AWS CloudFormation on Digi Hunch

EKS impression

Fri, 23 Dec 2022 18:18:19 -0400

I’ve worked on a few AKS projects previously. Since I joined AWS I wanted to put aside some time to check out EKS (Elastic Kubernetes Service). Here in this post, I put down my first impression on EKS, and also share my Terraform template in cloudkube project to create an EKS cluster.

Similar to AKS, EKS exposes API endpoint and the control plane components are hidden from AWS users. When creating EKS cluster it does not create the underlying VPC and subnets. Therefore, you have create an existing VPC and at least two subnets ahead of time, and specify them during EKS creation. Bear in mind that there is a list of requirement for the VPC and subnets.

In the cluster, the CNI that EKS officially supports is Amazon VPC CNI plugin. It is available as an add-on. Similar to Azure CNI, each Pod gets its own IP address. In addition, EKS supports other compatible CNI plugins such as Calico, Cilium, Weave Net and Antrea.

Computing Nodes in EKS

There are three modes to address computing capacity: self-managed nodes, EKS managed node groups and AWS Fargate. The documentation has a comparison table.

With self-managed nodes, users create EC2 instances separately and then register them to the control plane. The instances must use the same IAM role and AMI. You can use Auto Scaling groups of Bottlerocket (AWS-sponsored purpose-built Linux distro for container host) nodes. The self-managed node option is mostly for AWS outpost customers who bring in their own computing capacity from data centre.

If you provision computing capacity from AWS, it makes sense to assign EKS managed node groups when creating EKS cluster. We can turn on Cluster Autoscaler, a Kubernetes construct to manage the auto scaling of node groups. Sometimes we want to have more than one node groups. For example, to build a multi-architecture cluster, we need one node group with amd64 nodes and the other with arm64 nodes (e.g. instances with Graviton processor). In general, arm-based CPU delivers better performance with less power consumption and the industry is slowly moving towards more arm-based CPU architecture.

Fargate is what I call managed computing service for EKS. With Fargate you do not need to tweak Cluster Autoscaler to self-manage computing capacity. The Fargate documentation has a long list of considerations. For example, Pods must match a Fargate profile (here‘s an example) at the time that they’re scheduled to run on Fargate. So we need to build Fargate profile and Pod labelling properly. Also, Fargate does not support DaemonSet. Another big consideration is that Fargate does not support non-VPC CNI. In my opinion these are pretty significant limitations. Many workloads (system-level or application-level) would need Daemonset (e.g. kube-proxy, some CNI or CSI drivers, Dynatrace monitoring).

The pro of Fargate is the serverless computing model. The construct of a Fargate profile isn’t complicated. You just specify subnets, namespace and labels. However, the downside is the long list of considerations. Some teams may consider these restrictions too much. The other overhead is the need to manage Fargate profile to ensure all Pods are scheduled somewhere.

To me, using Fargate alone impairs portability of workload. The good thing is that Fargate and Managed Node Group are not mutually exclusive on a cluster. In most cases, we can go partially serverless, and reap the benefits of both of them.

Node AutoScaling

For workloads that don’t have a matching Fargate profile, we have to figure out node autoscaling ourselves. I touched on Cluster Autoscaler in “Autoscaling on Kubernetes Platform“. CA works on AWS as well and is triggered upon a Pod coming to unschedulable status in Scheduler. There is some limitations though. For example, CA interacts with Autoscaling Group (instead of EC2 instances directly). When it determines it’s time to scale up, it bumps up the desired capacity by one at a time in the Autoscaling group. The configurations in Autoscaling group may also be at play and CA do not have direct control. For example, the “scaling cooldown“. The pool of nodes is homogenous as per the pre-configured launch template and CA has no control. If a Pod requires a different type of node (e.g. ARM64 CPU, spot instance, etc), then we’d first have to create a node group with the desired node type. Moreover, in the worst cases, one-at-a-time scale-up does not meet the increase of demand driven by Pod increases, causing nuances such as racing conditions.

