Cloud computing is the on-demand delivery of IT resources and applications via the Internet with pay-as-you-go pricing. Whether you run applications that share photos to millions of mobile users or deliver services that support the critical operations of your business, the cloud provides rapid access to flexible and low-cost IT resources.
In its simplest form, cloud computing
provides an easy way to access servers, storage, databases, and a broad set of application services
over the Internet.
There are six advantages for AWS clouding
- Global in minutes
- Variable vs capital expense
- Economies of scale
- Stop guessing capacity
- Focus on business differentaiors
- Increate speed and agility
One of the key benefits of cloud computing is the opportunity to
replace up-front capital infrastructure expenses with low variable costs that scale with your business. With the cloud, businesses no longer need to plan for and procure servers and other IT infrastructure weeks or months in advance. Instead, they can instantly spin up hundres or thousands of servers in minutes and deliver results faster.
With pay-per-use billing, AWS clouding services
become an operational expense instead of a capital expense.
Metadata, known as tags, that you can create and assign to your Amazon EC2 resources
- Each availability zone is a physical data center in the region, but separate from the other ones (so that they’re isolated from disasters)
- AWS Consoles are region scoped (except IAM, S3 & Route53)
Here you need to create an AMI, but because AMI are bounded in the regions they are created, they need to be copied across regions for disaster recovery purposes
If you stopped an EBS-backed EC2 instance, the volume is preserved but the data in any attached Instance store volumes will be erased. Keep in mind that an EC2 instance has an underlying physical host computer. If the instance is stopped, AWS usually moves the instance to a new host computer. Your instance may stay on the same host computer if there are no problems with the host computer. In addition, its Elastic IP address is disassociated from the instance if it is an EC2-Classic instance. Otherwise, if it is an EC2-VPC instance, the Elastic IP address remains associated.
Placements groups are the answer here, where “cluster” guarantees high network performance (correct answer), whereas “spread” would guarantee independent failures between instances.
When you launch a new EC2 instance, the EC2 service attempts to place the instance in such a way that all of your instances are spread out across underlying hardware to minimize correlated failures. You can use placement groups to influence the placement of a group of interdependent instances to meet the needs of your workload. Depending on the type of workload, you can create a placement group using one of the following placement strategies:
Cluster – packs instances close together inside an Availability Zone. This strategy enables workloads to achieve the low-latency network performance necessary for tightly-coupled node-to-node communication that is typical of HPC applications.
Partition – spreads your instances across logical partitions such that groups of instances in one partition do not share the underlying hardware with groups of instances in different partitions. This strategy is typically used by large distributed and replicated workloads, such as Hadoop, Cassandra, and Kafka.
Spread – strictly places a small group of instances across distinct underlying hardware to reduce correlated failures.
There is no charge for creating a placement group.
Placement Groups is primarily used to determine how your instances are placed on the underlying hardware while Enhanced Networking, on the other hand, is for providing high-performance networking capabilities using single root I/O virtualization (SR-IOV) on supported EC2 instance types.
When you create a security group, it has no inbound rules. Therefore, no inbound traffic originating from another host to your instance is allowed until you add inbound rules to the security group. By default, a security group includes an outbound rule that allows all outbound traffic. You can remove the rule and add outbound rules that allow specific outbound traffic only. If your security group has no outbound rules, no outbound traffic originating from your instance is allowed.
Options 1 and 4 are both incorrect because any changes to the Security Groups or Network Access Control Lists are applied immediately and not after 60 minutes or after the instance reboot.
Option 2 is incorrect because the scenario says that VPC is using a default configuration. Since by default, Network ACL allows all inbound and outbound IPv4 traffic, then there is no point of explicitly allowing the port in the Network ACL. Security Groups, on the other hand, does not allow incoming traffic by default, unlike Network ACL.
To allow the custom port, you have to change the Inbound Rules in your Security Group to allow traffic coming from the mobile devices. Security Groups usually control the list of ports that are allowed to be used by your EC2 instances and the NACLs control which network or list of IP addresses can connect to your whole VPC.
Cluster Placement Groups
A cluster placement group is a logical grouping of instances within a single Availability Zone. A placement group can span peered VPCs in the same Region. The chief benefit of a cluster placement group, in addition to a 10 Gbps flow limit, is the non-blocking, non-oversubscribed, fully bi-sectional nature of the connectivity. In other words, all nodes within the placement group can talk to all other nodes within the placement group at the full line rate of 10 Gbps flows and 100 Gbps aggregate without any slowing due to over-subscription.
Launch configurations are immutable meaning they cannot be updated. You have to create a new launch configuration, attach it to the ASG and then terminate old instances / launch new instances
AZs will be balanced first, then the instance with the oldest launch configuration within that AZ will be terminated. For a reference to the default termination policy logic, have a look at this link: https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-instance-termination.html
the EC2 instances you are currently using depends on a pre-built AMI. This AMI is not accessible to another region hence, you have to copy it to the us-west-2 region to properly establish your disaster recovery instance.
You can copy an Amazon Machine Image (AMI) within or across an AWS region using the AWS Management Console, the AWS command line tools or SDKs, or the Amazon EC2 API, all of which support the CopyImage action. You can copy both Amazon EBS-backed AMIs and instance store-backed AMIs. You can copy encrypted AMIs and AMIs with encrypted snapshots
AWS Device Farm is an app testing service that lets you test and interact with your Android, iOS, and web apps on many devices at once, or reproduce issues on a device in real time.
Your whole AWS security is there:
IAM has a
Permissions let you specify access to AWS resources. Permissions are granted to IAM entities (users, groups, and roles) and by default these entities start with no permissions. In other words, IAM entities can do nothing in AWS until you grant them your desired permissions. To give entities permissions, you can attach a policy that specifies the type of access, the actions that can be performed, and the resources on which the actions can be performed. In addition, you can specify any conditions that must be set for access to be allowed or denied.
- Enable Multi-Factor Authentication
- Assign an IAM role to the Amazon EC2 instance
Always remember that you should associate IAM roles to EC2 instances and not an IAM user, for the purpose of accessing other AWS services. IAM roles are designed so that your applications can securely make API requests from your instances, without requiring you to manage the security credentials that the applications use. Instead of creating and distributing your AWS credentials, you can delegate permission to make API requests using IAM roles.
A permissions policy describes who has access to what. Policies attached to an IAM identity are identity-based policies (IAM policies) and policies attached to a resource are resource-based policies. Amazon RDS supports only identity-based policies (IAM policies).
MySQL and PostgreSQL both support IAM database authentication.
To protect the confidential data of your customers, you have to ensure that your RDS database can only be accessed using the profile credentials specific to your EC2 instances via an authentication token.
You can authenticate to your DB instance using AWS Identity and Access Management (IAM) database authentication. IAM database authentication works with MySQL and PostgreSQL. With this authentication method, you don’t need to use a password when you connect to a DB instance. Instead, you use an authentication token.
An authentication token is a unique string of characters that Amazon RDS generates on request. Authentication tokens are generated using AWS Signature Version 4. Each token has a lifetime of 15 minutes. You don’t need to store user credentials in the database, because authentication is managed externally using IAM. You can also still use standard database authentication.
• Big enterprises usually integrate their own repository of users with IAM
• This way, one can login into AWS using their company credentials
• Identity Federation uses the SAML standard (Active Directory)
• One IAM User per PHYSICAL PERSON
• One IAM Role per Application
Temporary Security Credentials
You can use the AWS Security Token Service (AWS STS) to create and provide trusted users with temporary security credentials that can control access to your AWS resources. Temporary security credentials work almost identically to the long-term access key credentials that your IAM users can use, with the following differences:
Temporary security credentials are short-term, as the name implies. They can be configured to last for anywhere from a few minutes to several hours. After the credentials expire, AWS no longer recognizes them or allows any kind of access from API requests made with them.
Temporary security credentials are not stored with the user but are generated dynamically and provided to the user when requested. When (or even before) the temporary security credentials expire, the user can request new credentials, as long as the user requesting them still has permissions to do so.
This service is primarily used for user authentication and not for providing access to your AWS resources. A JSON Web Token (JWT) is meant to be used for user authentication and session management.
This service uses STS, it does not issue short-lived credentials by itself. AWS Single Sign-On (SSO) is a cloud SSO service that makes it easy to centrally manage SSO access to multiple AWS accounts and business applications.
Instance Store will have the highest disk performance but comes with the storage being wiped if the instance is terminated, which is acceptable in this case. EBS volumes would provide good performance as far as disk goes, but not as good as Instance Store. EBS data survives instance termination or reboots. EFS is a network drive, and finally S3 cannot be mounted as a local disk (natively).
Need to define two terms:
• RPO: Recovery Point Objective
• RTO: Recovery Time Objective
Generating S3 pre-signed URLs would bypass CloudFront, therefore we should use CloudFront signed URL. To generate that URL we must code, and Lambda is the perfect tool for running that code on the fly.
As the file is greater than 5GB in size, you must use Multi Part upload to upload that file to S3.
