United States Region Pricing

Services

You can use AWS AppSync to build native mobile and web apps with iOS, Android, JavaScript and React Native. Get started by going to the AWS AppSync console, specify the data for your app with simple code statements, and AWS AppSync will manage everything needed to store, process, and retrieve the data for your application. (June, 2018) Retrieved from: https://aws.amazon.com/appsync/.

AWSApplicationMigrationSvc

With AWS CloudTrail, simplify your compliance audits by automatically recording and storing activity logs for actions made within your AWS account. Integration with Amazon CloudWatch Logs provides a convenient way to search through log data, identify out-of-compliance events, accelerate incident investigations, and expedite responses to auditor requests.

With AWS CloudTrail, you can discover and troubleshoot security and operational issues by capturing a comprehensive history of changes that occurred in your AWS account within a specified period of time. (June, 2017) Retrieved from: https://aws.amazon.com/cloudtrail/.

AWS Code Artifact - Secure, scalable, and cost-effective artifact management for software development

Development teams often rely on both open-source software packages and those packages built within their organization. IT leaders need to be able to control access to and validate the safety of these software packages. Teams need a way to find up-to-date packages that have been approved for use by their IT leaders. To address these challenges, IT leaders turn to central artifact repository services to store and share packages. However, existing solutions often require teams to purchase licenses for software solutions that are complex to setup, scale, and operate.

AWS CodeArtifact is a pay-as-you go artifact repository service that scales based on the needs of the organization. With CodeArtifact there is no software to update or servers to manage. In just a few clicks, IT leaders can set-up central repositories that make it easy for development teams to find and use the software packages they need. IT leaders can also approve packages and control distribution across the organization, ensuring development teams consume software packages that are safe for use. (June, 2020) Retrieved from: https://aws.amazon.com/codeartifact/.

AWS CodeDeploy - Automated Software Deployment

Once subscribed to a data product, you can use the AWS Data Exchange API to load data directly into Amazon S3 and then analyze it with a wide variety of AWS analytics and machine learning services. For example, property insurers can subscribe to data to analyze historical weather patterns to calibrate insurance coverage requirements in different geographies; restaurants can subscribe to population and location data to identify optimal regions for expansion; academic researchers can conduct studies on climate change by subscribing to data on carbon dioxide emissions; and healthcare professionals can subscribe to aggregated data from historical clinical trials to accelerate their research activities.

For data providers, AWS Data Exchange makes it easy to reach the millions of AWS customers migrating to the cloud by removing the need to build and maintain infrastructure for data storage, delivery, billing, and entitling.

Click here to browse the more than 1,000 data products now available from more than 80 qualified data providers in AWS Marketplace. Qualified data providers include category-leading and up-and-coming brands such as Reuters, Foursquare, TransUnion, Change Healthcare, Virtusa, Pitney Bowes, TP ICAP, Vortexa, IMDb, Epsilon, Enigma, TruFactor, ADP, Dun & Bradstreet, Compagnie Financière Tradition, Verisk, Crux Informatics, TSX Inc., Acxiom, Rearc, and many more. (June, 2020) Retrieved from: https://aws.amazon.com/data-exchange/.

AWS DataSync - Easily transfer data to and from AWS

Test these new found skills in either a single-car time-trial format or dual-car head-to-head racing in the AWS DeepRacer 3D racing simulator. Experiment with multiple sensor inputs, the latest reinforcement learning algorithms, neural network configurations and simulation to-real domain transfer methods.

The AWS DeepRacer League provides an opportunity for you to compete for prizes and meet fellow machine learning enthusiasts, online and in person. Share ideas and insights on how to succeed and create your own private virtual race. (June, 2020) Retrieved from: https://aws.amazon.com/deepracer/.

