web consumables

Transcript

1. WEB CONSUMABLES can burak çilingir @ xxxxxxx——- and opportunities
2. WHO AM I
3. WHAT IS WEB request response
4. TECHNOLOGY request response
5. TECHNOLOGY request response
6. TECHNOLOGY request response
7. TECHNOLOGY request response
9. TECHNOLOGY and much more!
10. YOUR EXPECTATION { This should happen in.. • INSTANT • ON CLICK • IMMEDIATELY • EVEN IF INTERNET
 IS SLOW!
11. LET’S ZOOM IN
12. if this should be instant… }
13. LET’S ZOOM OUT
14. TECHNOLOGY
15. TECHNOLOGY
17. …
19. ARCHITECTING
20. Elastic Load Balancing A Elastic Load Balancing B Amazon Route )z Amazon CloudFront Amazon Sz Auto Scaling Auto Scaling Amazon EC6 Amazon EC6 Auto Scaling Auto Scaling Amazon EC6 Amazon EC6 Database Servers Load Balancer Load Balancer Web Servers Web Servers Application Servers Application Servers Application Servers Application Servers Amazon RDS Multi-AZ Standby Amazon RDS Multi-AZ Standby Synchronous Replication Elastic Load Balancing Amazon RDS Master Amazon RDS Master Resources and Static Content Content Delivery Network DNS Resolution Web Servers Web Servers Highly available and scalable web hosting can be complex and expensiveZ Dense peak periods and wild swings in traffic patterns result in low utilization of expensive hardwareZ Amazon Web Services provides the reliableR scalableR secureR and high- performance infrastructure required for web applications while enabling an elasticR scale-out and scale-down infrastructure to match IT costs in real time as customer traffic fluctuatesZ System Overview WEB APPLICATION HOSTING Amazon Route )z Amazon Sz Amazon EC6 Elastic Load Balancing Amazon CloudFront AWS Reference Architectures Auto Scaling Amazon RDS 7 6 z ( ) 7 6 6 6 ( ) z 7 7 7 The userBs DNS requests are served by Amazon Route )zR a highly available Domain Name System 'DNSN serviceZ Network traffic is routed to infrastructure running in Amazon Web ServicesZ StaticR streamingR and dynamic content is delivered by Amazon CloudFrontR a global network of edge locationsZ Requests are automatically routed to the nearest edge locationR so content is delivered with the best possible performanceZ HTTP requests are first handled by Elastic Load BalancingR which automatically distributes incoming application traffic among multiple Amazon Elastic Compute Cloud OEC6P instances across Availability Zones 'AZsNZ It enables even greater fault tolerance in your applicationsR seamlessly providing the amount of load balancing capacity needed in response to incoming application trafficZ Web servers and application servers are deployed on Amazon ECj instancesZ Most organizations will select an Amazon Machine Image OAMIP and then customize it to their needsZ This custom AMI will then become the starting point for future web developmentZ Web servers and application servers are deployed in an Auto Scaling groupZ Auto Scaling automatically adjusts your capacity up or down according to conditions you defineZ With Auto ScalingR you can ensure that the number of Amazon EC6 instances you’re using increases seamlessly during demand spikes to maintain performance and decreases automatically during demand to minimize costsZ To provide high availabilityR the relational database that contains applicationBs data is hosted redundantly on a multi-AZ 'multiple Availability Zones–zones A and B hereN deployment of Amazon Relational Database Service 'Amazon RDSNZ Resources and static content used by the web application are stored on Amazon Simple Storage Service OSzPR a highly durable storage infrastructure designed for mission-critical and primary data storageZ