Expedited retrievals allow you to quickly access your data when occasional urgent requests for a subset of archives are required. For all but the largest archives (250 MB+), data accessed using Expedited retrievals are typically made available within 1–5 minutes. Provisioned Capacity ensures that retrieval capacity for Expedited retrievals is available when you need it.
To make an Expedited, Standard, or Bulk retrieval, set the Tier parameter in the Initiate Job (POST jobs) REST API request to the option you want, or the equivalent in the AWS CLI or AWS SDKs. If you have purchased provisioned capacity, then all expedited retrievals are automatically served through your provisioned capacity.
Provisioned capacity ensures that your retrieval capacity for expedited retrievals is available when you need it. Each unit of capacity provides that at least three expedited retrievals can be performed every five minutes and provides up to 150 MB/s of retrieval throughput. You should purchase provisioned retrieval capacity if your workload requires highly reliable and predictable access to a subset of your data in minutes. Without provisioned capacity Expedited retrievals are accepted, except for rare situations of unusually high demand. However, if you require access to Expedited retrievals under all circumstances, you must purchase provisioned retrieval capacity.
It is not an archive retrieval option and is primarily used to perform filtering operations using simple Structured Query Language (SQL) statements directly on your data archive in Glacier.
It typically complete within 5–12 hours hence, this does not satisfy the requirement of retrieving the data within 15 minutes. The provisioned capacity option is also not compatible with Bulk retrievals.
using ranged archive retrievals is not enough to meet the requirement of retrieving the whole archive in the given timeframe. In addition, it does not provide additional retrieval capacity which is what the provisioned capacity option can offer.
It is an Amazon S3 feature that makes it easy to retrieve specific data from the contents of an object using simple SQL expressions without having to retrieve the entire object.
Similiarly, Amazon Redshift Spectrum is a feature of Amazon Redshift that enables you to run queries against exabytes of unstructured data in Amazon S3 with no loading or ETL required.
Don’t make the S3 bucket public. You cannot attach IAM roles to the CloudFront distribution. S3 buckets don’t have security groups. Here you need to use an OAI. Read more here: https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/private-content-restricting-access-to-s3.html
Restricting Access to Amazon S3 Content by Using an Origin Access Identity
To restrict access to content that you serve from Amazon S3 buckets, you create CloudFront signed URLs or signed cookies to limit access to files in your Amazon S3 bucket, and then you create a special CloudFront user called an origin access identity (OAI) and associate it with your distribution. Then you configure permissions so that CloudFront can use the OAI to access and serve files to your users, but users can’t use a direct URL to the S3 bucket to access a file there. Taking these steps help you maintain secure access to the files that you serve through CloudFront.
In general, if you’re using an Amazon S3 bucket as the origin for a CloudFront distribution, you can either allow everyone to have access to the files there, or you can restrict access. If you limit access by using, for example, CloudFront signed URLs or signed cookies, you also won’t want people to be able to view files by simply using the direct URL for the file. Instead, you want them to only access the files by using the CloudFront URL, so your protections work. For more information about using signed URLs and signed cookies, see Serving Private Content with Signed URLs and Signed Cookies
Amazon S3 now provides increased performance to support at least 3,500 requests per second to add data and 5,500 requests per second to retrieve data, which can save significant processing time for no additional charge. Each S3 prefix can support these request rates, making it simple to increase performance significantly.
Applications running on Amazon S3 today will enjoy this performance improvement with no changes, and customers building new applications on S3 do not have to make any application customizations to achieve this performance. Amazon S3’s support for parallel requests means you can scale your S3 performance by the factor of your compute cluster, without making any customizations to your application. Performance scales per prefix, so you can use as many prefixes as you need in parallel to achieve the required throughput. There are no limits to the number of prefixes.
This S3 request rate performance increase removes any previous guidance to randomize object prefixes to achieve faster performance. That means you can now use logical or sequential naming patterns in S3 object naming without any performance implications. This improvement is now available in all AWS Regions.
Option 1 is incorrect because it is an archival/long term storage solution, which is not optimal if you are serving objects frequently and fast retrieval is a must.
Option 2 is incorrect. Adding a random prefix is not required in this scenario because S3 can now scale automatically to adjust perfomance. You do not need to add a random prefix anymore for this purpose since S3 has increased performance to support at least 3,500 requests per second to add data and 5,500 requests per second to retrieve data, which covers the workload in the scenario.
Option 4 is incorrect because Amazon S3 already maintains an index of object key names in each AWS region. S3 stores key names in alphabetical order. The key name dictates which partition the key is stored in. Using a sequential prefix increases the likelihood that Amazon S3 will target a specific partition for a large number of your keys, overwhelming the I/O capacity of the partition.
With SSE-C, your company can still provide the encryption key but let AWS do the encryption
EBS is already redundant storage (replicated within an AZ)
But what if you want to increase IOPS to say 100 000 IOPS?
One logical volume
EBS Volume 1
• Combining 2 or more volumes and getting the total disk space and I/O
• But one disk fails, all the data is failed
One logical volume
• RAID 1 = Mirroring a volume to another
• If one disk fails, our logical volume is still working
• We have to send the data to two EBS volume at the same time (2x network)
keeping as io1 but reducing the iops may interfere with the burst of performance we need. The EC2 instance type changes won’t affect the 90% of the costs that are incurred to us. CloudFormation is a free service to use. Therefore, gp2 is the right choice, allowing us to save on cost while keeping a burst in performance when needed
You can now choose between three Amazon EBS volume types to best meet the needs of your workloads: General Purpose (SSD), Provisioned IOPS (SSD), and Magnetic volumes.
GP2 volumes are suitable for a broad range of workloads, including small to medium-sized databases, development and test environments, and boot volumes.
Such volumes offer storage with consistent and low-latency performance, are designed for I/O-intensive applications such as large relational or NoSQL databases, and allow you to choose the level of performance you need.
formerly known as Standard volumes, provide the lowest cost per gigabyte of all Amazon EBS volume types and are ideal for workloads where data is accessed infrequently and applications where the lowest storage cost is important.
Backed by Solid-State Drives (SSDs), General Purpose (SSD) volumes provide the ability to burst to 3,000 IOPS per volume, independent of volume size, to meet the performance needs of most applications and also deliver a consistent baseline of 3 IOPS/GB. General Purpose (SSD) volumes offer the same five nines of availability and durable snapshot capabilities as other volume types. Pricing and performance for General Purpose (SSD) volumes are simple and predictable. You pay for each GB of storage you provision, and there are no additional charges for I/O performed on a volume. Prices start as low as $0.10/GB.
While it is completing, an in-progress snapshot is not affected by ongoing reads and writes to the volume.
You can take a snapshot of an attached volume that is in use. However, snapshots only capture data that has been written to your Amazon EBS volume at the time the snapshot command is issued. This might exclude any data that has been cached by any applications or the operating system. If you can pause any file writes to the volume long enough to take a snapshot, your snapshot should be complete. However, if you can’t pause all file writes to the volume, you should unmount the volume from within the instance, issue the snapshot command, and then remount the volume to ensure a consistent and complete snapshot. You can remount and use your volume while the snapshot status is pending.
S3 would imply changing the application code, Glacier is not applicable as the files are frequently requested, Storage Gateway isn’t for distributing files to end users. CloudFront is the right answer, because we can put it in front of our ASG and leverage a Global Caching feature that will help us distribute the content reliably with dramatically reduced costs (the ASG won’t need to scale as much)
Instance Stores or EBS volumes are local disks and cannot be shared across instances. Here, we need a network file system (NFS), which is exactly what EFS is designed for.
Creating a smaller cluster with the cold data would not decrease the storage cost of Redshift, which will increase as we keep on creating data. Moving the data to S3 glacier will prevent us from being able to query it. Redshift’s internal storage does not have “tiers”. Therefore, we should migrate the data to S3 IA and use Athena (serverless SQL query engine on top of S3) to analyze the cold data.
Amazon Redshift is a fast, scalable data warehouse that makes it simple and cost-effective to analyze all your data across your data warehouse and data lake. Redshift delivers ten times faster performance than other data warehouses by using machine learning, massively parallel query execution, and columnar storage on high-performance disk.
In this scenario, there is a requirement to have a storage service which will be used by a business intelligence application and where the data must be stored in a columnar fashion. Business Intelligence reporting systems is a type of Online Analytical Processing (OLAP) which Redshift is known to support. In addition, Redshift also provides columnar storage unlike the other options. Hence, the correct answer in this scenario is Option 1: Amazon Redshift.
Enables you to run queries against exabytes of data in S3 without having to load or transform any data.
Redshift Spectrum doesn’t use Enhanced VPC Routing.
If you store data in a columnar format, Redshift Spectrum scans only the columns needed by your query, rather than processing entire rows.
If you compress your data using one of Redshift Spectrum’s supported compression algorithms, less data is scanned.
Effective today we are opening up CloudFront and giving you the ability to use the origin server of your choice.
