Iniciando com Amazon DynamoDB
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O documento discute como o DynamoDB da AWS pode ser usado para construir aplicações serverless escaláveis com armazenamento não relacional. Ele resume como o DynamoDB oferece desempenho previsível e alta disponibilidade para casos de uso como MLBAM e Duolingo, e como ele pode integrar-se com outros serviços da AWS como Lambda e API Gateway para criar aplicações baseadas em eventos.
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Iniciando com Amazon DynamoDB
- 1. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Thiago Paulino, Arquiteto de soluções Jun/2017 Iniciando com Amazon DynamoDB
- 2. Agenda • Breve história sobre processamento de dados Relacional (SQL) vs. non-relacional (NoSQL) • Soluções NoSQL na AWS • Amazon DynamoDB’s 100% Gerenciado
- 3. Volume de dados desde 2010 • 90% dos dados armazenados foram gerados nos 2 últimos anos • 1 terabyte de dados em 2010 hoje representa o mesmo de 6.5 petabytes • Correlação linear entre dados e inovação tecnológica • Nenhuma razão para que essas tendências não continuem a acontecer.
- 4. Linha do tempo do banco de dados DataPressure
- 5. Curva de adoção de tecnologia
- 6. Relacional (SQL) vs. Non-relacional (NoSQL)
- 7. Banco de dados Relacional vs. Non-relacional Tradicional SQL NoSQL DB Primário Secundário Scale up DB DB DBDB DB DB Scale out
- 8. SQL (Relacional) Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Products Book Album Movie
- 9. SQL (Relacional) Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Products Book Album Movie Books Title Date Odyssey 1871 Book ID 1 Books Author Homer
- 10. SQL (Relacional) Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Products Book Album Movie Books Title Date Odyssey 1871 Book ID 1 Books Genre Director Drama, Comedy Chaplin Movie ID Title 3 The Kid Movies Author Homer
- 11. SQL (Relacional) Products Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Book Album Movie Books Albums Title Date Odyssey 1871 Book ID 1 Books Albums Title 6 Partitas Album ID Artist 2 Genre Director Drama, Comedy Chaplin Movie ID Title 3 The Kid Movies Bach Author Homer
- 12. SQL (Relacional) Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Books Albums Products Book Album Movie Title Date Odyssey 1871 Book ID 1 Books Albums Title 6 Partitas Album ID Artist 2 Genre Director Drama, Comedy Chaplin Movie ID Title 3 The Kid Movies Tracks Track Partita No. 1 Album ID Track ID 2 1 Bach Author Homer
- 13. SQL (Relacional) vs. NoSQL (Non-relacional) Product ID Type Odyssey Homer1 Book ID 2 Album ID 6 Partitas 2 Album ID: Track ID Partita No. 1 Bach Attributes Schema is defined per item Items Partition Key Sort Key 3 Movie ID The Kid Drama, Comedy 1871 Chaplin Primary Key Products Price Desc. $11.50 $8.99 Chaplin’s first … Columns Rows Primary Key Index $14.95 One of 2 major … The Partitas Product ID Type 1 2 3 Title Date Odyssey 1871 Book ID 1 Books Albums Title 6 Partitas Album ID Artist 2 Genre Director Drama, Comedy Chaplin Movie ID Title 3 The Kid Movies Products Book Album Movie Tracks Track Partita No. 1 Album ID Track ID 2 1 Author Homer Bach NoSQL design otimiza para computação em vez de armazenamento
- 14. Por que NoSQL? Otimizado para armazenamento Otimizado para processamento Normalizado/relacional Desnormalizado/Hierárquico Ad hoc queries Visualização instantânia Escala vertical Escala horizontal Bom para for OLTP/OLAP Bom para for OLTP em escalabilidade SQL NoSQL
- 15. NoSQL solutions using Amazon EC2 and EBS DB rodando no seu datacenter DB rodando em Amazon EC2
- 16. Amazon DynamoDB Foco no seu negócio, não na sua base de dados
- 17. 100% Gerenciado Rápido, desempenho consistênte Altamente escalavel Flexivel Aplicação baseada em eventos Seguro DynamoDB Benefícios