21. satisfactory player experience. Amazon Web Services provides different tools and services that can be used for building online games that scale under high usage traffic patterns. This document presents a cost-effective online game architecture featuring automatic capacity adjustment, a highly available and high-speed database, and a data processing cluster for player behavior analysis. System Overview ONLINE GAMES Amazon EC2 Elastic Load Balancing Amazon DynamoDB Amazon EMR Auto Scaling AWS Reference Architectures Amazon S3 Online games back-end infrastructures can be challenging to maintain and operate. Peak usage periods, multiple players, and high volumes of write operations are some of the most common problems that operations teams face. But the most difficult challenge is ensuring flexibility in the scale of that system. A popular game might suddenly receive millions of users in a matter of hours, yet it must continue to provide a ______ Amazon SES 1 Browser games can be represented as client-server applications. The client generally consists of static files, such as images, sounds, flash applications, or Java applets. Those files are hosted on Amazon Simple Storage Service (Amazon S3), a highly available and reliable data store. 5 Log files generated by each web server are pushed back into Amazon S3 for long-term storage. 2 As the user base grows and becomes more geographically distributed, a high-performance cache like Amazon CloudFront can provide substantial improvements in latency, fault tolerance, and cost. By using Amazon S3 as the origin server for the Amazon CloudFront distribution, the game infrastructure benefits from fast network data transfer rates and a simple publishing/caching workflow. 3 Requests from the game application are distributed by Elastic Load Balancing to a group of web servers running on Amazon Elastic Compute Cloud (Amazon EC2) instances. Auto Scaling automatically adjusts the size of this group, depending on rules like network load, CPU usage, and so on. 4 Player data is persisted on Amazon DynamoDB, a fully managed NoSQL database service. As the player population grows, Amazon DynamoDB provides predictable performance with seamless scalability. Amazon Route 53 6 Managing and analyzing high data volumes produced by online games platforms can be challenging. Amazon Elastic MapReduce (Amazon EMR) is a service that processes vast amounts of data easily. Input data can be retrieved from web server logs stored on Amazon S3 or from player data stored in Amazon DynamoDB tables to run analytics on player behavior, usage patterns, etc. Those results can be stored again on Amazon S3, or inserted in a relational database for further analysis with classic business intelligence tools. 7 Based on the needs of the game, Amazon Simple Email Service (Amazon SES) can be used to send email to players in a cost-effective and scalable way. Amazon CloudFront www.mygame.com Amazon Route 53 DNS Resolution Amazon Dynam o DB Game interaction (status, JSON, ...) Auto Scaling Auto Scaling Elastic Load Balancing Web Servers Amazon CloudFront Content Delivery Network Amazon S3 Game files (flash, applet, ...) Files Repository Game Database Amazon Elastic M apReduce Game Analysis log files 4 5 log files Game client files 7 Amazon SES • 6 Players Email Emitter log files 2 1 3
22. Customers want to find the products they are interested in quickly, and they expect pages to load quickly. Worldwide customers want to be able to make purchases at any time, so the website should be highly available. Meeting these challenges becomes harder as your catalog and customer base grow. With the tools that AWS provides, you can build a compelling, scalable website with a searchable product catalog that is accessible with very low latency. System Overview E-COMMERCE WEB SITE PART 1: WEB FRONT-END Amazon Route 53 Amazon DynamoDB Amazon ElastiCache AWS Elastic Beanstalk AWS Reference Architectures Amazon S3 With Amazon Web Services, you can build a highly available e- commerce website with a flexible product catalog that scales with your business. Maintaining an e-commerce website with a large product catalog and global customer base can be challenging. The catalog should be searchable, and individual product pages should contain a rich information set that includes, for example, images, a PDF manual, and customer reviews. Amazon CloudFront 1 DNS requests to the e-commerce website are handled by Amazon Route 53, a highly available Domain Name System (DNS) service. 5 Amazon DynamoDB is a fully-managed, high performance, NoSQL database service that is easy to set up, operate, and scale. It is used both as a session store for persistent session data, such as the shopping cart, and as the product database. Because DynamoDB does not have a schema, we have a great deal of flexibility in adding new product categories and attributes to the catalog. 