Because the Cluster Autoscaler doesn’t really deal with the nodes themselves, this kind of integration is clunky and slow. Nearly half of Kubernetes customers on AWS report that configuring cluster auto scaling using the Kubernetes Cluster Autoscaler is challenging and restrictive, according to this blog post. As a result, AWS launched an open-source cluster autoscaler project, Karpenter. Karpenter first only supported EKS but now the support includes other CSPs. For EKS, Karpenter directly interact with different types of EC2 instances.

Karpenter makes node scaling work in a more cloud-native manner. In the presence of unschedulable Pods, Karpenter bypasses the Kubernetes scheduler and works directly with the Cloud provider, to launch the minimal compute resources needed to fit those Pods and immediately binds the Pods to the newly provisioned Nodes without waiting for scheduler. As Pods are removed or rescheduled to other nodes, Karpenter looks for opportunities to terminate under-utilized nodes. Karpender defines a CR called Provisioner to specify node provisioning configuration, such as instance size, zone, CPU architecture, etc. It is a manifest that describes a node group so the node scaler is aware of all the available node types. You can have multiple Provisioners for different needs, just like node groups. The Provisioner CR can also set TTL for empty Nodes, such that once a Node has no pods other than DaemonSet, Karpenter will terminate the Node on TTL expiry.

Karpenter’s idea is similar to the idea of AutoPilot cluster in GKE. The new EKS workshop has an section on how to set up CA and Karpenter in practice.

Identity Management for EKS

For IAM, we need to be concerned with three aspects. The management traffic to the cloud service, the management traffic for Kubernetes cluster and business traffic.

Traffic type	AWS	Azure
I. Cloud Service Endpoint (Management Traffic for Cloud Service)	AWS IAM identity	Azure RBAC
II. Kubernetes API (Management Traffic for K8s Cluster)	IAM mapping or OIDC	Azure RBAC (implementation of OIDC)
III. Business traffic	Up to Kubernetes Ingress	Up to Kubernetes Ingress

For business traffic (type III), it is all up to the Ingress. I’ve written another article on managing ingress traffic on Kubernetes platforms. We interact with cloud service endpoint (type II) with either AWS CLI or Terraform, to create any object, including resources needed for a cluster. This is generally how we work with cloud service, not specific to Kubernetes. Usually the IAM identity assumes another IAM role, which empowers it with a lot of permissions.

For access to Kubernetes API (type III), EKS supports OIDC and IAM mapping. AWS documentation refers to this as “Cluster Authentication“. There is one special scenario where your identity for type II access inherits your identity for type I access. As the document puts:

When you create an Amazon EKS cluster, the AWS Identity and Access Management (IAM) entity user or role, such as a federated user that creates the cluster, is automatically granted system:masters permissions in the cluster’s role-based access control (RBAC) configuration in the Amazon EKS control plane. This IAM entity doesn’t appear in any visible configuration, so make sure to keep track of which IAM entity originally created the cluster.

This special scenario (I call it the “implicit master user“) allows us to perform critical activities on the cluster, such as creating IAM mapping, or OIDC configuration.

The above addressed how AWS resource access Kubernetes resource. On the other hand, to address how a Kubernetes resource access AWS resources, we need IRSA (IAM Roles for Service Account). We have a service account in Kubernetes and map it to an IAM role.

AppMesh

AppMesh is AWS’ Envoy based service-mesh offering supporting Kubernetes cluster, ECS service and even EC2 instance. AppMesh’s control plane is a managed AWS service, with a controller running on the Kubernetes cluster. To install AppMesh on the cluster:

On the EKS cluster, install AppMesh Controller using Helm
Associate the cluster with IAM OIDC provider
Create an IAM role for the appmesh-controller service account

After these steps, you can create a mesh using CloudFormation, Terraform, etc. The data plane (Envoy proxy) can run on Kubernetes (as sidecar). Traffic between control plane and data plane can go through private link (Interface VPC endpoint) for added security. Like Istio, AppMesh enables mTLS. For observability, you can export Envoy metrics with Prometheus. Coupled with XRay, AppMesh also supports distributed tracing.

