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AWS re:Invent 2016: Best practices for running enterprise workloads on AWS (ENT213)

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Fortune 500 companies are increasingly using cloud services to run enterprise workloads to improve security, increase agility, and enable scale. Learn how OpenEye is running their AWS-native platform and workflow engine to support collaboration and data sharing at large pharmaceutical companies like Pfizer. In this session, OpenEye will share cloud best practiced around security controls, cross-departmental collaboration across the enterprise, and agility at scale. Attendees will gain practical tips for using AWS in the enterprise and healthcare industries.

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AWS re:Invent 2016: Best practices for running enterprise workloads on AWS (ENT213)

  1. 1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amit Sharma, AWS Anthony Nicholls, Jharrod LaFon, Craig Bruce, OpenEye Scientific Software, Inc. November 30, 2016 ENT213 Best Practices for Running Enterprise Workloads on AWS
  2. 2. Agenda 1. AWS and Life Sciences 2. OpenEye Scientific 1. Use case 2. Demo 3. Learning 3. Q&A
  3. 3. Largest pace of innovation Partner and customer ecosystem Longest industry experience Why AWS?
  4. 4. Discovery Manufacturing and Distribution Development Marketing and Sales  Computational chemistry  Collaboration  Genomics  Pharmacovigilance  Pharmacokinetics  Clinical Trials Management  Supplier collaboration  Quality management  Processing analytics  Digital marketing  Online storefronts  Content distribution
  5. 5. Security is foundational at AWS Architected to be one of the most flexible and secure cloud computing environments available today
  6. 6.  You retain ownership of your IP and content – AWS does not have access  You control region(s) where your data is stored  You can build end-to-end compliance, including HIPAA compliance  AWS data centers always “on”; robust connectivity and bandwidth  Ongoing audit and assurance program  Industry certificationsAWS secures the infrastructure.... ....so you can secure your data Security: A shared responsibility
  7. 7. The AWS Cloud Improves Your Compliance Posture Controllable Infrastructure Repeatable Testing Automatic Traceability
  8. 8. Creating the Nimble Life Sciences Enterprise Bring agility to your business Add efficiency throughout the value chain Analytics to tackle any business problem Collaborate globally throughout your organization
  9. 9. What to Expect from the Session 1) An appreciation of the computational problems faced by the pharmaceutical Industry 2) To learn how Orion, our cloud-native platform, uses AWS to address these problems 3) To see how generalizations of our approach can apply to your organization
  10. 10. Outline 1) The Modern Pharmaceutical Industry 2) OpenEye- Why We Think We (and AWS) Can Help 3) Problem Solving with AWS and Orion 4) An Orion Demo 5) Orion, Under the Hood 6) Lessons Learned & Generalizations
  11. 11. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. The Modern Pharmaceutical Industry
  12. 12. The Inverse Moore’s Law of Pharmaceuticals “Classic” Law of Diminishing Returns
  13. 13. Texas Oil Production New Technology Where is the new technology for Pharma?
  14. 14. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. OpenEye Why We Think We (and AWS) Can Help
  15. 15. OpenEye Scientific Software- Inc. 1997, Santa Fe 2016: 50 employees- Santa Fe, Boston, Cologne, Tokyo • First-in-class software for Molecular Modeling / CADD: • Large Scale Virtual Screening, Cheminformatics, Software Toolkits • Trusted brand for Science & Computer Science • Deployed to: 19/20 Top Big Pharma • Deep knowledge of institutional problems
  16. 16. Computational Problems 1) Multidisciplinary  “silos” - Data, knowledge, methods 2) Computation and data scaling 3) Retaining data context 4) Security vs. need for collaborations vs. 106 , 109 ,1012 
  17. 17. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Problem Solving with AWS and Orion
  18. 18. Problems addressed by Orion and AWS 1) Easy authoring, publishing and versioning solutions 2) Automation & scaling 3) Data sharing via “change & notify” paradigm 4) Unlimited data & contexts 5) Collaborative workspaces 6) AWS Security 106 , 109 ,1012   Democratization of computation
  19. 19. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Jharrod LaFon, Chief Cloud Engineer An Orion Demo @jharrodlafon
  20. 20. Overview 1) Example problem solved with Orion & AWS 2) Capture of science and information necessary for collaborative, automated, scalable, scientific workflows 106 , 109 ,1012 
  21. 21. Problem: Finding new molecules (drugs) • Start with a known ‘active’ molecule (ligand): one with desirable biological properties • Find biologically similar molecules from a database, but with different chemical structure • Known as ‘Ligand Based Lead Discovery’ 106 , 109 ,1012 