2 Amazon CloudFront is a content distribution network (CDN) with edge locations around the globe. It can cache static and streaming content and deliver dynamic content with low latency from locations close to the customer. 3 The e-commerce application is deployed by AWS Elastic Beanstalk, which automatically handles the details of capacity provisioning, load balancing, auto scaling, and application health monitoring. 4 Amazon Simple Storage Service (Amazon S3) stores all static catalog content, such as product images, manuals, and videos, as well as all log files and clickstream information from Amazon CloudFront and the e-commerce application. 6 Amazon ElastiCache is used as a session store for volatile data and as a caching layer for the product catalog to reduce I/O (and cost) on DynamoDB. 7 Product catalog data is loaded into Amazon CloudSearch, a fully managed search service that provides fast and highly scalable search functionality. 8 When customers check out their products, they are redirected to an SSL-encrypted checkout service. 9 A marketing and recommendation service consumes log data stored on Amazon S3 to provide the customer with product recommendations. Amazon CloudSearch Custom er AW S Elastic Beanstalk Amazon CloudFront Amazon Route 53 1 6 Amazon ElastiCache 5 9 AW S Elastic Beanstalk AW S Elastic Beanstalk AW S Elastic Beanstalk AW S Elastic Beanstalk Amazon CloudSearch Amazon S3 Amazon Dynam oDB LOGS MARKETING AND RECOMMENDATION SERVICE Part 3 CHECKOUT SERVICE Part 2 E-commerce Application Recommendation Web Service Recommendation Web Service Catalog Cache & Transient Session Store Search Engine Product Catalog & Persistent Session Store Checkout Application Checkout Application Log File Repository & Static Catalog Content DNS 2 3 4 7 8 Secure Connection Secure Connection
23. Customers expect their private data, such as their purchase history and their credit card information, to be managed on a secure infrastructure and application stack. AWS has achieved multiple security certifications relevant to e-commerce business, including the Payment Cards Industry (PCI) Data Security Standard (DSS). With the tools that AWS provides, you can build a secure checkout service that manages the purchasing workflow from order to fulfillment. System Overview Amazon VPC Amazon SES Amazon EC2 Elastic Beanstalk AWS Reference Architectures Amazon RDS With Amazon Web Services, you can build a secure and highly available checkout service for your e-commerce website that scales with your business. Managing the checkout process involves many steps, which have to be coordinated. Some steps, such as credit card transactions, are subject to specific regulatory requirements. Other parts of the process involve manual labor, such as picking, packing, and shipping items from a warehouse. Amazon SW F 1 The e-commerce web front end redirects the customer to an SSL-encrypted checkout application to authenticate the customer and execute a purchase. 5 SWF Workers are deployed on Amazon EC2 instances within a private subnet. The EC2 instances are part of an Auto Scaling group, which can scale in and out according to demand. The Workers manage the different steps of the checkout pipeline, such as validating the order, reserving and charging the credit card, and triggering the sending of order and shipping confirmation emails. 2 The checkout application, which is deployed by AWS Elastic Beanstalk, uses Amazon Simple Workflow Service (Amazon SWF) to authenticate the customer and trigger a new order workflow. 3 Amazon SWF coordinates all running order workflows by using SWF Deciders and SWF Workers. 4 The SWF Decider implements the workflow logic. It runs on an Amazon Elastic Compute Cloud (Amazon EC2) instance within a private subnet that is isolated from the public Internet. 6 SWF Workers can also be implemented on mobile devices, such as tablets or smartphones, in order to integrate pick, pack, and ship steps into the overall order workflow. 