AppMesh uses a different set of CRDs than Istio. Key CRDs are:

Mesh: represents an entire service mesh. At mesh level you can configure Egress filter (to allow or deny external traffic) and set IP version (v4 vs v6)
VirtualGateway: a CRD that represents an Ingress in to the Mesh. A virtual gateway allows resources that are outside of your mesh to communicate to resources that are inside of your mesh. A virtual gateway references Envoy proxy deployment by podSelector. It references GatewayRoutes by namespaceSelector, and optionally gatewayRouteSelector. You also specify listeners in the manifest to reference Envoy proxy Service (LoadBalancer Type).
GatewayRoute: A gateway route is attached to a virtual gateway and routes traffic to an existing virtual service. If a route matches a request, it can distribute traffic to a target virtual service. In the manifest, you specify a list of httpRoute, each with matching condition and action. In the action section you can specify virtualService as target.
VirtualService: an abstraction of a real service provided by a virtual node directly or indirectly by means of a virtual router. Dependent services call your virtual service by its virtualServiceName, and those requests are routed to the VirtualNode or VirtualRouter that is specified as the provider for the VirtualService.
VirtualRouter: Virtual routers handle traffic for virtual services. In a virtual router manifest, you can define Route to direct incoming requests to virtual nodes as target.
VirtualNode: A virtual node acts as a logical pointer to a particular task group (i.e. ECS service, Kubernetes deployment). It represent a Service in the AppMesh. In the manifest, you reference Pods by podSelector, specify listeners for any inbound traffic that your virtual node expects, and specify serviceDiscovery for your task group.

You can configure those Custom Resources using YAML manifests (and check the API reference a lot). Alternatively, you can configure them from AWS CLI or AWS console. The console will help you visualize what can be configured. For further details on how these CRs play together, there is a workshop for AppMesh.

EKS cluster using Terraform

Officially, there is an EKS blueprint project for provisioning EKS cluster in Terraform.

I also keep my own Terraform code in the AWS directory of cloudkube project. It works out to be a little more complex than my Terraform template to create Azure Kubernetes Cluster (Azure directory). Because I had to create Cognito resources with initial credential to allow users to connect to cluster without using the implicit master account.

Below is the diagram of the processes.

Create EKS cluster with Terraform module

The template configures kubectl access on a Bastion host, which assumed the same role that our IAM user uses to create the Kubernetes cluster. Therefore, the IAM role is the master identity.

Note that the IAM user (power-user) has very powerful permissions. Usually it is ideal to assign lots of permission to IAM Roles (temporary credential) instead of IAM user (long-term credential). So the role chaining would look like:

The IAM user that Terraform uses has no permission other than assuming a “PowerUser” role
The PowerUser role trusts the IAM user. It also has the permission to assume the “EKS-Manager” role
The EKS-Manager role trusts PowerUser’s role session.

However, the role chaining scenario above is not currently supported in Terraform.

I use a Bastion host because the cluster endpoint is on private subnet. The bastion host is on a public subnet. However, if we do not like public subnet and public IP, we can place the bastion host on a private subnet, and use SSM system manager agent with SSH tunnel plugin to have SSH access to private bastion host.

Summary

I first came across this article about EKS and its awfulness and then decided to check out EKS. I’m not sure all points are still valid but it’s generally real-life experiences. There are also many peripheral services, such as AMP (AWS Managed Prometheus), AMG (AWS Managed Grafana), ADOT (AWS Distro for Open Telemetry), AppMesh (Another Envoy-based Service Mesh, easier to manage than Istio but less Powerful), with a lot to explore.

Landing Zone in AWS – An Introduction

Thu, 08 Dec 2022 22:37:00 -0400

Cloud adoption has gone through phases. Hashicorp’s CTO Armon Dadgar has a great stream on Hashcorp’s narrative of the three Phases of Cloud Adoption:

Phase 1, with main focus on agility, app teams in wild west, account sprawl, inconsistent configuration, security & compliance challenge
Phase 2. consistent platform layer providing an opinionated way of configurations, security and compliance control, introduction of platform team, whose customers are application team, scaling challenges with platform team capacity not keeping up with application team’s demand
Phase 3. self-service platform at scale for many application teams. CICD, infra-as-code

New greenfield clients today should aim at phase 2 or phase 3 depending on their target operation size. Either way, they need a landing zone for consistency. This post focuses on the landing zone options on AWS and the key constructs.

