There are three types of cloud storage: object, file, and block. Each storage option has a unique combination of performance, durability, cost, and interface.
Block storage – Enterprise applications like databases or enterprise resource planning (ERP) systems often require dedicated, low-latency storage for each host. This is similar to direct-attached storage (DAS) or a Storage Area Network (SAN). Block-based cloud storage solutions like Amazon Elastic Block Store (Amazon EBS) are provisioned with each virtual server and offer the ultra-low latency required for high-performance workloads.
File storage – Many applications must access shared files and require a file system. This type of storage is often supported with a Network Attached Storage (NAS) server. File storage solutions like Amazon Elastic File System (Amazon EFS) are ideal for use cases such as large content repositories, development environments, media stores, or user home directories.
Object storage – Applications developed in the cloud need the vast scalability and metadata of object storage. Object storage solutions like Amazon Simple Storage Service (Amazon S3) are ideal for building modern applications. Amazon S3 provides scale and flexibility. You can use it to import existing data stores for analytics, backup, or archive.
AWS provides you with services for your block, file and object storage needs. Select each hotspot in the image to see what services are available for you to explore to build solutions.
Amazon S3 use cases
Backup and restore.
Data Lake for analytics.
Media storage
Static website.
Archiving
Buckets and objects
Amazon S3 stores data as objects within buckets. An object is composed of a file and any metadata that describes that file. The diagram below contains a URL comprised of a bucket and an object key. The object key is the unique identifier of an object in a bucket. The combination of a bucket, key, and version ID uniquely identifies each object. The object is uniquely addressed through the combination of the web service endpoint, bucket name, key, and optionally, a version.
To store an object in Amazon S3, upload the file into a bucket. When you upload a file, you can set permissions on the object and add metadata. You can have one or more buckets in your account. For each bucket, you control who can create, delete, and list objects in the bucket.
Amazon S3 access control
By default, all Amazon S3 resources—buckets, objects, and related resources (for example, lifecycle configuration and website configuration)—are private. Only the resource owner, an AWS account that created it, can access the resource. The resource owner can grant access permissions to others by writing access policies.
AWS provides several different tools to help developers configure buckets for a wide variety of workloads.
Most Amazon S3 use cases do not require public access.
Amazon S3 usually stores data from other applications. Public access is not recommended for these types of buckets.
Amazon S3 includes a block public access feature. This acts as an additional layer of protection to prevent accidental exposure of customer data.
Amazon S3 Event Notifications
Amazon S3 event notifications enable you to receive notifications when certain object events happen in your bucket. Here is an example of an event notification workflow to convert images to thumbnails. To learn more, select each of the three hotspots in the diagram below.
Amazon S3 cost factors and best practices
Cost is an important part of choosing the right Amazon S3 storage solution. Some of the Amazon S3 cost factors to consider include the following:
Storage – Per-gigabyte cost to hold your objects. You pay for storing objects in your S3 buckets. The rate you’re charged depends on your objects’ size, how long you stored the objects during the month, and the storage class. There are per-request ingest charges when using PUT, COPY, or lifecycle rules to move data into any S3 storage class.
Requests and retrievals – The number of API calls: PUT and GET requests. You pay for requests made against your S3 buckets and objects. S3 request costs are based on the request type, and are charged on the quantity of requests. When you use the Amazon S3 console to browse your storage, you incur charges for GET, LIST, and other requests that are made to facilitate browsing.
Data transfer – Usually no transfer fee for data-in from the internet and, depending on the requestor location and medium of data transfer, different charges for data-out.
Management and analytics – You pay for the storage management features and analytics that are enabled on your account’s buckets. These features are not discussed in detail in this course.
S3 Replication and S3 Versioning can have a big impact on your AWS bill. These services both create multiple copies of your objects and you pay for each PUT request in addition to the storage tier charge. S3 Cross-Region Replication also requires data transfer between AWS Regions.
Shared file systems
Using a fully managed cloud shared file system solution removes complexities, reduces costs, and simplifies management. To learn more about shared file systems, select each hotspot in the image below.
Amazon Elastic File System (EFS)
Amazon EFS provides a scalable, elastic file system for Linux-based workloads for use with AWS Cloud services and on-premises resources.
You’re able to access your file system across Availability Zones, AWS Regions, and VPCs while sharing files between thousands of EC2 instances and on-premises servers through AWS Direct Connect or AWS VPN.
You can create a file system, mount the file system on an Amazon EC2 instance, and then read and write data to and from your file system.
Amazon EFS provides a shared, persistent layer that allows stateful applications to elastically scale up and down. Examples include DevOps, web serving, web content systems, media processing, machine learning, analytics, search index, and stateful microservices applications. Amazon EFS can support a petabyte-scale file system, and the throughput of the file system also scales with the capacity of the file system.
Because Amazon EFS is serverless, you don’t need to provision or manage the infrastructure or capacity. Amazon EFS file systems can be shared with up to tens of thousands of concurrent clients, no matter the type. These could be traditional EC2 instances, containers running in one of your self-managed clusters or in one of the AWS container services, Amazon ECS, Amazon EKS, and Fargate, or in a serverless function running in Lambda.
Use Amazon EFS to lower your total cost of ownership for shared file storage. Choose Amazon EFS One Zone for data that does not require replication across multiple Availability Zones and save on storage costs. Amazon EFS Standard-Infrequent Access (EFS Standard-IA) and Amazon EFS One Zone-Infrequent Access (EFS One Zone-IA) are storage classes that provide price/performance that is cost-optimized for files not accessed every day.
Use Amazon EFS scaling and automation to save on management costs, and pay only for what you use.
Amazon FSx
With Amazon FSx, you can quickly launch and run feature-rich and high-performing file systems. The service provides you with four file systems to choose from. This choice is based on your familiarity with a given file system or by matching the feature sets, performance profiles, and data management capabilities to your needs.
Amazon FSx for Windows File Server
FSx for Windows File Server provides fully managed Microsoft Windows file servers that are backed by a native Windows file system. Built on Windows Server, Amazon FSx delivers a wide range of administrative features such as data deduplication, end-user file restore, and Microsoft Active Directory.
