Cloud & Native Cloud for Managers
- 1. AWS for managers Eitan Sela - System Architect, Weissbeerger
- 2. $whoami • "Hands-On" system Architect with more than 17 years of experience with billing, banking, information security (DLP) and Cloud IoT/Big Data applications. • Big Data specialist – Hadoop, Spark, Hive and EMR on AWS. • Work with vast AWS services, and with serverless projects especially. • Java development, scalability performance and stabilization expert. • Chatbots and Alexa skills developer (Are you also interested? Go to www.israelclouds.com to read my articles). • Love to share my experience in lectures and meetups. • Part of AWS-IL user group leadership team (5684 members!). LinkedIn profile
- 3. What to expect from this session • Cloud Computing with Amazon Web Services. • AWS Cloud Solutions. • Using AWS basic building blocks. • Containers in AWS. • Big Data and the Data lake implementation in AWS. • Machine Learning and AI in AWS. • AWS Security & Compliance. • Pricing - How does AWS pricing work?
- 4. Cloud Computing with Amazon Web Services
- 5. Explaining on-prem, IaaS, PaaS, and SaaS with Bacon
- 8. Why are organizations using the Cloud?
- 9. Why does agility matter?
- 10. What is AWS
- 17. Gartner’s Infrastructure as a Service (IaaS) Magic Quadrant 2017 • AWS Named as a Leader in Gartner’s Infrastructure as a Service (IaaS) Magic Quadrant for 7th Consecutive Year.
- 18. Six Advantages of Cloud Computing
- 19. Trade capital expense for variable expense • Instead of having to invest heavily in data centers and servers before you know how you’re going to use them, you can pay only when you consume computing resources, and pay only for how much you consume.
- 20. Benefit from massive economies of scale • By using cloud computing, you can achieve a lower variable cost than you can get on your own. • Because usage from hundreds of thousands of customers is aggregated in the cloud, providers such as AWS can achieve higher economies of scale, which translates into lower pay as-you-go prices.
- 21. Stop guessing about capacity • When you make a capacity decision prior to deploying an application, you often end up either sitting on expensive idle resources or dealing with limited capacity. • With cloud computing, these problems go away. You can access as much or as little capacity as you need, and scale up and down as required with only a few minutes’ notice.
- 22. Increase speed and agility • In a cloud computing environment, new IT resources are only a click away, which means that you reduce the time to make those resources available to your developers from weeks to just minutes. • This results in a dramatic increase in agility for the organization, since the cost and time it takes to experiment and develop is significantly lower.
- 23. Stop spending money running and maintaining data centers • Focus on projects that differentiate your business, not the infrastructure. • Cloud computing lets you focus on your own customers, rather than on the heavy lifting of racking, stacking, and powering servers.
- 24. Go global in minutes • Easily deploy your application in multiple regions around the world with just a few clicks. • This means you can provide lower latency and a better experience for your customers at minimal cost.
- 26. AWS Regions and Availability Zones • The AWS Cloud infrastructure is built around Regions and Availability Zones (AZs). • AWS Regions provide multiple, physically separated and isolated Availability Zones which are connected with low latency, high throughput, and highly redundant networking. • Availability Zones are physically separated within a typical metropolitan region and are located in lower risk flood plains.
- 27. Availability Zones - Benefits • Availability Zones offer AWS customers an easier and more effective way to design and operate applications and databases, making them: – Highly available – Fault tolerant – Scalable
- 28. Region & Number of Availability Zones
- 30. Solutions by Application • The AWS platform handles demanding requirements for virtually any application.
- 31. Example - Data Lakes
- 34. Solutions by Application • Amazon Web Services offers a broad set of global cloud-based products including compute, storage, databases, analytics, networking, mobile, developer tools, management tools, IoT, security and enterprise applications.
- 35. Solutions by Application – con’t
- 36. Using AWS basic building blocks
- 37. Amazon EC2
- 38. Amazon S3 • Object storage built to store and retrieve any amount of data from anywhere.