AWS Device Farm - Mobile App Testing Service

AWS Direct Connect lets you establish a dedicated network connection between your network and one of the AWS Direct Connect locations. Using industry standard 802.1q VLANs, this dedicated connection can be partitioned into multiple virtual interfaces. This allows you to use the same connection to access public resources such as objects stored in Amazon S3 using public IP address space, and private resources such as Amazon EC2 instances running within an Amazon Virtual Private Cloud (VPC) using private IP space, while maintaining network separation between the public and private environments. Virtual interfaces can be reconfigured at any time to meet your changing needs. (June, 2017) Retrieved from: https://aws.amazon.com/directconnect/.

AWS Directory Service

AWS Glue generates code that is customizable, reusable, and portable. Once your ETL job is ready, you can schedule it to run on AWS Glue's fully managed, scale-out Apache Spark environment. AWS Glue provides a flexible scheduler with dependency resolution, job monitoring, and alerting.

AWS Glue is serverless, so there is no infrastructure to buy, set up, or manage. It automatically provisions the environment needed to complete the job, and customers pay only for the compute resources consumed while running ETL jobs. With AWS Glue, data can be available for analytics in minutes. (June, 2018) Retrieved from: https://aws.amazon.com/glue/.

AWS Glue - Fully Managed Extract, Transform, and Load (ETL) Service

AWS Glue generates code that is customizable, reusable, and portable. Once your ETL job is ready, you can schedule it to run on AWS Glue's fully managed, scale-out Apache Spark environment. AWS Glue provides a flexible scheduler with dependency resolution, job monitoring, and alerting.

AWS Glue is serverless, so there is no infrastructure to buy, set up, or manage. It automatically provisions the environment needed to complete the job, and customers pay only for the compute resources consumed while running ETL jobs. With AWS Glue, data can be available for analytics in minutes. (June, 2018) Retrieved from: https://aws.amazon.com/glue/.

AWS Greengrass - Embedded Lambda Compute for Connected Devices

AWS Greengrass seamlessly extends AWS to devices so they can act locally on the data they generate, while still using the cloud for management, analytics, and durable storage. With Greengrass, you can use familiar languages and programming models to create and test your device software in the cloud, and then deploy it to your devices. AWS Greengrass can be programmed to filter device data and only transmit necessary information back to the cloud. AWS Greengrass authenticates and encrypts device data at all points of connection using AWS IoT’s security and access management capabilities. This way data is never exchanged between devices when they communicate with each other and the cloud without proven identity. (June, 2017) Retrieved from: https://aws.amazon.com/greengrass/.

AWS Ground Station - Easily control satellites and ingest data with fully managed Ground Station as a Service

IoT data is highly unstructured which makes it difficult to analyze with traditional analytics and business intelligence tools that are designed to process structured data. IoT data comes from devices that often record fairly noisy processes (such as temperature, motion, or sound). The data from these devices can frequently have significant gaps, corrupted messages, and false readings that must be cleaned up before analysis can occur. Also, IoT data is often only meaningful in the context of additional, third party data inputs. For example, to help farmers determine when to water their crops, vineyard irrigation systems often enrich moisture sensor data with rainfall data from the vineyard, allowing for more efficient water usage while maximizing harvest yield.

AWS IoT Analytics automates each of the difficult steps that are required to analyze data from IoT devices. AWS IoT Analytics filters, transforms, and enriches IoT data before storing it in a time-series data store for analysis. You can setup the service to collect only the data you need from your devices, apply mathematical transforms to process the data, and enrich the data with device-specific metadata such as device type and location before storing the processed data. Then, you can analyze your data by running ad hoc or scheduled queries using the built-in SQL query engine, or perform more complex analytics and machine learning inference. AWS IoT Analytics makes it easy to get started with machine learning by including pre-built models for common IoT use cases.

You can also use your own custom analysis, packaged in a container, to execute on AWS IoT Analytics. AWS IoT Analytics automates the execution of your custom analyses created in Jupyter Notebook or your own tools (such as Matlab, Octave, etc.) to be executed on your schedule.

AWS IoT Analytics is a fully managed service that operationalizes analyses and scales automatically to support up to petabytes of IoT data. With AWS IoT Analytics, you can analyze data from millions of devices and build fast, responsive IoT applications without managing hardware or infrastructure. (June, 2020) Retrieved from: https://aws.amazon.com/iot-analytics/.