- 18. • Alta disponibilidae com transparência • Replicação sem custo extra • Recuperação de disastre caso uma região tenha falha • Escale-out direcionando tráfego para as replicas de leitura de leitura Multi-AZ & Replicação entre região 1 2
- 19. • Reduz o custo para deletar itens que não são mais necessários • Otimização de performance ao controlar o tamanho da tabela • Trigger (Eventos) com streamming e AWS Lambda DynamoDB Time-to-Live (TTL) ID Name Size Expiry 1234 A 100 1456702305 2222 B 240 1456702400 3423 C 150 1459207905 TTL Value (Epoch format) TTL Attribute
- 20. Programação baseada em eventos DynamoDB Triggers Implementado com funções de AWS Lambda functions Seu código escala automáticamente Java, Node.js, Python e .NET Core DynamoDB Streams Stream dos updates da tabela Processamento assíncrono Exatamente uma vez Com ordenação 24-hr lifetime per item
- 21. Plataforma de integração DynamoDB IoT S3 Kinesis EMR Redshift Data Pipeline Mobile Hub Lambda Elasticsearch SNS CloudWatch CloudTrail
- 22. Integração com AWS • Camada de cache 100% gerênciado com Elasticache • Full-text search query com Elasticsearch • Big Data Analytics com EMR e Redshifit • Processamento em tempo real com Kinesis
- 23. • Controle de acesso restritivo e controlado com AWS IAM • Biblioteca de criptografia no lado do cliente • Log de configurações e acesso com AWS CloudTrail • Monitoramento de desempenho e alarme de eventos com AWS CloudWatch Segurança com DynamoDB
- 24. Serviço totalmente gerenciado = operações automatizadas DB hosted on-premises DB hosted on Amazon EC2
- 25. Serviço totalmente gerenciado = operações automatizadas DB hosted on premise DynamoDB
- 26. Latência consistente mesmo com requisições crescentes DESEMPENHO PREVISÍVEL!
- 27. Escritas Replicação continua em 3 AZs Leituras Strongly or eventually consistent Sem trade-off de latência Desenhado para ter 99.99% de disponibilidade Contruído para alta durabilidade Alta disponibilidade e durabilidade
- 28. Casos de uso
- 29. MLBAM (MLB Advanced Media) is a full service solutions provider, operating a powerful content delivery platform. Pela primeira vez, nós conseguimos mensurar coisas que nós nunca mensuramos antes Joe Inzerillo Executive Vice President and CTO, MLBAM ” “ • MLBAM Conseguiu suportar vários jogos no mesmo dia e escalar sua capacidade para atender essa demanda. • Amazon DynamoDB permite o acesso ao dado de uma maneira muito rápida. • MLBAM realiza 25,000 eventos ao vivo anualmente e realiza 10 milhões de transmissões por dia. Major League Baseball Fields Big Data, Excitement with Amazon DynamoDB
- 30. Duolingo escalou seu armazenamento para 31 Bilhões de Itens usando DynamoDB Duolingo is a free language learning service where users help translate the web and rate translations. Usando a AWS, podemos lidar com os picos de tráfego que aumenta até sete vezes a quantidade de tráfego normal. Severin Hacker CTO, Duolingo ” “ • Duolingo armazena dado para cada usuário para gerar lições personalizadas. • O banco de dados MySQL database não conseguiu acompanhar o crescimento do negócio • Ao utilizar um banco de dados escalavel aumentou a capacidade de armazenamento de 100 milhões para bilhões de itens • Duolingo possuí capacidade para escalar e suportar mais de 8 milhões de usuários ativos
- 31. Ad Tech Gaming MobileIoT Web Scaling high-velocity use cases with DynamoDB
- 32. Use case Aplicação web Serverless com DynamoDB, API Gateway, and AWS Lambda
- 33. Aplicação web simples serverless – use case
- 34. Aplicação elástica baseada em eventos
- 35. Aplicação elástica baseada em eventos
- 36. Aplicação elástica baseada em eventos
- 37. Aplicação elástica baseada em eventos
- 38. Aplicação elástica baseada em eventos
- 39. • Free Tier 25GB of storage 25 Reads per second 25 Writes per second DynamoDB Free Tier
- 40. Resources Amazon DynamoDB: https://aws.amazon.com/dynamodb/ NoSQL on AWS: https://aws.amazon.com/nosql/document/
- 41. Obrigado!