  22. 22. Problem: Finding new molecules (drugs) Patented molecule 3D Overlay Patentable molecule
  23. 23. DEMO
  24. 24. Example Virtual Screening Workflow Pfizer Intends to Deploy in Orion • Currently possible to do all of this with in-house resources. Very manual, very time consuming (both setup and calculation) • Goal is to reduce this to setup of under 1 minute and run time of under 15 minutes…as easy as a substructure search Pfizer Proprietary – Not for Distribution eMolecules (5M compounds) Similarity search 2D fingerprint-based FastROCS GPU Shape-based ROCS Shape & Color EON Shape & Electrostatics Final Hitlist AWS Storage AWS GPUs AWS CPUs AWS CPUs and Storage AWS CPUs Query Internal Docking Algorithm Docking AWS CPUs
  25. 25. Ligand Based Lead Discovery Workflow
  26. 26. Orion Workflows with Floe on AWS • Composed of small, reusable components (Cubes) • Cubes are defined by a few lines of Python • Runs on automated Docker container infrastructure in AWS • Built in parallelism, scales to 1000s of CPUs
  27. 27. Workflow Lifecycle • An expert designs and builds the workflow • Once ready, the workflow is published so that others may use it • Built-in scheduler automates & scales all necessary infrastructure 106 , 109 ,1012 
  28. 28. DEMO
  29. 29. Merck: Compute and Storage to Support Protein Design Goal: Protein interaction to design or optimize Enumeration Large virtual library of synthetically accessible amino acids AWS Storage AWS Compute Tasks continuously mining from literature and patents Tasks continuously mining from internal data sources AWS Push Alerts for new reagents of interest Mixed QSAR + empirical interaction filtering and ranking AWS Compute Filter and Rank Molecular dynamics stability evaluation Free energy perturbation energetic evaluation AWS Compute AWS Storage++ Evaluate Protein design Floe using a mix of OpenEye, third party and in house methods Orion Analysis Tools Analysis and decision making done in the context of aggregated project knowledge Aggregate
  30. 30. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Craig Bruce, Head of DevOps Orion, Under the Hood @craigbruce
  31. 31. Architecture Diagram VPC Direct Connect
  32. 32. Management tools CloudFormation • Blueprint for all your AWS resources • Reproducible • Updatable • Sharable
  33. 33. Compute & Application Services
  34. 34. Compute EC2 • Multiple instance types • Including GPUs • Spot • Auto Scaling groups • CloudWatch • Metrics with alarms 106 , 109 ,1012 
  35. 35. Compute & Application Services 106 , 109 ,1012 
  36. 36. Compute & Application Services 106 , 109 ,1012 
  37. 37. Storage & Databases
  38. 38. Storage & Databases S3 • Large datasets • Unlimited storage • Archiving RDS • Amazon Aurora ElastiCache • Redis • In-memory data store106 , 109 ,1012 
  39. 39. Developer Tools CodeDeploy & CodePipeline • Automate deployments • Integrated with our CI/CD solution • Deploys to a real stack • Runs Browser tests via
  40. 40. Development • Boto (Boto3) • Configuration management
  41. 41. Plus many others • IAM • KMS (EBS, RDS & S3) • Lambda • SES • Route 53 • CloudTrail • Evaluating others (ACM, ECS)
  42. 42. OpenEye Hosted • OpenEye account/VPC • No access to customer datacenter • Multi-tenancy • EC2 shared tenancy • OpenEye administration and support Hosting options Customer Hosted • Customer account/VPC • Access to your datacenters • Single tenancy • EC2 shared/dedicated/host tenancy • Customer administration and support
  43. 43. A platform requires this many pieces • A small team could not have built Orion without AWS • AWS services are continually more enterprise-friendly • Great individually, very powerful together • Enables startup agility at scale, every day: • Hundreds of deployments • Thousands of workflows • Millions of messages • Always automate 106 , 109 ,1012 
  44. 44. 6) Lessons Learned
  45. 45. Lessons Learned CloudTrail CloudFormation CodeDeploy EC2
  46. 46. 6) Generalizations 106 , 109 ,1012 
  47. 47. Automation and Scaling Expert Automation Scaling HighLow High Low Guru Novice High-functioning Novice Empowering Productive Organization 106 , 109 ,1012 
  48. 48. Central resource Individuals Accessibility Scale HighLow High Low Silos Community Enterprise Productive Organization
  49. 49. Workflow Design Hackers Ease-of-use Power HighLow High Low Gurus Community Revolution Innovation Best Practices Ownership 106 , 109 ,1012 
  50. 50. Confluence & Synergy 1) Compute 2) Analyze 3) Share 4) Develop Change Your World
  51. 51. p.s. Come change the World with us! Visit our booth #2235 to try Orion Hiring: 1) Cloud Engineers 2) DevOps Engineers 3) Python experts 4) Scientific programmers
  52. 52. Thank you!
  53. 53. Remember to complete your evaluations!

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