AWS IoT Events - Easily detect and respond to events from IoT sensors and applications

Today, getting performance metrics from industrial equipment is challenging because data is often locked into proprietary on-premises data stores and typically requires specialized expertise to retrieve and place in a format that is useful for analysis. AWS IoT SiteWise simplifies this process by providing software running on a gateway that resides in your facilities and automates the process of collecting and organizing industrial equipment data. This gateway securely connects to your on-premises data servers, collects data, and sends the data to the AWS Cloud. AWS IoT SiteWise also provides interfaces for collecting data from modern industrial applications through MQTT messages or APIs.

You can use AWS IoT SiteWise to model your physical assets, processes and facilities, quickly compute common industrial performance metrics, and create fully managed web applications to help analyze industrial equipment data, reduce costs and make faster decisions. With AWS IoT SiteWise, you can focus on understanding and optimizing your operations, rather than building costly in-house data collection and management applications. (June, 2020) Retrieved from: https://aws.amazon.com/iot-sitewise/.

AWS IoT Things Graph - Visually develop IoT applications

IoT applications are being built today using a variety of devices and web services to automate tasks for a wide range of use cases, such as smart homes, industrial automation, and energy management. Because there aren't any widely adopted standards, it's difficult today for developers to get devices from multiple manufacturers to connect to each other as well as with web services. This forces developers to write lots of code to wire together all of the devices and web services they need for their IoT application. AWS IoT Things Graph provides a visual drag-and-drop interface for connecting and coordinating interactions between devices and web services, so you can build IoT applications quickly. For example, in a commercial agriculture application, you can define interactions between humidity, temperature, and sprinkler sensors with weather data services in the cloud to automate watering. You represent devices and services using pre-built reusable components, called models, that hide low-level details, such as protocols and interfaces, and are easy to integrate to create sophisticated workflows.

You can get started with AWS IoT Things Graph using these pre-built models for popular device types, such as cameras, motion sensors, and switches, as well as web services such as Amazon Simple Storage Service (S3) or Amazon Rekognition, or create your own custom models. You can deploy and run your IoT applications to the AWS Cloud or AWS IoT Greengrass-enabled devices such as edge gateways and cable set-top boxes, in just a few clicks. AWS IoT Greengrass is software that provides local compute and secure cloud connectivity so devices can respond quickly to local events even without internet connectivity, and runs on a huge range of devices from a Raspberry Pi to a server-level appliance. (June, 2020) Retrieved from: https://aws.amazon.com/iot-things-graph/.

AWSLakeFormation

AWS Outposts offers you the same AWS hardware infrastructure, services, APIs, and tools to build and run your applications on premises and in the cloud for a truly consistent hybrid experience. AWS compute, storage, database, and other services run locally on Outposts, and you can access the full range of AWS services available in the Region to build, manage, and scale your on-premises applications using familiar AWS services and tools.

Outposts are connected to the nearest AWS Region to provide the same management and control plane services on premises for a truly consistent operational experience across your on-premises and cloud environments. Your Outposts infrastructure and AWS services are managed, monitored, and updated by AWS just like in the cloud. (June, 2020) Retrieved from: https://aws.amazon.com/outposts/.

Amazon SQS - Message Queuing Service

All AWS customers benefit from the automatic protections of AWS Shield Standard, at no additional charge. AWS Shield Standard defends against most common, frequently occurring network and transport layer DDoS attacks that target your web site or applications.

For higher levels of protection against attacks targeting your web applications running on Elastic Load Balancing (ELB), Amazon CloudFront, and Amazon Route 53 resources, you can subscribe to AWS Shield Advanced. In addition to the common network and transport layer protections that come with Standard, AWS Shield Advanced provides additional detection and mitigation against large and sophisticated DDoS attacks, near real-time visibility into attacks, and integration with AWS WAF, a web application firewall. AWS Shield Advanced also gives you access to the AWS DDoS Response Team (DRT) and protection against DDoS related spikes in your ELB, CloudFront or Route 53 charges.