Notas do Editor
- We will look at the history of databases, and we’ll discuss relational database and non-relational databases, and the differences. I’ll introduce Amazon DynamoDB and we’ll look at customer references who have built scalable applications using this technology.
- To fully appreciate the need for NoSQL… Let’s start by looking into how much data volume has grown in the last 5 years. 90% of data was generated in the last 2 years. 1 TB vs 6.5 PB We are starting to see Businesses with multi-TB have exploded to multi-PB databases. As data volume increased, we started innovating data processing systems that would scale to process the large volume of data
- We started by remembering everything (human brain) and advanced to writing things down (for centuries). As data pressure increased we saw Magnetic storage, File systems, and then finally Relational Databases. 40 years. Table normalization was designed to eliminate duplicates and save storage costs. Multiple tables – Complex SQL joins – Resource intensive. Optimize for the costlier asset. AGNOSTIC TO ACCESS PATTERNS -- Great for adhoc queries –NOT optimized. Business are seeing the limitations in relational databases. Switching to NoSQL.
- Every time there is a new technology, there is initial excitement with early adopters… They may run into roadblocks. It’s the same with NoSQL. The goal of this presentation is to explain the difference between relational and NoSQL databases. And as you gain more experience with this technology you will start to realize the benefits of NoSQL for your application. And that will help you cross the chasm in getting started with DynamoDB.
- Let’s deep dive into the differences between relational and non-relational databases. Why? Databases are a crucial part of your application and your choice of database technology will determine how your application scales. To understand the benefits of NoSQL…
- Relational - Data is normalized. To enable joins, You are tied to a single partition and a single system. performance on the hardware specs of the primary server. To improve performance, Optimize -- Move to a bigger box. You may still run out of headroom. Create Read Replicas. You will still run out. Scale UP. NoSQL -- NoSQL databases were designed specifically to overcome scalability issues. Scale “out” data using distributed clusters, low-cost hardware, throughput + low latency Therefore, Using NoSQL, businesses can scale virtually without limit.
- Relational databases normalize data into tabular structures known as tables, which consist of rows and columns.
- In relational databases, a schema strictly defines the tables, columns, indexes, relationships between tables, and other database elements. There is a 1:1 relationship between the Products table and Books table.
- There is a 1:1 relationship between the Products table and Movies table.
- There is a 1:1 relationship between the Products table and Albums table.
- m:n relationship between albums and tracks. Notice how you can execute a complex join to run adhoc queries - agnostic to data access patterns - they are not optimized for a specific access pattern. Businesses are starting to see a limitation in relational databases.
- NoSQL you have to ask – how will the application access the data? And store your data in such a way to retrieve the data with just a Select, and No joins. Designed by keeping in mind Access patterns. Via duplication of data (storage) and using Hierarchical structures, you can now optimize for compute, and therefore it is very fast. == Non-relational (NoSQL) databases typically do not enforce a schema. A “partition key” is generally used to retrieve values, column sets, or semi-structured JSON, XML, or other documents containing related item attributes.
- Businesses are starting to see scalability problems with relational databases. I once had a customer say they top out with relational at around 3,000 requests per second and had to scale up to move to bigger hardware. With NoSQL, we have a technology that can easily sale to 100s of nodes, or even 1000s, and the scalability bottleneck goes away. Excellent for OLTP applications that scale, real time data access, fast, low latency, user cannot wait. == They store data in a denormalized hierarchical view, that makes it faster and easier to access the data.
- Those if you who are involved in spinning up and managing your own servers surely realize how resource intensive it is to manage your own infrastructure. It can be possible to underestimate the cost and complexity of maintaining…. You have to think about power, cooling, OS maintenance and patching. Now imagine managing a 1000 node cluster, this can become very resuource intensive Amazon EC2 is an AWS service for is the comupte capacity in cloud, it is resizable. Database instance hosted in an EC2 instance takes away some of the overhead. But, you still need to think about scalability and availability.
