Amazon Cloud Practioner Flashcards

(68 cards)

1
Q

AWS Management Console

A

Access and manage Amazon Web Services through the AWS Management Console, a simple and intuitive
user interface. You can also use the AWS Console Mobile Application to quickly view resources on the go.

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2
Q

AWS Command Line Interface

A

The AWS Command Line Interface (CLI) is a unified tool to manage your AWS services. With just one tool
to download and configure, you can control multiple AWS services from the command line and automate
them through scripts.

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3
Q

Amazon Athena

A

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. Most results are delivered within seconds. With Athena, there’s no need for complex
extract, transform, and load (ETL) jobs to prepare your data for analysis. This makes it easy for anyone
with SQL skills to quickly analyze large-scale datasets.
Athena is out-of-the-box integrated with AWS Glue Data Catalog, allowing you to create a unified
metadata repository across various services, crawl data sources to discover schemas and populate your
Catalog with new and modified table and partition definitions, and maintain schema versioning.

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4
Q

Amazon CloudSearch

A

Amazon CloudSearch is a managed service in the AWS Cloud that makes it simple and cost-effective to set up, manage, and scale a search solution for your website or application.
Amazon CloudSearch supports 34 languages and popular search features such as highlighting, autocomplete, and geospatial search. For more information, see

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5
Q

Amazon Elasticsearch Service

A

makes it easy to deploy, secure, operate, and scale Elasticsearch to search,
analyze, and visualize data in real-time. With Amazon Elasticsearch Service, you get easy-to-use APIs
and real-time analytics capabilities to power use-cases such as log analytics, full-text search, application
monitoring, and clickstream analytics, with enterprise-grade availability, scalability, and security. The
service offers integrations with open-source tools like Kibana and Logstash for data ingestion and
visualization. It also integrates seamlessly with other AWS services such as Amazon Virtual Private Cloud
(Amazon VPC), AWS Key Management Service (AWS KMS), Amazon Kinesis Data Firehose, AWS Lambda,
AWS Identity and Access Management (IAM), Amazon Cognito, and Amazon CloudWatch, so that you can
go from raw data to actionable insights quickly.

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6
Q

Amazon EMR

A

Amazon EMR is the industry-leading cloud big data platform for processing vast amounts of data
using open source tools such as Apache Spark, Apache Hive, Apache HBase, Apache Flink, Apache Hudi,
and Presto. Amazon EMR makes it easy to set up, operate, and scale your big data environments by
automating time-consuming tasks like provisioning capacity and tuning clusters. With EMR you can
run petabyte-scale analysis at less than half of the cost of traditional on-premises solutions andover 3x
faster than standard Apache Spark. You can run workloads on Amazon EC2 instances, on Amazon Elastic
Kubernetes Service (EKS) clusters, or on-premises using EMR on AWS Outposts

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7
Q

Amazon FinSpace

A

is a data management and analytics service purpose-built for the financial services
industry (FSI). FinSpace reduces the time you spend finding and preparing petabytes of financial data to
be ready for analysis from months to minutes.
Financial services organizations analyze data from internal data stores like portfolio, actuarial, and
risk management systems as well as petabytes of data from third-party data feeds, such as historical
securities prices from stock exchanges. It can take months to find the right data, get permissions to
access the data in a compliant way, and prepare it for analysis.
FinSpace removes the heavy lifting of building and maintaining a data management system for financial
analytics. With FinSpace, you collect data and catalog it by relevant business concepts such as asset class,
risk classification, or geographic region. FinSpace makes it easy to discover and share data across your
organization in accordance with your compliance requirements. You define your data access policies in
one place and FinSpace enforces them while keeping audit logs to allow for compliance and activity
reporting. FinSpace also includes a library of 100+ functions, like time bars and Bollinger bands, for you
to prepare data for analysis.

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8
Q

Amazon Kinesis

A

makes it easy to collect, process, and analyze real-time, streaming data so you can get
timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to costeffectively process streaming data at any scale, along with the flexibility to choose the tools that best
suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such
as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning,
analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives
and respond instantly instead of having to wait until all your data is collected before the processing can
begin.
11

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9
Q

Amazon Kinesis Data Analytics

A

is the easiest way to analyze streaming data, gain actionable insights,
and respond to your business and customer needs in real time. Amazon Kinesis Data Analytics reduces
the complexity of building, managing, and integrating streaming applications with other AWS services.
SQL users can easily query streaming data or build entire streaming applications using templates and an
interactive SQL editor. Java developers can quickly build sophisticated streaming applications using open
source Java libraries and AWS integrations to transform and analyze data in real-time.
Amazon Kinesis Data Analytics takes care of everything required to run your queries continuously and
scales automatically to match the volume and throughput rate of your incoming data.

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10
Q

Amazon Kinesis Video Streams

A

Amazon Kinesis Video Streams makes it easy to securely stream video from connected devices to AWS
for analytics, machine learning (ML), playback, and other processing. Kinesis Video Streams automatically
provisions and elastically scales all the infrastructure needed to ingest streaming video data from
millions of devices. It also durably stores, encrypts, and indexes video data in your streams, and allows
you to access your data through easy-to-use APIs. Kinesis Video Streams enables you to playback
video for live and on-demand viewing, and quickly build applications that take advantage of computer
vision and video analytics through integration with Amazon Rekognition Video, and libraries for ML
frameworks such as Apache MxNet, TensorFlow, and OpenCV.