Amazon FSx for Lustre (FSx for Lustre)
FSx for Lustre is a fully managed service that provides high-performance, cost-effective storage. FSx for Lustre is compatible with the most popular Linux-based AMIs, including Amazon Linux, Amazon Linux 2, Red Hat Enterprise Linux (RHEL), CentOS, SUSE Linux, and Ubuntu.
Amazon FSx for NETapp ONTAP
FSx for NETapp ONTAP provides fully managed shared storage in the AWS Cloud with the popular data access and management capabilities of ONTAP.
Amazon FSx for OpenZFS
Where the road leads, I will go. Along the stark desert, across the wide plains, into the deep forests I will follow the call of the world and embrace its ferocious beauty.
AWS edge computing services provide infrastructure and software that move data processing and analysis as close to the endpoint as necessary. This includes deploying AWS managed hardware and software to locations outside AWS data centers, and even onto customer-owned devices.
You can extend the cloud for a consistent hybrid experience using these AWS edge services related to locations:
AWS edge locations – Edge locations are connected to the AWS Regions through the AWS network backbone. Amazon CloudFront, AWS WAF, and AWS Shield are services you use here.
AWS Local Zones – Local Zones are an extension of the AWS Cloud located close to large population and industry centers. You learned about Local Zones in Module 1: Architecting Fundamentals.
AWS Outposts – With AWS Outposts, you can run some AWS services on premises or at your own data center.
AWS Snow Family – The Snow Family of products provides offline storage at the edge, which is used to deliver data back to AWS Regions.
Edge services architecture
Review the edge services architecture. A user sends a request to an application partly hosted on premises. The user’s request interacts with Amazon Route 53, AWS WAF, Amazon CloudFront and AWS Outposts. The AWS services hosted in the cloud are protected with AWS Shield.
Amazon Route 53
Amazon Route 53 provides a DNS, domain name registration, and health-checks. Route 53 was designed to give developers and businesses a reliable and cost-effective way to route end users to internet applications. It translates names like example.com into the numeric IP addresses that computers use to connect to each other.
Route 53 effectively connects user requests to infrastructure running in AWS—such as EC2 instances, ELB load balancers, or Amazon S3 buckets—and can also be used to route users to infrastructure outside of AWS.
You can configure a Amazon CloudWatch alarm to check on the state of your endpoints. Combine your DNS with Health Check Metrics to monitor and route traffic to healthy endpoints.
Amazon Route 53 public and private DNS
A hosted zone is a container for records. Records contain information about how you want to route traffic for a specific domain, such as example.com, and its subdomains such as dev.example.com or mail.example.com. A hosted zone and the corresponding domain have the same name.
PUBLIC HOSTED ZONE
Public hosted zones contain records that specify how you want to route traffic on the internet.
For internet name resolution
Delegation set – for authoritative name servers to be provided to the registrar or parent domain
Route to internet-facing resources
Resolve from the internet
Global routing policies
PRIVATE HOSTED ZONE
Private hosted zones contain records that specify how you want to route traffic in your Amazon VPC.
For name resolution inside a VPC
Can be associated with multiple VPCs and across accounts
Route to VPC resources
Resolve from inside the VPC
Integrate with on-premises private zones using forwarding rules and endpoints
Routing policies
When you create a record, you choose a routing policy, which determines how Amazon Route 53 responds to queries.
Failover routing
Amazon Route 53 health checks monitor the health and performance of your web applications, web servers, and other resources.
Each health check that you create can monitor one of the following:
The health of a specified resource, such as a web server
The status of other health checks
The status of an Amazon CloudWatch alarm
After you create a health check, you can get the status of the health check, get notifications when the status changes, and configure DNS failover.
Geolocation routing
Geolocation routing lets you choose the resources that serve your traffic based on the geographic location of your users, meaning the location that DNS queries originate from. For example, you might want all queries from Europe to be routed to an ELB load balancer in the Frankfurt Region.
Geoproximity routing
Geoproximity routing lets Amazon Route 53 route traffic to your resources based on the geographic location of your users and your resources. You can also optionally choose to route more traffic or less to a given resource by specifying a value, known as a bias. A bias expands or shrinks the size of the geographic Region from which traffic is routed to a resource.
Latency-based routing
If your application is hosted in multiple AWS Regions, you can improve performance for your users by serving their requests from the AWS Region that provides the lowest latency.
Data about the latency between users and your resources is based entirely on traffic between users and AWS data centers. If you aren’t using resources in an AWS Region, the actual latency between your users and your resources can vary significantly from AWS latency data. This is true even if your resources are located in the same city as an AWS Region.
Multivalue answer routing
Multivalue answer routing lets you configure Route 53 to return multiple values, such as IP addresses for your web servers, in response to DNS queries. You can specify multiple values for almost any record, but multivalue answer routing also lets you check the health of each resource. Route 53 returns only values for healthy resources.
The ability to return multiple health-checkable IP addresses is a way for you to use DNS to improve availability and load balancing. However, it is not a substitute for a load balancer.
Weighted routing
Weighted routing enables you to assign weights to a resource record set to specify the frequency with which different responses are served.
In this example of a blue/green deployment, a weighted routing policy is used to send a small amount of traffic to a new production environment. If the new environment is operating as intended, the amount of weighted traffic can be increased to confirm it can handle the increased load. If the test is successful, all traffic can be sent to the new environment.
Amazon CloudFront
Content delivery networks
It’s not always possible to replicate your entire infrastructure across the globe when your web traffic is geo-dispersed. It is also not cost effective. With a content delivery network (CDN), you can use its global network of edge locations to deliver a cached copy of your web content to your customers.
To reduce response time, the CDN uses the nearest edge location to the customer or the originating request location. Using the nearest edge location dramatically increases throughput because the web assets are delivered from cache. For dynamic data, you can configure many CDNs to retrieve data from the origin servers.