- So, this brings us to Amazon DynamoDB, which is what we are going to discuss today. Let’s take a closer look.
- Fully managed – With just a few clicks on the AWS console – create a table that is highly scalalable, highly available, and gives you fast consistent predictable performance. No need to launch or maintain any servers. Tell DynamoDB read/write – DynamoDB will scale to meet your application’s requirements Only pay for what you use. You get all of this with just a few clicks. Key take away: Using DynamoDB customers get consistent, single-digit millisecond latency at any scale. == DynamoDB supports both document and key-value store models, and offers a range of features including global secondary indexes, fine-grained access control via AWS Identity and Access Management, support for event-driven programming, and more. == Fully Managed Amazon DynamoDB is a fully managed cloud NoSQL database service – you simply create a database table, set your throughput, and let the service handle the rest. You no longer need to worry about database management tasks such as hardware or software provisioning, setup and configuration, software patching, operating a reliable, distributed database cluster, or partitioning data over multiple instances as you scale. Fast, Consistent Performance Amazon DynamoDB is designed to deliver consistent, fast performance at any scale for all applications. Average service-side latencies are typically single-digit milliseconds. As your data volumes grow and application performance demands increase, Amazon DynamoDB uses automatic partitioning and SSD technologies to meet your throughput requirements and deliver low latencies at any scale. Highly Scalable When creating a table, simply specify how much request capacity you require. If your throughput requirements change, simply update your table's request capacity using the AWS Management Console or the Amazon DynamoDB APIs. Amazon DynamoDB manages all the scaling behind the scenes, and you are still able to achieve your prior throughput levels while scaling is underway. Flexible Amazon DynamoDB supports both document and key-value data structures, giving you the flexibility to design the best architecture that is optimal for your application. Event Driven Programming Amazon DynamoDB integrates with AWS Lambda to provide Triggers which enables you to architect applications that automatically react to data changes. Fine-grained Access Control Amazon DynamoDB integrates with AWS Identity and Access Management (IAM) for fine-grained access control for users within your organization. You can assign unique security credentials to each user and control each user's access to services and resources. http://aws.amazon.com/dynamodb
- Built-In 3-way data replication to three Availability Zones (AZ) within an AWS region Replicate to other regions with open source, fully-extensible, library
- Automatically delete items from a table based on expiration timestamp User defined TTL attribute in epoch time format TTL activity recorded in DynamoDB Streams Amazon DynamoDB Time-to-Live (TTL) enables you to automatically delete expired items from your tables, at no additional cost. Now, you no longer need to deal with the complexity and cost of manually scanning your tables and deleting the items that you don’t want to retain. Instead, you can simply specify an attribute containing the timestamp when each item in your table should expire and DynamoDB will delete the items for you automatically. You can also view and archive items deleted via TTL using DynamoDB Streams. TTL is useful for customers whose storage is growing rapidly and want to control their costs by either archiving or deleting items that they don’t wish to retain indefinitely. It is also helpful for customers who have contractual requirements around data retention and want to closely manage the data in their tables. To learn more about using TTL for your tables, read our blog post and TTL Documentation. https://aws.amazon.com/blogs/aws/new-manage-dynamodb-items-using-time-to-live-ttl/ http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/TTL.html
- The new DynamoDB Streams feature is designed to address this very intriguing use case. Once you enable it for a DynamoDB table, all changes (puts, updates, and deletes) made to the table are tracked on a rolling 24-hour basis. You can retrieve this stream of update records with a single API call and use the results to build tools and applications that function as described above. You have full control over the records that appear in the DynamoDB Stream: no values, all values, or changed values. If you are building mobile, ad-tech, gaming, web or IoT applications, you can use the DynamoDB Streams capability to make your applications respond to high velocity data changes without having to track the changes yourself. With the recent free tier increase (now including 25 GB of storage and over 200 million requests per month), you can try DynamoDB for your new applications at little or no cost. You can think of the combination of Streams and Lambda as a clean and lightweight way to implement database triggers, NoSQL style! Historically, relational database triggers were implemented within the database engine itself. As such, the repertoire of possible responses to an operation is limited to the operations defined by the engine. Using Lambda to implement the actions associated with the triggers (inserting, deleting, and changing table items) is far more powerful and significantly more expressive.