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11
Q

Amazon Redshift

A

is the most widely used cloud data warehouse. It makes it fast, simple and costeffective to analyze all your data using standard SQL and your existing Business Intelligence (BI) tools.

It allows you to run complex analytic queries against terabytes to petabytes of structured and semistructured data, using sophisticated query optimization, columnar storage on high-performance storage,
and massively parallel query execution. Most results come back in seconds. You can start small for just
$0.25 per hour with no commitments and scale out to petabytes of data for $1,000 per terabyte per
year, less than a tenth the cost of traditional on-premises solutions.

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12
Q

Amazon QuickSight

A

is a fast, cloud-powered business intelligence (BI) service that makes it easy for you
to deliver insights to everyone in your organization. QuickSight lets you create and publish interactive
dashboards that can be accessed from browsers or mobile devices. You can embed dashboards into your
applications, providing your customers with powerful self-service analytics. QuickSight easily scales to
tens of thousands of users without any software to install, servers to deploy, or infrastructure to manage

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13
Q

AWS Data Exchange

A

AWS Data Exchange makes it easy to find, subscribe to, and use third-party data in the cloud. Qualified
data providers include category-leading brands such as Reuters, who curate data from over 2.2 million
unique news stories per year in multiple languages; Change Healthcare, who process and anonymize
more than 14 billion healthcare transactions and $1 trillion in claims annually; Dun & Bradstreet, who
maintain a database of more than 330 million global business records; and Foursquare, whose location
data is derived from 220 million unique consumers and includes more than 60 million global commercial
venues.
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.

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14
Q

AWS Data Pipeline

A

is a web service that helps you reliably process and move data between different
AWS compute and storage services, as well as on-premises data sources, at specified intervals. With AWS
Data Pipeline, you can regularly access your data where it’s stored, transform and process it at scale, and
efficiently transfer the results to AWS services such as Amazon S3 (p. 74), Amazon RDS (p. 28),
Amazon DynamoDB (p. 26), and Amazon EMR (p. 11).
AWS Data Pipeline helps you easily create complex data processing workloads that are fault tolerant,
repeatable, and highly available. You don’t have to worry about ensuring resource availability, managing
inter-task dependencies, retrying transient failures or timeouts in individual tasks, or creating a failure
notification system. AWS Data Pipeline also allows you to move and process data that was previously
locked up in on-premises data silos.

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15
Q

AWS Glue

A

AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning, and application development. AWS Glue provides all the capabilities needed for data integration so that you can start analyzing your data and putting it to use in minutes instead of months.

Data integration is the process of preparing and combining data for analytics, machine learning, and application development. It involves multiple tasks, such as discovering and extracting data from various sources; enriching, cleaning, normalizing, and combining data; and loading and organizing data in databases, data warehouses, and data lakes. These tasks are often handled by different types of users that each use different products.

AWS Glue provides both visual and code-based interfaces to make data integration easier. Users can easily find and access data using the AWS Glue Data Catalog. Data engineers and ETL (extract, transform, and load) developers can visually create, run, and monitor ETL workflows with a few clicks in AWS Glue Studio. Data analysts and data scientists can use AWS Glue DataBrew to visually enrich, clean, and normalize data without writing code. With AWS Glue Elastic Views, application developers can use familiar Structured Query Language (SQL) to combine and replicate data across different data stores.

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16
Q

AWS Lake Formation

A

is a service that makes it easy to set up a secure data lake in days. A data lake is
a centralized, curated, and secured repository that stores all your data, both in its original form and
prepared for analysis. A data lake enables you to break down data silos and combine different types of
analytics to gain insights and guide better business decisions.
However, setting up and managing data lakes today involves a lot of manual, complicated, and timeconsuming tasks. This work includes loading data from diverse sources, monitoring those data flows,
setting up partitions, turning on encryption and managing keys, defining transformation jobs and
monitoring their operation, re-organizing data into a columnar format, configuring access control
settings, deduplicating redundant data, matching linked records, granting access to data sets, and
auditing access over time.
Creating a data lake with Lake Formation is as simple as defining where your data resides and what data
access and security policies you want to apply. Lake Formation then collects and catalogs data from
databases and object storage, moves the data into your new Amazon S3 data lake, cleans and classifies
data using machine learning algorithms, and secures access to your sensitive data. Your users can then
access a centralized catalog of data which describes available data sets and their appropriate usage. Your
users then leverage these data sets with their choice of analytics and machine learning services, like
Amazon EMR for Apache Spark, Amazon Redshift, Amazon Athena, SageMaker, and Amazon QuickSight.

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17
Q

Amazon Managed Streaming for Apache Kafka

Amazon MSK

A

Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that makes
it easy for you to build and run applications that use Apache Kafka to process streaming data. Apache
Kafka is an open-source platform for building real-time streaming data pipelines and applications.
With Amazon MSK, you can use Apache Kafka APIs to populate data lakes, stream changes to and from
databases, and power machine learning and analytics applications.
Apache Kafka clusters are challenging to setup, scale, and manage in production. When you run Apache
Kafka on your own, you need to provision servers, configure Apache Kafka manually, replace servers
when they fail, orchestrate server patches and upgrades, architect the cluster for high availability, ensure
data is durably stored and secured, setup monitoring and alarms, and carefully plan scaling events to
support load changes. Amazon MSK makes it easy for you to build and run production applications on
Apache Kafka without needing Apache Kafka infrastructure management expertise. That means you
spend less time managing infrastructure and more time building applications.
With a few clicks in the Amazon MSK console you can create highly available Apache Kafka clusters
with settings and configuration based on Apache Kafka’s deployment best practices. Amazon MSK
automatically provisions and runs your Apache Kafka clusters. Amazon MSK continuously monitors
cluster health and automatically replaces unhealthy nodes with no downtime to your application. In
addition, Amazon MSK secures your Apache Kafka cluster by encrypting data at rest.