You can now create a CloudFront distribution using a custom origin. Each distribution will can point to an S3 or to a custom origin. This could be another storage service, or it could be something more interesting and more dynamic, such as an EC2 instance or even an Elastic Load Balancer:
Elastic Beanstalk provides an environment to easily deploy and run applications in the cloud.
CloudFormation is a convenient provisioning mechanism for a broad range of AWS resources.
you can optionally connect to your own network, known as virtual private clouds (VPCs)
Amazon Web Services. Amazon Elastic Compute Cloud.
Amazon VPC lets you provision a logically isolated section of the Amazon Web Services (AWS) cloud where you can launch AWS resources in a virtual network that you define. You have complete control over your virtual networking environment, including selection of your own IP address ranges, creation of subnets, and configuration of route tables and network gateways. You can also create a hardware Virtual Private Network (VPN) connection between your corporate datacenter and your VPC and leverage the AWS cloud as an extension of your corporate datacenter.
A subnet is a range of IP addresses in your VPC. You can launch AWS resources into a specified subnet. Use a public subnet for resources that must be connected to the internet, and a private subnet for resources that won’t be connected to the internet.
To protect the AWS resources in each subnet, use security groups and network access control lists (ACL).
Remember that one subnet is mapped into one specific Availability Zone.
A VPC spans all the Availability Zones in the region. After creating a VPC, you can add one or more subnets in each Availability Zone. When you create a subnet, you specify the CIDR block for the subnet, which is a subset of the VPC CIDR block. Each subnet must reside entirely within one Availability Zone and cannot span zones. Availability Zones are distinct locations that are engineered to be isolated from failures in other Availability Zones. By launching instances in separate Availability Zones, you can protect your applications from the failure of a single location. AWS assigns a unique ID to each subnet.
By default, a “default subnet” of your VPC is actually a public subnet, because the main route table sends the subnet’s traffic that is destined for the internet to the internet gateway. You can make a default subnet into a private subnet by removing the route from the destination 0.0.0.0/0 to the internet gateway. However, if you do this, any EC2 instance running in that subnet can’t access the internet.
Instances that you launch into a default subnet receive both a public IPv4 address and a private IPv4 address, and both public and private DNS hostnames. Instances that you launch into a nondefault subnet in a default VPC don’t receive a public IPv4 address or a DNS hostname. You can change your subnet’s default public IP addressing behavior
By default, nondefault subnets have the IPv4 public addressing attribute set to false, and default subnets have this attribute set to true. An exception is a nondefault subnet created by the Amazon EC2 launch instance wizard — the wizard sets the attribute to true.
Newly created instance does not have a public IP address since it was deployed on a nondefault subnet. The other 4 instances are accessible over the Internet because they each have an Elastic IP address attached, unlike the last instance which only has a private IP address. An Elastic IP address is a public IPv4 address, which is reachable from the Internet. If your instance does not have a public IPv4 address, you can associate an Elastic IP address with your instance to enable communication with the Internet.
You must remember that the two services that use a VPC Endpoint Gateway are Amazon S3 and DynamoDB. The rest are VPC Endpoint Interface
NACL is stateless.
• NACL are like a firewall which control traffic from and to subnet
• Default NACL allows everything outbound and everything inbound
• One NACL per Subnet, new Subnets are assigned the Default NACL
• Define NACL rules:
• Rules have a number (1-32766) and higher precedence with a lower number
• E.g. If you define #100 ALLOW
• AWS recommends adding rules by increment of 100
• Newly created NACL will deny everything
• NACL are a great way of blocking a specific IP at the subnet level
Network ACL Basics
- Your VPC automatically comes with a modifiable default network ACL. By default, it allows all inbound and outbound IPv4 traffic and, if applicable, IPv6 traffic.
After creating an IGW, make sure the route tables are updated. Additionally, ensure the security group allow the ICMP protocol for ping requests
NAT Instances would work but won’t scale and you would have to manage them (as they’re EC2 instances). Egress-Only Internet Gateways are for IPv6, not IPv4. Internet Gateways must be deployed in a public subnet. Therefore you must use a NAT Gateway in your public subnet in order to provide internet access to your instances in your private subnets.
You do not need a NAT Gateway nor a NAT instance when the instances are already in public subnet. Remember that a NAT Gateway or a NAT instance is primarily used to enable instances in a private subnet to connect to the Internet or other AWS services, but prevent the Internet from initiating a connection with those instances.
AWS provides flexible infrastructure and services that help customers implement strong DDoS mitigations and create highly available application architectures that follow AWS Best Practices for DDoS Resiliency. These include services such as Amazon Route 53, Amazon CloudFront, Elastic Load Balancing, and AWS WAF to control and absorb traffic, and deflect unwanted requests. These services integrate with AWS Shield, a managed DDoS protection service that provides always-on detection and automatic inline mitigations to safeguard web applications running on AWS.
AWS Shield is a managed DDoS protection service that is available in two tiers: Standard and Advanced. AWS Shield Standard applies always-on detection and inline mitigation techniques, such as deterministic packet filtering and priority-based traffic shaping, to minimize application downtime and latency.
It is included automatically and transparently to your Elastic Load Balancing load balancers, Amazon CloudFront distributions, and Amazon Route 53 resources at no additional cost. When you use these services that include AWS Shield Standard, you receive comprehensive availability protection against all known infrastructure layer attacks. Customers who have the technical expertise to manage their own monitoring and mitigation of application layer attacks can use AWS Shield together with AWS WAF rules to create a comprehensive DDoS attack mitigation strategy.
It provides enhanced DDoS attack detection and monitoring for application-layer traffic to your Elastic Load Balancing load balancers, CloudFront distributions, Amazon Route 53 hosted zones and resources attached to an Elastic IP address, such Amazon EC2 instances. AWS Shield Advanced uses additional techniques to provide granular detection of DDoS attacks, such as resource-specific traffic monitoring to detect HTTP floods or DNS query floods. AWS Shield Advanced includes 24x7 access to the AWS DDoS Response Team (DRT), support experts who apply manual mitigations for more complex and sophisticated DDoS attacks, directly create or update AWS WAF rules, and can recommend improvements to your AWS architectures. AWS WAF is included at no additional cost for resources that you protect with AWS Shield Advanced.
AWS Shield Advanced includes access to near real-time metrics and reports, for extensive visibility into infrastructure layer and application layer DDoS attacks. You can combine AWS Shield Advanced metrics with additional, fine-tuned AWS WAF metrics for a more comprehensive CloudWatch monitoring and alarming strategy. Customers subscribed to AWS Shield Advanced can also apply for a credit for charges that result from scaling during a DDoS attack on protected Amazon EC2, Amazon CloudFront, Elastic Load Balancing, or Amazon Route 53 resources. See the AWS Shield Developer Guide for a detailed comparison of the two AWS Shield offerings.
To add a CIDR block to your VPC, the following rules apply:
-The allowed block size is between a /28 netmask and /16 netmask.
-The CIDR block must not overlap with any existing CIDR block that’s associated with the VPC.
-You cannot increase or decrease the size of an existing CIDR block.
-You have a limit on the number of CIDR blocks you can associate with a VPC and the number of routes you can add to a route table. You cannot associate a CIDR block if this results in you exceeding your limits.
-The CIDR block must not be the same or larger than the CIDR range of a route in any of the VPC route tables. For example, if you have a route with a destination of 10.0.0.0/24 to a virtual private gateway, you cannot associate a CIDR block of the same range or larger. However, you can associate a CIDR block of 10.0.0.0/25 or smaller.
-The first four IP addresses and the last IP address in each subnet CIDR block are not available for you to use, and cannot be assigned to an instance.
IPv4 CIDR block size should be between a /16 netmask (65,536 IP addresses) and /28 netmask (16 IP addresses).
The first four IP addresses and the last IP address in each subnet CIDR block are NOT available for you to use, and cannot be assigned to an instance.
If you’re using AWS Direct Connect to connect to multiple VPCs through a direct connect gateway, the VPCs that are associated with the direct connect gateway must not have overlapping CIDR blocks.
Each subnet must be associated with a route table, which specifies the allowed routes for outbound traffic leaving the subnet.
Every subnet that you create is automatically associated with the main route table for the VPC.
You can change the association, and you can change the contents of the main route table.
You can allow an instance in your VPC to initiate outbound connections to the internet over IPv4 but prevent unsolicited inbound connections from the internet using a NAT gateway or NAT instance.
To initiate outbound-only communication to the internet over IPv6, you can use an egress-only internet gateway
You can associate one or more (up to five) security groups to an instance in your VPC.
If you don’t specify a security group, the instance automatically belongs to the default security group.
When you create a security group, it has no inbound rules. By default, it includes an outbound rule that allows all outbound traffic.
Network Access Control Lists — control inbound and outbound traffic for your
Each subnet in your VPC must be associated with a network ACL. If none is associated, automatically associated with the default network ACL.
You can associate a network ACL with multiple subnets; however, a subnet can be associated with only one network ACL at a time.
