Detailed Component Design

So the first non functional requirement is latency should be low for read.Here for the search we are following a query and that query will be extremely slow as the wildcard matching is there.So what we can do is we can replace that by having an elastic search .So the elastic search uses inverted search so with the words like taylor or swift it maps and gives the list of events related to the term.So internally the elastic search uses BM25 ranking for performing the search and give the results in less time.We dont use the elastic search as our primary DB as it is not reliable and we will loose our primary properties of ACID and so what we want to do is update our Elastic search along with PostgreSQL but if we write our application code like that then there might be chances that our DB got updated but not elastic search or elastic search got updated but not DB so we can use the change data capture or CDC which will identify the changes in the DB and push those stream of changes to the Elastic search. So to reduce the read latency further we can use the elastic search inbuilt AWS Opensearch which will cache the frequently accessed data to the cache or we can use the redis in between and cache the frequently used keys and use the LRU as the eviction policy.But we can use the elastic search AWS Open search as to reduce the overhead of maintaining other cache.The other thing which we can do is place a CDN in between client and api gateway which will cache and fetch the results .But the problem with the CDN is the search currently had many parameters to consider so the search key may change frequently so the many of the cache become less useful as it wont be able to figure our which one is same.So it also add's more complexity and comes with more cost too.So we satisfied that non functional requirement and the other non functional requirement is about that consistency should be prioritised like when 2 users open the events displayed should be same like suppose if user opens to look at the tickets which are available and we gave the correct available seats for that moment but as user sits on that page for long the data will be stale so what we can do is do a long polling which will poll for 30seconds and update the latest available seats to the user and this works for 5mins but according to data user sits on this page for longer so what we can do is create a persistant connection like SSE and update the data accordigly.So now another functional requirement is handling events when taylor swift or other popular celebrity posts something then millions of people fight for limited seats it will be a bad user experience if the entire screen goes blank.So the admin can specify few events as special events or so where the requests will go to a virtual waiting queue where the redis will be used with priority queue so that the one first entered will be prioritised so this is our choke point.So now whatever request came we will redirect those to virtual waiting queue and say as your request is taken into consideration will let you know the availability in few mins or so.Now if we see other functional requirements it was that availability should be prioritise when viewing the events so we can redis to cache and fetch the results faster.This redis should be kept up to date .If any of the event is dismissed immediately the redis should also be updated to remove that cache entry.

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