Use Regional edge caches when you have content that is not accessed frequently enough to remain in an edge location. Regional edge caches absorb this content and provide an alternative to having to retrieve that content from the origin server.
Edge caching
Edge caching helps applications perform dramatically faster and cost significantly less at scale. Review the content below to learn the benefits of edge caching.
WITHOUT EDGE CACHING
As an example, let’s say you are serving an image from a traditional web server, not from Amazon CloudFront. You might serve an image named sunsetphoto.png using the URL:
Your users can easily navigate to this URL and see the image. They don’t realize that their request was routed from one network to another (through the complex collection of interconnected networks that comprise the internet) until the image was found.
WITH EDGE CACHING
Amazon CloudFront speeds up the distribution of your content by routing each user request through the AWS backbone network to the edge location that can best serve your content. Typically, this is a CloudFront edge server that provides the fastest delivery to the viewer.
Using the AWS network can dramatically reduce the number of networks your users’ requests must pass through, which improves performance. Users get lower latency (the time it takes to load the first byte of the file) and higher data transfer rates.
You also get increased reliability and availability because copies of your files (also called objects) are now held (or cached) in multiple edge locations around the world.
Amazon CloudFront
Amazon CloudFront is a global CDN service that accelerates delivery of your websites, APIs, video content, or other web assets. It integrates with other AWS products to give developers and businesses a straightforward way to accelerate content to end users. There are no minimum usage commitments.
Amazon CloudFront provides extensive flexibility for optimizing cache behavior, coupled with network-layer optimizations for latency and throughput. The CDN offers a multi-tier cache by default, with regional edge caches that improve latency and lower the load on your origin servers when the object is not already cached at the edge.
Amazon CloudFront supports real-time, bidirectional communication over the WebSocket protocol. This persistent connection permits clients and servers to send real-time data to one another without the overhead of repeatedly opening connections. This is especially useful for communications applications such as chat, collaboration, gaming, and financial trading.
Support for WebSockets in Amazon CloudFront makes it possible for customers to manage WebSocket traffic through the same avenues as any other dynamic and static content. With CloudFront, customers can take advantage of distributed denial of service (DDoS) protection using the built-in CloudFront integrations with Shield and AWS WAF.
Amazon CloudFront caching
When a user requests content that you are serving with Amazon CloudFront, the user is routed to the edge location that provides the lowest latency. Content is delivered with the best possible performance. To review the steps for CloudFront caching, select each hotspot in the image below.
Improving CloudFront performance
WHAT AWS DOES
AWS provides features that improve the performance of your content delivery:
TCP optimization – CloudFront uses TCP optimization to observe how fast a network is already delivering your traffic and the latency of your current round trips. It then uses that data as input to automatically improve performance.
TLS 1.3 support – CloudFront supports TLS 1.3, which provides better performance with a simpler handshake process that requires fewer round trips. It also adds improved security features.
Dynamic content placement – Serve dynamic content, such as web applications or APIs from ELB load balancers or Amazon EC2 instances, by using CloudFront. You can improve the performance, availability, and security of your content.
You can also adjust the configuration of your CloudFront distribution to accommodate for better performance:
Define your caching strategy – Choosing an appropriate TTL is important. In addition, consider caching based on things like query string parameters, cookies, or request headers.
Improve your cache hit ratio – You can view the percentage of viewer requests that are hits, misses, and errors in the CloudFront console. Make changes to your distribution based on statistics collected in the CloudFront cache statistics report.
Use Origin Shield – Get an additional layer of caching between the regional edge caches and your origin. It is not always a best fit for your use case, but it can be beneficial for viewers that are spread across geographic regions or on-premises origins with capacity or bandwidth constraints.
DDoS Protection
A DDoS attack is an attack in which multiple compromised systems attempt to flood a target, such as a network or web application, with traffic. A DDoS attack can prevent legitimate users from accessing a service and can cause the system to crash due to the overwhelming traffic volume.
OSI layer attacks
In general, DDoS attacks can be segregated by which layer of the OSI model they attack. They are most common at the Network (layer 3), Transport (Layer 4), Presentation (Layer 6) and Application (Layer 7) Layers.
Infrastructure Layer Attacks – Attacks at Layer 3 and 4, are typically categorized as Infrastructure layer attacks. These are also the most common type of DDoS attack and include vectors like synchronized (SYN) floods and other reflection attacks like User Datagram Packet (UDP) floods. These attacks are usually large in volume and aim to overload the capacity of the network or the application servers. But fortunately, these are also the type of attacks that have clear signatures and are easier to detect.
Application Layer Attacks – An attacker may target the application itself by using a layer 7 or application layer attack. In these attacks, similar to SYN flood infrastructure attacks, the attacker attempts to overload specific functions of an application to make the application unavailable or extremely unresponsive to legitimate users.
AWS Solutions
AWS Shield Standard, AWS Web Application Firewall (WAF), and AWS Firewall Manager are AWS services that protect architectures against web-based attacks. Review the section below to learn more about each of these AWS services.
AWS Shield
AWS Shield is a managed DDoS protection service that safeguards your applications running on AWS. It provides you with dynamic detection and automatic inline mitigations that minimize application downtime and latency. There are two tiers of AWS Shield: Shield Standard and Shield Advanced.
AWS Shield Standard provides you protection against some of the most common and frequently occurring infrastructure (Layer 3 and 4) attacks. This includes SYN/UDP floods and reflection attacks. Shield Standard improves availability of your applications on AWS. The service applies a combination of traffic signatures, anomaly algorithms, and other analysis techniques. Shield Standard detects malicious traffic and it provides real-time issue mitigation. You are protected by Shield Standard at no additional charge.
If you need even more protection from DDoS attacks on your applications, consider using Shield Advanced. You get additional detection and mitigation against large and sophisticated DDoS attacks, near real-time visibility, and integration with AWS WAF, a web application firewall.
