It seems to me that the 24ms was the whole process they were using, i.e. put data in memcached, take data out using a seperate process, and put data in mongodb; versus putting the data straight into mongodb.
Nope. From those metrics, Memcache is using all that time by itself. New Relic breaks down the network map based on distinct services. The database layer has a separate entry.
I had a similar issue with my Django project on Heroku. My site performance went down once I enabled memcache, almost entirely due to latency (going up to 100ms at times). This is one of the reasons why I ended up moving off of Heroku and onto an EC2 instance: now I have full control of my stack, I can run what I want locally on the server, and I'm getting much better performance (nginx+gunicorn+memcached+django+johnnycache+rds)
I'm not affiliated with the OP. I maintain my own stack on EC2 due to very specific application requirements. However, something is suspicious if the latency goes up so much due to Memcache alone.
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It seems to me that the 24ms was the whole process they were using, i.e. put data in memcached, take data out using a seperate process, and put data in mongodb; versus putting the data straight into mongodb.
Nope. From those metrics, Memcache is using all that time by itself. New Relic breaks down the network map based on distinct services. The database layer has a separate entry.
I had a similar issue with my Django project on Heroku. My site performance went down once I enabled memcache, almost entirely due to latency (going up to 100ms at times). This is one of the reasons why I ended up moving off of Heroku and onto an EC2 instance: now I have full control of my stack, I can run what I want locally on the server, and I'm getting much better performance (nginx+gunicorn+memcached+django+johnnycache+rds)
I'm not affiliated with the OP. I maintain my own stack on EC2 due to very specific application requirements. However, something is suspicious if the latency goes up so much due to Memcache alone.