7 Amazon Simple Email Service (Amazon SES) is used to send transactional email, such as order and shipping confirmations, to the customer. 8 To provide high availability, the customer and orders databases are hosted redundantly on a multi-AZ (multi Availability Zone) deployment of Amazon Relational Database Service (Amazon RDS)within private subnets that are isolated from the public Internet. E-COMMERCE WEB SITE PART 2: CHECKOUT SERVICE • 7 2 1 5 4 AW S Elastic Beanstalk AW S Elastic Beanstalk WEB FRONT-END Part 1 E-Commerce Application E-Commerce Application Custom er AW S Elastic Beanstalk Amazon SES Checkout Application Email Service Customers & Orders Database Mobile Workers (in warehouse) Auto Scaling Auto Scaling Amazon SW F Amazon RDS Master Amazon RDS Multi-AZ Standby Workers Workers Decider Decider Order Emails 6 8 Workflow Service 3
24. CHECKOUT SERVICE Part 2 AW S Elastic Beanstalk • Amazon SES 7 5 3 Amazon RDS Read Replica Amazon Elastic MapReduce Amazon Dynam oDB Amazon S3 Amazon S3 1 Email Service Marketing Mgmt App User Profiles Amazon RDS Master Amazon RDS Master Customer & Orders DB Customer & Orders DB Log File Repository Log File Repository Recommendation Web Service Customer & Orders DB Read Replica AW S Elastic Beanstalk AW S Elastic Beanstalk AW S Elastic Beanstalk WEB FRONT-END Part 1 E-commerce Application E-commerce Application Marketing Emails Marketing Manager Custom ers 4 6 2 The insights that you gain about your customers can also be used to manage personalized marketing campaigns targeted at specific customer segments. With the tools that AWS provides, you can build highly scalable recommendation services that can be consumed by different channels, such as dynamic product recommendations on the e - commerce website or targeted email campaigns for your customers. System Overview E-COMMERCE WEBSITE PART 3: MARKETING & RECOMMENDATIONS Amazon EMR Amazon SES AWS Elastic Beanstalk AWS Elastic Beanstalk AWS Reference Architectures Amazon RDS With Amazon Web Services, you can build a recommendation and marketing service to manage targeted marketing campaigns and offer personalized product recommendations to customers who are browsing your e-commerce site. In order to build such a service, you have to process very large amounts of data from multiple data sources. The resulting user profile information has to be available to deliver real-time product recommendations on your e-commerce website. Amazon S3 1 Amazon Elastic MapReduce (Amazon EMR) is a hosted Hadoop framework that runs on Amazon Elastic Compute Cloud (Amazon EC2) instances. It aggregates and processes user data from server log files and from the customer´s purchase history. 5 A recommendation web service used by the web front end is deployed by AWS Elastic Beanstalk. This service uses the profile information stored on Amazon DynamoDB to provide personalized recommendations to be mm shown on the e-commerce web front end. 2 An Amazon Relational Database Services (Amazon RDS) Read Replica of customer and order databases is used by Amazon EMR to compute user profiles and by Amazon Simple Email Service (Amazon SES) to send targeted marketing emails to customers. 3 Log files produced by the e-commerce web front end have been stored on Amazon Simple Storage Service (Amazon S3) and are consumed by the Amazon EMR cluster to compute user profiles. 4 User profile information generated by the Amazon EMR cluster is stored in Amazon DynamoDB, a scalable, high-performance managed NoSQL database that can serve recommendations with low latency. 6 A marketing administration application deployed by AWS Elastic Beanstalk is being used by marketing managers to send targeted email campaigns to customers with specific user profiles. The application reads customer email addresses from an Amazon RDS Read Replica of the customer database. 7 Amazon SES is used to send marketing emails to customers. Amazon SES is based on the scalable technology used by Amazon web sites around the world to send billions of messages a year. Amazon DynamoDB