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18
Q

AWS Step Functions

A

s is a fully managed service that makes it easy to coordinate the components of
distributed applications and microservices using visual workflows. Building applications from individual
components that each perform a discrete function lets you scale easily and change applications quickly.
Step Functions is a reliable way to coordinate components and step through the functions of your
application. Step Functions provides a graphical console to arrange and visualize the components of
your application as a series of steps. This makes it simple to build and run multi-step applications.
Step Functions automatically triggers and tracks each step, and retries when there are errors, so your
application runs in order and as expected. Step Functions logs the state of each step, so when things do
go wrong, you can diagnose and debug problems quickly. You can change and add steps without even
writing code, so you can easily evolve your application and innovate faster.

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19
Q

Amazon AppFlow

A

is a fully managed integration service that enables you to securely transfer data
between Software-as-a-Service (SaaS) applications like Salesforce, Zendesk, Slack, and ServiceNow, and
AWS services like Amazon S3 and Amazon Redshift, in just a few clicks. With Amazon AppFlow, you can
run data flows at enterprise scale at the frequency you choose - on a schedule, in response to a business
event, or on demand. You can configure data transformation capabilities like filtering and validation to
generate rich, ready-to-use data as part of the flow itself, without additional steps. Amazon AppFlow
automatically encrypts data in motion, and allows users to restrict data from flowing over the public
Internet for SaaS applications that are integrated with AWS PrivateLink, reducing exposure to security
threats.

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20
Q

Amazon EventBridge

A

is a serverless event bus that makes it easier to build event-driven applications
at scale using events generated from your applications, integrated Software-as-a-Service (SaaS)
applications, and AWS services. EventBridge delivers a stream of real-time data from event sources such
as Zendesk or Shopify to targets like AWS Lambda and other SaaS applications. You can set up routing
rules to determine where to send your data to build application architectures that react in real-time to
your data sources with event publisher and consumer completely decoupled.

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21
Q

Amazon Managed Workflows for Apache Airflow

MWAA

A

Amazon Managed Workflows for Apache Airflow (MWAA) is a managed orchestration service for Apache Airflow1 that makes it easier to set up and operate end-to-end data pipelines in the cloud at scale. Apache Airflow is an open-source tool used to programmatically author, schedule, and monitor sequences of processes and tasks referred to as “workflows.” With Managed Workflows, you can use Airflow and Python to create workflows without having to manage the underlying infrastructure for scalability, availability, and security. Managed Workflows automatically scales its workflow execution capacity to meet your needs, and is integrated with AWS security services to help provide you with fast and secure access to data.

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22
Q

Amazon MQ

A

is a managed message broker service for Apache ActiveMQ and RabbitMQ that makes it
easy to set up and operate message brokers in the cloud. Message brokers allow different software
systems–often using different programming languages, and on different platforms–to communicate
and exchange information. Amazon MQ reduces your operational load by managing the provisioning,
setup, and maintenance of ActiveMQ and RabbitMQ, popular open-source message brokers. Connecting
your current applications to Amazon MQ is easy because it uses industry-standard APIs and protocols for
messaging, including JMS, NMS, AMQP, STOMP, MQTT, and WebSocket. Using standards means that in
most cases, there’s no need to rewrite any messaging code when you migrate to AWS.

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23
Q

Amazon Simple Notification Service

A

is a highly available, durable, secure, fully managed
pub/sub messaging service that enables you to decouple microservices, distributed systems, and
serverless applications. Amazon SNS provides topics for high-throughput, push-based, many-to-many
messaging. Using Amazon SNS topics, your publisher systems can fan out messages to a large number of
subscriber endpoints for parallel processing, including Amazon SQS queues, AWS Lambda functions, and
HTTP/S webhooks. Additionally, SNS can be used to fan out notifications to end users using mobile push,
SMS, and email.

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24
Q

Amazon Simple Queue Service

A

is a fully managed message queuing service that enables
you to decouple and scale microservices, distributed systems, and serverless applications. SQS eliminates
the complexity and overhead associated with managing and operating message oriented middleware,
and empowers developers to focus on differentiating work. Using SQS, you can send, store, and receive
messages between software components at any volume, without losing messages or requiring other
services to be available. Get started with SQS in minutes using the AWS console, Command Line
Interface or SDK of your choice, and three simple commands.
SQS offers two types of message queues. Standard queues offer maximum throughput, best-effort
ordering, and at-least-once delivery. SQS FIFO queues are designed to guarantee that messages are
processed exactly once, in the exact order that they are sent