- For those of you who want to learn more, there is a session later today that will cover advanced topics.
- For those of you who want to learn more, there is a session later today that will cover advanced topics.
- Amazon DynamoDB provides features to help you secure your data: Fine-grained Access Control - DynamoDB integrates with AWS Identity and Access Management (IAM) for fine-grained access control for users within your organization. You can assign unique security credentials to each user and control each user's access to services and resources. You can control access at the table, item or attribute level with AWS IAM Client-side encryption library with optional AWS KMS integration; encrypt select or all attributes Log DynamoDB configuration, table setup changes and API calls with AWS CloudTrail Monitor performance and trigger alarms with AWS CloudWatch
- Those if you who are involved in spinning up and managing your own servers surely realize how resource intensive it is to manage your own infrastructure. It can be possible to underestimate the cost and complexity of maintaining…. You have to think about power, cooling, OS maintenance and patching. Now imagine managing a 1000 node cluster, this can become very resuource intensive Amazon EC2 is an AWS service for is the comupte capacity in cloud, it is resizable. Database instance hosted in an EC2 instance takes away some of the overhead. But, you still need to think about scalability and availability.
- This is the value that is built into DynamoDB. With DynamoDB, you have get an easy-to-use database. You don’t have to spin up any servers. You can easily design serverless scalable aplications with DynamoDB. You get scalability and multi-AZ replication without designing a distributed system. You get ongoing security upgrades, software improvements, cost reduction efforts, monitoring…without any effort at all. DDB is fully managed service, you have all of that benefit built into it. We built Dynamo to just work so you can focus on your app.
- Note: This represents several days. It is real data, and we can’t share the Y axis. This represents swings of millions of RPS. In any business, as your business scales up, you need a way to easy scale to meet the traffic, and be able to get consistent predicatable latency at any scale. You need a way to scale down as your business needs changes. DynamoDB was designed to offer consistent and predictable single-digit millisecond latency, at any scale. And you only pay for what you use. NO limit on throughouput. No limit on Size – PB of data any number of items. The latency characteristics of DynamoDB are under 10 milliseconds and highly consistent. Most importantly, the data is durable in DynamoDB, constantly replicated across multiple data centers and persisted to SSD storage. Predictable Performance This is obviously something that’s important and valuable in any industry, whether it’s powering the New York Times recommendation engine, storing and retrieving game data for the game Fruit Ninja, or powering queries and fast data retrieval for Major League Baseball Advanced Media. Predictable performance at scale is a must-have for many web apps, and DynamoDB was designed specifically to deliver on this.
- 13/35. 4 more regions. DynamoDB is highly durable. AWS has a concept of regions and Availability zones. AWS region is a geographic area. Each region has multiple availability zones. Each AZ has 1 or more physical DCs. They have redundant power and cooling, and interconnected via high speed low latency fiber. Take for example the AWS region in NVIrgina. It has 4 Azs. When you create a DynamoDB table in Nvirgina, we will replicate the data to 3 Azs. All the data is stored in SSDs. A lot of value built into DynamoDB– a few clicks.
- Growing number of customers in the Mobile, IoT, Gaming space are using DynamoDB.
