When designing and maintaining concurrent systems, deadlocks are one of the most infamous issues that can arise. From my own experience working on distributed systems and high-performance architectures, I’ve seen how easily they can sneak in, especially as systems scale and become more complex. Deadlocks can either severely degrade performance Read more…
Concurrency-related latency is one of the most fascinating and challenging topics in system architecture, especially when dealing with lock contention. When multiple threads or processes contend for shared resources, performance can degrade significantly, leading to bottlenecks. In this article, we’ll focus on the compare-and-swap (CAS) approach, a mechanism that sidesteps Read more…
Continuing from pessimistic locking, let’s dive into optimistic locking, a different approach to managing concurrency and minimizing latency. Instead of assuming conflicts will occur (as pessimistic locking does), optimistic locking takes a more hopeful stance: it assumes that most operations will succeed without interference. This approach can significantly reduce lock Read more…
When working with shared data in a concurrent environment, ensuring consistency and avoiding corruption are non-negotiable. That’s where locking mechanisms come into play. Today, let’s dive into pessimistic locking—a tried-and-true method to handle contention for shared resources—and see how it works through a practical example. I’ll keep this grounded in Read more…
Concurrency in modern systems is both a blessing and a curse. On one hand, it unlocks the potential of multi-core CPUs and parallel processing. On the other hand, it introduces challenges like lock contention—a silent performance killer. In this article, we’ll explore some practical strategies for minimizing lock contention and Read more…
We took a close look at system resource contention and the many ways it can slow down a system. Whether it’s network queues, CPU threads, or database connections, contention can creep in and wreak havoc on performance. Now, let’s dive into how we can reduce shared resource contention and design Read more…
When we talk about system performance in the context of concurrency, contention often takes center stage as one of the biggest bottlenecks. Contention occurs when multiple processes or threads compete for limited resources, whether it’s CPU, memory, disk, network bandwidth, or locks. Over time, I’ve learned to recognize and mitigate Read more…
In a previous post, we mentioned the Amdahl’s Law, examining how the presence of serial portions in code can put a hard ceiling on system throughput. This time, we’re going to take it a step further by exploring another critical factor in concurrency: coherence, as defined by the Universal Scalability Law (USL). Together, queuing and coherence form Read more…
While serial performance sets the foundation for individual request handling, real-world systems rarely deal with just one request at a time. As systems scale, concurrency-related latency becomes a critical factor in performance. Concurrency refers to a system’s ability to handle multiple requests simultaneously, leveraging parallelism to maximize throughput. However, as concurrency increases, so does Read more…
When it comes to system performance, network latency often steals the spotlight. It’s that invisible time thief between your request and the response. We’ve all been there—trying to squeeze out every millisecond from our systems, only to realize that the network is a major bottleneck. In this post, let’s explore the nuances Read more…