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25
Amazon Simple Workflow Service
helps developers build, run, and scale background jobs that have parallel or sequential steps. You can think of Amazon SWF as a fully-managed state tracker and task coordinator in the cloud. If your application’s steps take more than 500 milliseconds to complete, you need to track the state of processing. If you need to recover or retry if a task fails, Amazon SWF can help you.
26
Amazon Sumerian
lets you create and run virtual reality (VR), augmented reality (AR), and 3D applications quickly and easily without requiring any specialized programming or 3D graphics expertise. With Sumerian, you can build highly immersive and interactive scenes that run on popular hardware such as Oculus Go, Oculus Rift, HTC Vive, HTC Vive Pro, Google Daydream, and Lenovo Mirage as well as Android and iOS mobile devices. For example, you can build a virtual classroom that lets you train new employees around the world, or you can build a virtual environment that enables people to tour a building remotely. Sumerian makes it easy to create all the building blocks needed to build highly immersive and interactive 3D experiences including adding objects (e.g. characters, furniture, and landscape), and designing, animating, and scripting environments. Sumerian does not require specialized expertise and you can design scenes directly from your browse
27
Amazon Managed Blockchain
s a fully managed service that makes it easy to create and manage scalable blockchain networks using the popular open source frameworks Hyperledger Fabric and Ethereum. Blockchain makes it possible to build applications where multiple parties can execute transactions without the need for a trusted, central authority. Today, building a scalable blockchain network with existing technologies is complex to set up and hard to manage. To create a blockchain network, each network member needs to manually provision hardware, install software, create and manage certificates for access control, and configure networking components. Once the blockchain network is running, you need to continuously monitor the infrastructure and adapt to changes, such as an increase in transaction requests, or new members joining or leaving the network. Amazon Managed Blockchain is a fully managed service that allows you to set up and manage a scalable blockchain network with just a few clicks. Amazon Managed Blockchain eliminates the overhead required to create the network, and automatically scales to meet the demands of thousands of applications running millions of transactions. Once your network is up and running, Managed Blockchain makes it easy to manage and maintain your blockchain network. It manages your certificates, lets you easily invite new members to join the network, and tracks operational metrics such as usage of compute, memory, and storage resources. In addition, Managed Blockchain can replicate an immutable copy of your blockchain network activity into Amazon Quantum Ledger Database (QLDB), a fully managed ledger database. This allows you to easily analyze the network activity outside the network and gain insights into trends
28
Alexa for Business (business applications)
is a service that enables organizations and employees to use Alexa to get more work done. With Alexa for Business, employees can use Alexa as their intelligent assistant to be more productive in meeting rooms, at their desks, and even with the Alexa devices they already have at hom
29
Amazon Chime ( business application)
is a communications service that transforms online meetings with a secure, easy-to-use application that you can trust. Amazon Chime works seamlessly across your devices so that you can stay connected. You can use Amazon Chime for online meetings, video conferencing, calls, chat, and to share content, both inside and outside your organization. Amazon Chime works with Alexa for Business, which means you can use Alexa to start your meetings with your voice. Alexa can start your video meetings in large conference rooms, and automatically dial into online meetings in smaller huddle rooms and from your desk.
30
Amazon SES(business application)
is a cost-effective, flexible, and scalable email service that enables developers to send mail from within any application. You can configure Amazon SES quickly to support several email use cases, including transactional, marketing, or mass email communications. Amazon SES's flexible IP deployment and email authentication options help drive higher deliverability and protect sender reputation, while sending analytics measure the impact of each email. With Amazon SES, you can send email securely, globally, and at scale.
31
Amazon WorkDocs (business application)
is a fully managed, secure enterprise storage and sharing service with strong administrative controls and feedback capabilities that improve user productivity. Users can comment on files, send them to others for feedback, and upload new versions without having to resort to emailing multiple versions of their files as attachments. Users can take advantage of these capabilities wherever they are, using the device of their choice, including PCs, Macs, tablets, and phones. Amazon WorkDocs offers IT administrators the option of integrating with existing corporate directories, flexible sharing policies and control of the location where data is stored. You can get started using Amazon WorkDocs with a 30-day free trial providing 1 TB of storage per user for up to 50 users.
32
Amazon WorkMail(business application)
is a secure, managed business email and calendar service with support for existing desktop and mobile email client applications. Amazon WorkMail gives users the ability to seamlessly access their email, contacts, and calendars using the client application of their choice, including Microsoft Outlook, native iOS and Android email applications, any client application supporting the IMAP protocol, or directly through a web browser. You can integrate Amazon WorkMail with your existing corporate directory, use email journaling to meet compliance requirements, and control both the keys that encrypt your data and the location in which your data is stored. You can also set up interoperability with Microsoft Exchange Server, and programmatically manage users, groups, and resources using the Amazon WorkMail SDK
33
AWS Application Cost Profiler
provides you the ability to track the consumption of shared AWS resources used by software applications and report granular cost breakdown across tenant base. You can achieve economies of scale with the shared infrastructure model, while still maintaining a clear line of sight to detailed resource consumption information across multiple dimensions. With the proportionate cost insights of shared AWS resources, organizations running applications can establish the data foundation for accurate cost allocation model, and ISV selling applications can better understand your profitability and customize pricing strategies for your end customers.
34
AWS Cost Explorer
has an easy-to-use interface that lets you visualize, understand, and manage your AWS costs and usage over time. Get started quickly by creating custom reports (including charts and tabular data) that analyze cost and usage data, both at a high level (e.g., total costs and usage across all accounts) and for highly-specific requests (e.g., m2.2xlarge costs within account Y that are tagged “project: secretProject”).
35
AWS Budgets
