Note Scale out based on Load costs are not calculated in both Apache Solr and Amazon CloudSearch. Scale out during heavy load is automatic in CloudSearch and it is a manual cumbersome effort in Apache Solr on EC2.Larger and more elastic our search setup requirements, then Amazon CloudSearch will easily beat the hell out of Apache Solr on EC2. Labour cost is one of the important costs in large scale search tier setups and Amazon CloudSearch helps us keep it at minimum as we grow. Spot prices can be queried using the command line tools provided by Amazon EC2. Amazon CloudSearch eliminates all the scaling up/out/portioning complexities automatically. 0 Instance Type (a) Newer instance types.This under performance may lead to losing customers itself. After having all this, there is no guarantee that Apache Solr on EC2 can handle the load, since the volatility pattern is spikey in nature for a day, there could be times where Solr is pounded and not performing well also.Still at the end of 6th month, we need to Shard Solr on EC2 because it will exceed m2.4xlarge capacity / or Scale up again with more costly EC2 instances to keep up with the growth. Still monitoring, backups etc have to done on Apache Solr on EC2.The above table indicates cost calculated in this approach. ![]() If we decide not to frequently scale up but start Solr initially itself with m2.4xlarge, then we have overprovisioned for first 5 months, which essentially means cost leakage again.If we are scaling up the capacity of Solr Nodes in multiple phases from m1.xlarge to m2.4xlarge depending upon the index growth (10 GB in our case) every month, then lots of manual admin labour efforts is needed.EBS: 100 GB volume + 500 Million IO per month+ X GB snapshot for Apache Solr on EC2. ![]()
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