- Amazon’s path from Relational Databases to NoSQL reflects the journey many customers are now taking. Amazon.com, the online retail business, runs on one of the world’s largest web infrastructures. Back in 2004, Amazon.com was using Relational Oracle Databases and they were unable to scale their relational database. Maintenance and administration. In order to keep Amazon.com highly scalable to support all the incoming traffic, Internal project to investigate options… “If availability, durability, and scalability are the priority, what would the database look like?”. This resulted in a whitepaper that described what the database should look like. This paper made the way for many NoSQL technologies out there today. This was also the beginning of DynamoDB. Database as a Swiss Army Knife - Hundreds of applications built on RDBMS, Poor Scalability (Q4 was a pain), Poor availability, Exorbitantly high costs for h/w, software, admin Dynamo = replicated DHT with consistency management Specialist tool with limited query and simpler consistency Problem: required significant effort to maintain DynamoDB was designed to deliver consistently high performance at any scale: Predictable Performance Massively Scalable Fully Managed Low Cost Give brief, give citations, give list of engines that reference it. Mention where the writers are today. 4 still with Amazon, at least 1 boomeranged.
- Major League Baseball – A great example of a customer using DynamoDB to build IoT solution. Amazon DynamoDB powers queries required to support many games on a single day. When there are only a few games, it dials down throughput to save money; MLBAM only pays for the capacity it uses. === STORY BACKGROUND MLBAM (MLB Advanced Media) is a full service solutions provider, operating a powerful content delivery platform. Amazon DynamoDB powers queries and supports the fast data retrieval required to support many games on a single day. MLBAM distributes 25,000 live events annually and 10 million streams daily. SOLUTION AND BENEFITS MLBAM only pays for the capacity it uses. When there are only a few games, it dials down throughput to save money. MLBAM can focus on what it does best, rather than spending resources managing clusters of non-relational (NoSQL) databases. On big game days, MLBAM can quickly scale up DynamoDB read and write capacity to meet its demand without increased latency. ADDITIONAL INFORMATION https://aws.amazon.com/solutions/case-studies/major-league-baseball-mlbam/
- A customer who is using DynamoDB to power their Mobile applications -- Redfin – people use this application for searching buying and selling homes. More than 10,000 customers buy or sell homes with Redfin each year. == STORY BACKGROUND Redfin offers full-service real estate brokerage services with local agents and online tools to help people buy & sell homes. Redfin built technology to make customers smarter and faster when buying and selling homes. More than 10,000 customers buy or sell homes with Redfin each year. SOLUTION AND BENEFITS Redfin connects users with properties and agents. Redfin uses DynamoDB to deliver insights to its website and apps. DynamoDB stores property scores, recommendations, property data (e.g., sold, est. value), agent scoring (i.e., how the agent is performing). Redfin websites and apps consume these data from DynamoDB. Using Amazon DynamoDB, Amazon Redshift, Amazon EMR, Amazon S3 ADDITIONAL INFORMATION [Coming December 2015]
- Duolingo provides a free language-learning app that uses crowd sourcing to translate web content as users learn. Duolingo has to be able to scale to manage new users and in addition, expand the service to offer new languages. DynamoDB is Duolingo’s largest and most active data store. Elastic Load Balancing distributes web and mobile traffic across approximately 170 Amazon Elastic Compute Cloud (Amazon EC2) instances. STORY BACKGROUND Duolingo provides a free language-learning app that uses crowd sourcing to translate web content as users learn. In 2012, Apple named the Duolingo app iPhone App of the Year. Duolingo has to be able to scale to manage new users and in addition, expand the service to offer new languages. SOLUTION AND BENEFITS Learned about Amazon DynamoDB at re:Invent 2012. DynamoDB is Duolingo’s largest and most active data store. The company also uses Amazon Relational Database Service (Amazon RDS) running MySQL with provisioned IOPS storage. Elastic Load Balancing distributes web and mobile traffic across approximately 170 Amazon Elastic Compute Cloud (Amazon EC2) instances. Using Amazon DynamoDB, Amazon EC2, Elastic Load Balancing, Amazon SNS, Amazon SQS, Amazon VPC, Amazon CloudFront and Amazon CloudWatch ADDITIONAL INFORMATION https://aws.amazon.com/solutions/case-studies/duolingo