AWS Web Application Firewall (WAF)
AWS WAF is a web application firewall that helps protect your web applications or APIs against common web exploits and bots. AWS WAF gives you control over how traffic reaches your applications. Create security rules that control bot traffic and block common attack patterns, such as SQL injection (SQLi) or cross-site scripting (XSS). You can also monitor HTTP(S) requests that are forwarded to your compatible AWS services.
AWS WAF: Components of access control
Before configuring AWS WAF, you should understand the components used to control access to your AWS resources.
Web ACLs – You use a web ACL to protect a set of AWS resources. You create a web ACL and define its protection strategy by adding rules.
Rules – Each rule contains a statement that defines the inspection criteria and an action to take if a web request meets the criteria.
Rules groups – You can use rules individually or in reusable rule groups.
Rule statements – This is the part of a rule that tells AWS WAF how to inspect a web request.
IP set – This is a collection of IP addresses and IP address ranges that you want to use together in a rule statement.
Regex pattern set – This is a collection of regular expressions that you want to use together in a rule statement.
AWS Firewall Manager
AWS Firewall Manager simplifies your AWS WAF and Amazon VPC security groups administration and maintenance tasks. Set up your AWS WAF firewall rules, Shield protections, and Amazon VPC security groups once.
The service automatically applies the rules and protections across your accounts and resources, even as you add new resources. Firewall Manager helps you to:
Simplify management of rules across accounts and application.
Automatically discover new accounts and remediate noncompliant events.
Deploy AWS WAF rules from AWS Marketplace.
Enable rapid response to attacks across all accounts.
As new applications are created, Firewall Manager also facilitates bringing new applications and resources into compliance with a common set of security rules from day one. Now you have a single service to build firewall rules, create security policies, and enforce them in a consistent, hierarchical manner across your entire AWS infrastructure.
AWS Outposts solutions
These applications might need to generate near-real-time responses to end-user applications, or they might need to communicate with other on-premises systems or control on-site equipment. Examples include workloads running on factory floors for automated operations in manufacturing, real-time patient diagnosis or medical imaging, and content and media streaming.
You need a solution to securely store and process customer data that must remain on premises or in countries outside an AWS Region. You need to run data-intensive workloads and process data locally, or when you want closer controls on data analysis, backup, and restore.
With Outposts, you can extend the AWS Cloud to an on-premises data center. Outposts come in different form factors, each with separate requirements. Verify that your site meets the requirements for the form factor that you’re ordering.
The AWS Outposts family is made up of two types of Outposts: Outposts racks and Outposts servers. Choose each tab to learn more about the Outposts family products.
OUTPOSTS RACKS
When you order an Outposts rack, you can choose from a variety of Outposts configurations. Each configuration provides a mix of EC2 instance types and Amazon Elastic Block Store (Amazon EBS) volumes.
The benefits of Outposts racks include the following:
Scale up to 96 42U–standard racks.
Pool compute and storage capacity between multiple Outposts racks.
Get more service options than Outposts servers.
To fulfill the Outposts rack order, AWS will schedule a date and time with you. You will also receive a checklist of items to verify or provide before the installation. The team will roll the rack to the identified position, and your electrician can power the rack. The team will establish network connectivity for the rack over the uplink that you provide, and they will configure the rack’s capacity.
The installation is complete when you confirm that the Amazon EC2 and Amazon EBS capacity for your AWS Outpost is available from your AWS account.
OUTPOSTS SERVERS
With Outposts servers, you can order hardware at a smaller scale while still providing you AWS services on premises. You can choose from Arm-based or Intel-based options. Not all services available in Outposts racks are supported in Outposts servers.
Outposts servers are delivered directly to you and installed by either your own onsite personnel or a third-party vendor. Once connected to your network, AWS will remotely provision compute and storage resources.
Benefits of Outposts servers include the following:
Place in your own rack
Choose from:
1U Graviton-based processor
2U Intel Xeon Scalable processor
Outposts extend your VPC
A virtual private cloud (VPC) spans all Availability Zones in its AWS Region. You can extend any VPC in the Region to your Outpost by adding an Outpost subnet.
Outposts support multiple subnets. You choose the EC2 instance subnet when you launch the EC2 instance in your Outpost. You cannot choose the underlying hardware where the instance is deployed, because the Outpost is a pool of AWS compute and storage capacity.
Each Outpost can support multiple VPCs that can have one or more Outpost subnets.
You create Outpost subnets from the VPC CIDR range where you created the Outpost. You can use the Outpost address ranges for resources, such as EC2 instances that reside in the Outpost subnet. AWS does not directly advertise the VPC CIDR, or the Outpost subnet range to your on-premises location.
Amazon RDS is a web service that makes it easy to set up, operate, and scale a relational database in the cloud. It provides cost-efficient and resizable capacity while managing time-consuming database administration tasks. This allows you to focus on your applications and business. Amazon RDS gives you access to the full capabilities of a MySQL, Oracle, SQL Server, or Aurora database engines. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS.
Amazon RDS automatically patches the database software and backs up your database. It stores the backups for a user-defined retention period and provides point-in-time recovery. You benefit from the flexibility of scaling the compute resources or storage capacity associated with your relational DB instance with a single API call.
Amazon RDS is available on six database engines, which optimize for memory, performance, or I/O. The database engines include:
Amazon Aurora
PostgreSQL
MySQL
MariaDB
Oracle Database
SQL Server
Amazon RDS Multi-AZ deployments
Amazon RDS Multi-AZ deployments provide enhanced availability and durability for DB instances, making them a natural fit for production database workloads. When you provision a Multi-AZ DB instance, Amazon RDS synchronously replicates the data to a standby instance in a different Availability Zone.
You can modify your environment from Single-AZ to Multi-AZ at any time. Each Availability Zone runs on its own physically distinct, independent infrastructure and is engineered to be highly reliable. Upon failure, the secondary instance picks up the load. Note that this is not used for read-only scenarios.
Read replicas
With Amazon RDS, you can create read replicas of your database. Amazon automatically keeps them in sync with the primary DB instance. Read replicas are available in Amazon RDS for Aurora, MySQL, MariaDB, PostgreSQL, Oracle, and Microsoft SQL Server. Read replicas can help you:
Relieve pressure on your primary node with additional read capacity.