gives you the ability to set custom budgets that alert you when your costs or usage exceed (or are forecasted to exceed) your budgeted amount. You can also use AWS Budgets to set RI utilization or coverage targets and receive alerts when your utilization drops below the threshold you define. RI alerts support Amazon EC2, Amazon RDS, Amazon Redshift, and Amazon ElastiCache reservations. Budgets can be tracked at the monthly, quarterly, or yearly level, and you can customize the start and end dates. You can further refine your budget to track costs associated with multiple dimensions, such as AWS service, linked account, tag, and others. Budget alerts can be sent via email and/or Amazon Simple Notification Service (SNS) topic. Budgets can be created and tracked from the AWS Budgets dashboard or via the Budgets API.
36
AWS Cost & Usage Report
is a single location for accessing comprehensive information about your AWS costs and usage. The AWS Cost & Usage Report lists AWS usage for each service category used by an account and its IAM users in hourly or daily line items, as well as any tags that you have activated for cost allocation purposes. You can also customize the AWS Cost & Usage Report to aggregate your usage data to the daily or monthly level
37
Reserved Instance (RI) Reporting
AWS provides a number of RI-specific cost management solutions out-of-the-box to help you better understand and manage your RIs. Using the RI Utilization and Coverage reports available in AWS Cost Explorer, you can visualize your RI data at an aggregate level or inspect a particular RI subscription. To access the most detailed RI information available, you can leverage the AWS Cost & Usage Report. You can also set a custom RI utilization target via AWS Budgets and receive alerts when your utilization drops below the threshold you define
38
Savings Plans
is a flexible pricing model offering lower prices compared to On-Demand pricing, in exchange for a specific usage commitment (measured in $/hour) for a one or three-year period. AWS offers three types of Savings Plans – Compute Savings Plans, EC2 Instance Savings Plans, and Amazon SageMaker Savings Plans. Compute Savings Plans apply to usage across Amazon EC2, AWS Lambda, and AWS Fargate. The EC2 Instance Savings Plans apply to EC2 usage, and Amazon SageMaker Savings Plans apply to Amazon SageMaker usage. You can easily sign up a 1- or 3-year term Savings Plans in AWS Cost Explorer and manage your plans by taking advantage of recommendations, performance reporting, and budget alerts.
39
Amazon EC2 (Compute Services)
is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale computing easier for developers. The simple web interface of Amazon EC2 allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 reduces the time required to obtain and boot new server instances (called Amazon EC2 instances) to minutes, allowing you to quickly scale capacity, both up and down, as your computing requirements change. Amazon EC2 changes the economics of computing by allowing you to pay only for capacity that you actually use. Amazon EC2 provides developers and system administrators the tools to build failure resilient applications and isolate themselves from common failure scenarios.
40
Amazon EC2 Instance Types (Compute Services)
• On-Demand Instances— With On-Demand instances, you pay for compute capacity by the hour or the second depending on which instances you run. No longer-term commitments or upfront payments are needed. You can increase or decrease your compute capacity depending on the demands of your application and only pay the specified per hourly rates for the instance you use. On-Demand instances are recommended for: • Users that prefer the low cost and flexibility of Amazon EC2 without any up-front payment or longterm commitment • Applications with short-term, spiky, or unpredictable workloads that cannot be interrupted • Applications being developed or tested on Amazon EC2 for the first time • Spot Instances—Spot Instances are available at up to a 90% discount compared to On-Demand prices and let you take advantage of unused Amazon EC2 capacity in the AWS Cloud. You can significantly reduce the cost of running your applications, grow your application’s compute capacity and throughput for the same budget, and enable new types of cloud computing applications. Spot instances are recommended for: • Applications that have flexible start and end times • Applications that are only feasible at very low compute prices • Users with urgent computing needs for large amounts of additional capacity • Reserved Instances—Reserved Instances provide you with a significant discount (up to 72%) compared to On-Demand instance pricing. You have the flexibility to change families, operating system types, and tenancies while benefitting from Reserved Instance pricing when you use Convertible Reserved Instances. • Savings Plans—Savings Plans are a flexible pricing model that offer low prices on EC2 and Fargate usage, in exchange for a commitment to a consistent amount of usage (measured in $/hour) for a 1 or 3 year term. • Dedicated Hosts—A Dedicated Host is a physical EC2 server dedicated for your use. Dedicated Hosts can help you reduce costs by allowing you to use your existing server-bound software licenses, including Windows Server, SQL Server, and SUSE Linux Enterprise Server (subject to your license terms), and can also help you meet compliance requirements.
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Amazon EC2 Auto Scaling(Compute Services)
helps you maintain application availability and allows you to automatically add or remove EC2 instances according to conditions you define. You can use the fleet management features of Amazon EC2 Auto Scaling to maintain the health and availability of your fleet. You can also use the dynamic and predictive scaling features of Amazon EC2 Auto Scaling to add or remove EC2 instances. Dynamic scaling responds to changing demand and predictive scaling automatically schedules the right number of EC2 instances based on predicted demand. Dynamic scaling and predictive scaling can be used together to scale faster.
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Amazon EC2 Image Builder(Compute Services)
simplifies the building, testing, and deployment of Virtual Machine and container images for use on AWS or on-premises. Keeping Virtual Machine and container images up-to-date can be time consuming, resource intensive, and error-prone. Currently, customers either manually update and snapshot VMs or have teams that build automation scripts to maintain image Image Builder significantly reduces the effort of keeping images up-to-date and secure by providing a simple graphical interface, built-in automation, and AWS-provided security settings. With Image Builder, there are no manual steps for updating an image nor do you have to build your own automation pipeline. Image Builder is offered at no cost, other than the cost of the underlying AWS resources used to create, store, and share the images.
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Amazon Lightsail(Compute Services)
is designed to be the easiest way to launch and manage a virtual private server with AWS. Lightsail plans include everything you need to jumpstart your project – a virtual machine, SSDbased storage, data transfer, DNS management, and a static IP address – for a low, predictable price.
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AWS App Runner(Compute Services)