25. AW S Data Pipeline This elasticity is achieved by using Auto Scaling groups for ingest processing, AWS Data Pipeline for scheduled Amazon Elastic MapReduce jobs, AWS Data Pipeline for intersystem data orchestration, and Amazon Redshift for potentially massive-scale analysis. Key architectural throttle points involving Amazon SQS for sensor message buffering and less frequent AWS Data Pipeline scheduling keep the overall solution costs predictable and controlled. System Overview TIME SERIES PROCESSING Amazon EC2 Amazon EMR Amazon DynamoDB AWS Data Pipeline Auto Scaling AWS Reference Architectures Amazon S3 When data arrives as a succession of regular measurements, it is known as time series information. Processing of time series information poses systems scaling challenges that the elasticity of AWS services is uniquely positioned to address. Amazon SQS Amazon EC2 Spot 2 Send messages to an Amazon Simple Queue Service queue for processing into Amazon DynamoDB using autoscaled Amazon EC2 workers. Or, if the sensor source can do so, post sensor samples directly to Amazon DynamoDB. Try starting with a DynamoDB table that is a week-oriented, time-based table structure. 2 1 6 3 3 If a Supervisory Control and Data Acquisition (SCADA) system exists, create a flow of samples to or from Amazon DynamoDB to support additional cloud processing or other existing systems, respectively. 4 Using AWS Data Pipeline, create a pipeline with a regular Amazon Elastic MapReduce job that both calculates expensive sample processing and delivers samples and results. 4 7 7 The pipeline also optionally exports results in a format custom applications can accept. Corporate Data Center Amazon SQS Am azon Dynam oDB Auto Scaling Worker Nodes Sensor Sam pled Data SCADA Amazon S3 Rem ote Sensor M essages Amazon Elastic MapReduce +EC2 Spot Instances Amazon Redshift 5 Custom Application 5 The pipeline places results into Amazon Redshift for additional analysis. 8 Amazon Redshift optionally imports historic samples to reside with calculated results. 9 Using in-house or Amazon partner business intelligence solutions, Amazon Redshift supports additional analysis on a potentially massive scale. 1 Remote devices such as power meters, mobile clients, ad-network clients, industrial meters, satellites, and environmental meters measure the world around them and send sampled sensor data as messages via HTTP(S) for processing. 6 The pipeline exports historical week-oriented sample tables, from Amazon DynamoDB to Amazon Simple Storage Service (Amazon S3) Business Intelligence User 8 9 Amazon EC2
26. PROBLEMS SUMMARISED • So many types of clients • So many users • Low latency expectance • So many servers • Many data-centers • So many services • Inter-service communication • Inter-dc communication • Service consumer to dc routing • Low latency expectance! W H AT ABO UT D EPLO YM EN T
27. DEVELOPMENT • Developers develop • They need to develop together • They need to see how their code works together • Customers need to see what is happening • Staging, testing
28. DEPLOYMENT Developed code must be deployed to…
29. DEPLOYMENT • Rolling to a subset of servers • Testing new features by selectively enabling traffic • Pulling back • Tools!
30. SOME TOOLS
31. POSTGRESQL • SQL • Stores data
32. ELASTICSEARCH • stores structured data: • {a: 1, b:2, c:3} • output: immediate reply to searches • all documents where a>1
33. JENKINS • deploys code • runs code when code changes
34. DOCKER • packages the application • highest level of dependancy management • eases deployment/scales dractically
35. GIT - GITHUB • code management • discussion on bugs • project management
36. DJANGO • framework • building web services • web apps
37. NAEMON • monitoring anything • even temperature • graphing • spotting trends • why mornings dc is hot?
38. PUPPET • mass server management • ensures clocks are ticking • services are running
39. GRAYLOG • applications log internal data • analyzes, monitors logs
40. REDIS • stores data structures • provides immediate access • no searching • caching
41. AMAZON WEB SERVICES • datacenter on cloud • services on cloud • everything on cloud
42. SOME NUMBERS 6 digits ($) hosting invoice ~200k RPM more than 500 servers You can compare us with others: https://aws.amazon.com/solutions/case-studies/all/ ik@metglobal.com
43. CAN BURAK ÇİLİNGİR can@canb.net