![]() ![]() What are your thoughts on this approach to software design? Share your insights in the comments section below. So when designing a reliable service, try to create an escalator-like system instead of an elevator. During rush hour, elevators tend to get overwhelmed and stop functioning effectively. In comparison, an elevator is like a service that does not handle variability in demand very well. It operates at a consistent pace and can handle a certain amount of demand. It can run as part of Amazon RDS, and is also provided in a serverless model, known as Aurora Serverless. Had Ticketmaster used this mechanism, it’d have protected their service from crashing while ensuring that a portion of the demand was still being served. Amazon Aurora PostgreSQL is an Amazon-developed database engine that is compatible with PostgreSQL and fully complies with ACID requirements (Atomicity, Consistency, Isolation, Durability). If 50,000 requests arrive, instead of crashing, it will show an error message or queue up the other 49500 requests while it serves the 500. Suppose your service can handle 500 requests per second. You do that by putting a queue in front of your service, which acts as a buffer between the service and the incoming requests. ![]() To me, that’s nonsense because this situation could have been easily avoided if they had load tested their systems properly.īut I want to talk about a deeper underlying issue: The first job of a service is to protect itself. We will do this using Amazon Relational Database Service (Amazon RDS) and everything done in this tutorial is Free Tier eligible. They said that it happened due to the unprecedented demand. In this tutorial, you will learn how to create an environment to run your PostgreSQL database (we call this environment an instance ), connect to the database, and delete the DB instance. You may remember this incident where Ticketmaster tried to sell tickets for a Taylor Swift concert, and their site went down for hours. It'll suck, and it'll bankrupt you.Let’s talk about the Ticketmaster (Taylor Swift) Debacle and what we can learn from it. Especially when it's an RDS database, because they think "just crank that sucker up and it'll work better!". I've seen this happen at previous companies because the attitude was that it was everybody's (therefore nobody's) job. Or at least make this one person's problem. ![]() We will do this using Amazon Relational Database Service (Amazon RDS) and. ![]() Hire a DBA or someone who's halfways there. Tutorial: Create and Connect to a PostgreSQL Database with Amazon RDS. This request takes the whole week because you have no index, have to do a "full table scan", and the librarian maxes out "disk IO" running around the pile and occasionally up and down the stairs to apologize for how long it's taking. Your first customer is an old gentleman coming in and asking "have you got 'Fly Fishing', by J.R. You're a business man who rented a block down town, wants to be the "Salesforce for Book Loans", and bought a million random books and dumped all of them into the middle of the basement car park without looking att them. Throughput it's high, disk IO is low.īut let's say you are not a proper librarian. The librarian has arranged the building into different categories, created an excellent filing system with cross references, kept a record of popular books so they have a cache of them available on a "popular" shelf in each section, a bucket of bestsellers right at the front door, a book return bin, and one or two junior staff to organize returns by category and shuttle returns back to the right places in bulk. disk IO is every footstep the librarian takes while doing their duty. ![]()
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