is a fully managed service that makes it easy for developers to quickly deploy containerized web applications and APIs, at scale and with no prior infrastructure experience required. Start with your source code or a container image. App Runner automatically builds and deploys the web application and load balances traffic with encryption. App Runner also scales up or down automatically to meet your traffic needs. With App Runner, rather than thinking about servers or scaling, you have more time to focus on your applications.
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AWS Batch(Compute Services)
enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory-optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters that you use to run your jobs, allowing you to focus on analyzing results and solving problems. AWS Batch plans, schedules, and runs your batch computing workloads across the full range of AWS compute services and features, such as Amazon EC2 and Spot Instances.
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AWS Elastic Beanstalk(Compute Services)
is an easy-to-use service for deploying and scaling web applications and services developed with Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker on familiar servers such as Apache, Nginx, Passenger, and Internet Information Services (IIS). You can simply upload your code, and AWS Elastic Beanstalk automatically handles the deployment, from capacity provisioning, load balancing, and auto scaling to application health monitoring. At the same time, you retain full control over the AWS resources powering your application and can access the underlying resources at any time.
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AWS Fargate(compute Services)
is a compute engine for Amazon ECS that allows you to run containers without having to manage servers or clusters. With AWS Fargate, you no longer have to provision, configure, and scale clusters of virtual machines to run containers. This removes the need to choose server types, decide when to scale your clusters, or optimize cluster packing. AWS Fargate removes the need for you to interact with or think about servers or clusters. Fargate lets you focus on designing and building your applications instead of managing the infrastructure that runs them. Amazon ECS has two modes: Fargate launch type and EC2 launch type. With Fargate launch type, all you have to do is package your application in containers, specify the CPU and memory requirements, define networking and IAM policies, and launch the application. EC2 launch type allows you to have server-level, more granular control over the infrastructure that runs your container applications. With EC2 launch type, you can use Amazon ECS to manage a cluster of servers and schedule placement of containers on the servers. Amazon ECS keeps track of all the CPU, memory and other resources in your cluster, and also finds the best server for a container to run on based on your specified resource requirements. You are responsible for provisioning, patching, and scaling clusters of servers. You can decide which type of server to use, which applications and how many containers to run in a cluster to optimize utilization, and when you should add or remove servers from a cluster. EC2 launch type gives you more control of your server clusters and provides a broader range of customization options, which might be required to support some specific applications or possible compliance and government requirements.
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AWS Lambda (Compute Services)
lets you run code without provisioning or managing servers. You pay only for the compute time you consume—there is no charge when your code is not running. With Lambda, you can run code for virtually any type of application or backend service—all with zero administration. 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 you can call it directly from any web or mobile app
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AWS Serverless Application Repository (Compute Services)
The AWS Serverless Application Repository enables you to quickly deploy code samples, components, and complete applications for common use cases such as web and mobile back-ends, event and data processing, logging, monitoring, IoT, and more. Each application is packaged with an AWS Serverless Application Model (SAM) template that defines the AWS resources used. Publicly shared applications also include a link to the application’s source code. There is no additional charge to use the Serverless Application Repository - you only pay for the AWS resources used in the applications you deploy. You can also use the Serverless Application Repository to publish your own applications and share them within your team, across your organization, or with the community at large. To share an application you've built, publish it to the AWS Serverless Application Repository.
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AWS Outposts (Compute Services)
bring native AWS services, infrastructure, and operating models to virtually any data center, co-location space, or on-premises facility. You can use the same APIs, the same tools, the same hardware, and the same functionality across on-premises and the cloud to deliver a truly consistent hybrid experience. Outposts can be used to support workloads that need to remain on-premises due to low latency or local data processing needs. AWS Outposts come in two variants: 1) VMware Cloud on AWS Outposts allows you to use the same VMware control plane and APIs you use to run your infrastructure, 2) AWS native variant of AWS Outposts allows you to use the same exact APIs and control plane you use to run in the AWS cloud, but on-premises. AWS Outposts infrastructure is fully managed, maintained, and supported by AWS to deliver access to the latest AWS services. Getting started is easy, you simply log into the AWS Management Console to order your Outposts servers, choosing from a wide range of compute and storage options. You can order one or more servers, or quarter, half, and full rack units.
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AWS Wavelength (Compute Services)
is an AWS Infrastructure offering optimized for mobile edge computing applications. Wavelength Zones are AWS infrastructure deployments that embed AWS compute and storage services within communications service providers’ (CSP) datacenters at the edge of the 5G network, so application traffic from 5G devices can reach application servers running in Wavelength Zones without leaving the telecommunications network. This avoids the latency that would result from application traffic having to traverse multiple hops across the Internet to reach their destination, enabling customers to take full advantage of the latency and bandwidth benefits offered by modern 5G networks.
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VMware Cloud on AWS (Compute Services)
