Now, we live in a world powered by software systems. These systems penetrate into every aspect of our daily lives, and their continuous, reliable performance is no longer a luxury, but a necessity. Now more than ever, businesses need to keep their systems available, reliable, and resilient. This demand is driven by the need to meet customer expectations and outperform competitors. So, what is the key to achieving this goal? The answer is to build fault-tolerant software systems.
The importance of fault-tolerant systems lies in their ability to prevent prolonged downtime and loss of revenue. Imagine a financial institution that relies so heavily on a trading platform to execute trades that it cannot afford the risk of platform downtime during market hours. If the platform does become unavailable, the company could face millions in lost revenue, and the consequent loss of reputation. However, by implementing fault tolerance policies and patterns, companies can ensure that the platform remains available even in the event of a failure.
In this blog post, we'll take a deeper dive into how some large tech companies and software engineering teams use strategies and patterns to keep systems available.
The Eight Pillars of a Fault Tolerant System
- Redundancy and replication are one of the common strategies for building fault-tolerant software systems. Redundancy involves duplicating critical components of a system and ensuring that multiple instances of those components are available. If one component instance fails, another instance can take over immediately. Redundancy can be implemented at different levels of the system such as hardware, software and data. For example, hardware redundancy involves using multiple servers or storage devices, while software redundancy involves duplicating application instances on multiple servers.
- Load balancing is another critical and well-known strategy for building fault-tolerant software systems. Load balancing involves splitting incoming network traffic across multiple servers to ensure that no server is overloaded. If one server fails, traffic can be automatically redirected to another server, reducing the impact of the failure. Load balancing can be implemented through hardware or software solutions and is often used in conjunction with redundancy and replication to maximize the fault tolerance of the system.
- Modularity is essentially the breaking down of a system into smaller, self-contained parts that can be developed, deployed and maintained independently. This practice makes it easier to locate and isolate faults and restore normal operations more quickly. Microservices are an extension of modularity, which further divides the system into smaller services that can be developed and deployed independently. The emergence of microservices has greatly improved the fault tolerance of the system, which can minimize the impact of failures and achieve rapid recovery.
- Graceful degradation refers to the design of the system to ensure that even if some components fail, the system can maintain at least basic functions. This design approach ensures that even if some functions or performance are temporarily affected, the system remains available. Graceful degradation is achieved by designing the system to detect failures and automatically adjust its behavior to accommodate failure conditions. For example, if a feature that relies on a third-party service is unavailable, the web application can display a simplified version of that page.
- A fuse is a design pattern used to prevent cascading failures in a system. It wraps calls to external dependencies such as databases or web services in circuit breakers. A circuit breaker monitors the health of external dependencies, and if a failure is detected, it opens the circuit, preventing further dependency calls. This design allows the system to gracefully degrade when external dependencies fail, without directly crashing.
- Fail-fast is a mode designed to halt system execution as soon as a failure is detected to prevent further damage. This approach ensures that the system fails fast in the event of a failure, avoiding more serious cascading failures. By adding assertions or preconditions to the code, we can detect bugs early in the development process and thus fail fast. Setting appropriate timeouts and deadlines is also a form of fail-fast, where the system terminates operations that run for too long, preventing further damage to the system.
- Retry is a design pattern that automatically re-executes failed operations in the expectation of success on subsequent attempts. This approach may be effective for transient failures such as network timeouts or temporary service unavailability. Implementations of retries can employ different algorithms, such as exponential backoff, which adds a delay between each retry to reduce system load.
- Throttle is a policy whose goal is to limit the rate at which the system can process requests. This strategy prevents overloading and ensures that the system can handle traffic spikes without being overwhelmed. Throttle can be achieved by setting the number of requests that can be processed per second or per minute. This strategy is especially effective for systems that depend on external APIs or services that have usage restrictions.
Summarize
This article does not give specific implementation details, but these techniques and methods can be used to increase the reliability and availability of the system. The patterns mentioned above provide a good idea for developers looking to improve the resilience of software systems.