AWS Shield Advanced is available globally on all Amazon CloudFront and Amazon Route 53 edge locations. You can protect your web applications hosted anywhere in the world by deploying Amazon CloudFront in front of your application. Your origin servers can be Amazon S3, Amazon EC2, Elastic Load Balancing, or a custom server outside of AWS. You can also enable AWS Shield Advanced directly on Elastic Load Balancing in the following AWS Regions - Northern Virginia, Oregon, Ireland, and Tokyo. (June, 2017) Retrieved from: https://aws.amazon.com/shield/.

AWS Storage Gateway - Hybrid Cloud Storage

Many machine learning applications require humans to review low confidence predictions to ensure the results are correct. For example, extracting information from scanned mortgage application forms can require human review in some cases due to low-quality scans or poor handwriting. But building human review systems can be time consuming and expensive because it involves implementing complex processes or “workflows”, writing custom software to manage review tasks and results, and in many cases, managing large groups of reviewers.

Amazon A2I makes it easy to build and manage human reviews for machine learning applications. Amazon A2I provides built-in human review workflows for common machine learning use cases, such as content moderation and text extraction from documents, which allows predictions from Amazon Rekognition and Amazon Textract to be reviewed easily. You can also create your own workflows for ML models built on Amazon SageMaker or any other tools. Using Amazon A2I, you can allow human reviewers to step in when a model is unable to make a high confidence prediction or to audit its predictions on an on-going basis. (June, 2020) Retrieved from: https://aws.amazon.com/augmented-ai/.

Amazon API Gateway - Fully Managed API Service

Athena is easy to use. Simply point to your data in Amazon S3, define the schema, and start querying using standard SQL. Most results are delivered within seconds. With Athena, there’s no need for complex ETL jobs to prepare your data for analysis. This makes it easy for anyone with SQL skills to quickly analyze large-scale datasets. (June, 2017) Retrieved from: https://aws.amazon.com/athena/.

Amazon Braket - Explore and experiment with quantum computing

Quantum computing has the potential to solve computational problems that are beyond the reach of classical computers by harnessing the laws of quantum mechanics to process information in new ways. This approach to computing could transform areas such as chemical engineering, material science, drug discovery, financial portfolio optimization, and machine learning. But defining those problems and programming quantum computers to solve them requires new skills, which are difficult to acquire without easy access to quantum computing hardware.

Amazon Braket overcomes these challenges so you can explore quantum computing. With Amazon Braket you can design and build your own quantum algorithms from scratch or choose from a set of pre-built algorithms. Once you have built your algorithm, Amazon Braket provides a choice of simulators to test, troubleshoot and run your algorithms. When you are ready, you can also run your algorithm on your choice of different quantum computers, including quantum annealers from D-Wave, and gate-based computers from Rigetti and IonQ. With Amazon Braket you can now evaluate the potential of quantum computing for your organization, and build expertise. (June, 2020) Retrieved from: https://aws.amazon.com/braket/.

Amazon Chime - Online Meetings

Business Calling is easy to set up, and administrators can assign Business Calling features to individual Chime users as needed. Customers can purchase new telephone numbers, or port their existing numbers from their telecommunications provider. (June, 2020) Retrieved from: https://aws.amazon.com/about-aws/whats-new/2019/03/introducing-amazon-chime-business-calling/.

Amazon Chime Call Me - Have Chime Call You

Amazon Cloud Directory automatically scales to hundreds of millions of objects and provides an extensible schema that can be shared with multiple applications. As a fully-managed service, Cloud Directory eliminates time-consuming and expensive administrative tasks, such as scaling infrastructure and managing servers. You simply define the schema, create a directory, and then populate your directory by making calls to the Cloud Directory API. (June, 2017) Retrieved from: https://aws.amazon.com/cloud-directory/.

