In distributed systems, retries are inevitable. From network errors to replication issues and even outages in downstream dependencies, services operating at a massive scale must be prepared to encounter, identify, and handle failure as gracefully as possible.

A Workflow is a series of decisions made by different people that determines what happens to a particular request that one of those people made, according to a defined and repeatable process. An example of this process is shown in this flowchart.

A series on different rela time application system design and architecture

Whatsapp System design or software architecture video

Sports sytem design architecture cricbuzz or cricinfo

Design a scalable service that supports timy url

The core components of this architecture are a web front end that serves client requests, and a worker that performs resource-intensive tasks, long-running workflows, or batch jobs. The web front end communicates with the worker through a message queue.

By sharing what we do (and I mean all of us), we better our world. Everyone that works at Stack shares at least one passion: improving life for all developers. Sharing how we do things is one of the best and biggest ways we can do that. It helps you. It helps me. It helps all of us.

I think it’s important here to discuss just how expensive some of the above things are. There are several layers of caching already in play in your modern computer. As a concrete example, we’re going to use one of our web servers which currently houses a pair of Intel Xeon E5-2960 v3 CPUs and 2133MHz DIMMs. Cache access is a “how many cycles” feature of a processor, so by knowing that we always run at 3.06GHz (performance power mode), we can derive the latencies (Intel architecture reference her

Reddit team answers more of your questions about keeping Reddit running (most of the time). We're also working on things like developer tooling, Kubernetes, moving to a service-oriented architecture, lots of fun things.