A network ACL contains a numbered list of rules that is evaluated in order, starting with the lowest numbered rule, to determine whether traffic is allowed in or out of any subnet associated with the network ACL.
The default network ACL is configured to allow all traffic to flow in and out of the subnets to which it is associated.
Amazon security groups and network ACLs don’t filter traffic to or from link-local addresses or AWS-reserved IPv4 addresses. Flow logs do not capture IP traffic to or from these addresses.
- Security group operates at the instance level while NetACL at the subnet level
- Security group support allow rules only while ACL allows rules and deny rules
- Security group is stateful, return traffic is automatcially allowed, regardless of any rules.
While ACL is stateless, return traffic must be explicitely allowed by rules
- Security group evalaute all rules before deciding whether to allow traffic, while ACL process rules in number order when deciding whether to allow traffic.
- Security group appiles to an insatnce only while ACL appies to all instances in teh subect it’s associated with.
A network access control list (ACL) is an optional layer of security for your VPC that acts as a firewall for controlling traffic in and out of one or more subnets. You might set up network ACLs with rules similar to your security groups in order to add an additional layer of security to your VPC.
Network ACL Rules are evaluated by rule number,
from lowest to highest, and
executed immediately when a matching allow/deny rule is founds.
To enable access to or from the Internet for instances in a VPC subnet, you must do the following:
- Attach an Internet Gateway to your VPC
- Ensure that your subnet’s route table points to the Internet Gateway.
- Ensure that instances in your subnet have a globally unique IP address (public IPv4 address, Elastic IP address, or IPv6 address).
- Ensure that your network access control and security group rules allow the relevant traffic to flow to and from your instance
Enable instances in a private subnet to connect to the internet or other AWS services, but prevent the internet from initiating connections with the instances.
You must specify the public subnet in which the NAT gateway should reside.
You must specify an Elastic IP address to associate with the NAT gateway when you create it.
You can optionally connect your VPC to your own corporate data center using an IPsec AWS managed VPN connection, making the AWS Cloud an extension of your data center.
A VPN connection consists of:
- a virtual private gateway (which is the VPN concentrator on the Amazon side of the VPN connection) attached to your VPC.
- a customer gateway (which is a physical device or software appliance on your side of the VPN connection) located in your data center.
By default, instances that you launch into a virtual private cloud (VPC) can’t communicate with your own network. You can enable access to your network from your VPC by attaching a virtual private gateway to the VPC, creating a custom route table, updating your security group rules, and creating an AWS managed VPN connection.
Although the term VPN connection is a general term, in the Amazon VPC documentation, a VPN connection refers to the connection between your VPC and your own network. AWS supports Internet Protocol security (IPsec) VPN connections.
A customer gateway is a physical device or software application on your side of the VPN connection.
To create a VPN connection, you must create a customer gateway resource in AWS, which provides information to AWS about your customer gateway device. Next, you have to set up an Internet-routable IP address (static) of the customer gateway’s external interface.
The following diagram illustrates single VPN connections. The VPC has an attached virtual private gateway, and your remote network includes a customer gateway, which you must configure to enable the VPN connection. You set up the routing so that any traffic from the VPC bound for your network is routed to the virtual private gateway.
With AWS Site-to-Site VPN, you can connect to an Amazon VPC in the cloud the same way you connect to your branches. AWS Site-to-Site VPN establishes secure and private sessions with IP Security (IPSec) and Transport Layer Security (TLS) tunnels. a VPN connection is that you will be able to connect your Amazon VPC to other remote networks securely. Although it is true that a VPN provides a cost-effective, hybrid connection from your VPC to your on-premises data centers, it certainly does not bypasses the public Internet. A VPN connection actually goes through the public Internet, unlike the AWS Direct Connect connection which has a direct and dedicated connection to your on-premises network.
AWS Direct Connect connection which has a direct and dedicated connection to your on-premises network.
It enables you to privately connect your VPC to supported AWS services, services hosted by other AWS accounts (VPC endpoint services), and supported AWS Marketplace partner services. You do not require an internet gateway, NAT device, public IP address, AWS Direct Connect connection, or VPN connection to communicate with the service. Traffic between your VPC and the service does not leave the Amazon network.
You can create a VPC peering connection between your VPCs, or with a VPC in another AWS account, and enable routing of traffic between the VPCs using private IP addresses. You cannot create a VPC peering connection between VPCs that have overlapping CIDR blocks.
Applications in an Amazon VPC can securely access AWS PrivateLink endpoints across VPC peering connections. The support of VPC peering by AWS PrivateLink makes it possible for customers to privately connect to a service even if that service’s endpoint resides in a different Amazon VPC that is connected using VPC peering.
AWS PrivateLink endpoints can now be accessed across both intra- and inter-region VPC peering connections.
You can do the following to provide a highly available, fault-tolerant network connection:
- Establish a hardware VPN over the Internet between the VPC and the on-premises network.
- Establish another AWS Direct Connect connection and private virtual interface in the same AWS region.
First, the Network ACL should be properly set to allow communication between the two subnets. The security group should also be properly configured so that your web server can communicate with the database server. Hence, options 1 and 4 are the correct answers:
Check if all security groups are set to allow the application host to communicate to the database on the right port and protocol.
Check the Network ACL if it allows communication between the two subnets.
Option 2 is incorrect because the EC2 instances do not need to be of the same class in order to communicate with each other.
Option 3 is incorrect because an Internet gateway is primarily used to communicate to the Internet.
Option 5 is incorrect because Placement Group is mainly used to provide low-latency network performance necessary for tightly-coupled node-to-node communication.
AWS WAF is a web application firewall that helps protect web applications from common web exploits that could affect application availability, compromise security, or consume excessive resources. You can use AWS WAF to define customizable web security rules that control which traffic accesses your web applications. If you use AWS Shield Advanced, you can use AWS WAF at no extra cost for those protected resources and can engage the DRT to create WAF rules.
AWS WAF rules use conditions to target specific requests and trigger an action, allowing you to identify and block common DDoS request patterns and effectively mitigate a DDoS attack. These include size constraint conditions to block a web request based on the length of its query string or request body, and geographic match conditions to implement geo restriction (also known as geoblocking) on requests that originate from specific countries.
AWS SSM is parameter store.
To automatically distribute incoming application traffic across multiple instances, use Elastic Load Balancing.
For HA, even though our ASG is deployed across 3 AZ, the minimum capacity to be highly available is 2. Finally, we can save costs by reserving these two instances as we know they’ll be up and running at any time
Path based routing and host based routing are only available for the Application Load Balancer (ALB). Deploying an NGINX load balancer on EC2 would work but would suffer management and scaling issues. Read more here: https://aws.amazon.com/blogs/aws/new-host-based-routing-support-for-aws-application-load-balancers/
Adding the entire CIDR of the ALB would work, but wouldn’t guarantee that only the ALB can access the EC2 instances that are part of the ASG. Here, the right solution is to add a rule on the ASG security group to allow incoming traffic from the security group configured for the ALB.
support for multiple TLS/SSL certificates on Application Load Balancers (ALB) using Server Name Indication (SNI). You can now host multiple TLS secured applications, each with its own TLS certificate, behind a single load balancer. In order to use SNI, all you need to do is bind multiple certificates to the same secure listener on your load balancer. ALB will automatically choose the optimal TLS certificate for each client. These new features are provided at no additional charge.
One of our most frequent requests on forums, reddit, and in my e-mail inbox has been to use the Server Name Indication (SNI) extension of TLS to choose a certificate for a client. Since TLS operates at the transport layer, below HTTP, it doesn’t see the hostname requested by a client. SNI works by having the client tell the server “This is the domain I expect to get a certificate for” when it first connects. The server can then choose the correct certificate to respond to the client. All modern web browsers and a large majority of other clients support SNI. In fact, today we see SNI supported by over 99.5% of clients connecting to CloudFront.
RDS stands for Relational Database Service
RDS Read Replicas for read scalability
- Up to 5 Read Replicas
- Within AZ, Cross AZ or Cross Region
- Replication is ASYNC, so reads are eventually consistent
- Replicas can be promoted to their own DB
- Applications must update the connection string to leverage read replicas
Amazon RDS Multi-AZ deployments provide enhanced availability and durability for Database (DB) Instances, making them a natural fit for production database workloads. When you provision a Multi-AZ DB Instance, Amazon RDS automatically creates a primary DB Instance and synchronously replicates the data to a standby instance in a different Availability Zone (AZ). Each AZ runs on its own physically distinct, independent infrastructure, and is engineered to be highly reliable. In case of an infrastructure failure, Amazon RDS performs an automatic failover to the standby (or to a read replica in the case of Amazon Aurora), so that you can resume database operations as soon as the failover is complete. Since the endpoint for your DB Instance remains the same after a failover, your application can resume database operation without the need for manual administrative intervention.
Use security groups to control what IP addresses or Amazon EC2 instances can connect to your databases on a DB instance.
