What factors should you consider when scaling distributed systems?

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.

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.

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.

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.

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.

One more thing you need is the right infrastructure. Improving a distributed system will require careful, gradual release with feature flags.

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.

Uncoordinated systems, wherein work items can be handled independently, scale the best. Note that coordination is not a binary feature but a spectrum.

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.