top of the whole system think of it as

an operating system that runs over the

nodes collectively once this layer is

established distributed applications

could be built and run over it this

middleware layer manages resources

provides communication and security

services handles barriers and the other

complexities of distributed computing

etc next is concurrency we have talked

about this concept before in the

characteristics in simple words

concurrency is the fact that multiple

operations and activities are executed

in parallel these activities can

interact among each other to perform a

particular operation in this diagram for

example a simple distributed program is

visualized we could see that in phase 1

task 1 and 2 are executed in parallel

and there is a simple interaction

between them phase 2 has three

operations in parallel in one

cooperation between two of them and as

we saw earlier concurrency is an

intrinsic property of distributed

systems all right

coordination and synchronization these

are two important concepts that tackle

the problems of no shared clock between

processes and also they solve the

problem of data corruption and

inconsistency if two entities try to

access data at the same time

coordination ensure the smooth

collaboration between operations and

activities and help achieve agreement

among them synchronization on the other

hand orders and controls access to

shared resources

the next concept is the architectural

model the architectural model dictates

how the nodes in the system are

organized it defines the structure of

the network as well as how knows

communicate and interact the

architectural model is extremely

important

in distributed computing for the sake of

better management of the complexities of

such systems and also for ease of

maintenance mainly the architecture is

needed for software components and

that's because as we said earlier most

distributed systems are overlay networks

the last concept I want to talk about is

global state global state in distributed

systems is the union of the states of

the separate processes it is sort of a

global view of the system that describes

its properties at a particular point in

time it's sort of the equivalent of a

global objects that contains all the

global variables used by the software

system now why not use one single

supercomputer that could do everything

we want and save ourselves the trouble

why use instead of that several

computers and add the overhead of

managing and maintaining them that's

actually a good question

and the answer is that the motives to

use a distributed system instead of a

single computer are many one of the most

common ones is the need for a solution

where we need to reach a consensus among

parties that are dispersed

geographically examples of such cases

are online banking blockchain barian

platforms etc resource sharing is

another reason why we need distributed

system such as databases or distributed

file systems another example that falls

under the same reason are peer-to-peer

systems like the BitTorrent Network etc

another case where we need a distributed

system is one we can not or it's

inefficient to replicate data using one

computer also when scalability is of

crucial importance a distributed system

is probably the optimal solution of

course there are other reasons why one

would choose a distributed system such

as availability reliability etc so these

are the main reasons why one would

prefer to go for a distributed system

related to the motives for using such

systems are the advantages of

distributed computing but before talking

about the advantages and challenges of

distributed systems let's briefly talk

about their types when talking about

types of distributed systems or any kind

of systems it's important to understand

that classification depends on the

context and on the level of complexity

we're taking into account are we talking

about architecture

are we classifying the system based on

the end goal is the context related to

the topology is it related to how couple

at the nodes are etc in this section I'm

going to address two types of

classification the first is general

and relates to the type of coupling and

scale and the second is related to the

architectural model of the whole system

when talking about distributed systems

in terms of scale there are two main

types of distributed computing cluster

computing and grid computing in cluster

computing systems the underlying

infrastructure is composed of identical

computers that are closely connected and

the management is local and centralized

cluster computing is used to achieve

high performance and minimize downtime

grid computing on the other hand is a

type of systems in which heterogeneity

is the norm in terms of hardware

software and technology nodes of

dispersed over a very large area and

administration is decentralized such

systems are used when a large repository

of data is involved and a lot of

computing power is required all right

and if we're talking about architecture

styles on the other hand distributed

systems fall under one of the following

categories first layered architecture in

this architectural model nodes are

grouped into separate layers each with a

specific goal to achieve an example of a

simple layer distributed system is the

client-server model next the object

based architecture knows in subsystems

are less structured and loosely coupled

than the layered model communication is

a synchronous and the elements of the

system can directly interact with other

elements through direct calls the third

architectural model is the data center

architecture in such systems nodes

communicate through a common repository

the system is based on a data center

through which trimeric communication

happens and the last one which is more

common one is the advanced driven

architecture model eventual driven

systems achieve their goals by means of

events nodes communicate and perform

operations through the propagation of

and the reaction to events feel free to

check my video about the event driven

architecture pattern to know more so

these are the main architectural styles

for distributed systems in a nutshell

all right and let's talk now about the

pros and cons of distributed computing

as always let's start with the

advantages the first advantage I want to

talk about is reliability a defining

characteristic of distributed systems is

the reliable interconnection and

cooperation between nodes in the whole

system this makes it easy to share data

between node another great advantage is

scalability in fact this is one of the

main reasons as to why someone or an

organization would opt for a distributed

system in distributed computing

scalability is a matter of adding more

nodes to the system at the correspondent

layer or level or what is referred to as

horizontal scaling and

common advantages for tolerance it means

the system and its services will still

be operational and reliable even when

parts of the system goes down of course

as we said before resource sharing

becomes not only possible but also easy

in subsistence and last but not least

increased performance but as all matters

of life distributed systems are not a

silver bullet and actually talking about

the downsides of distributes computing

is a separate topic in itself first

failure detection failure detection is

almost impossible in distributed systems

especially if the system is large and

evolves over time very elaborate

measures need to be taken to mitigate

risks of this issue redundancy is a

common issue among distributed systems

as well another challenge or problem is

the difficulty to achieve consistency

among nodes and finally performance

bottlenecks is a serious issue as well

actually when it comes to distributed

systems the more we design for failure

any kind of failure at all levels the

less problems we will have this leads us

to the final section issues and

considerations of the most important

pitfalls when building distributed

systems is the four assumptions made by

developers such as the network is

reliable and secure or the topology of

the underlying network doesn't change or

that latency is zero this leads to a

poor and fragile system that breaks

easily and actually one of the crucial

principles developers and architects

abide by when designing and developing

distributed systems is the design for

failure principle under this rule there

are a lot of considerations to take into

account but generally speaking designed

for failure is expecting the worst-case

scenario in each and every aspect when

the system is operational and planned

for that all right this should be enough

for a brief overview of distributed

systems the last thing I want to say is

that unlike distributed systems nodes in

a network are explicitly visible and

have to be explicitly addressed also a

network in itself doesn't have to have a

specific end goal and it's usually not

robust and secure as a distributed

system that's difference between a

distributed system and a network alright

I hope you've enjoyed this video and

learned something new don't forget to

subscribe until the next video stay

tuned