Run your DB instance in an Amazon Virtual Private Cloud (VPC) for the greatest possible network access control.
Your VPC must have at least two subnets. These subnets must be in two different Availability Zones in the region where you want to deploy your DB instance.
If you want your DB instance in the VPC to be publicly accessible, you must enable the VPC attributes DNS hostnames and DNS resolution.
Amazon RDS automatically performs a failover in the event of any of the following:
Loss of availability in primary Availability Zone
Loss of network connectivity to primary
Compute unit failure on primary
Storage failure on primary
IAM Auth is not supported by ElastiCache
To monitor basic statistics for your instances and Amazon EBS volumes, use Amazon CloudWatch.
Amazon Web Services. Amazon Elastic Compute Cloud .
Disabling the Termination from the ASG would prevent our ASG to be Elastic and impact our costs. Making a snapshot of the EC2 instance before it gets terminated could work but it’s tedious, not elastic and very expensive, as all we’re interested about are log files. Using AWS Lambda would be extremely hard to use for this task. Here, the natural and by far easiest solution would be to use the CloudWatch Logs agents on the EC2 instances to automatically send log files into CloudWatch, so we can analyze them in the future easily should any problems arise.
Using Amazon CloudWatch alarm actions, you can create alarms that automatically stop, terminate, reboot, or recover your EC2 instances. You can use the stop or terminate actions to help you save money when you no longer need an instance to be running. You can use the reboot and recover actions to automatically reboot those instances or recover them onto new hardware if a system impairment occurs.
you can use Amazon CloudWatch to monitor the database and then Amazon SNS to send the emails to the Operations team. Take note that you should use SNS instead of SES (Simple Email Service) when you want to monitor your EC2 instances.
CloudWatch collects monitoring and operational data in the form of logs, metrics, and events, providing you with a unified view of AWS resources, applications, and services that run on AWS, and on-premises servers.
SNS is a highly available, durable, secure, fully managed pub/sub messaging service that enables you to decouple microservices, distributed systems, and serverless applications.
Option 1 is incorrect. SES is a cloud-based email sending service designed to send notification and transactional emails.
Option 3 is incorrect. SQS is a fully-managed message queuing service. It does not monitor applications nor send email notifications unlike SES.
Option 4 is incorrect. Route 53 is a highly available and scalable cloud Domain Name System (DNS) web service. It does not monitor applications nor send email notifications.
Q: What API types are supported by Amazon API Gateway?
Amazon API Gateway offers two options to create RESTful APIs, HTTP APIs (Preview) and REST APIs, as well as an option to create WebSocket APIs.
HTTP API: HTTP APIs, currently available in Preview, are optimized for building APIs that proxy to AWS Lambda functions or HTTP backends, making them ideal for serverless workloads. They do not currently offer API management functionality.
REST API: REST APIs offer API proxy functionality and API management features in a single solution. REST APIs offer API management features such as usage plans, API keys, publishing, and monetizing APIs.
WebSocket API: WebSocket APIs maintain a persistent connection between connected clients to enable real-time message communication. With WebSocket APIs in API Gateway, you can define backend integrations with AWS Lambda functions, Amazon Kinesis, or any HTTP endpoint to be invoked when messages are received from the connected clients.
To monitor the calls made to the Amazon EC2 API for your account, including calls made by the AWS Management Console, command line tools, and other services, use AWS CloudTrail.
In general, to analyze any API calls made within your AWS account, you should use CloudTrail
Set up a new CloudTrail trail in a new S3 bucket using the AWS CLI and also pass both the –is-multi-region-trail and –include-global-service-events parameters then encrypt log files using KMS encryption. Apply Multi Factor Authentication (MFA) Delete on the S3 bucket and ensure that only authorized users can access the logs by configuring the bucket policies.
the first copy of management events is free.
Management event activity is recorded by AWS CloudTrail for the last 90 days, and can be viewed and searched free of charge from the AWS CloudTrail console, or by using the AWS CLI.
• ECS is a container orchestration service
• ECS helps you run Docker containers on EC2 machines
• ECS is complicated, and made of:
• “ECS Core”: Running ECS on user-provisioned EC2 instances
• Fargate: Running ECS tasks on AWS-provisioned compute (serverless)
• EKS: Running ECS on AWS-powered Kubernetes (running on EC2)
• ECR: Docker Container Registry hosted by AWS
• ECS & Docker are very popular for microservices
• For now, for the exam, only “ECS Core” & ECR is in scope
• IAM security and roles at the ECS task level
• ECS cluster: set of EC2 instances
• ECS service: applications definitions running on ECS cluster
• ECS tasks + definition: containers running to create the application
• ECS IAM roles: roles assigned to tasks to interact with AWS
• Application Load Balancer (ALB) has a direct integration feature with ECS called “port mapping”, This allows you to run multiple instances of the same application on the same EC2 machine
Dynamic Port Mapping is available for the Application Load Balancer. A reverse proxy solution would work but would be too much work to manage. Here the ALB has a feature that provides a direct dynamic port mapping feature and integration with the ECS service so we will leverage that. Read more here: https://aws.amazon.com/premiumsupport/knowledge-center/dynamic-port-mapping-ecs/
• Run an EC2 instance, install the ECS agent with ECS config file
• Or use an ECS-ready Linux AMI (still need to modify config file) • ECS Config file is at /etc/ecs/ecs.config
• Store, managed and deploy your containers on AWS
• Fully integrated with IAM & ECS
• Sent over HTTPS (encryption in flight) and encrypted at rest
Amazon ECS enables you to inject sensitive data into your containers by storing your sensitive data in either AWS Secrets Manager secrets or AWS Systems Manager Parameter Store parameters and then referencing them in your container definition. This feature is supported by tasks using both the EC2 and Fargate launch types.
To use this feature, you must have the Amazon ECS task execution role and reference it in your task definition. This allows the container agent to pull the necessary AWS Systems Manager or Secrets Manager resources. For more information, see Amazon ECS Task Execution IAM Role.
To provide access to the AWS Systems Manager Parameter Store parameters that you create, manually add the following permissions as an inline policy to the task execution role. For more information, see Adding and Removing IAM Policies.
ssm:GetParameters—Required if you are referencing a Systems Manager Parameter Store parameter in a task definition.
secretsmanager:GetSecretValue—Required if you are referencing a Secrets Manager secret either directly or if your Systems Manager Parameter Store parameter is referencing a Secrets Manager secret in a task definition.
kms:Decrypt—Required only if your secret uses a custom KMS key and not the default key. The ARN for your custom key should be added as a resource.
AWS Lambda functions time out after 15 minutes, and are not usually meant for long running jobs.
Although Lambda encrypts the environment variables in your function by default, the sensitive information would still be visible to other users who have access to the Lambda console. This is because Lambda uses a default KMS key to encrypt the variables, which is usually accessible by other users. The best option in this scenario is to use encryption helpers to secure your environment variables.
Enabling SSL would encrypt data only when in-transit. Your other teams would still be able to view the plaintext at-rest. Use AWS KMS instead.
Option 3 is incorrect since, as mentioned, Lambda does provide encryption functionality of environment variables.
You upload your application code in the form of one or more Lambda functions. Lambda stores code in Amazon S3 and encrypts it at rest.
A layer is a ZIP archive that contains libraries, a custom runtime, or other dependencies. Use layers to manage your function’s dependencies independently and keep your deployment package small.
Lambda supports synchronous and asynchronous invocation of a Lambda function. You can control the invocation type only when you invoke a Lambda function (referred to as on-demand invocation).
An event source is the entity that publishes events, and a Lambda function is the custom code that processes the events.
Event source mapping maps an event source to a Lambda function. It enables automatic invocation of your Lambda function when events occur.
If you’re using the AWS Lambda compute platform, you must choose one of the following deployment configuration types to specify how traffic is shifted from the original AWS Lambda function version to the new AWS Lambda function version:
-Canary: Traffic is shifted in two increments. You can choose from predefined canary options that specify the percentage of traffic shifted to your updated Lambda function version in the first increment and the interval, in minutes, before the remaining traffic is shifted in the second increment.
-Linear: Traffic is shifted in equal increments with an equal number of minutes between each increment. You can choose from predefined linear options that specify the percentage of traffic shifted in each increment and the number of minutes between each increment.
-All-at-once: All traffic is shifted from the original Lambda function to the updated Lambda function version at once.
Lets you run Lambda functions to customize content that CloudFront delivers, executing the functions in AWS locations closer to the viewer. The functions run in response to CloudFront events, without provisioning or managing servers.
Need to define two terms:
• RPO: Recovery Point Objective
• RTO: Recover y Time Objective
Disaster Recovery Strategies
• Backup and Restore
• Pilot Light
• Warm Standby
• Hot Site / Multi Site Approach
Simple Records do not have health checks, here the most likely issue is that the TTL is still in effect so you have to wait until it expires for the new users to perform another DNS query and get the value for your new Load Balancer.
ElastiCache / RDS / Neptune are not serverless databases. DynamoDB is serverless, single digit latency and horizontally scales.