- Nexon is a leading South Korean video game developer. Their blockbuster game titled HIT attracts over 2 million players. They were ranked #1 Mobile Game in Korea on the day of its launch. They used Amazon DynamoDB to scale and to provide a reliable user experience. === STORY BACKGROUND Nexon is a leading South Korean video game developer and a pioneer in the world of interactive entertainment. Nexon provides 150 games to 150 countries, including FIFA Online 3, MapleStory, and Sudden Attack. As of 2014, sales reached $1.6 billion, with 60% from overseas business Nexon used DynamoDB as its primary game database for a new blockbuster Mobile Game, HIT SOLUTION AND BENEFITS DynamoDB serves as the primary game database, offering low latency and scale to match player demand Despite a steady increase in the size of the data, DynamoDB delivered steady latency of less than 10ms. This enabled Nexon to provide a reliable service to users HIT, which was the foundation for the success of HIT. ADDITIONAL INFORMATION https://aws.amazon.com/solutions/case-studies/nexon/
- Here are just a few examples of customers achieving tremendous scale with DynamoDB: And what do customers want? They want Predictable consistent low latency performance at scale; and DynamoDB was designed specifically to deliver on this. == Ad Tech AdRoll http://aws.amazon.com/solutions/case-studies/adroll/ DataXu http://info.qubole.com/how-dataxu-manages-big-data AdBrain http://www.adbrain.com/careers-generalapp/ DoApp https://aws.amazon.com/solutions/case-studies/doapp/ VidRoll https://aws.amazon.com/solutions/case-studies/vidroll/ Fiksu https://aws.amazon.com/solutions/case-studies/fiksu/ TubeMogul https://www.tubemogul.com/engineering/using-contextual-information-in-programmatic-advertising/ TCC https://github.com/TheClimateCorporation/mandolin Gaming Supercell http://aws.amazon.com/solutions/case-studies/supercell/ Zynga https://aws.amazon.com/solutions/case-studies/zynga/ Nexon http://aws.amazon.com/solutions/case-studies/nexon PennyPop http://aws.amazon.com/solutions/case-studies/battle-camp/ Frontier http://aws.amazon.com/solutions/case-studies/frontier-games/ scopely https://aws.amazon.com/solutions/case-studies/scopely/ Unalis https://aws.amazon.com/solutions/case-studies/unalis/ IoT MLBAM http://aws.amazon.com/solutions/case-studies/major-league-baseball-mlbam/ ACTi https://aws.amazon.com/solutions/case-studies/acti-case-study/ Canary https://aws.amazon.com/solutions/case-studies/canary/ Dropcam https://aws.amazon.com/solutions/case-studies/dropcam/ MediaTek https://aws.amazon.com/solutions/case-studies/mediatek/ Devicescape https://aws.amazon.com/solutions/case-studies/devicescape/ Mobile Duolingo http://aws.amazon.com/solutions/case-studies/duolingo-case-study-dynamodb/ Mapbox https://www.mapbox.com/blog/scaling-the-mapbox-infrastructure-with-dynamodb-streams/ Redfin http://aws.amazon.com/solutions/case-studies/redfin/ and https://www.youtube.com/watch?v=YiaPjILR9zw Remind https://aws.amazon.com/solutions/case-studies/remind/ Infraware http://aws.amazon.com/solutions/case-studies/infraware/ Myriad http://aws.amazon.com/solutions/case-studies/myriad-group/ Peak http://aws.amazon.com/solutions/case-studies/peak/ Web Expedia https://aws.amazon.com/solutions/case-studies/expedia/ Nordstrom https://aws.amazon.com/solutions/case-studies/nordstrom/ JustGiving http://aws.amazon.com/solutions/case-studies/justgiving/ Tokyu Hands https://aws.amazon.com/blogs/aws/how-tokyu-hands-architected-a-cost-effective-shopping-system-with-amazon-dynamodb/ jobandtalent https://aws.amazon.com/solutions/case-studies/jobandtalent/ Tigerspike http://aws.amazon.com/solutions/case-studies/tigerspike/
- Amazon DynamoDB is a fully Managed Service. So, to get started with Amazon DynamoDB you simply have to create a table.
- After you logon to the AWS console, select DynamoDB, and click create table, here’s what the screen looks like. Specify a table name, specify a “partition key”. IT’s like a primary key, and uniquely identifies a row. Next, if required change the value for amount of reads / writes the table should support. Or accept the defaults and Click Create.
