From a60620012a746b4d546a5f0c63cdd057cf28be4c Mon Sep 17 00:00:00 2001 From: Lucas Schneider Date: Mon, 13 Jan 2020 13:24:13 -0300 Subject: [PATCH] Fix typos in readme.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index e25a987..613abca 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # Swarm Example Cluster: Microservices App -This is a sample Swarm cluster that illustrates how Swarm can be used as the foundation for a high-traffic microservice-architecture web application. It is based on the Docker Cats-vs-Dogs voting example application, but re-architected to accomodate arbitrarily large scale through the use of parallel vote capture frontends and asynchronous background workers processing each vote. +This is a sample Swarm cluster that illustrates how Swarm can be used as the foundation for a high-traffic microservice-architecture web application. It is based on the Docker Cats-vs-Dogs voting example application, but re-architected to accommodate arbitrarily large scale through the use of parallel vote capture frontends and asynchronous background workers processing each vote. # Use Case @@ -8,7 +8,7 @@ Imagine that your company is planning to buy an ad during the Superbowl to drive # Architecture -An Interlock load balancer (ha\_proxy plugin) sits in front of N web containers, each of which runs a simple Python (Flask) app that accepts votes and queues them into a redis container on the same node. These N web (+ redis) nodes capture votes quickly and can scale up to any value of N since they operate independently. Any level of expected voting traffic can thus be accomodated. +An Interlock load balancer (ha\_proxy plugin) sits in front of N web containers, each of which runs a simple Python (Flask) app that accepts votes and queues them into a redis container on the same node. These N web (+ redis) nodes capture votes quickly and can scale up to any value of N since they operate independently. Any level of expected voting traffic can thus be accommodated. Asynchronously, M background workers running on separate nodes scan through those N redis containers, dequeueing votes, de-duplicating them (to prevent double voting) and committing the results to a single postgres container that runs on its own node.