- 39. AWS Lambda – Serverless Compute • Run code without thinking about servers. Pay only for the compute time you consume. • Just upload your code and Lambda takes care of everything required to run and scale your code with high availability. • You can set up your code to automatically trigger from other AWS services or call it directly from any web or mobile app.
- 40. Amazon Web Services Cloud Platform
- 41. AWS Cloud Platform • AWS consists of many cloud services that you can use in combinations tailored to your business or organizational needs. • To access the services, you can use the AWS Management Console, the Command Line Interface, or Software Development Kits (SDKs).
- 42. Upload to S3 - AWS Management Console
- 43. Upload to S3 - Command Line Interface
- 44. Upload to S3 - SDK
- 45. Containers in AWS - Amazon Elastic Container Service, Fargate, and EKS
- 46. Amazon EC2 Container Service • Amazon Elastic Container Service (Amazon ECS) is a highly scalable, high-performance container orchestration service that supports Docker containers and allows you to easily run and scale containerized applications on AWS. • Amazon ECS eliminates the need for you to install and operate your own container orchestration software, manage and scale a cluster of virtual machines, or schedule containers on those virtual machines.
- 47. When to use Amazon ECS
- 48. Amazon Elastic Container Registry • Amazon Elastic Container Registry (Amazon ECR) is a managed AWS Docker registry service that is secure, scalable, and reliable. • Amazon ECR supports private Docker repositories with resource-based permissions using AWS IAM so that specific users or Amazon EC2 instances can access repositories and images. • Developers can use the Docker CLI to push, pull, and manage images.
- 49. Amazon ECS Clusters • An Amazon ECS cluster is a logical grouping of tasks or services. • If you are running tasks or services that use the EC2 launch type, a cluster is also a grouping of container instances. • When you first use Amazon ECS, a default cluster is created for you, but you can create multiple clusters in an account to keep your resources separate.
- 50. Amazon ECS Task Definitions • A task definition is required to run Docker containers in Amazon ECS. Some of the parameters you can specify in a task definition include: – The Docker images to use with the containers in your task – How much CPU and memory to use with each container – The launch type to use, which determines the infrastructure on which your tasks are hosted – Whether containers are linked together in a task – The Docker networking mode to use for the containers in your task – (Optional) The ports from the container to map to the host container instance – Whether the task should continue to run if the container finishes or fails – The command the container should run when it is started – (Optional) The environment variables that should be passed to the container when it starts – Any data volumes that should be used with the containers in the task – (Optional) The IAM role that your tasks should use for permissions
- 51. Services • Amazon ECS allows you to run and maintain a specified number of instances of a task definition simultaneously in an Amazon ECS cluster. • This is called a service. • If any of your tasks should fail or stop for any reason, the Amazon ECS service scheduler launches another instance of your task definition to replace it and maintain the desired count of tasks in the service.
- 52. AWS Fargate - Run containers without managing servers or clusters • With AWS Fargate, you no longer have to provision, configure, and scale clusters of virtual machines to run containers. • With AWS Fargate, you no longer have to provision, configure, and scale clusters of virtual machines to run containers. • Fargate lets you focus on designing and building your applications instead of managing the infrastructure that runs them.
- 53. AWS Fargate – How it work
- 54. AWS Fargate – use the console to create task
- 55. Amazon Elastic Container Service for Kubernetes • Amazon Elastic Container Service for Kubernetes (Amazon EKS) makes it easy to deploy, manage, and scale containerized applications using Kubernetes on AWS. • Amazon EKS runs the Kubernetes management infrastructure for you across multiple AWS availability zones to eliminate a single point of failure. • Applications running on any standard Kubernetes environment are fully compatible and can be easily migrated to Amazon EKS.
- 56. EKS - How it work
- 57. Big Data in AWS - Amazon EMR, Athena, Kinesis and data lakes
- 58. Amazon EMR • Easily Run and Scale Apache Hadoop, Spark, HBase, Presto, Hive, and other Big Data Frameworks. • Amazon EMR provides a managed Hadoop framework that makes it easy, fast, and cost-effective to process vast amounts of data across dynamically scalable Amazon EC2 instances.
