Key Points
- A distributed system is a group of connected computers or nodes that work together as one system, distributing workloads across cloud platforms and large-scale applications to improve scalability and fault tolerance.
- Distributed systems work by splitting tasks across multiple nodes that communicate over a network, allowing services and data processing to run simultaneously while maintaining performance.
- Compared to centralized systems, distributed systems reduce single points of failure and scale more efficiently, but they also introduce challenges like latency and security risks.
Distributed systems are used across cloud platforms and large-scale applications, among others. Instead of relying on one computer or service, distributed systems divide work across multiple connected components.
This structure is useful, as it improves scalability and fault tolerance. However, it also introduces operational complexity. As a result, IT teams need to understand how distributed systems communicate and affect monitoring and security.
What is a distributed system?
A distributed computing system is a collection of software components found on different computers (called nodes) that work together as a single system.
These nodes communicate to share data and tasks to achieve a common goal, ensuring coordination between multiple systems while appearing unified to the user. This process is transparent to the end-user, who interacts with an app or website.
Distributed systems commonly appear in cloud applications, distributed databases, container clusters, and the like. The defining trait is coordination across different components instead of execution on a single machine.
How do distributed systems work?
There isn’t a single design or implementation pattern that best describes how distributed systems work. It’s usually broken down into patterns aligned with different types of businesses involved.
The best way to understand how distributed systems work is through an example. Let’s say you’re rendering a video. The video editor splits the job into pieces. Afterward, the algorithm gives one video frame to each of a dozen nodes to complete the rendering.
Once the frame is complete, the application gives the nodes a new frame to work on until the entire rendering process is done.
Distributed vs. centralized systems
A centralized system relies on a primary server to manage processing or services. This approach is easier to manage and troubleshoot because fewer components are involved.
However, centralized systems can create bottlenecks and single points of failure if the main system is unavailable. Distributed systems spread workloads across connected nodes, which can improve scalability and fault tolerance since workloads continue even if a component fails.
The tradeoff is complexity, since distributed systems require stronger coordination and dependency management. Issues like latency and partial failures can make troubleshooting more difficult than in centralized environments.
Distributed vs. decentralized systems
Distributed and decentralized systems are related, but they describe different concepts. For one, a distributed system spreads workloads across nodes or services, focusing on where processing and data handling occur.
Meanwhile, a decentralized system spreads control or decision-making across participants instead of relying on one central authority. A system can be distributed but still centrally managed.
For example, a cloud platform may operate across different regions while remaining under the control of a provider. Blockchain and P2P networks are often distributed and decentralized because workloads and control are shared across participants.
Common types of distributed systems
You can classify distributed systems into different types based on how nodes are organized, how they communicate, and how tasks are distributed across the system.
As such, there are numerous types, with the common ones including client-server systems, P2P systems, clustered systems, and cloud-based distributed systems.
Client-server systems
A client-server system is a system where a central server provides services, while different clients request these services over a network. The general gist is that a server manages data and processing, while the clients receive responses.
Some examples include email applications, such as Gmail, and online banking systems.
Peer-to-peer (P2P) Systems
A peer-to-peer (P2P) system is a distributed system where all nodes are equal and act as both client and server without a central authority.
A popular example of this includes blockchain networks. Blockchains operate as a decentralized, distributed database, with data stored across different computers.
Clustered systems
A clustered system is a group of connected computers that work as a single system to improve performance and reliability.
The backbones of this system are nodes working in a tightly connected network, and the fact that tasks are shared. Some examples of clustered systems include weather forecasts and animated movies.
Cloud-based distributed systems
A cloud-based distributed system uses cloud infrastructure where computing resources are distributed across data centers and accessed over the internet. This system ensures resources are scalable on demand.
Popular examples of cloud-based distributed systems include AWS and Microsoft Azure.
Benefits of distributed systems
Distributed systems have a number of advantages when compared to single systems. Below are some of the other pros of using distributed systems:
- Scalability: You can spin up servers to a distributed system on the fly, increasing performance and reducing time to completion.
- Fault tolerance: Distributed systems bolster reliability and fault tolerance, reducing the risks involved with having a single point of failure.
- Reliability: A well-designed system can tolerate some node failures without impacting performance.
- Speed: Distributed databases are scalable, making them easier to maintain and sustain high-performance levels.
Challenges of distributed systems
There are numerous challenges around design and maintenance, since distributed systems are more complex than monolithic computing environments. There are a lot of potential issues you face, but common ones include the following:
- More opportunities for failure: A system that’s not properly designed may result in the entire system going down.
- Synchronization challenges: Distributed systems require careful planning to ensure that processes are synced to avoid errors.
- Imperfect scalability: Making an effective distributed system that maximizes scalability is difficult, as you need to take into account different issues.
- Complex security: Managing a large number of nodes creates numerous security challenges. A single weak link in a file system can expose the entire system to attack.
- Increased complexity: Distributed systems are more complex to design and understand compared to traditional computing environments.
How IT teams should manage distributed systems
Managing distributed systems requires visibility across services and dependencies. Teams should maintain accurate inventories of nodes, databases, and supporting services so they can understand how components interact.
Monitoring should focus on service health and dependency performance instead of individual servers alone. Centralized logging and tracing tools help teams identify root causes faster during incidents.
Lastly, IT teams should enforce consistent configuration management and apply least-privilege access controls across services. Clear ownership and documentation are essential to reduce operational confusion.
Improve scalability by designing a proper distributed system
Distributed systems help organizations scale workloads and reduce reliance on a single component. They also introduce new operational challenges around latency, partial failure, consistency, monitoring, and recovery.
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