Last updated on Sep 5, 2024
- All
- Engineering
- Computer Engineering
Powered by AI and the LinkedIn community
1
Load balancing
2
Consistency and availability
3
Partitioning and replication
4
Monitoring and testing
5
Here’s what else to consider
Scaling distributed systems is a challenging task that requires careful planning and design. Distributed systems are composed of multiple nodes that communicate and coordinate with each other to perform a common goal, such as processing large amounts of data, serving web requests, or running complex algorithms. However, as the system grows in size, complexity, and demand, it may face issues such as performance degradation, reliability loss, security risks, or cost inefficiency. Therefore, it is important to consider some key factors when scaling distributed systems, such as:
Key takeaways from this article
-
Implement load balancing:
Distribute workload evenly across your system's nodes to prevent any single point from becoming overwhelmed. This can significantly boost system performance and reliability.
-
CAP theorem trade-offs:
Decide between consistency, availability, and partition tolerance based on your system's needs. This decision guides how you handle data across nodes, impacting user experience.
This summary is powered by AI and these experts
- Bipul Khan Deputy Director and Head of Solutions…
- Yotam Kadishay Experienced Engineering Leader |…
1 Load balancing
Load balancing is the process of distributing the workload among the nodes in the system, so that no single node becomes overloaded or underutilized. Load balancing can improve the performance, availability, and fault tolerance of the system, as well as reduce the latency and bandwidth consumption. Load balancing can be achieved by using different strategies, such as round-robin, hashing, or dynamic allocation, depending on the characteristics of the workload and the system. Load balancing can also be applied at different levels, such as network, application, or data, depending on the type and location of the bottleneck.
Help others by sharing more (125 characters min.)
- Nishant Mishra Software Engineer, AWS, GCP, Cloud Computing
(edited)
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
In my experience, load balancers also play a crucial role in security by distributing incoming traffic in a way that can help mitigate certain types of attacks, such as (DDoS) attack. It also provides features like SSL termination and web application firewalls for filtering malicious traffic.
Like
Like Celebrate Support Love Insightful Funny 1
2 Consistency and availability
Consistency and availability are two important properties of distributed systems that describe how the system handles failures and updates. Consistency means that all the nodes in the system have the same view of the data at any given time, while availability means that the system can respond to requests even if some nodes fail. However, achieving both consistency and availability at the same time is impossible in a distributed system, as proven by the CAP theorem. Therefore, scaling distributed systems requires making trade-offs between consistency and availability, depending on the requirements and expectations of the system and the users. For example, some systems may prefer to sacrifice consistency for availability, such as social media platforms, while others may prefer to sacrifice availability for consistency, such as banking applications.
Help others by sharing more (125 characters min.)
- Bipul Khan Deputy Director and Head of Solutions Engineering,Technology at উপায় (UCB Fintech Company Limited)|MFS-DFS Architect|Micro-Service Architect|Financial Solution Architect|Blockchain Specialist.
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
These two properties are often considered in conjunction with partition tolerance (the "P" in CAP theorem), which refers to a system's ability to continue operating despite network partitions or communication failures between nodes.According to the CAP theorem, in a distributed system, it is impossible to simultaneously achieve all three properties of Consistency, Availability, and Partition Tolerance.Ultimately, the choice between consistency and availability depends on the specific needs and use cases of the distributed system, as well as considerations such as performance, fault tolerance, and user experience.
Like Like Celebrate Support Love Insightful Funny 7 - Mahdi Azarboon Cloud Architect | Serverless | Content Developer
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Use asynchronous communication protocols and design autonomous components that interact through events. To share any value outside the component, use events and consumers should ideally subscribe to event streams. Implement end to end flow control mechanisms to manage unpredictable workloads and to degrade gracefully: consumers should control their own rate of consumption. Producers should be able to slow down or halt whenever needed. Message queues are good options to absorb extra workload and to allow consumers to drain the work at their leisure.
Like Like Celebrate Support Love Insightful Funny
3 Partitioning and replication
Partitioning and replication are two techniques that can help scale distributed systems by dividing and duplicating the data across the nodes in the system. Partitioning is the process of splitting the data into smaller and manageable chunks, called partitions or shards, and assigning them to different nodes. Partitioning can improve the scalability, performance, and availability of the system, as well as reduce the contention and hotspots. However, partitioning also introduces challenges, such as choosing a suitable partitioning scheme, balancing the load across the partitions, and handling cross-partition queries and transactions. Replication is the process of creating copies of the data on multiple nodes, called replicas. Replication can improve the availability, fault tolerance, and performance of the system, as well as provide backup and recovery options. However, replication also introduces challenges, such as maintaining consistency among the replicas, resolving conflicts and updates, and choosing a suitable replication strategy.