Overview

AWS Prescriptive Guidance defines landing zone as a well-architected (secure, scalable, compliant, etc), multi-account AWS environment that is a secure baseline from which you can deploy workloads and applications. A landing zone may consists of:

Multi-account architecture
Identity and Access management solution
Governance, compliance, logging and auditing solutions
Security and networking design

Landing zone reflects an enterprise opinion on how to configure networking and IAM. Establishing a landing zone can be a very involving process. In early days of cloud operation people used build landing zone by “clickops” on AWS console, which cannot keep up with the growth of landing zone and associated security services. Compared to SMB clients, some sectors such healthcare and national security have much more regulations and compliance frameworks.

In fact, landing zone is such a buzzword that I have learned to be very sensitive to the context. If a solution has words “landing zone” in its name, given the complexity and loose use of the words, there is a good chance that the solution only delivers some of the aspects above. Cloud consultants are still to address the gaps. Therefore I decided to write this post about what I learned about landing zone in AWS.

Multi-account and Organization

Since 2017, AWS has been officially advocating the use of multiple accounts as a best practice and security strategy. They encourage clients to view an account as a resource container, just like Resource Group in Azure (here is an article on the account structure between AWS and Azure) Client builds an account for security boundary and financial container. Many blog post came along (such as this one) on the implementation details. From tooling perspective, AWS launched AWS Organization in 2017 to facilitate multi-account management. This presentation from re:Inforce 2019 is a good material to understand multi-account environment with AWS Organizations. In 2021, AWS published a new white paper on best practices with multiple accounts. My previous coworkers authored two blog posts here and here to reflect multi-account setup as of late 2020.

AWS Organization is an account management service that provides a vehicle to centrally manage AWS accounts by groups, which brings many benefits, such as centralized logging, compliance management, consolidated billing, etc. As an administrator, you can create accounts in your organization and invite existing accounts to join the organization.

Typical account structure involves:

A root organization named Root
A organization hierarchy with one or more OUs under root, with each OU having one or more child OUs.
Each OU can have multiple accounts, with each account having one email address.

You can also configure service control policies (SCPs), a type of organization-level policy that you can use to manage permissions in your organization. SCPs offer central control over the maximum available permissions for all accounts in your organization. SCPs are a means of implementing guardrails in your AWS organization.

To vend multiple account automatically, AWS introduced the Account Factory (which became part of Control Tower later in 2019) and let users create new account from AWS console and specify which OU it belongs to. It also allows users to implement customization after account creation with Service Catalog products. Some legacy orchestration solution (e.g. Augmented Account Factory) were based on this mechanism. Another orchestration solution prior to the launch of Control Tower was the AWS Landing Zone solution (ALZ, introduced in 2018), which uses AWS CodePipeline to provision accounts and deploy resources.

From Landing Zone Solution (ALZ) to Control Tower

The launch of Control Tower was a game changer in 2019 to bring users to multi-account best practices. Control Tower, as an AWS product (instead of a solution by some service teams at AWS) matured over several years. It gradually deprecated the previous generation orchestration solutions. Newer orchestration solutions all have to support Control Tower. According to this page, we can customize Control Tower based Landing Zone in these ways:

AWS Control Tower console:
- Instead of creating OU in AWS organization, do it under Control Tower in the console, under “create required OUs”.
Outside of AWS Control Tower console
- using Account Factory for Terraform (AFT): Terraform-based account provisioning pipeline, for heavy Terraform shops.
- using Customizations for AWS Control Tower (CfCT) solution. The LZ created remains in sync with Control Tower.
  - You first launch a standardized CF stack to set up the mechanisms for customization.
  - Then you create a custom package to define the customization. This includes a manifest file.

On the other hand, the original ALZ solution is currently in long-term support and will not receive any additional features. It is deprecated. AWS advises its customers migrate to AWS Control Tower based landing zone. The ALZ page is redirected to a page about customizing Control Tower landing zone.

The Control Tower based landing zone configures OUs, accounts, SSO and guardrails. It however does not entail networking design except for the guardrails.

