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Accelerating Business Agility with Serverless Microservices

Accelerating Business Agility with Serverless Microservices

Accelerating Business Agility with Serverless Microservices

Julian Wood

January 23, 2020
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  1. © 2019, Amazon Web Services, Inc. or its affiliates. All

    rights reserved. © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Julian Wood Ben Smith @julian_wood @benjamin_l_s Senior Developer Advocates AWS Serverless Applications Accelerating Business Agility with Serverless Microservices
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    rights reserved. Amazon Confidential and Trademark A Modern Digital Business © 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Modern Digital Business Operational Efficiency Technical Resiliency Access to Insights Business Agility
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    rights reserved. Architecture evolution Monolithic application Does everything Shared release pipeline Rigid scaling High impact of change Hard to adopt new technologies Microservices Does one thing Independent deployments Independent scaling Small impact of change Choice of technology When the impact of change is small, release velocity can increase
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    rights reserved. Development transformation at Amazon: 2001–2002 monolithic application + teams 2001 Lesson learned: decompose for agility 2002 microservices + 2 pizza teams Full ownership & autonomy You build it, you run it DevOps – small, nimble teams Focused innovation
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    rights reserved. Deployment at scale 1000s of teams Micro- services CI/CD Serverless >60 million deployments a year*
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    rights reserved. Changes to Compute
  7. Where do teams focus their efforts? Physical Infrastructure Virtual infrastructure