Help others by sharing more (125 characters min.)
- Mahdi Azarboon Cloud Architect | Serverless | Content Developer
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Leverage multi-core server’s parallelism by partitioning the monolithic state into smaller chunks which are managed independently from each other. This helps with scalability and fault tolerance but at the cost of consistency and simplicity.
Like Like Celebrate Support Love Insightful Funny
4 Monitoring and testing
Monitoring and testing are essential activities that can help scale distributed systems by detecting and resolving issues, ensuring quality and reliability, and providing feedback and insights. Monitoring is the process of collecting and analyzing various metrics and indicators from the system, such as performance, availability, errors, resources, or events. Monitoring can help identify and diagnose problems, optimize and tune the system, and alert and notify the stakeholders. Testing is the process of verifying and validating the functionality, performance, and security of the system, using different methods and tools, such as unit testing, integration testing, or load testing. Testing can help prevent and fix bugs, ensure compliance and compatibility, and evaluate and compare the system.
Scaling distributed systems is a complex and dynamic process that requires constant evaluation and adaptation. By considering these factors, you can design and implement scalable distributed systems that can meet the needs and expectations of your users and clients.
Help others by sharing more (125 characters min.)
- Bipul Khan Deputy Director and Head of Solutions Engineering,Technology at উপায় (UCB Fintech Company Limited)|MFS-DFS Architect|Micro-Service Architect|Financial Solution Architect|Blockchain Specialist.
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Monitoring is crucial for large systems for several reasons as follows Performance Optimization: Monitoring allows you to track the performance of various components and identify bottlenecks. It helps with Scalability Planning. Fault Detection and Diagnosis: Monitoring helps you detect and diagnose faults or failures in real time.Security Monitoring: Large systems are prime targets for cyberattacks, data breaches, and unauthorized access. Overall, monitoring plays a critical role in ensuring large systems' reliability, performance, security, and scalability. It enables proactive management, rapid problem resolution, and continuous optimization, ultimately contributing to the overall success and effectiveness of the system.
Like Like Celebrate Support Love Insightful Funny 2 - Yotam Kadishay Experienced Engineering Leader | Building Elite Teams and Innovative Products
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
One more thing you need is the right infrastructure.Improving a distributed system will require careful, gradual release with feature flags.
Like Like Celebrate Support Love Insightful Funny
5 Here’s what else to consider
This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?
Help others by sharing more (125 characters min.)
- Yotam Kadishay Experienced Engineering Leader | Building Elite Teams and Innovative Products
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Another aspect to consider is having the proper communication methodology to ensure the scale and required delivery semantics. This should also include recovery and minimizing damage, such as using DLQ, circuit breakers, etc.
Like Like Celebrate Support Love Insightful Funny 1 - Mahdi Azarboon Cloud Architect | Serverless | Content Developer
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Uncoordinated systems, wherein work items can be handled independently, scale the best. Note that coordination is not a binary feature but a spectrum.
Like Like Celebrate Support Love Insightful Funny - Mahdi Azarboon Cloud Architect | Serverless | Content Developer
- Report contribution
Thanks for letting us know! You'll no longer see this contribution
Always stay responsive even during times of unexpected failures.Embrace uncertainty in your architecture, expect failure and design for resilience. Tailor consistency per component and use eventual consistency whenever possible.Scalability can be lifted by avoiding needless communication, coordination, and waiting.
Like Like Celebrate Support Love Insightful Funny
Computer Engineering
Computer Engineering
+ Follow
Rate this article
We created this article with the help of AI. What do you think of it?
It’s great It’s not so great
Thanks for your feedback
Your feedback is private. Like or react to bring the conversation to your network.
Tell us more
Tell us why you didn’t like this article.
If you think something in this article goes against our Professional Community Policies, please let us know.
We appreciate you letting us know. Though we’re unable to respond directly, your feedback helps us improve this experience for everyone.
If you think this goes against our Professional Community Policies, please let us know.
More articles on Computer Engineering
No more previous content
- What do you do if you're a late-career computer engineer navigating the tech industry's rapid changes? 7 contributions
- Here's how you can confidently navigate conflicts with colleagues as a computer engineer in the workplace.
- You're facing technical debt in your software projects. How will you tackle the accumulated burden?
No more next content
Explore Other Skills
- Programming
- Web Development
- Machine Learning
- Software Development
- Computer Science
- Data Engineering
- Data Analytics
- Data Science
- Artificial Intelligence (AI)
- Cloud Computing
More relevant reading
- Computer Networking How can you ensure scalability in distributed applications with a publish-subscribe model?
- Computer Engineering How can message queues be used in distributed systems?
- Operating Systems What are the benefits of using the memento pattern in distributed systems?
- Systems Design How can you balance scalability and consistency in distributed systems?
