Distributed Systems | Distributed Computing Explained
Summary
TLDRThis 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
🌐 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.
🔍 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.
🛠 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.
📚 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.
Mindmap
Keywords
💡Distributed Systems
💡Distributed Computing
💡Nodes
💡Client-Server Model
💡Resource
💡Middleware
💡Concurrency
💡Coordination and Synchronization
💡Architectural Model
💡Global State
💡Scalability
💡Failure Detection
💡Design for Failure
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
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