In a multiple-business-site marketplace, distributed systems are more popular than ever before—and for good reason. By spreading workload across a variety of resources, such as servers or containers, distributed systems reduce the risk of bottlenecks and single points of failure, thus enhancing overall system robustness. Products such as Gmail, Netflix, and Google Search demonstrate the effectiveness of distributed systems. But as valuable as these systems are on a large scale, they also offer numerous benefits to companies on a smaller scale, such as increased speed, greater flexibility, and improved fault tolerance.
By far, one of the biggest benefits of distributed systems is their combination of scalability and reliability. For companies to dominate their market and scale quickly and efficiently, it’s essential for them to handle increased user demand and data volume while maintaining a high level of performance. This is where distributed systems truly shine. To receive maximum benefits from these systems, it’s vital for companies to be prepared to address some common challenges.
Distributed systems explained
Distributed systems are collections of computers, devices, servers, and containers that may be geographically distant but are linked to the same network. This type of setup offers businesses several advantages, ranging from increased computational speed due to parallel processing to improved fault tolerance due to replication across multiple nodes. Other benefits include greater availability thanks to geo-distribution, redundant resources, and better transparency from interacting with distributed resources as one entity.
Spotify is an example of a business that heavily relies on a distributed system to do business. The company has created a distributed network of servers (a content delivery network or CDN) to make its music and podcasts easily available to customers. When a user submits a request, it is routed to the nearest server to reduce distance and speed up service. Spotify has a vast customer base and can receive millions of requests in a short period. Its load-balancing distributed system helps ensure each request is handled optimally.
Distributed systems and scalability
The distributed systems utilized by companies like Amazon, Uber, Netflix, and Google are designed to foster scalability while maintaining reliability. The systems make it easy to expand resource capacity as demand grows by adding nodes, a process known as horizontal scaling. Their systems are also effective for vertical scaling, where the capacity of existing machines is improved.
The high degree of scalability offered by distributed systems enhances service reliability by allowing companies to handle increased loads and demands without experiencing system degradation or failure. Then, as user traffic grows, scalable systems can dynamically allocate resources to accommodate the influx, maintaining consistent performance and availability. Companies avoid growing pains and enjoy reduced system response times, better throughput, and improved user experience. They can also count on greater availability during hardware failure or network disruption. Yet, there are some challenges in getting a distributed system up and running smoothly.
Distributed system challenges and solutions
While distributed systems offer several advantages compared to traditional monolithic computer environments, they can also become complex if designed incorrectly. This complexity opens the doorway to a few potential challenges that, if not appropriately addressed, could negatively impact the benefits a company receives from its distributed system. For example, the more devices connected to a computer network, the greater the opportunities for failure. Compounding this issue is that if a distributed system is poorly designed, a single failure could cause the entire system to go down. Other challenges that often accompany the use of a distributed system include:
- Process synchronization. If processes across the system are not properly synchronized, it could lead to errors and data corruption.
- Inefficient scalability. Simply adding nodes will not necessarily improve performance as expected. It’s also critical for system administrators to consider bandwidth management, load balancing, and other factors.
- Security weaknesses. A distributed system with many connected devices creates a bigger attack surface for cybercriminals.
- Privacy concerns. Incorrect data storage and encryption choices could lead to accidental data exposure that may violate privacy laws.
- Unexpected costs. While distributed systems make it easier to scale, boosting capacity can increase costs. For example, many cloud-based systems have usage charges, and increasing capacity could raise them.
To avoid these challenges, it’s vital for system administrators to be aware of them from the start and take steps during design and implementation to account for them. First, administrators can implement redundancy and failover mechanisms to ensure their system can handle failures efficiently. Next, they can promote scalability by applying load-balancing techniques like replication, sharding, and caching. The round-robin algorithm is another effective approach for sharing computational resources between processes in a distributed system. Additional steps to ensure scalability and reliability include managing concurrent access to shared resources, as well as partitioning and replicating data across multiple nodes to distribute workload and boost performance.
An example of taking a forward-looking approach to the challenges presented by distributed systems is Netflix, which has boosted its system’s performance by proactively addressing potential failures. The company gives its system a regular stress test through a technique called chaos engineering. Netflix simulates distributed system failures to identify vulnerabilities and fix them before they have a chance to become serious issues.
The future of distributed systems
The need for highly available, easily scalable computer systems isn’t going away anytime soon. Scalable architectures deliver multiple benefits, such as incorporating redundancy and failover mechanisms that ensure continuity of service even in the event of hardware failures or disruptions. Through horizontal and vertical scaling, these systems can conveniently adapt to changing requirements based on increasing user base, data volume, and processing needs to deliver a reliable and consistent user experience under varying conditions. That ability makes them ideal for a fast-evolving marketplace where flexibility and scalability are crucial to success. By being aware of the challenges that come with distributed system adoption and addressing them early in the process, companies can set themselves up to do business more efficiently and achieve new levels of success.
About the Author:
Kevin Macwan is a software development manager for a major online retailer. Kevin holds bachelor’s and master’s degrees in computer science from the University of Southern California. Connect with Kevin on LinkedIn.