Amazon CloudFront - Content Delivery Network (CDN)

AWS security services like Amazon GuardDuty, Amazon Macie, and AWS Security Hub as well as partner security products can be used to identify potential security issues, or findings. These services are really helpful in alerting you when something is wrong and pointing out where to go to fix it. But sometimes there might be a security finding where you need to dig a lot deeper and analyze more information to isolate the root cause and take action. Determining the root cause of security findings can be a complex process that often involves collecting and combining logs from many separate data sources, using extract, transform, and load (ETL) tools or custom scripting to organize the data, and then security analysts having to analyze the data and conduct lengthy investigations.

Amazon Detective simplifies this process by enabling your security teams to easily investigate and quickly get to the root cause of a finding. Amazon Detective can analyze trillions of events from multiple data sources such as Virtual Private Cloud (VPC) Flow Logs, AWS CloudTrail, and Amazon GuardDuty, and automatically creates a unified, interactive view of your resources, users, and the interactions between them over time. With this unified view, you can visualize all the details and context in one place to identify the underlying reasons for the findings, drill down into relevant historical activities, and quickly determine the root cause.

You can get started with Amazon Detective in just a few clicks in the AWS Console. There is no software to deploy, or data sources to enable and maintain. (June, 2020) Retrieved from: https://aws.amazon.com/detective/.

AmazonDevOpsGuru

With simple API calls, you can launch and stop Docker-enabled applications, query the complete state of your application, and access many familiar features such as IAM roles, security groups, load balancers, Amazon CloudWatch Events, AWS CloudFormation templates, and AWS CloudTrail logs. (June, 2018) Retrieved from: https://aws.amazon.com/ecs/.

Amazon EFS - Cloud File Storage

Based on the same technology used at Amazon.com, Amazon Forecast uses machine learning to combine time series data with additional variables to build forecasts. Amazon Forecast requires no machine learning experience to get started. You only need to provide historical data, plus any additional data that you believe may impact your forecasts. For example, the demand for a particular color of a shirt may change with the seasons and store location. This complex relationship is hard to determine on its own, but machine learning is ideally suited to recognize it. Once you provide your data, Amazon Forecast will automatically examine it, identify what is meaningful, and produce a forecasting model capable of making predictions that are up to 50% more accurate than looking at time series data alone.

Amazon Forecast is a fully managed service, so there are no servers to provision, and no machine learning models to build, train, or deploy. You pay only for what you use, and there are no minimum fees and no upfront commitments. (June, 2020) Retrieved from: https://aws.amazon.com/forecast/.

AmazonFraudDetector

Enabled with a few clicks in the AWS Management Console, Amazon GuardDuty can immediately begin analyzing billions of events across your AWS accounts for signs of risk. GuardDuty identifies suspected attackers through integrated threat intelligence feeds and uses machine learning to detect anomalies in account and workload activity. When a potential threat is detected, the service delivers a detailed security alert to the GuardDuty console and AWS CloudWatch Events. This makes alerts actionable and easy to integrate into existing event management and workflow systems. (June, 2018) Retrieved from: https://aws.amazon.com/guardduty/.

AmazonHealthLake

With Amazon Honeycode, customers can use a simple visual application builder to create highly interactive web and mobile applications backed by a powerful AWS-built database to perform tasks like tracking data over time and notifying users of changes, routing approvals, and facilitating interactive business processes. Using Amazon Honeycode, customers can create applications that range in complexity from a task-tracking application for a small team to a project management system that manages a complex workflow for multiple teams or departments.

Amazon Honeycode is available in beta. Customers can get started creating applications in minutes, build applications with up to 20 users for free, and only pay for the users and storage used for larger applications. (June, 2020) Retrieved from: https://aws.amazon.com/about-aws/whats-new/2020/06/announcing-amazon-honeycode/.

Amazon Inspector - Automated Security Assessment Service

Use natural language questions instead of just simple keywords to get the answers you’re looking for, whether that is a precise answer, an FAQ, or an entire document. Say goodbye to sifting through long lists of links and hoping one has the information you need.