DynamoDB Streams will contain a stream of all the changes that happen to a DynamoDB table. It can be chained with a Lambda function that will be triggered to react to these changes, one of which being a developer’s milestone. DAX is a caching layer
DynamoDB Auto Scaling is primarily used to automate capacity management for your tables and global secondary indexes.
DAX will be transparent and won’t require an application refactoring, and will cache the “hot keys”. ElastiCache could also be a solution, but it will require a lot of refactoring work on the AWS Lambda side.
DynamoDB is horizontally scalable, has a DynamoDB streams capability and is multi AZ by default. On top of it, we can adjust the RCU and WCU automatically using Auto Scaling.
DynamoDB supports two types of primary keys:
Partition key: A simple primary key, composed of one attribute known as the partition key. Attributes in DynamoDB are similar in many ways to fields or columns in other database systems.
Partition key and sort key: Referred to as a composite primary key, this type of key is composed of two attributes. The first attribute is the partition key, and the second attribute is the sort key. Following is an example.
Use high-cardinality attributes. These are attributes that have distinct values for each item, like e-mailid, employee_no, customerid, sessionid, orderid, and so on.
Use composite attributes. Try to combine more than one attribute to form a unique key, if that meets your access pattern. For example, consider an orders table with customerid+productid+countrycode as the partition key and order_date as the sort key.
Cache the popular items when there is a high volume of read traffic using Amazon DynamoDB Accelerator (DAX). The cache acts as a low-pass filter, preventing reads of unusually popular items from swamping partitions. For example, consider a table that has deals information for products. Some deals are expected to be more popular than others during major sale events like Black Friday or Cyber Monday. DAX is a fully managed, in-memory cache for DynamoDB that doesn’t require developers to manage cache invalidation, data population, or cluster management. DAX also is compatible with DynamoDB API calls, so developers can incorporate it more easily into existing applications.
Add random numbers or digits from a predetermined range for write-heavy use cases. Suppose that you expect a large volume of writes for a partition key (for example, greater than 1000 1 K writes per second). In this case, use an additional prefix or suffix (a fixed number from predetermined range, say 1–10) and add it to the partition key.
When the word durability pops out, the first service that should come to your mind is Amazon S3. Since this service is not available in the answer options, we can look at the other data store available which is Amazon DynamoDB.
DynamoDB is durable, scalable, and highly available data store which can be used for real-time tabulation. You can also use AppSync with DynamoDB to make it easy for you to build collaborative apps that keep shared data updated in real time. You just specify the data for your app with simple code statements and AWS AppSync manages everything needed to keep the app data updated in real time. This will allow your app to access data in Amazon DynamoDB, trigger AWS Lambda functions, or run Amazon Elasticsearch queries and combine data from these services to provide the exact data you need for your app.
Option 2 is incorrect as Amazon Redshift is mainly used as a data warehouse and for online analytic processing (OLAP). Although this service can be used for this scenario, DynamoDB is still the top choice given its better durability and scalability.
Options 3 and 4 are possible answers in this scenario, however, DynamoDB is much more suitable for simple mobile apps which do not have complicated data relationships compared with enterprise web applications. The scenario says that the mobile app will be used from around the world, which is why you need a data storage service which can be supported globally. It would be a management overhead to implement multi-region deployment for your RDS and Aurora database instances compared to using the Global table feature of DynamoDB.
Aurora Read Replicas can be deployed globally
Amazon Aurora typically involves a cluster of DB instances instead of a single instance. Each connection is handled by a specific DB instance. When you connect to an Aurora cluster, the host name and port that you specify point to an intermediate handler called an endpoint. Aurora uses the endpoint mechanism to abstract these connections. Thus, you don’t have to hardcode all the hostnames or write your own logic for load-balancing and rerouting connections when some DB instances aren’t available.
For certain Aurora tasks, different instances or groups of instances perform different roles. For example, the primary instance handles all data definition language (DDL) and data manipulation language (DML) statements. Up to 15 Aurora Replicas handle read-only query traffic.
Using endpoints, you can map each connection to the appropriate instance or group of instances based on your use case. For example, to perform DDL statements you can connect to whichever instance is the primary instance. To perform queries, you can connect to the reader endpoint, with Aurora automatically performing load-balancing among all the Aurora Replicas. For clusters with DB instances of different capacities or configurations, you can connect to custom endpoints associated with different subsets of DB instances. For diagnosis or tuning, you can connect to a specific instance endpoint to examine details about a specific DB instance.
An endpoint is represented as an Aurora-specific URL that contains a host address and a port. The following types of endpoints are available from an Aurora DB cluster.
A cluster endpoint for an Aurora DB cluster that connects to the current primary DB instance for that DB cluster. This endpoint is the only one that can perform write operations such as DDL statements. Because of this, the cluster endpoint is the one that you connect to when you first set up a cluster or when your cluster only contains a single DB instance.
Each Aurora DB cluster has one cluster endpoint and one primary DB instance.
You use the cluster endpoint for all write operations on the DB cluster, including inserts, updates, deletes, and DDL changes. You can also use the cluster endpoint for read operations, such as queries.
The cluster endpoint provides failover support for read/write connections to the DB cluster. If the current primary DB instance of a DB cluster fails, Aurora automatically fails over to a new primary DB instance. During a failover, the DB cluster continues to serve connection requests to the cluster endpoint from the new primary DB instance, with minimal interruption of service.
A reader endpoint for an Aurora DB cluster connects to one of the available Aurora Replicas for that DB cluster. Each Aurora DB cluster has one reader endpoint. If there is more than one Aurora Replica, the reader endpoint directs each connection request to one of the Aurora Replicas.
The reader endpoint provides load-balancing support for read-only connections to the DB cluster. Use the reader endpoint for read operations, such as queries. You can’t use the reader endpoint for write operations.
A custom endpoint for an Aurora cluster represents a set of DB instances that you choose. When you connect to the endpoint, Aurora performs load balancing and chooses one of the instances in the group to handle the connection. You define which instances this endpoint refers to, and you decide what purpose the endpoint serves.
An Aurora DB cluster has no custom endpoints until you create one. You can create up to five custom endpoints for each provisioned Aurora cluster. You can’t use custom endpoints for Aurora Serverless clusters.
The custom endpoint provides load-balanced database connections based on criteria other than the read-only or read-write capability of the DB instances. For example, you might define a custom endpoint to connect to instances that use a particular AWS instance class or a particular DB parameter group. Then you might tell particular groups of users about this custom endpoint. For example, you might direct internal users to low-capacity instances for report generation or ad hoc (one-time) querying, and direct production traffic to high-capacity instances.
Instead of using one DB instance for each specialized purpose and connecting to its instance endpoint, you can have multiple groups of specialized DB instances. In this case, each group has its own custom endpoint. This way, Aurora can perform load balancing among all the instances dedicated to tasks such as reporting or handling production or internal queries. The custom endpoints provide load balancing and high availability for each group of DB instances within your cluster. If one of the DB instances within a group becomes unavailable, Aurora directs subsequent custom endpoint connections to one of the other DB instances associated with the same endpoint.
An instance endpoint connects to a specific DB instance within an Aurora cluster. Each DB instance in a DB cluster has its own unique instance endpoint. So there is one instance endpoint for the current primary DB instance of the DB cluster, and there is one instance endpoint for each of the Aurora Replicas in the DB cluster.
The instance endpoint provides direct control over connections to the DB cluster, for scenarios where using the cluster endpoint or reader endpoint might not be appropriate. For example, your client application might require more fine-grained load balancing based on workload type. In this case, you can configure multiple clients to connect to different Aurora Replicas in a DB cluster to distribute read workloads.
Amazon Kinesis is the streaming data platform of AWS and has four distinct services under it: Kinesis Data Firehose, Kinesis Data Streams, Kinesis Video Streams, and Amazon Kinesis Data Analytics. For a specific use case of the requirement by the question, use Kinesis Data Firehose.
SQS FIFO will not work here as they cannot sustain thousands of messages per second. SNS cannot be used for data streaming. Lambda isn’t meant to retain data. Kinesis is the right answer here, with providing a partition key in our message we can guarantee ordering for a specific sensor, even if our stream is sharded
Amazon Macie is mainly used as a security service that uses machine learning to automatically discover, classify, and protect sensitive data in AWS. As a security feature of AWS, it does not meet the requirements of being able to load and stream data into data stores for analytics. You have to use Kinesis Data Firehose instead.
Data Producer – An application that typically emits data records as they are generated to a Kinesis data stream. Data producers assign partition keys to records. Partition keys ultimately determine which shard ingests the data record for a data stream.
Data Consumer – A distributed Kinesis application or AWS service retrieving data from all shards in a stream as it is generated. Most data consumers are retrieving the most recent data in a shard, enabling real-time analytics or handling of data.
Data Stream – A logical grouping of shards. There are no bounds on the number of shards within a data stream. A data stream will retain data for 24 hours, or up to 7 days when extended retention is enabled.