Bring data close to your applications in different AWS Regions.
Promote a read replica to a standalone instance as a disaster recovery (DR) solution if the primary DB instance fails.
You can add read replicas to handle read workloads so your primary database doesn’t become overloaded with read requests. Depending on the database engine, you can also place your read replica in a different Region from your primary database. This gives you the ability to have a read replica closer to a particular locality.
You can configure a source database as Multi-AZ for high availability and create a read replica (in Single-AZ) for read scalability. With RDS for MySQL and MariaDB, you can also set the read replica as Multi-AZ, and as a DR target. When you promote the read replica to be a standalone database, it will be replicated to multiple Availability Zones.
Amazon DynamoDB tables
DynamoDB is a fully managed NoSQL database service. DynamoDB uses primary keys to uniquely identify each item in a table and secondary indexes to provide more querying flexibility. When creating a table, you must specify a table name and a primary key. These are the only two required entities.
There are two types of primary keys supported:
Simple primary key: A simple primary key is composed of just one attribute designated as the partition key. If you use only the partition, no two items can have the same value.
Composite primary key: A composite primary key is composed of both a partition key and a sort key. In this case the partition key value for multiple items can be the same, but their sort key values must be different.
You work with the core components: tables, items, and attributes. A table is a collection of items, and each item is a collection of attributes. In the example above, the table includes two items, with primary keys Nikki Wolf and John Stiles. The item with the primary key Nikki Wolf includes three attributes: Role, Year, and Genre. The primary key for John Stiles includes a Height attribute, and it does not include the Genre attribute.
Amazon DynamoDB consistency options
When your application writes data to a DynamoDB table and receives an HTTP 200 response (OK), the write has occurred and is durable. The data is eventually consistent across all storage locations, usually within one second or less. DynamoDB supports eventually consistent and strongly consistent reads.
DynamoDB uses eventually consistent reads, unless you specify otherwise. Read operations (such as GetItem, Query, and Scan) provide a ConsistentRead parameter. If you set this parameter to true, DynamoDB uses strongly consistent reads during the operation.
EVENTUALLY CONSISTENT READS
When you read data from a DynamoDB table, the response might not reflect the results of a recently completed write operation. The response might include some stale data. If you repeat your read request after a short time, the response should return the latest data.
STRONGLY CONSISTENT READS
When you request a strongly consistent read, DynamoDB returns a response with the most up-to-date data, reflecting the updates from all prior write operations that were successful. A strongly consistent read might not be available if there is a network delay or outage.
Amazon DynamoDB global tables
A global table is a collection of one or more DynamoDB tables, all owned by a single AWS account, identified as replica tables. A replica table (or replica, for short) is a single DynamoDB table that functions as part of a global table. Each replica stores the same set of data items. Any given global table can only have one replica table per Region, and every replica has the same table name and the same primary key schema.
DynamoDB global tables provide a fully managed solution for deploying a multi-Region, multi-active database, without having to build and maintain your own replication solution. When you create a global table, you specify the AWS Regions where you want the table to be available. DynamoDB performs all the necessary tasks to create identical tables in these Regions and propagate ongoing data changes to all of them.
Database Caching
Without caching, EC2 instances read and write directly to the database. With a caching, instances first attempt to read from a cache which uses high performance memory. They use a cache cluster that contains a set of cache nodes distributed between subnets. Resources within those subnets have high-speed access to those nodes.
Common caching strategies
There are multiple strategies for keeping information in the cache in sync with the database. Two common caching strategies include lazy loading and write-through.
Lazy loading
In lazy loading, updates are made to the database without updating the cache. In the case of a cache miss, the information retrieved from the database can be subsequently written to the cache. Lazy loading ensures that the data loaded in the cache is data needed by the application but can result in high cache-miss-to-cache-hit ratios in some use cases.
Write-through
An alternative strategy is to write through to the cache every time the database is accessed. This approach results in fewer cache misses. This improves performance but requires additional storage for data, which may not be needed by the applications.
Managing your cache
As your application writes to the cache, you need to consider cache validity and make sure that the data written to the cache is accurate. You also need to develop a strategy for managing cache memory. When your cache is full, you determine which items should be deleted by setting an eviction policy.
CACHE VALIDITY
Lazy loading allows for stale data but doesn’t fail with empty nodes. Write-through ensures that data is always fresh but can fail with empty nodes and can populate the cache with superfluous data. By adding a time to live (TTL) value to each write to the cache, you can ensure fresh data without cluttering up the cache with extra data.
TTL is an integer value that specifies the number of seconds or milliseconds, until the key expires. When an application attempts to read an expired key, it is treated as though the data is not found in cache, meaning that the database is queried and the cache is updated. This keeps data from getting too stale and requires that values in the cache are occasionally refreshed from the database.
MANAGING MEMORY
When cache memory is full, the cache engine removes data from memory to make space for new data. It chooses this data based on the eviction policy you set. An eviction policy evaluates the following characteristics of your data:
Which were accessed least recently?
Which have been accessed least frequently?
Which have a TTL set and the TTL value?
Amazon Elasticache
Amazon ElastiCache is a web service that makes it easy to set up, manage, and scale a distributed in-memory data store or cache environment in the cloud. When you’re using a cache for a backend data store, a side-cache is perhaps the most commonly known approach. Redis and Memcached are general-purpose caches that are decoupled from the underlying data store.
Use ElastiCache for Memcached for data-intensive apps. The service works as an in-memory data store and cache to support the most demanding applications requiring sub-millisecond response times. It is fully managed, scalable, and secure—making it an ideal candidate for cases where frequently accessed data must be in memory. The service is a popular choice for web, mobile apps, gaming, ad tech, and e-commerce.
ElastiCache for Redis is an in-memory data store that provides sub-millisecond latency at internet scale. It can power the most demanding real-time applications in gaming, ad tech, e-commerce, healthcare, financial services, and IoT.