Security Reference Architecture (SRA)

SRA is just a reference architecture and accompanying recommendations on AWS security services, and how they work together in a multi-account environment to host a single-page application. It comes with a repository to demonstrate how to configure a secure multi-account environment with Control Tower, CfCT, as well as security services. Alternatively, you can deploy it with CloudFormation StackSets. For fully automated deployment of this architecture, check out Landing Zone Accelerator down below.

One important feature that reflects the notion of centralized security in a multi-VPC topology, is the use of a dedicated VPC for centralized interface endpoints. This pattern is seen in all generations of security reference architectures.

AWS Security Environment Accelerator (ASEA)

Regulated customers often find they need to add additional controls and capabilities to be defined and setup outside of Control Tower. ASEA, as an orchestration solution, aims to remove the complexity of having to develop and maintain a separate codebase to manage the additional customizations, by providing a tool to help deploy and operate secure multi-account, multi-region AWS environments on an ongoing basis.

Overtime, as Control Tower introduces new capabilities to support the customizations required in heavily regulated environments, the capabilities will be removed from ASEA and enabled directly within the Control Tower managed service, further reducing operational burden. Read this for its relationship with ALZ and Control Tower.

ASEA was first released in late 2020. It covers more on networking design and has a fairly comprehensive installation process. ASEA primarily cater to government of Canada‘s PBMM Security Configuration Profile with an opinionated configuration. The first few revisions were referred to as PMBB architecture. While it provides a great reference architecture for highly regulated landing zone, it has not gotten much traction elsewhere. The recommendation going forward, is to use Landing Zone Accelerator, which incorporates the features and lessons learned from ASEA.

Landing Zone Accelerator (LZA)

First released in May 2022, the Landing Zone Accelerator on AWS solution deploys a cloud foundation that is architected to align with AWS best practices and multiple global compliance frameworks. LZA operates on top of Control Tower managed landing zone. This page in the documentation brings a good explanation of how it works. Basically it employs CodeBuild as an orchestration engine, and leverages CDK to drive resource deployment. There are two repositories: the GitHub repository for Landing Zone Accelerator itself, and a CodeCommit configuration repository provisioned during preparation.

As document states, LZA is a fully automated implementation of the architecture guidelines documented in the SRA. LZA also incorporates features and lessons learned from ASEA and Compliant Framework for Federal and DoD Workloads in GovCloud (US), neither of which are recommended for new deployment. In addition, LZA aims to enable iterations and extensions of a secure environment over time. The vision is to eventually replace AFT, CfCT, and ASEA. As AWS releases newer versions of LZA, client should be able to upgrade it in a pipeline run.

Baseline architecture for LZA

The Landing Zone Accelerator project also provides a samples configurations in each regulated frameworks. For example, the healthcare best practice come up in Oct 2022 for healthcare industry. The healthcare best practice sample incorporates healthcare specific configurations, such as the detective guardrails defined in the Operational Best Practices for HIPAA Security conformance pack. To deploy the best practices, modify the configuration in config repo, and run the pipeline again.

Landing Zone Orchestration Options

To summarize, we have the following landing zone options in AWS:

Orchestration Layer	Lifecycle	Summary
Solutions based on account factory with Service Catalog (e.g. ALZ, Augmented Account Factory)	All solutions pre-dates the launch of control tower have been or will soon be deprecated.	Pre-Control Tower solutions should migrate to current alternatives.
AWS Control Tower	GA in June 2019	To customize the landing zone, use AWS console, or alternatively, one of the following three options: – CfCT: Customization for Control Tower – AFT: Account Factory Terraform – AFC: Account Factory Customizations For example, CfCT can be used to deploy Security Reference Architecture (SRA)
AWS Secure Environment Accelerator (ASEA)	Released 2020	Canadian Centre for Cyber Security (CCCS) Medium Cloud Control Profile, formerly known as PBMM. This approach will be replaced by LZA
AWS Landing Zone Accelerator (LZA)	Released in 2022	A low-code deployment option. Samples provided in support of reference architectures that align with industry best practices or compliance frameworks. Examples for industry best practices: – general best practice – healthcare – finance and tax – education Example for compliance frameworks: – US state local government – FedRAMP for US Federal and Department of Defence (DoD) – CCCS Medium for Canadian government – AWS Trusted Secure Enclave (TSE) Sensitive Edition (SE), which also aligns with other medium level security profiles such as NIST 800-53, ITSG-33, FedRAMP moderate, CCCS-Medium, IRAP, etc

If your organization has a compliance framework that LZA supports, it makes sense to start with LZA. Otherwise, it is sufficient to use Control Tower for multi-account setup.