A shard is an append-only log and a unit of streaming capability. A shard contains an ordered sequence of records ordered by arrival time.
Add or remove shards from your stream dynamically as your data throughput changes.
One shard can ingest up to 1000 data records per second, or 1MB/sec. Add more shards to increase your ingestion capability.
When consumers use enhanced fan-out, one shard provides 1MB/sec data input and 2MB/sec data output for each data consumer registered to use enhanced fan-out.
When consumers do not use enhanced fan-out, a shard provides 1MB/sec of input and 2MB/sec of data output, and this output is shared with any consumer not using enhanced fan-out.
You will specify the number of shards needed when you create a stream and can change the quantity at any time.
A record is the unit of data stored in a Kinesis stream. A record is composed of a sequence number, partition key, and data blob.
A data blob is the data of interest your data producer adds to a stream. The maximum size of a data blob is 1 MB.
A partition key is typically a meaningful identifier, such as a user ID or timestamp. It is specified by your data producer while putting data into a Kinesis data stream, and useful for consumers as they can use the partition key to replay or build a history associated with the partition key.
The partition key is also used to segregate and route data records to different shards of a stream.
A sequence number is a unique identifier for each data record. Sequence number is assigned by Kinesis Data Streams when a data producer calls PutRecord or PutRecords API to add data to a Kinesis data stream.
You can monitor shard-level metrics in Kinesis Data Streams.
You can monitor your data streams in Amazon Kinesis Data Streams using CloudWatch, Kinesis Agent, Kinesis libraries.
Log API calls with CloudTrail.
You can specify a batch size or batch interval to control how quickly data is uploaded to destinations. Additionally, you can specify if data should be compressed.
You can configure Kinesis Data Firehose to prepare your streaming data before it is loaded to data stores. Kinesis Data Firehose provides pre-built Lambda blueprints for converting common data sources such as Apache logs and system logs to JSON and CSV formats. You can use these pre-built blueprints without any change, or customize them further, or write your own custom functions.
When you create an AWS Elastic Beanstalk environment, you can specify an Amazon Machine Image (AMI) to use instead of the standard Elastic Beanstalk AMI included in your platform version. A custom AMI can improve provisioning times when instances are launched in your environment if you need to install a lot of software that isn’t included in the standard AMIs. Read more here: https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/using-features.customenv.html
SNS, SQS and Kinesis are AWS’ proprietary technologies and do not come with MQTT compatibility. Here the only possible answer is Amazon MQ
Analyze and debug production, distributed applications
AWS X-Ray helps developers analyze and debug production, distributed applications, such as those built using a microservices architecture. With X-Ray, you can understand how your application and its underlying services are performing to identify and troubleshoot the root cause of performance issues and errors. X-Ray provides an end-to-end view of requests as they travel through your application, and shows a map of your application’s underlying components. You can use X-Ray to analyze both applications in development and in production, from simple three-tier applications to complex microservices applications consisting of thousands of services.
An ElastiCache for Redis node is the smallest building block of an Amazon ElastiCache for Redis deployment. Each ElastiCache for Redis node supports the Redis protocol and has its own DNS name and port. Multiple types of ElastiCache for Redis nodes are supported, each with varying amount of CPU capability, and associated memory. An ElastiCache for Redis node may take on a primary or a read replica role. A primary node can be replicated to multiple read replica nodes. An ElastiCache for Redis cluster is a collection of one or more ElastiCache for Redis nodes of the same role; the primary node will be in the primary cluster and the read replica node will be in a read replica cluster. At this time a cluster can only have one node. In the future, we will increase this limit. A cluster manages a logical key space, where each node is responsible for a part of the key space. Most of your management operations will be performed at the cluster level. An ElastiCache for Redis replication group encapsulates the primary and read replica clusters for a Redis installation. A replication group will have only one primary cluster and zero or many read replica clusters. All nodes within a replication group (and consequently cluster) will be of the same node type, and have the same parameter and security group settings.
Yes, with Amazon ElastiCache for Redis you can create a read replica in another AWS Availability Zone. Upon a failure of the primary node, we will provision a new primary node. In scenarios where the primary node cannot be provisioned, you can decide which read replica to promote to be the new primary.
An ElastiCache for Redis replication group consists of a primary and up to five read replicas. Redis asynchronously replicates the data from the primary to the read replicas. During certain types of planned maintenance, or in the unlikely event of ElastiCache node failure or Availability Zone failure, Amazon ElastiCache will automatically detect the failure of a primary, select a read replica, and promote it to become the new primary. ElastiCache also propagates the DNS changes of the promoted read replica, so if your application is writing to the primary node endpoint, no endpoint change will be needed.
Encryption in-transit, encryption at-rest, and Redis AUTH are all opt-in features. At the time of Redis cluster creation via the console or command line interface, you can specify if you want to enable encryption and Redis AUTH and can proceed to provide an authentication token for communication with the Redis cluster. Once the cluster is setup with encryption enabled, ElastiCache seamlessly manages certificate expiration and renewal without requiring any additional action from the application. Additionally, the Redis clients need to support TLS to avail of the encrypted in-transit traffic.
Yes, Amazon ElastiCache for Redis supports Redis passwords via Redis AUTH feature. It is an opt-in feature available in ElastiCache for Redis version 3.2.6 onwards. You must enable encryption in-transit to use Redis AUTH on your ElastiCache for Redis cluster.
ElastiCache for Redis at-rest encryption is an optional feature to increase data security by encrypting on-disk data. When enabled on a replication group, it encrypts the following aspects:
Disk during sync, backup and swap operations
Backups stored in Amazon S3
ElastiCache for Redis offers default (service managed) encryption at rest, as well as ability to use your own symetric customer managed customer master keys in AWS Key Management Service (KMS).
Manage keys used for encrypted DB instances using the AWS KMS. KMS encryption keys are specific to the region that they are created in.
You can bring part or all of your public IPv4 address range from your on-premises network to your AWS account. You continue to own the address range, but AWS advertises it on the Internet. After you bring the address range to AWS, it appears in your account as an address pool. You can create an Elastic IP address from your address pool and use it with your AWS resources, such as EC2 instances, NAT gateways, and Network Load Balancers. This is also called “Bring Your Own IP Addresses (BYOIP)”.
To ensure that only you can bring your address range to your AWS account, you must authorize Amazon to advertise the address range and provide proof that you own the address range.
A Route Origin Authorization (ROA) is a document that you can create through your Regional internet registry (RIR), such as the American Registry for Internet Numbers (ARIN) or Réseaux IP Européens Network Coordination Centre (RIPE). It contains the address range, the ASNs that are allowed to advertise the address range, and an expiration date. Hence, Option 3 is the correct answer.
The ROA authorizes Amazon to advertise an address range under a specific AS number. However, it does not authorize your AWS account to bring the address range to AWS. To authorize your AWS account to bring an address range to AWS, you must publish a self-signed X509 certificate in the RDAP remarks for the address range. The certificate contains a public key, which AWS uses to verify the authorization-context signature that you provide. You should keep your private key secure and use it to sign the authorization-context message.
Option 1 is incorrect because you cannot map the IP address of your on-premises network, which you are migrating to AWS, to an EIP address of your VPC. To satisfy the requirement, you must authorize Amazon to advertise the address range that you own.
Option 2 is incorrect because the IP match condition in CloudFront is primarily used in allowing or blocking the incoming web requests based on the IP addresses that the requests originate from. This is the opposite of what is being asked in the scenario, where you have to migrate your suite of applications from your on-premises network and advertise the address range that you own in your VPC.
Option 4 is incorrect because you don’t need to submit an AWS request in order to do this. You can simply create a Route Origin Authorization (ROA) then once done, provision and advertise your whitelisted IP address range to your AWS account.
It is a managed cloud service that lets connected devices easily and securely interact with cloud applications and other devices. AWS IoT Core provides secure communication and data processing across different kinds of connected devices and locations so you can easily build IoT applications.
You cannot set a priority to individual items in the SQS queue.
In this scenario, it is stated that the SQS queue is configured with the maximum message retention period. The maximum message retention in SQS is 14 days, there will be no missing messages.
The queue can contain an unlimited number of messages, not just 10,000 messages.
In Amazon SQS, you can configure the message retention period to a value from 1 minute to 14 days. The default is 4 days. Once the message retention limit is reached, your messages are automatically deleted.
A single Amazon SQS message queue can contain an unlimited number of messages. However, there is a 120,000 limit for the number of inflight messages for a standard queue and 20,000 for a FIFO queue. Messages are inflight after they have been received from the queue by a consuming component, but have not yet been deleted from the queue.
SWF workflow defines all the activities in the workflow.
The purpose of a decision task tells the decider the state of the workflow execution. The decider can be viewed as a special type of worker. Like workers, it can be written in any language and asks Amazon SWF for tasks. However, it handles special tasks called decision tasks.
