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Medlife journey with AWS

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Medlife journey with AWS conducted at AWS Community Day, Bangalore 2019

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Medlife journey with AWS

  1. 1. What is Medlife? MEDICINE DELIVERY MEDLIFE ESSENTIALSDOCTOR E-CONSULTMEDLIFE LABS www.pinhealth.com
  2. 2. When did we come into existence? First Order Delivered – May 2015 First Production Deployment – May 2015
  3. 3. Stage 1 : Very early days of Medlife Stage 2 : Automation Stage 3: Migrating from Singapore to Mumbai Stage 4: Optimize & align ourselves to the larger goal Stage 5: Taking Medlife to the next level
  4. 4. Stage 1
  5. 5. 2 tier monolith architecture Only t2.medium instances Default AWS VPC No application level optimization Single point of failure CPU credits would get exhausted Lot of unwanted visitors High data transfer costs Managing configuration was SETUP SHORTFALLS
  6. 6. Stage 2
  7. 7. Move EC2 instances to private subnet Automated zero down-time deployment during the day Auto scaling during the spikes Decouple the front-end & back-end, move towards multi-tier architecture Optimizing the application & database ECS for micro-services Introduce Kafka in our architecture ElasticSearch for search S3 for storage
  8. 8. Stage 3
  9. 9. REFERENCE LINKS FOR PREVIOUS TALKS https://www.slideshare.net/PraneshVittal/success-story-of-migrating-entire- infrastructure-from-aws-singapore-to-aws-mumbai-for-medlifecom https://www.youtube.com/watch?v=3QvTzRMIxok https://www.youtube.com/watch?v=zCqcIr8rbyA 1. 2. 3.
  10. 10. Stage 4
  11. 11. Analytics on EMR Cluster Introduce Apache Airflow Redis for faster data retrieval AWS WAF to secure our API end- points Multiple databases GROWTH SCALE Infrastructure monitoring ELK & AWS Cloudwatch for application monitoring Carve some of the monolith into micro-services VPC flow logs
  12. 12. Forecast your RIs Keep a check on some of the new AWS announcements Don’t neglect any anomalies in your invoice VPC end point for S3 cost optimization Detect idle instances COST OPTIMIZATION Build stateless applications to leverage spot instances Optimum values for auto-scaling rules Right-sizing EC2 instances Keep exploring interesting projects on Github
  13. 13. Stage 5
  14. 14. Data lake architecture and POC on “AWS Lake Formation” AI / ML use cases and POC on AWS SageMaker, Textract
  15. 15. THANK YOU 1. https://in.linkedin.com/in/praneshvittal 2. https://in.linkedin.com/in/prasanna-desai-6b785562

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