Get rid of information silos. Kendra lets you easily add content from file systems, SharePoint, intranet sites, file sharing services, and more, into a centralized location so you can quickly search all of your information to find the best answer.

Your results get better over time search, because Kendra’s machine learning algorithms learn which results your users find most valuable. You also have the option to fine-tune results by manually adjusting the importance of certain data sources or document freshness. (June, 2020) Retrieved from: https://aws.amazon.com/kendra/.

Amazon Kinesis - Easily Collect, Process, and Analyze Real-time, Streaming Data

Amazon Neptune is highly available, with read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across Availability Zones. Neptune is secure, with support for encryption at rest and in transit. Neptune is fully-managed, so you no longer need to worry about database management tasks such as hardware provisioning, software patching, setup, configuration, or backups. (June, 2018) Retrieved from: https://aws.amazon.com/neptune/.

Amazon Personalize - Create personalized user experiences faster

Ledgers are typically used to record a history of economic and financial activity in an organization. Many organizations build applications with ledger-like functionality because they want to maintain an accurate history of their applications' data, for example, tracking the history of credits and debits in banking transactions, verifying the data lineage of an insurance claim, or tracing movement of an item in a supply chain network. Ledger applications are often implemented using custom audit tables or audit trails created in relational databases. However, building audit functionality with relational databases is time-consuming and prone to human error. It requires custom development, and since relational databases are not inherently immutable, any unintended changes to the data are hard to track and verify. Alternatively, blockchain frameworks, such as Hyperledger Fabric and Ethereum, can also be used as a ledger. However, this adds complexity as you need to set-up an entire blockchain network with multiple nodes, manage its infrastructure, and require the nodes to validate each transaction before it can be added to the ledger.

Amazon QLDB is a new class of database that eliminates the need to engage in the complex development effort of building your own ledger-like applications. With QLDB, your data’s change history is immutable – it cannot be altered or deleted – and using cryptography, you can easily verify that there have been no unintended modifications to your application’s data. QLDB uses an immutable transactional log, known as a journal, that tracks each application data change and maintains a complete and verifiable history of changes over time. QLDB is easy to use because it provides developers with a familiar SQL-like API, a flexible document data model, and full support for transactions. QLDB’s streaming capability provides a near real-time flow of your data stored within QLDB, allowing you to develop event-driven workflows, real-time analytics, and to replicate data to other AWS services to support advanced analytical processing. QLDB is also serverless, so it automatically scales to support the demands of your application. There are no servers to manage and no read or write limits to configure. With QLDB, you only pay for what you use. (June, 2020) Retrieved from: https://aws.amazon.com/qldb/.

Amazon QuickSight - Business Intelligence for Big Data

Rekognition’s API lets you easily build powerful visual search and discovery into your applications. With Amazon Rekognition, you only pay for the images you analyze and the face metadata you store. There are no minimum fees and there are no upfront commitments. (June, 2017) Retrieved from: https://aws.amazon.com/rekognition/.

Amazon Route 53 - Domain Name Service

If your app's steps take more than 500 milliseconds to complete, you need to track the state of processing, and you need to recover or retry if a task fails, Amazon SWF can help you.

Amazon SWF promotes a separation between the control flow of your background job's stepwise logic and the actual units of work that contain your unique business logic. This allows you to separately manage, maintain, and scale "state machinery" of your application from the core business logic that differentiates it. As your business requirements change, you can easily change application logic without having to worry about the underlying state machinery, task dispatch, and flow control.

Amazon SWF runs within Amazon’s high-availability data centers, so the state tracking and task processing engine is available whenever applications need them. Amazon SWF redundantly stores the tasks, reliably dispatches them to application components, tracks their progress, and keeps their latest state. (June, 2017) Retrieved from: https://aws.amazon.com/swf/.