Amazon SWF issues decision tasks whenever a workflow execution has transitions such as an activity task completing or timing out. A decision task contains information on the inputs, outputs, and current state of previously initiated activity tasks. Your decider uses this data to decide the next steps, including any new activity tasks, and returns those to Amazon SWF. Amazon SWF in turn enacts these decisions, initiating new activity tasks where appropriate and monitoring them.
By responding to decision tasks in an ongoing manner, the decider controls the order, timing, and concurrency of activity tasks and consequently the execution of processing steps in the application. SWF issues the first decision task when an execution starts. From there on, Amazon SWF enacts the decisions made by your decider to drive your execution. The execution continues until your decider makes a decision to complete it.
An activity task tells the worker to perform a function
A single task in the workflow represents a single task in the workflow.
Amazon Simple Queue Service (SQS) and Amazon Simple Workflow Service (SWF) are the services that you can use for creating a decoupled architecture in AWS. Decoupled architecture is a type of computing architecture that enables computing components or layers to execute independently while still interfacing with each other.
Amazon SQS offers reliable, highly-scalable hosted queues for storing messages while they travel between applications or microservices. Amazon SQS lets you move data between distributed application components and helps you decouple these components. Amazon SWF is a web service that makes it easy to coordinate work across distributed application components.
Power your applications with the right data, from one or more data sources, at global scale
AWS AppSync simplifies application development by letting you create a flexible API to securely access, manipulate, and combine data from one or more data sources. AppSync is a managed service that uses GraphQL to make it easy for applications to get exactly the data they need.
With AppSync, you can build scalable applications, including those requiring real-time updates, on a range of data sources such as NoSQL data stores, relational databases, HTTP APIs, and your custom data sources with AWS Lambda. For mobile and web apps, AppSync additionally provides local data access when devices go offline, and data synchronization with customizable conflict resolution, when they are back online.
Start effortlessly; scale with your business
Get started in minutes directly from your IDE of choice (such as Xcode, Android Studio, VS Code), leverage the intuitive AWS AppSync management console, or use AWS Amplify CLI to automatically generate your API and client-side code. AWS AppSync integrates with Amazon DynamoDB, Amazon Aurora, Amazon Elasticsearch, AWS Lambda, and other AWS services, enabling you to create sophisticated applications, with virtually unlimited throughput and storage, that scale according to your business needs.
Real-time subscriptions and offline access
AWS AppSync enables real-time subscriptions across millions of devices, as well as offline access to app data. When an offline device reconnects, AWS AppSync automatically syncs only the updates that occurred when the device was disconnected, and not the entire data set. AWS AppSync offers user-customizable server-side conflict detection and resolution that does the heavy lifting of managing data conflicts so you don’t have to.
Unify and secure access to your distributed data
Perform complex queries and aggregation across multiple data sources with a single network call using GraphQL. AWS AppSync makes it easy to secure your app data using multiple concurrent authentication modes as well as allowing to define security and fine grained access control at the data definition level directly from your GraphQL schema.
Make Mobile Development Easier with Open Source Libraries for iOS and Android
Build real-time, global mobile apps that can handle millions of requests per second using Amplify libraries.
Read the blog
How it works
AWS AppSync is generally available. If you would like try building data driven mobile and web applications, watch the re:Invent session video to learn more and open the AWS AppSync console to get started. For pricing details, please see the pricing page. AWS AppSync is available in multiple regions. For details on region availability, please see the regions detail page.
AWS AppSync re:Invent session
Customers using AWS AppSync
Real Time Collaboration
You can use AWS AppSync to enable scalable, real-time collaboration use cases by broadcasting data from the backend to all connected clients (one-to-many) or broadcasting data between clients themselves (many-to-many). For example, you can build a second screen scenario where you broadcast the same data to all clients, and users then respond in real time by voting and commenting about what’s on the screen.
Reference Architecture: Sample Code
You can use AWS AppSync to power collaborative and conversational applications. For example, you can build a mobile and web application that supports multiple private chat rooms, offers access to conversation history, and enqueues outbound messages, even when the device is offline.
Reference Architecture: Sample Code
Internet of Things
You can use AWS AppSync to access IoT device data sent to AWS IoT. For instance, you can build a real-time dashboard in a mobile or web application to visualize telemetry from a connected car.
Polyglot Backend Data Access
You can retrieve or modify data from multiple data sources (SQL databases in Amazon Aurora Serverless, NoSQL tables in Amazon DynamoDB, search data in Amazon Elasticsearch Service, REST endpoints in Amazon API Gateway, or serverless backends in AWS Lambda) with a single call. Query and create relations between data sources using GraphQL connections. Provide real-time and offline capabilities to web and mobile clients.
Microservices Access Layer
You can use AWS AppSync as a single interface to access and combine data from multiple microservices in your application, even if they’re running in different environments such as containers in a VPC, behind a REST API on Amazon API Gateway, or behind a GraphQL API on another AWS AppSync endpoint.
Offline Delta Sync
You can use AppSync with Amplify DataStore, an on-device persistent storage engine that automatically synchronizes data between mobile/web apps and the cloud using GraphQL with a local-first and familiar programming model, leveraging AWS AppSync built-in support for data versioning with advanced conflict detection and resolution strategies such as auto-merge, optimistic concurrency or custom resolution with your own Lambda functions.
Lambda would time out after 15 minutes (2000*3=6000 seconds = 100 minutes). Glue is for performing ETL, but cannot run custom Python scripts. Kinesis Streams is for real time data (here we are in a batch setup), RDS could be used to run SQL queries on the data, but no Python script. The correct answer is EC2
Elastic Beanstalk cannot manage AWS Lambda functions, OpsWorks is for Chef / Puppet, and Trusted Advisor is to get recommendations regarding the 5 pillars of the well architected framework.
Kinesis cannot scale infinitely and we may have the same throughput issues. SNS won’t keep our data if it cannot be delivered, and DAX is used for caching reads, not to help with writes. Here, using SQS as a middleware will help us sustain the write throughput during write peaks
CloudFront is not a good solution here as the content is highly dynamic, and CloudFront will cache things. Dynamic applications cannot be deployed to S3, and Route53 does not help in scaling your application. ASG is the correct answer here
Network Load Balancers expose a fixed IP to the public web, therefore allowing your application to be predictably reached using these IPs, while allowing you to scale your application behind the Network Load Balancer using an ASG. Application and Classic Load Balancers expose a fixed DNS (=URL). Finally, the ASG does not have a dynamic Elastic IPs attachment feature
Hosting the master pack into S3 will require an application code refactor. Upgrading the EC2 instances won’t help save network cost and ELB does not have any caching capability. Here you need to create a CloudFront distribution to add a caching layer in front of your ELB. That caching layer will be very effective as the image pack is a static file, and tremendously save in network cost.
Adding Aurora Read Replicas would greatly increase the cost, switching to a Load Balancer would not improve the problems, and AWS Lambda has no native in memory caching capability. Here, using API Gateway Caching feature is the answer, as we can accept to serve stale data to our users
SQS will allow you to buffer the image compression requests and process them asynchronously. It also has a direct built-in mechanism for retries and scales seamlessly. To process these jobs, due to the unpredictable nature of their volume, and the desire to save on costs, Spot Instances are recommended.
Distributing the static content through S3 allows to offload most of the network usage to S3 and free up our applications running on ECS. EFS will not change anything as static content on EFS would still have to be distributed by our ECS instances
S3 does not work as overwrites are eventually consistent so the latest data will not always be read. Neptune is a graph database so it’s not a good fit, ElastiCache could work but it’s a better fit as a caching technology to enhance reads. Here, the best fit is RDS.
RDS Multi AZ helps with disaster recovery in case of an AZ failure. ElastiCache would definitely help with the read load, but would require a refactor of the application’s core logic. DynamoDB with DAX would also probably help with the read load, but once again it would require a refactor of the application’s core logic. Here, our only option to scale reads is to use RDS Read Replicas
Which of the following AWS services encrypts data at rest by default? (Choose 2)
All data transferred between any type of gateway appliance and AWS storage is encrypted using SSL. By default, all data stored by AWS Storage Gateway in S3 is encrypted server-side with Amazon S3-Managed Encryption Keys (SSE-S3). Also, when using the file gateway, you can optionally configure each file share to have your objects encrypted with AWS KMS-Managed Keys using SSE-KMS. This is the reason why Option 1 is correct.
Data stored in Amazon Glacier is protected by default; only vault owners have access to the Amazon Glacier resources they create. Amazon Glacier encrypts your data at rest by default and supports secure data transit with SSL. This is the reason why Option 4 is correct.
Although Amazon RDS, ECS and Lambda all support encryption, you still have to enable and configure them first with tools like AWS KMS to encrypt the data at rest.
- RDS cheatsheet: https://tutorialsdojo.com/aws-cheat-sheet-amazon-relational-database-service-amazon-rds/
- VPC cheatsheet: https://tutorialsdojo.com/aws-cheat-sheet-amazon-vpc/
- Amazon Kinesis cheatsheet: https://tutorialsdojo.com/aws-cheat-sheet-amazon-kinesis/