The client engaged TO THE NEW<\/a> as a trusted DevOps service provider to help them reduce the infrastructure costs. In our client\u00a0<\/span>ecosystem, we have microservices architecture with 50+ services and every service in their <\/span>ecosystem comprised of a load balancer, two application instances with auto scaling, and a 3 node MongoDB replica set. Our application stack majorly leverages Java<\/span>, but we had also adopted Node js and Angular js for our frontend apps. For managing database, we were mostly using NoSQL databases (MongoDB and Elasticsearch), but for transaction\u00a0purposes, we were using Postgresql. Apart from the above-mentioned technologies, we are using Apache Kafka for event-based notifications and Hbase for preference engine.<\/p>\n How we identified the scope of Cost Optimizations<\/strong><\/p>\n The business requirement was pretty straight forward i.e. they wanted a web application that can handle high traffic and can scale independently, therefore the engineering team decided to go head with microservices architecture as it gives individual teams the flexibility to scale and develop new features independently.<\/p>\n In the initial days of our engagement with the customer, in the beginning, we implemented open source monitoring tool as AWS cloud<\/a> watch doesn\u2019t provide memory and hard disk utilizations. After analyzing the report for the last 15-21 days, we were able to get more insights about the existing infrastructure. Few stats are given below from the report:<\/p>\n After looking at the stats above, we were able to make our cost optimization roadmap with cloud aggressive approach in mind. (by cloud aggressive approach, I mean running all the AWS Resources at 75-80% utilization rates and after crossing that threshold it can automatically scale). In the roadmap, we decided to divide the entire cost optimization activity into 4 steps based on the cost savings. These four steps are explained further in detail below:<\/p>\n Overall Cost Comparison:<\/strong><\/p>\n\n
\n
\n\n
\n <\/td>\n Before (in $ per month)<\/strong><\/td>\n After 3 months (in $ per month)<\/strong><\/td>\n<\/tr>\n \n EC2<\/span><\/td>\n 65k<\/span><\/td>\n 39k<\/span><\/td>\n<\/tr>\n \n RDS<\/span><\/td>\n 30k<\/span><\/td>\n 7k<\/span><\/td>\n<\/tr>\n \n Data Transfer<\/span><\/td>\n 3k<\/span><\/td>\n 2k<\/span><\/td>\n<\/tr>\n \n Cloudfront<\/span><\/td>\n 2k<\/td>\n 2k<\/span><\/td>\n<\/tr>\n \n Total<\/span><\/td>\n 100k<\/b><\/td>\n 40k<\/b><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n ![\"AWS](\"\/blog\/wp-ttn-blog\/uploads\/2017\/01\/Screen-Shot-2017-01-03-at-1.12.01-PM.png\")
<\/p>\n