    Service software (orchestration, routing) Application packages (OS, runtimes) What you need Business Logic
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    rights reserved. LEVEL OF ABSTRACTION FOCUS ON BUSINESS LOGIC VIRTUAL MACHINES Hardware independence Faster provisioning speed (minutes/hours) Trade capex for opex More scale Elastic resources Faster speed and agility Reduced maintenance Computing evolution – A paradigm shift Physical Infrastructure Virtual infrastructure Service software (orchestration, routing) Application packages (OS, runtimes) Business logic
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    rights reserved. LEVEL OF ABSTRACTION FOCUS ON BUSINESS LOGIC CONTAINER SYSTEMS Platform independence Consistent runtime environment Higher resource utilization Easier and faster deployments Isolation and sandboxing Start speed (deploy in seconds) Computing evolution – A paradigm shift Physical Infrastructure Virtual infrastructure Service software (orchestration, routing) Application packages (OS, runtimes) Business logic
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    rights reserved. AWS Lambda AWS Fargate LEVEL OF ABSTRACTION FOCUS ON BUSINESS LOGIC Continuous scaling Fault tolerance built-in Pay for value Zero maintenance SERVERLESS Computing evolution – A paradigm shift Physical Infrastructure Virtual infrastructure Service software (orchestration, routing) Application packages (OS, runtimes) Business logic
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    rights reserved. Serverless Operational Model No infrastructure to provision or manage Automatically scales by unit of consumption Pay for value billing model Highly available and durable
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    rights reserved. Event-driven architecture Decouple state from code using messaging APIs to expose services Scale without capacity planning Serverless Programming Model
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    rights reserved. ” “ Financial Engines Cuts Costs by 94% Using AWS Lambda & Serverless Computing They replaced 50 IPO servers running in 21 different environments with four Lambda endpoints to handle the same amount of traffic. IPO requests trigger a Lambda to run the IPO code. AWS Lambda can run as many copies of the function as needed in parallel, dynamically allocating compute capacity to match the rate of incoming requests. • Saves 94% on hard costs • Handles 10x normal traffic during peak times • Reduces operational costs • Creates near-zero downtime Solution Challenge Company: Financial Engines Industry: Financial Regulatory Non- Profit Country: United States Website: www.financialengines.com Financial Engines is the largest independent investment advisor in the United States for assets under management. They offer financial help to more than nine million people and manage more than one million individual investment accounts worth more than $160 billion. ” “We project 94 percent savings in hard costs, or about $110,000 annually. That’s not including the cost savings in operational maintenance—security patches and library upgrades—which AWS Lambda takes care of automatically. -Alex Yavorskiy, Chief Technology Officer, Financial Engines About Financial Engines Financial Engines needed the ability to quickly recover from a potential major disruption. They needed to decrease the time their teams spent on event monitoring and analysis and server management. Benefits
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    rights reserved. ” “ FINRA Doubles Cost Efficiency with AWS Lambda Data is ingested into Amazon S3 via FTP and AWS Lambda performs the validations. Amazon EC2 manages data feeds coming into, and notifications going out of, AWS Lambda. Amazon SQS is used for input /output messaging notifications while Amazon VPC partitions the system into separate test and production accounts. • Delivered solution in three months • Accelerated data validation by 700% • Increased cost efficiency by a factor of two Solution Challenge Benefits Company: FINRA Industry: Financial Regulatory Non- Profit Country: United States Website: www.finra.org The Financial Industry Regulatory Authority (FINRA) is a not-for-profit organization which protects investors and ensures market integrity through effective regulation of 3,800 broker- dealers. They write and enforce rules, examine firms for compliance, foster market transparency, and educate investors. ” “Using AWS Lambda, we’ve increased cost efficiency by a factor of two. We only pay for what we use, and we don’t have to manage on-premises server infrastructure.” - Tim Greisback, Senior Director of Technology, FINRA About FINRA FINRA validates the data of 50,000 broker-dealer OATS (Order Audit Trail System) files and formats them according to 200 rules, which totals half a trillion validations each day. FINRA needed a solution that could scale with processing demand, which can double or triple in response to market conditions.
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    rights reserved. ” “ Thomson Reuters Achieves 200% Productivity Increase with AWS Lambda When news breaks, Thomson Reuters’ traffic doubles or triples. They needed a way to elastically scale and were tasked with producing a solution on a tight timeline—5 months. They also needed to encrypt and protect information in transit and at rest, while handling thousands of events per second. Thomson Reuters built a solution that ingests events using Amazon Elastic Load Balancer, encrypts events using AWS Key Management Service (KMS), and hands them off to a streaming data pipeline using Amazon Kinesis Streams, Amazon Kinesis Firehose, and AWS Lambda. AWS Lambda then auto-batches and delivers data to Amazon S3 for storage. • Achieved 200% productivity increase • Launched two months ahead of schedule • Allows for fast data analysis & quick internal adoption • Optimizes streaming data processing costs Solution Challenge Benefits Company: Thomson Reuters Industry: Worldwide News Country: United States Website: www.thomsonreuters.com Thomson Reuters is a leading source of information, including one of the world’s most trusted news organizations, for the world’s businesses and professionals. ” “Our initial goal was to accommodate 2,000 events per second. Now, we can process up to 4,000, and within a year we expect to increase that to more than 10,000 events per second.” - Anders Fritz, Senior Manager, Product Innovation About Thomson Reuters
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    rights reserved. Nasdaq CIO Sees Serverless Computing as a 2020 Tech Trend The technology “is reducing capital costs and shifting the focus to customers’ needs instead of setting up, configuring, patching and maintaining servers in the data center,” Brad Peterson, Nasdaq Inc.’s CIO “A better client experience for a lower price point is on offer for those willing to understand the technology,” Nigel Faulkner, head of technology at T. Rowe Price Group Inc. https://www.wsj.com/articles/nasdaq-cio-sees-serverless-computing-as-a-2020-tech-trend- 11579213416?_lrsc=7e26e436-569f-49b6-92b6-304160490541
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    rights reserved. Systems Integrators specializing in serverless
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    rights reserved. Growing Partner Ecosystem
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    rights reserved. Build PCI and HIPAA compliant serverless applications! Serverless platform services that can be used in both:
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    rights reserved. Serverless and Functions
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    rights reserved. Event-driven compute Functions as a service Serverless FaaS Serverless FaaS Lambda
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    rights reserved. Common AWS Lambda use cases Web Apps Backends Data Processing Chatbots Amazon Alexa IT Automation • Static websites • Complex web apps • Packages for Flask and Express • Apps & services • Mobile • IoT • Real time • MapReduce • Batch • Powering chatbot logic • Powering voice- enabled apps • Alexa Skills Kit • Policy engines • Extending AWS services • Infrastructure management
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    rights reserved. Fine-grained pricing Buy compute time in 100ms increments Low request charge No hourly, daily, or monthly minimums No per-device fees Never pay for idle Free Tier 1M requests and 400,000 GBs of compute. Every month, every customer.
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    rights reserved. Serverless is more than compute APPLICATION PRIMITIVES – COMPUTE AND DATASTORES AWS Lambda AWS Fargate Amazon API Gateway Amazon SNS Amazon MQ Amazon SQS AWS Step Functions APPLICATION INTEGRATION DEVELOPER TOOLS SECURITY AND ADMINISTRATION Amazon Aurora Serverless Amazon S3 Amazon DynamoDB AWS AppSync AWS IAM Amazon Cognito Amazon Inspector Amazon VPC Amazon GuardDuty AWS CloudFormation AWS Cloud9 AWS CloudTrail Amazon CloudWatch AWS X-Ray AWS CodePipeline AWS Config AWS SSO AWS Shield AWS WAF Amazon Kinesis AWS Serverless Application Repository Amazon EventBridge APPLICATION PRIMITIVES – COMPUTE AND DATASTORES
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    rights reserved. Organic Adoption LAMBDA USAGE IT AUTOMATION LOG PROCESSING/ CRON JOBS DATA TRANSFORMATION MICROSERVICES DEVELOPER DIRECTOR EXECUTIVE Production Mission Critical Adoption Curve
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    rights reserved. Serverless Adoption Patterns LAMBDA USAGE I T A u t o m a t i o n D a t a T r a n s f o r m a t i o n B u s i n e s s C r i t i c a l A p p l i c a t i o n D E V E L O P E R D I R E C T O R E X E C U T I V E CONSIDERATIONS Rapid development Time to market—agility Organizational changes Long-term commitment Production Mission Critical Adoption Curve
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    rights reserved. Leap Frog Adoption C AP AC I TY P R OC E S S E S C OS T M OD E L S OP E R ATIONAL P R OC E S S E S D E VE L OP M E NT M OD E L S ON-PREMISES CLOUD “LEGACY” ARCHITECTURES MODERN ARCHITECTURES AWS EC2 AWS ECS AWS FARGATE AWS EKS Containers AWS ECS AWS FARGATE AWS EKS
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    rights reserved. What changes have to be made in this new world? Operational model Architectural patterns Software delivery People
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    rights reserved. Changes to the operational model
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    rights reserved. Comparison of shared operational responsibility AWS Lambda Serverless functions AWS Fargate Serverless containers ECS/EKS Container-management as a service EC2 Infrastructure-as-a-Service More opinionated Less opinionated AWS manages Customer manages • Data source integrations • Application-level runtime and updates • Physical hardware, software, networking, and facilities • Provisioning • Application code • Security and network configuration • Container orchestration, provisioning • Cluster scaling • Physical hardware, host OS/kernel, networking, and facilities • Application code • Service scaling • Data source integrations • Security config network config, management tasks, application runtime updates • Container orchestration control plane • Physical hardware software, networking, and facilities • Application code • Data source integrations • Worker hosts and service scaling • Security config and updates, network config, firewall, management tasks • Physical hardware software, networking, and facilities • Application code • Data source integrations • Instance scaling • Security config and updates, network config, management tasks • Provisioning, managing scaling and patching of servers
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    rights reserved. Changes to the architectural patterns
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    rights reserved. Architecture diagrams change from simple… APPLICATION SERVERS DATABASE SERVERS WEB SERVERS
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    rights reserved. …to more complex MICROSERVICE API API MICROSERVICE MICROSERVICE EVENT API MICROSERVICE EVENT API MICROSERVICE APPLICATION Mobile client Client IoT PERSISTENCE PERSISTENCE
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    rights reserved. APIs are the front door of microservices
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    rights reserved. Event-driven architectures
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    rights reserved. Queues Simple Fully managed Any volume Pub/sub Simple Fully managed Flexible Amazon Simple Queue Service Amazon Simple Notification Service Messaging Synchronization Rapid Fully managed Real-time Amazon EventBridge Decouple state from code using messaging
  37. And data streams Ingest Data streams Data processing Real-time Data