is an integrated cloud offering jointly developed by AWS and VMware delivering a highly scalable, secure and innovative service that allows organizations to seamlessly migrate and extend their on-premises VMware vSphere-based environments to the AWS Cloud running on next-generation Amazon Elastic Compute Cloud (Amazon EC2) bare metal infrastructure. VMware Cloud on AWS is ideal for enterprise IT infrastructure and operations organizations looking to migrate their on-premises vSphere-based workloads to the public cloud, consolidate and extend their data center capacities, and optimize, simplify and modernize their disaster recovery solutions. VMware Cloud on AWS is delivered, sold, and supported globally by VMware and its partners with availability in the following AWS Regions: AWS Europe (Stockholm), AWS US East (Northern Virginia), AWS US East (Ohio), AWS US West (Northern California), AWS US West (Oregon), AWS Canada (Central), AWS Europe (Frankfurt), AWS Europe (Ireland), AWS Europe (London), AWS Europe (Paris), AWS Europe (Milan), AWS Asia Pacific (Singapore), AWS Asia Pacific (Sydney), AWS Asia Pacific (Tokyo), AWS Asia Pacific (Mumbai) Region, AWS South America (Sao Paulo), AWS Asia Pacific (Seoul), and AWS GovCloud (US West). With each release, VMware Cloud on AWS availability will expand into additional global regions. VMware Cloud on AWS brings the broad, diverse and rich innovations of AWS services natively to the enterprise applications running on VMware's compute, storage and network virtualization platforms. This allows organizations to easily and rapidly add new innovations to their enterprise applications by natively integrating AWS infrastructure and platform capabilities such as AWS Lambda, Amazon Simple Queue Service (SQS), Amazon S3, Elastic Load Balancing, Amazon RDS, Amazon DynamoDB, Amazon Kinesis, and Amazon Redshift, among many others. With VMware Cloud on AWS, organizations can simplify their Hybrid IT operations by using the same VMware Cloud Foundation technologies including vSphere, vSAN, NSX, and vCenter Server across their on-premises data centers and on the AWS Cloud without having to purchase any new or custom hardware, rewrite applications, or modify their operating models. The service automatically provisions infrastructure and provides full VM compatibility and workload portability between your on-premises environments and the AWS Cloud. With VMware Cloud on AWS, you can leverage AWS's breadth of services, including compute, databases, analytics, Internet of Things (IoT), security, mobile, deployment, application services, and more
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Amazon Connect (Conact Center)
is a self-service, omnichannel cloud contact center service that makes it easy for any business to deliver better customer service at lower cost. Amazon Connect is based on the same contact center technology used by Amazon customer service associates around the world to power millions of customer conversations. The self-service graphical interface in Amazon Connect makes it easy for nontechnical users to design contact flows, manage agents, and track performance metrics – no specialized skills required. There are no up-front payments or long-term commitments and no infrastructure to manage with Amazon Connect; customers pay by the minute for Amazon Connect usage plus any associated telephony services.
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Amazon Elastic Container Registry(Containers)
is a fully-managed Docker container registry that makes it easy for developers to store, manage, and deploy Docker container images. Amazon ECR is integrated with Amazon Elastic Container Service (Amazon ECS), simplifying your development to production workflow. Amazon ECR eliminates the need to operate your own container repositories or worry about scaling the underlying infrastructure. Amazon ECR hosts your images in a highly available and scalable architecture, allowing you to reliably deploy containers for your applications. Integration with AWS Identity and Access Management (IAM) (p. 69) provides resource-level control of each repository. With Amazon ECR, there are no upfront fees or commitments. You pay only for the amount of data you store in your repositories and data transferred to the Internet
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Amazon Elastic Container Service/ECS(Containers)
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. 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.
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Amazon Elastic Kubernetes Service(containers)
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. Amazon EKS is certified Kubernetes conformant so you can use existing tooling and plugins from partners and the Kubernetes community. Applications running on any standard Kubernetes environment are fully compatible and can be easily migrated to Amazon EKS.
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AWS App2Container(Containers)
is a command-line tool for modernizing .NET and Java applications into containerized applications. A2C analyzes and builds an inventory of all applications running in virtual machines, on-premises or in the cloud. You simply select the application you want to containerize, and A2C packages the application artifact and identified dependencies into container images, configures the network ports, and generates the ECS task and Kubernetes pod definitions. A2C provisions, through CloudFormation, the cloud infrastructure and CI/CD pipelines required to deploy the containerized .NET or Java application into production. With A2C, you can easily modernize your existing applications and standardize the deployment and operations through containers.
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Red Hat OpenShift Service on AWS(Containers)
provides an integrated experience to use OpenShift. If you are already familiar with OpenShift, you can accelerate your application development process by leveraging familiar OpenShift APIs and tools for deployments on AWS. With ROSA, you can use the wide range of AWS compute, database, analytics, machine learning, networking, mobile, and other services to build secure and scalable applications faster. ROSA comes with pay-as-you-go hourly and annual billing, a 99.95% SLA, and joint support from AWS and Red Hat. ROSA makes it easier for you to focus on deploying applications and accelerating innovation by moving the cluster lifecycle management to Red Hat and AWS. With ROSA, you can run containerized applications with your existing OpenShift workflows and reduce the complexity of management.
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Amazon Aurora(Database)
is a MySQL and PostgreSQL compatible relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora is up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases. It provides the security, availability, and reliability of commercial databases at 1/10th the cost. Amazon Aurora is fully managed by Amazon Relational Database Service (Amazon RDS), which automates time-consuming administration tasks like hardware provisioning, database setup, patching, and backups. Amazon Aurora features a distributed, fault-tolerant, self-healing storage system that auto-scales up to 128TB per database instance. It delivers high performance and availability with up to 15 low-latency read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across three Availability Zones (AZs).
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Amazon DynamoDB(Database)
is a key-value and document database that delivers single-digit millisecond performance at any scale. It's a fully managed, multiregion, multimaster database with built-in security, backup and restore, and in-memory caching for internet-scale applications. DynamoDB can handle more than 10 trillion requests per day and support peaks of more than 20 million requests per second. Many of the world's fastest growing businesses such as Lyft, Airbnb, and Redfin as well as enterprises such as Samsung, Toyota, and Capital One depend on the scale and performance of DynamoDB to support their mission-critical workloads. Hundreds of thousands of AWS customers have chosen DynamoDB as their key-value and document database for mobile, web, gaming, ad tech, IoT, and other applications that need low-latency data access at any scale. Create a new table for your application and let DynamoDB handle the rest