Amazon SageMaker - Machine Learning Platform

Machine learning often feels a lot harder than it should be to most developers because the process to build and train models, and then deploy them into production is too complicated and too slow. First, you need to collect and prepare your training data to discover which elements of your data set are important. Then, you need to select which algorithm and framework you’ll use. After deciding on your approach, you need to teach the model how to make predictions by training, which requires a lot of compute. Then, you need to tune the model so it delivers the best possible predictions, which is often a tedious and manual effort. After you’ve developed a fully trained model, you need to integrate the model with your application and deploy this application on infrastructure that will scale. All of this takes a lot of specialized expertise, access to large amounts of compute and storage, and a lot of time to experiment and optimize every part of the process. In the end, it's not a surprise that the whole thing feels out of reach for most developers. (June, 2018) Retrieved from: https://aws.amazon.com/sagemaker/.

Amazon SimpleDB - Simple Database Service

AWS Step Functions is part of the AWS Serverless Platform, and makes it simple to orchestrate AWS Lambda functions for serverless applications. You can also use Step Functions for microservices orchestration using compute resources such as Amazon EC2 and Amazon ECS.

AWS Step Functions manages the operations and underlying infrastructure for you to help ensure your application is available at any scale. (June, 2017) Retrieved from: https://aws.amazon.com/step-functions/.

AWS Cost Explorer - Dive Deeper Into Cost and Usage Data

Amazon WAM allows you to build and curate a selection of desktop applications for your users and control access to those applications. You can build an application catalog of third party applications that you already own the license for, internally-developed custom applications, and applications purchased through the AWS Marketplace for Desktop Apps. Simple, pay as you go, user-based pricing ensures that you only pay for the applications that people use. (June, 2017) Retrieved from: https://aws.amazon.com/workspaces/applicationmanager/.

Amazon WorkDocs - OnDemand Enterprise Applications

Amazon EMR securely and reliably handles a broad set of big data use cases, including log analysis, web indexing, data transformations (ETL), machine learning, financial analysis, scientific simulation, and bioinformatics. (June, 2017) Retrieved from: https://aws.amazon.com/emr/.

Amazon Data Ingestion Disk

AWS Import/Export Disk supports data transfer into and out of Amazon S3 buckets in the US East (N. Virginia), US West (Oregon), US West (Northern California), EU (Ireland), and Asia Pacific (Singapore) Regions. The service also supports importing data into Amazon EBS snapshots in the same regions. In addition, AWS Import/Export supports importing data into Amazon Glacier in the US East (N. Virginia), US West (Oregon), US West (Northern California), and EU (Ireland) regions. (June, 2017) Retrieved from: https://aws.amazon.com/snowball/disk/.

Snowball Ingestion - Petabyte-scale Data Transport

With Snowball, you don’t need to write any code or purchase any hardware to transfer your data. Simply create a job in the AWS Management Console and a Snowball appliance will be automatically shipped to you*. Once it arrives, attach the appliance to your local network, download and run the Snowball client to establish a connection, and then use the client to select the file directories that you want to transfer to the appliance. The client will then encrypt and transfer the files to the appliance at high speed. Once the transfer is complete and the appliance is ready to be returned, the E Ink shipping label will automatically update and you can track the job status via Amazon Simple Notification Service (SNS), text messages, or directly in the Console. (June, 2017) Retrieved from: https://aws.amazon.com/snowball/.

AWS IoT Device Defender - Security management for IoT devices

With Snowball, you don’t need to write any code or purchase any hardware to transfer your data. Simply create a job in the AWS Management Console and a Snowball appliance will be automatically shipped to you*. Once it arrives, attach the appliance to your local network, download and run the Snowball client to establish a connection, and then use the client to select the file directories that you want to transfer to the appliance. The client will then encrypt and transfer the files to the appliance at high speed. Once the transfer is complete and the appliance is ready to be returned, the E Ink shipping label will automatically update and you can track the job status via Amazon Simple Notification Service (SNS), text messages, or directly in the Console. (June, 2017) Retrieved from: https://aws.amazon.com/snowball/.

VMwareCloudOnAWS