    Store Microservices Performance at scale Fast and Flexible Amazon Kinesis Data Streams Amazon Dynamo DB Data Stream Capture
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    rights reserved. Cloud-native architectures are small pieces, loosely joined
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    rights reserved. Changes to the delivery of software
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    rights reserved. developers delivery pipelines services monitor release test build Monolith development lifecycle
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    rights reserved. developers services monitor release test build delivery pipelines monitor release test build monitor release test build monitor release test build monitor release test build monitor release test build Microservice development lifecycle
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    rights reserved. Architecture evolution Monolithic application Does everything Shared release pipeline Rigid scaling High impact of change Hard to adopt new technologies Microservices Does one thing Independent deployments Independent scaling Small impact of change Choice of technology When the impact of change is small, release velocity can increase
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    rights reserved. What Drives Our Priorities? Excelling in service fundamentals Availability, latency, security, scale and associated controls Equipping developers and operators Constantly improving tools for monitoring, troubleshooting, and auditing Adding efficiency to application development patterns New patterns through events, workflows, functions, and APIs
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    rights reserved. re:Invent 2019 Launches Express Step Functions Faster, Cheaper Step Functions Orchestration Lambda Enhanced Controls Async Controls, Enhanced Streaming Controls Lambda Destinations Send execution results to a Destination Lambda Provisioned Concurrency Managed Prewarming API Gateway HTTP APIs Faster, Cheaper APIs RDS Proxy Managed Database Connection Pools
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    rights reserved. Customers Build better products Innovate more often Release features faster Focus on business logic Decouple software systems Our goal is to automate and abstract away as much as is possible so customers can focus on building applications for their business We are witnessing a paradigm shift
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    rights reserved. aws.amazon.com/serverless
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    rights reserved. Feedback appreciated  https://rebrand.ly/lm- serverless