ElastiCache engines
ElastiCache for Memcached
ElastiCache for Redis
Simple cache to offload database burden
Yes
Yes
Ability to scale horizontally for writes and storage
Yes
Yes (if cluster mode is enabled)
Multi-threaded performance
Yes
–
Advanced data types
–
Yes
Sorting and ranking data sets
–
Yes
Pub and sub capability
–
Yes
Multi-AZ with Auto Failover
–
Yes
Backup and restore
–
Yes
Amazon DynamoDB Accelerator
DynamoDB is designed for scale and performance. In most cases, the DynamoDB response times can be measured in single-digit milliseconds. However, there are certain use cases that require response times in microseconds. For those use cases, DynamoDB Accelerator (DAX) delivers fast response times for accessing eventually consistent data.
DAX is an Amazon DynamoDB compatible caching service that provides fast in-memory performance for demanding applications.
AWS Database Migration Service
AWS Database Migration Service (AWS DMS) supports migration between the most widely used databases like Oracle, PostgreSQL, SQL Server, Amazon Redshift, Aurora, MariaDB, and MySQL. AWS DMS supports both homogeneous (same engine) and heterogeneous (different engines) migrations.
The service can be used to migrate between databases on Amazon EC2, Amazon RDS, and on-premises. Either the target or the source database must be located in Amazon EC2. It cannot be used to migrate between two on-premises databases.
AWS DMS automatically handles formatting of the source data for consumption by the target database. It does not perform schema or code conversion.
For homogenous migrations, you can use native tools to perform these conversions. For heterogeneous migrations, you can use the AWS Schema Conversion Tool (AWS SCT).
AWS Schema Conversion Tool
The AWS Schema Conversion Tool (AWS SCT) automatically converts the source database schema and a majority of the database code objects. The conversion includes views, stored procedures, and functions. They are converted to a format that is compatible with the target database. Any objects that cannot be automatically converted are marked so that they can be manually converted to complete the migration.
Source databases
Target databases on AWS
Oracle database Oracle data warehouse Azure SQL SQL server Teradata IBM Netezza Greenplum HPE Vertica MySQL and MariaDB PostgreSQL Aurora IBM DB2 LUW Apache Cassandra SAP ASE
AWS SCT
MySQL PostgreSQL Oracle AmazonDB RDS for MySQL Aurora for MySQL RDS for PostgreSQL Aurora PostgreSQL
The AWS SCT can also scan your application source code for embedded SQL statements and convert them as part of a database schema conversion project. During this process, the AWS SCT performs cloud native code optimization by converting legacy Oracle and SQL Server functions to their equivalent AWS service, modernizing the applications at the same time of migration.
a complete reusable module that can be used to deploy ECS, Task Definetion, and services from the ECR and VPC that has been created manually thru the console.
The AWS Global Cloud Infrastructure is the most secure, extensive, and reliable cloud platform, offering over 200 fully featured services from data centers globally.
AWS Data Center
AWS pioneered cloud computing in 2006 to provide rapid and secure infrastructure. AWS continuously innovates on the design and systems of data centers to protect them from man-made and natural risks. Today, AWS provides data centers at a large, global scale. AWS implements controls, builds automated systems, and conducts third-party audits to confirm security and compliance. As a result, the most highly-regulated organizations in the world trust AWS every day.
Availability Zone – AZ
An Availability Zone (AZ) is one or more discrete data centers with redundant power, networking, and connectivity in an AWS Region. Availability Zones are multiple, isolated areas within a particular geographic location. When you launch an instance, you can select an Availability Zone or let AWS choose one for you. If you distribute your instances across multiple Availability Zones and one instance fails, you can design your application so that an instance in another Availability Zone can handle requests.
Region
Each AWS Region consists of multiple, isolated, and physically separate Availability Zones within a geographic area. This achieves the greatest possible fault tolerance and stability. In your account, you determine which Regions you need. You can run applications and workloads from a Region to reduce latency to end users. You can do this while avoiding the upfront expenses, long-term commitments, and scaling challenges associated with maintaining and operating a global infrastructure.
AWS Local Zone
AWS Local Zones can be used for highly demanding applications that require single-digit millisecond latency to end users. Media and entertainment content creation, real-time multiplayer gaming, and Machine learning hosting and training are some use cases for AWS Local Zones.
CloudFront – Edge Location
An edge location is the nearest point to a requester of an AWS service. Edge locations are located in major cities around the world. They receive requests and cache copies of your content for faster delivery.
The AWS Snow Family is a collection of physical devices that help to physically transport up to exabytes of data into and out of AWS.
AWS Snow Family is composed of AWS Snowcone, AWS Snowball, and AWS Snowmobile.
These devices offer different capacity points, and most include built-in computing capabilities. AWS owns and manages the Snow Family devices and integrates with AWS security, monitoring, storage management, and computing capabilities.
AWS Snowcone
AWS Snowcone is a small, rugged, and secure edge computing and data transfer device.
It features 2 CPUs, 4 GB of memory, and 8 TB of usable storage.
Snowball Edge Storage Optimized devices are well suited for large-scale data migrations and recurring transfer workflows, in addition to local computing with higher capacity needs.
Storage: 80 TB of hard disk drive (HDD) capacity for block volumes and Amazon S3 compatible object storage, and 1 TB of SATA solid state drive (SSD) for block volumes.
Compute: 40 vCPUs, and 80 GiB of memory to support Amazon EC2 sbe1 instances (equivalent to C5).
Snowball Edge Compute Optimized provides powerful computing resources for use cases such as machine learning, full motion video analysis, analytics, and local computing stacks.
Storage: 42-TB usable HDD capacity for Amazon S3 compatible object storage or Amazon EBS compatible block volumes and 7.68 TB of usable NVMe SSD capacity for Amazon EBS compatible block volumes.
Compute: 52 vCPUs, 208 GiB of memory, and an optional NVIDIA Tesla V100 GPU. Devices run Amazon EC2 sbe-c and sbe-g instances, which are equivalent to C5, M5a, G3, and P3 instances.