- 59. What can you build with Amazon EMR?
- 60. Create an EMR cluster in few minutes
- 61. Amazon Athena - Serverless Interactive Query Service • Start querying data instantly. Get results in seconds. Pay only for the queries you run. • Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. • Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. • Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL.
- 62. Amazon Athena - Features • Start Querying Instantly - Serverless. No ETL. • Pay Per Query - Only pay for data scanned. • Open. Powerful. Standard - Built on Presto. Runs standard SQL (supports CSV, JSON, ORC, Avro, and Parquet). • Fast. Really Fast - Interactive performance even for large datasets. You don't have to worry about having enough compute resources to get fast, interactive query performance.
- 63. Amazon Athena – AWS Management Console
- 64. Amazon Kinesis • Easily collect, process, and analyze video and data streams in real time. • Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information.
- 66. Amazon Kinesis Data Streams
- 67. Amazon Kinesis Data Firehose
- 68. What is a data lake? • A centralized repository that allows you to store all your structured and unstructured data at any scale.
- 69. Building a Data Lake on AWS
- 70. Machine Learning in AWS - Amazon Lex, Rekognition and SageMaker
- 71. Amazon Lex • Conversational interfaces for your applications. • Powered by the same deep learning technologies as Alexa. • Amazon Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU): – To recognize the intent of the text. – To enable you to build applications with highly engaging user experiences and lifelike conversational interactions.
- 72. Amazon Lex - Benefits
- 73. Amazon Lex – Use cases - Call Center Bots
- 74. Amazon Rekognition – Video and Image • Amazon Rekognition makes it easy to add image and video analysis to your applications. • You just provide an image or video to the Rekognition API, and the service can identify the: – Objects – People – Text – Scenes – Activities – Any inappropriate content. • Amazon Rekognition also provides highly accurate facial analysis and facial recognition on images and video that you provide.
- 75. Amazon Rekognition – Key features
- 76. Amazon Rekognition – Key features – con’t
- 77. Amazon Rekognition – Key features – con’t
- 78. Rekognition Image Use Cases
- 79. Amazon SageMaker • Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. • Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.
- 80. Amazon SageMaker – How it works
- 81. Amazon SageMaker – Benefits
- 82. Amazon SageMaker – Use cases
- 83. Amazon Alexa • Amazon Alexa is a virtual assistant developed by Amazon, first used in the Amazon Echo and the Amazon Echo Dot smart speakers developed by Amazon Lab126. • It is capable of voice interaction, music playback, making to-do lists, setting alarms, streaming podcasts, playing audiobooks, and providing weather, traffic, sports, and other real-time information, such as news.
- 84. Alexa Has Skills
- 85. Start building for voice today
- 86. Security and Compliance in AWS
- 87. Benefits of AWS Security
- 88. Security, Identity, and Compliance Products
- 89. Security, Identity, and Compliance Products – con’t
- 90. AWS Identity and Access Management (IAM( • AWS Identity and Access Management (IAM( enables you to manage access to AWS services and resources securely. • Using IAM, you can create and manage AWS users and groups, and use permissions to allow and deny their access to AWS resources. • AM is a feature of your AWS account offered at no additional charge. You will be charged only for use of other AWS services by your users.
- 91. Use Cases
- 92. AWS - Pricing & Billing
- 93. How do you pay for AWS?
- 94. Simple Monthly Calculator • Whether you are running a single instance or dozens of individual services, you can estimate your monthly bill using AWS Simple Monthly Calculator. The calculator allows you to estimate individual or multiple prices and use templates to appraise complete solutions.
- 95. Simple Monthly Calculator – EC2 example
- 96. Amazon EC2 Pricing – On-Demand
- 97. Amazon EC2 Pricing – Spot Instances d
- 98. Amazon EC2 Pricing – Reserved Instances d
- 99. Q & A
- 100. We are hiring! • Senior Data Scientist • Senior Designer (UI/UX( • Senior Full Stack Developer • Java Developer • Senior Manual QA • Director of Ops • BI Analyst • Data Management Analyst • Customer Success Manager • Senior BI Analyst