- And you’ve created your table – this table which you’ve created in just a few clicks is highly scalable, highly available, and is designed to provide consistent low ms latency at scale.
- Attributes can vary between the items, Each item can have a different set of attributes than the other items. (as with any NoSQL database). Partition key – Primary key – uniquely identifies each item. Also determines HOW DATA IS Partitioned STORED Optional Sort key – you have a composite key; Sort keys help to create 1:many relationships, and useful in range queries.
- Some applications might need to perform many kinds of queries, using a variety of different attributes as query criteria. Global Secondary Indexes – Parallel tables or secondary tables. GSI can have a partition key that is different from the Table. They can also have an alternate sort key. Customers, Orders, Date Range. Partition by Order Id and query for a date range. Note: When you create a GSI, you must specify read and write capacity units for the expected workload on that index.
- Customers often ask if LSI should be used or GSI. Think of this as a parallel table asynchronously populated by DynamoDB. Eventually consistent. GSI updates typically happen within a second. Throughput for GSI is important.. That is important on how soon the GSI will be updated. Note: When you create a GSI, you must specify read and write capacity units for the expected workload on that index. 1 Table update = 0, 1 or 2 GSI updates
- Some applications only need to query data using the table's primary key; however, there may be situations where an alternate sort key would be helpful. You can use LSIs. LSI is collocated on the same partition as the item in the table, so this gives us consistency. When an item is updated, LSI is updated, and then ack’d. LSI is partitioned by the same primary key as the parent table. Different Sort key. Say, there is a table containing Customers, Orders, date range. Customers and Orders. LSI can have sort key on a “date range”. A local secondary index maintains an alternate sort key for a given partition key value.
- For those of you who want to learn more, there is a session later today that will cover advanced topics.
- I’ll show you a Demo of building a serveless web app, and we’ll also look at the integration capabilities of DynamoDB with AWS services. DynamoDB is a managed NoSQL offering from AWS, and we are looking for talented engineers to help build the next generation of this service. Contact Raja for more details.
- We will build a web application, that will ask you for feedback and store in securely on the AWS Cloud. The website is a simple HTML/javascript web interface. All the non-PII data – Names of the Super heroes and the mission details is stored in Amazon DynamoDB. All the PII data is stored in Amazon S3 with SSE. When we created this application, I had to main objectives. I do not want to spin up or have to manage any servers. Two, I want to take advantage of the high availability, scalability, and durability features of AWS services..
- *** Amazon S3 is secure, durable, highly-scalable cloud storage, where you can store and retrieve any amount of data.. In this demo, I will access a website using the internet. The website is a simple HTML/javascript web interface. The website is stored in Amazon S3. The application is a simple web interface that will retrieve flight schedules, flight number, wait list, etc stored in a DynamoDB table. In order to set this up, I did not have to spin up any servers, so no servers to maintain. I am taking advantage of all the fully managed capabilities of AWS services to securely access my data. All I did is create my application and let AWS handle the infrastructure and the scaling.
- So we said that API Gateway acts as a front door to the “business logic”. So my business logic is running on AWS Lambda. AWS Lambda is a Fully managed compute service – you just write the code and upload it. In this example, the APIs created from the API Gateway front-door, will call the business logic running on AWS lambda functions.
- And all the data is stored in DynamoDB. DynamoDB is a fully managed NoSQL database service that provides consistent, single-digit millisecond latency at any scale. [CLICK] So if you put this together, I will show you a demo where I will access a website hosted in an S3 bucket, which uses API Gateway calls to send requests to Lambda backends to store the DynamoDB data.
- You can get started with creating your first serverless web application in AWS, by taking advantage of the DynamoDB free tier, that can handle up to 200 million requests for free. == As part of the AWS Free Tier, DynamoDB customers get 25GB of storage, 25 writes per second, and 25 reads per second. This lets you handle up to 200 million requests per month so you can deploy a proof-of-concept and begin testing the live cloud service. The DynamoDB free tier does not expire at the end of your 12 month AWS Free Tier term. http://aws.amazon.com/free