AWS Snowmobile
AWS Snowmobile is an exabyte-scale data transfer service used to move large amounts of data to AWS.
You can transfer up to 100 petabytes of data per Snowmobile, a 45-foot long ruggedized shipping container, pulled by a semi trailer truck.
AWS offers four different Support plans to help you troubleshoot issues, lower costs, and efficiently use AWS services.
You can choose from the following Support plans to meet your company’s needs:
Basic
Developer
Business
Enterprise
Basic Support
Basic Support is free for all AWS customers. It includes access to whitepapers, documentation, and support communities. With Basic Support, you can also contact AWS for billing questions and service limit increases.
With Basic Support, you have access to a limited selection of AWS Trusted Advisor checks. Additionally, you can use the AWS Personal Health Dashboard, a tool that provides alerts and remediation guidance when AWS is experiencing events that may affect you.
If your company needs support beyond the Basic level, you could consider purchasing Developer, Business, or Enterprise Support.
Developer, Business, and Enterprise Support
The Developer, Business, and Enterprise Support plans include all the benefits of Basic Support, in addition to the ability to open an unrestricted number of technical support cases. These three Support plans have pay-by-the-month pricing and require no long-term contracts.
The information in this course highlights only a selection of details for each Support plan. A complete overview of what is included in each Support plan, including pricing for each plan, is available on the AWS Support site.
In general, for pricing, the Developer plan has the lowest cost, the Business plan is in the middle, and the Enterprise plan has the highest cost.
Developer Support
Customers in the Developer Support plan have access to features such as:
Best practice guidance
Client-side diagnostic tools
Building-block architecture support, which consists of guidance for how to use AWS offerings, features, and services together
For example, suppose that your company is exploring AWS services. You’ve heard about a few different AWS services. However, you’re unsure of how to potentially use them together to build applications that can address your company’s needs. In this scenario, the building-block architecture support that is included with the Developer Support plan could help you to identify opportunities for combining specific services and features.
Business Support
Customers with a Business Support plan have access to additional features, including:
Use-case guidance to identify AWS offerings, features, and services that can best support your specific needs
All AWS Trusted Advisor checks
Limited support for third-party software, such as common operating systems and application stack components
Suppose that your company has the Business Support plan and wants to install a common third-party operating system onto your Amazon EC2 instances. You could contact AWS Support for assistance with installing, configuring, and troubleshooting the operating system. For advanced topics such as optimizing performance, using custom scripts, or resolving security issues, you may need to contact the third-party software provider directly.
Enterprise Support
In addition to all the features included in the Basic, Developer, and Business Support plans, customers with an Enterprise Support plan have access to features such as:
Application architecture guidance, which is a consultative relationship to support your company’s specific use cases and applications
Infrastructure event management: A short-term engagement with AWS Support that helps your company gain a better understanding of your use cases. This also provides your company with architectural and scaling guidance.
You can upload any type of file to Amazon S3, such as images, videos, text files, and so on. For example, you might use Amazon S3 to store backup files, media files for a website, or archived documents. Amazon S3 offers unlimited storage space. The maximum file size for an object in Amazon S3 is 5 TB.
Amazon S3 storage classes
With Amazon S3, you pay only for what you use. You can choose from a range of storage classes to select a fit for your business and cost needs. When selecting an Amazon S3 storage class, consider these two factors:
How often you plan to retrieve your data
How available you need your data to be
S3 Standard
Designed for frequently accessed data
Stores data in a minimum of three Availability Zones
S3 Standard provides high availability for objects. This makes it a good choice for a wide range of use cases, such as websites, content distribution, and data analytics. S3 Standard has a higher cost than other storage classes intended for infrequently accessed data and archival storage.
S3 Standard-Infrequent Access (S3 Standard-IA)
Ideal for infrequently accessed data
Similar to S3 Standard but has a lower storage price and higher retrieval price
S3 Standard-IA is ideal for data infrequently accessed but requires high availability when needed. Both S3 Standard and S3 Standard-IA store data in a minimum of three Availability Zones. S3 Standard-IA provides the same level of availability as S3 Standard but with a lower storage price and a higher retrieval price.
S3 One Zone-Infrequent Access (S3 One Zone-IA)
Stores data in a single Availability Zone
Has a lower storage price than S3 Standard-IA
Compared to S3 Standard and S3 Standard-IA, which store data in a minimum of three Availability Zones, S3 One Zone-IA stores data in a single Availability Zone. This makes it a good storage class to consider if the following conditions apply:
You want to save costs on storage.
You can easily reproduce your data in the event of an Availability Zone failure.
S3 Intelligent-Tiering
Ideal for data with unknown or changing access patterns
Requires a small monthly monitoring and automation fee per object
In the S3 Intelligent-Tiering storage class, Amazon S3 monitors objects’ access patterns. If you haven’t accessed an object for 30 consecutive days, Amazon S3 automatically moves it to the infrequent access tier, S3 Standard-IA. If you access an object in the infrequent access tier, Amazon S3 automatically moves it to the frequent access tier, S3 Standard.
S3 Glacier
Low-cost storage designed for data archiving
Able to retrieve objects within a few minutes to hours
S3 Glacier is a low-cost storage class that is ideal for data archiving. For example, you might use this storage class to store archived customer records or older photos and video files.
S3 Glacier
Low-cost storage designed for data archiving
Able to retrieve objects within a few minutes to hours
S3 Glacier is a low-cost storage class that is ideal for data archiving. For example, you might use this storage class to store archived customer records or older photos and video files.
S3 Glacier Deep Archive
Lowest-cost object storage class ideal for archiving
Able to retrieve objects within 12 hours
When deciding between Amazon S3 Glacier and Amazon S3 Glacier Deep Archive, consider how quickly you need to retrieve archived objects. You can retrieve objects stored in the S3 Glacier storage class within a few minutes to a few hours. By comparison, you can retrieve objects stored in the S3 Glacier Deep Archive storage class within 12 hours.
