"...Soon we were reading 7.8 MB/second from Redis which was not going to be sustainable as we continued to grow...."
Was the option of a multi-node Redis cluster on dedicated hardware considered? 7.8MB/s read from RAM memory does not seem all that terrible.
Could clarify the solution a bit please. Instead of hitting Redis before each MySQL request you will referance the local AR conneciton object; does the connection object keep the Redi data in memory? I am confused (not familar with the Octopus gem).
"...Another great way to learn more about how your gems are working is through logging!..."
Great article Molly, I look forward to the next one!
We honestly could have let this ride for a bit. 7.8 MB/sec was high but was not causing any issues for our beefy ElastiCache(In that logging post I mention that due to other requests we actually got to a level where it was causing other errors). However, we knew it was only going to get worse as we grew and while we could have beefed up ElastiCache we really wanted to save that as a last resort. We felt there had to be a way to be smarter about how we were getting the sharding data we needed which is why we went poking around ActiveRecord.
A big theme for our SRE team over the past year has been "working smarter" not harder. Every time we come across high loads we first look for ways to "fix" the loads. We use beefing up hardware as last resort.
The ActiveRecord/Octopus Proxy object reads the data from MySQL actually when the process starts up and then holds that hash in memory to be used throughout the lifetime of the process. Prior to this, when the process would start up we would write the data to Redis from MySQL then every time we made a MySQL request we would read it from Redis.
Let me know if that makes sense or if you have any other questions!
Next post coming up will involve processing data in bulk, stay tuned 😁
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