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Amazon ElastiCache(Database)
is a web service that makes it easy to deploy, operate, and scale an in-memory cache in the cloud. The service improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases. Amazon ElastiCache supports two open-source in-memory caching engines: • Redis - a fast, open-source, in-memory key-value data store for use as a database, cache, message broker, and queue. Amazon ElastiCache for Redis is a Redis-compatible in-memory service that delivers the ease-of-use and power of Redis along with the availability, reliability, and performance suitable for the most demanding applications. Both single-node and up to 15-shard clusters are available, enabling scalability to up to 3.55 TiB of in-memory data. ElastiCache for Redis is fully managed, scalable, and secure. This makes it an ideal candidate to power high-performance use cases such as web, mobile apps, gaming, ad-tech, and IoT. • Memcached - a widely adopted memory object caching system. ElastiCache for Memcached is protocol compliant with Memcached, so popular tools that you use today with existing Memcached environments will work seamlessly with the service.
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Amazon Keyspaces (for Apache Cassandra)(Database)
is a scalable, highly available, and managed Apache Cassandra–compatible database service. With Amazon Keyspaces, you can run your Cassandra workloads on AWS using the same Cassandra application code and developer tools that you use today. You don’t have to provision, patch, or manage servers, and you don’t have to install, maintain, or operate software. Amazon Keyspaces is serverless, so you pay for only the resources you use and the service can automatically scale tables up and down in response to application traffic. You can build applications that serve thousands of requests per second with virtually unlimited throughput and storage. Data is encrypted by default and Amazon Keyspaces enables you to back up your table data continuously using point-in-time recovery. Amazon Keyspaces gives you the performance, elasticity, and enterprise features you need to operate business-critical Cassandra workloads at scale.
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Amazon Neptune(Database)
is a fast, reliable, fully-managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purposebuilt, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. 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. 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.
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Amazon Relational Database Service(Database)
makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while automating timeconsuming administration tasks such as hardware provisioning, database setup, patching and backups. It frees you to focus on your applications so you can give them the fast performance, high availability, security and compatibility they need. Amazon RDS is available on several database instance types - optimized for memory, performance or I/O - and provides you with six familiar database engines to choose from, including Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle Database, and SQL Server. You can use the AWS Database Migration Service to easily migrate or replicate your existing databases to Amazon RDS.
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Amazon RDS on VMware(Database)
on VMware lets you deploy managed databases in on-premises VMware environments using the Amazon RDS technology enjoyed by hundreds of thousands of AWS customers. Amazon RDS provides cost-efficient and resizable capacity while automating time-consuming administration tasks including hardware provisioning, database setup, patching, and backups, freeing you to focus on your applications. RDS on VMware brings these same benefits to your on-premises deployments, making it easy to set up, operate, and scale databases in VMware vSphere private data centers, or to migrate them to AWS. Amazon RDS on VMware allows you to utilize the same simple interface for managing databases in on-premises VMware environments as you would use in AWS. You can easily replicate RDS on VMware databases to RDS instances in AWS, enabling low-cost hybrid deployments for disaster recovery, read replica bursting, and optional long-term backup retention in Amazon Simple Storage Service (Amazon S3)
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Amazon Quantum Ledger Database (QLDB)(Database)
is a fully managed ledger database that provides a transparent, immutable, and cryptographically verifiable transaction log owned by a central trusted authority. Amazon QLDB tracks each and every application data change and maintains a complete and verifiable history of changes over time. 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 timeconsuming 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 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.
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Amazon Timestream(Database)
is a fast, scalable, fully managed time series database service for IoT and operational applications that makes it easy to store and analyze trillions of events per day at 1/10th the cost of relational databases. Driven by the rise of IoT devices, IT systems, and smart industrial machines, time-series data — data that measures how things change over time — is one of the fastest growing data types. Time-series data has specific characteristics such as typically arriving in time order form, data is append-only, and queries are always over a time interval. While relational databases can store this data, they are inefficient at processing this data as they lack optimizations such as storing and retrieving data by time intervals. Timestream is a purpose-built time series database that efficiently stores and processes this data by time intervals. With Timestream, you can easily store and analyze log data for DevOps, sensor data for IoT applications, and industrial telemetry data for equipment maintenance. As your data grows over time, Timestream’s adaptive query processing engine understands its location and format, making your data simpler and faster to analyze. Timestream also automates rollups, retention, tiering, and compression of data, so you can manage your data at the lowest possible cost. Timestream is serverless, so there are no servers to manage. It manages time-consuming tasks such as server provisioning, software patching, setup, configuration, or data retention and tiering, freeing you to focus on building your applications.
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Amazon DocumentDB (with MongoDB compatibility)(Database)
is a fast, scalable, highly available, and fully managed document database service that supports MongoDB workloads. Amazon DocumentDB (with MongoDB compatibility) is designed from the ground-up to give you the performance, scalability, and availability you need when operating mission-critical MongoDB workloads at scale. Amazon DocumentDB (with MongoDB compatibility) implements the Apache 2.0 open source MongoDB 3.6 and 4.0 APIs by emulating the responses that a MongoDB client expects from a MongoDB server, allowing you to use your existing MongoDB drivers and tools with Amazon DocumentDB (with MongoDB compatibility