With Amazon EC2, you pay only for the compute time that you use. Amazon EC2 offers a variety of pricing options for different use cases. For example, if your use case can withstand interruptions, you can save with Spot Instances. You can also save by committing early and locking in a minimum level of use with Reserved Instances.
On-Demand
are ideal for short-term, irregular workloads that cannot be interrupted. No upfront costs or minimum contracts apply. The instances run continuously until you stop them, and you pay for only the compute time you use.
Sample use cases for On-Demand Instances include developing and testing applications and running applications that have unpredictable usage patterns. On-Demand Instances are not recommended for workloads that last a year or longer because these workloads can experience greater cost savings using Reserved Instances.
Amazon EC2 Savings Plans
AWS offers Savings Plans for several compute services, including Amazon EC2. Amazon EC2 Savings Plans enable you to reduce your compute costs by committing to a consistent amount of compute usage for a 1-year or 3-year term. This term commitment results in savings of up to 66% over On-Demand costs.
Any usage up to the commitment is charged at the discounted plan rate (for example, $10 an hour). Any usage beyond the commitment is charged at regular On-Demand rates.
Later in this course, you will review AWS Cost Explorer, a tool that enables you to visualize, understand, and manage your AWS costs and usage over time. If you are considering your options for Savings Plans, AWS Cost Explorer can analyze your Amazon EC2 usage over the past 7, 30, or 60 days. AWS Cost Explorer also provides customized recommendations for Savings Plans. These recommendations estimate how much you could save on your monthly Amazon EC2 costs, based on previous Amazon EC2 usage and the hourly commitment amount in a 1-year or 3-year plan.
Reserved Instances
are a billing discount applied to the use of On-Demand Instances in your account. You can purchase Standard Reserved and Convertible Reserved Instances for a 1-year or 3-year term, and Scheduled Reserved Instances for a 1-year term. You realize greater cost savings with the 3-year option.
At the end of a Reserved Instance term, you can continue using the Amazon EC2 instance without interruption. However, you are charged On-Demand rates until you do one of the following:
Terminate the instance.
Purchase a new Reserved Instance that matches the instance attributes (instance type, Region, tenancy, and platform).
Spot Instances
are ideal for workloads with flexible start and end times, or that can withstand interruptions. Spot Instances use unused Amazon EC2 computing capacity and offer you cost savings at up to 90% off of On-Demand prices.
Suppose that you have a background processing job that can start and stop as needed (such as the data processing job for a customer survey). You want to start and stop the processing job without affecting the overall operations of your business. If you make a Spot request and Amazon EC2 capacity is available, your Spot Instance launches. However, if you make a Spot request and Amazon EC2 capacity is unavailable, the request is not successful until capacity becomes available. The unavailable capacity might delay the launch of your background processing job.
After you have launched a Spot Instance, if capacity is no longer available or demand for Spot Instances increases, your instance may be interrupted. This might not pose any issues for your background processing job. However, in the earlier example of developing and testing applications, you would most likely want to avoid unexpected interruptions. Therefore, choose a different EC2 instance type that is ideal for those tasks.
Dedicated Hosts
are physical servers with Amazon EC2 instance capacity that is fully dedicated to your use.
You can use your existing per-socket, per-core, or per-VM software licenses to help maintain license compliance. You can purchase On-Demand Dedicated Hosts and Dedicated Hosts Reservations. Of all the Amazon EC2 options that were covered, Dedicated Hosts are the most expensive.
Amazon EC2 instance types are optimized for different tasks. When selecting an instance type, consider the specific needs of your workloads and applications. This might include requirements for compute, memory, or storage capabilities.
General purpose instances
provide a balance of compute, memory, and networking resources. You can use them for a variety of workloads, such as:
application servers
gaming servers
backend servers for enterprise applications
small and medium databases
Suppose that you have an application in which the resource needs for compute, memory, and networking are roughly equivalent. You might consider running it on a general purpose instance because the application does not require optimization in any single resource area.
Compute optimized instances
are ideal for compute-bound applications that benefit from high-performance processors. Like general purpose instances, you can use compute optimized instances for workloads such as web, application, and gaming servers.
However, the difference is compute optimized applications are ideal for high-performance web servers, compute-intensive applications servers, and dedicated gaming servers. You can also use compute optimized instances for batch processing workloads that require processing many transactions in a single group.
Memory optimized instances
are designed to deliver fast performance for workloads that process large datasets in memory. In computing, memory is a temporary storage area. It holds all the data and instructions that a central processing unit (CPU) needs to be able to complete actions. Before a computer program or application is able to run, it is loaded from storage into memory. This preloading process gives the CPU direct access to the computer program.
Suppose that you have a workload that requires large amounts of data to be preloaded before running an application. This scenario might be a high-performance database or a workload that involves performing real-time processing of a large amount of unstructured data. In these types of use cases, consider using a memory optimized instance. Memory optimized instances enable you to run workloads with high memory needs and receive great performance.
Accelerated computing instances
use hardware accelerators, or coprocessors, to perform some functions more efficiently than is possible in software running on CPUs. Examples of these functions include floating-point number calculations, graphics processing, and data pattern matching.
In computing, a hardware accelerator is a component that can expedite data processing. Accelerated computing instances are ideal for workloads such as graphics applications, game streaming, and application streaming.
Storage optimized instances
are designed for workloads that require high, sequential read and write access to large datasets on local storage. Examples of workloads suitable for storage optimized instances include distributed file systems, data warehousing applications, and high-frequency online transaction processing (OLTP) systems.
In computing, the term input/output operations per second (IOPS) is a metric that measures the performance of a storage device. It indicates how many different input or output operations a device can perform in one second. Storage optimized instances are designed to deliver tens of thousands of low-latency, random IOPS to applications.
You can think of input operations as data put into a system, such as records entered into a database. An output operation is data generated by a server. An example of output might be the analytics performed on the records in a database. If you have an application that has a high IOPS requirement, a storage optimized instance can provide better performance over other instance types not optimized for this kind of use case.
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