My Website has following issues on database scaling.
1) HOMEPAGE (something like Pinterest/Facebook/LinkedIN's homepage) where you get all the feeds becomes very slow.
2) SEARCH RESULTS become slow.
3) GROUP page (something like Pinterest's Interest page) also becomes inresponsive on scaling.
TIME TO RESOLVE THE ABOVE THREE POINTS - 4 days. URGENT!
The above three points will be tested on different scaled databases, which can be negotiated at the time of agreement.
Some of the other issues are :
1) There are repititive posts on the Homepage. Needs to be fixed.
2) After posting, remind users that they have NOT posted it in a group. Scroll down and show them a popup.
3) Whenever a user adds youtube, insta, facebook, etc links, we automatically embed it (like wordpress)
4) I create a new group, if it is a sub-group, the user should have joined it who has joined the uplevel group. Received a message in which there are JOIN/UNJOIN icons. … create a new group, all users should anyways get the message and email., but I should get an option after the group is created to send an email to the members of which all top-level groups and all users.
5) Invite friends option in GROUP : where he can hit SEND to ALL and also hit send like Messenger and search friends like in ‘tagging’, and also invite friends off from linkedIN, facebook, google, twitter and those accounts should get connected, unless there is an another account by that social media.
The above issues require expert knowledge of laravel, mySQL, GIT and some one who has worked on scaling up a high-traffic website (espcially some kind of high-content website) All the points need to be resolved on a separate branch on GIT. I will also provide an Amazon EC2 server where these need to be fixed. When you post your proposal, please let me know the experience / LinkedIN profile of the lead developer who is going to work on the project.
20 freelancers are bidding on average ₹24652 for this job
Can be done within couple of days. Have seen similar issues with DB, index tuning, partition prunning implementation will solve great part of this. Can start today.