Networking constructs

Landing zone involves multiple VPCs so it’s important to understand VPC peering and Transit Gateway. VPC peering can only be setup between two VPCs and transitive peering relationship is not supported. For 6 VPCs to talk to all each other, we’d need 15 peering setups, which is not sustainable. We have two options:

We can connect many VPCs to a single Transit Gateway and the VPCs will be able to talk to each other. We can also connect Transit Gateway to site-to-site VPN or Direct Connect. This is a good explanation.
We can still use peering, but dedicate one VPC as “Transit VPC” in a hub and spoke model.

When you attach a VPC to a transit gateway, you must specify one subnet from each AZ to be used by the transit gateway to route traffic. Specifying one subnet from an AZ enables traffic to reach resources in every subnet in that AZ.

Here is a comparison table. Read the white-paper “Building a Scalable and Secure Multi-VPC AWS Network Infrastructure” for more about network design. For example, Some clients need to inspect traffic. When deploying multiple VPCs, we also need to ensure DNS resolution works across VPCs, and between on-prem networks, by configuring Amazon DNS server.

Our VPCs also need to connect to managed AWS services. For services like S3 or DynamoDB (of the same or different account), workload in VPC can access them via public DNS. The traffic goes through Internet Gateway of VPC and then public Internet. It is neither secure nor economical. We often want all network traffic to stay on the global AWS backbone. There are three types of Endpoint under VPC to help us.

	Gateway VPC Endpoint or Gateway Endpoint	Interface VPC Endpoint or Interface Endpoint	Gateway Load Balancer Endpoint
Purpose	VPC access native AWS services	VPC access native AWS services	VPC access your own service (aka Endpoint Service)
Enabled by Private Link	No	Yes	Yes
Traffic remain on AWS network	Yes	Yes	Yes
Mechanism	Use the public IP address of the service along with configuration in routing table to access target resource. The routing table acts as gateway. You can use the public DNS name of the service.	Use private IP address from the VPC to access the target service. Require endpoint-specific DNS name for the target service. Incur extra charge. S3 as example. More secure because there is ENI in the VPC controlled by security group.	Your Endpoint Services is hosted in front of a fleet of network virtual appliances. You can select endpoint type as you create it in console under VPC
Access from clients on premise or from other region	Does NOT allow access from clients on premise or in VPC from other region	Allows access from clients on premise or clients in VPC from other region	Allowed

Private Link integrates with a subset of AWS services. To check the list of interface endpoint, use:

aws ec2 describe-vpc-endpoint-services --query "ServiceDetails[?ServiceType[0].ServiceType=='Interface'].ServiceName"

Given the inter-VPC connectivity, most deployment centralizes interface endpoint into a dedicated VPC.

Centralized Interface Endpoints

There are several benefits to use a single VPC as dedicated provider of interface endpoint in a multi-VPC topology. First, the interface endpoints incurs a standing charge and it makes financial sense to consolidate them in one VPC. Second, this setup centralizes the configuration and security aspects as well.

In most cases, interface endpoint services follow the format of com.amazonaws.<region>.<endpoint>, with the dns name looking like: <endpoint>.<region>.amazonaws.com. For example:

Endpoint Service Name: com.amazonaws.us-east-1.ssm
Private Hosted Zone: ssm.us-east-1.amazonaws.com
Zone Record (A alias): ssm.us-east-1.amazonaws.com

However, there are a few exceptions to that which can make it tricky to implement interface endpoint with infrastructure as code.

Exception 1. Private DNS name suffix is api.aws instead of amazonaws.com:

Endpoint Service Name: com.amazonaws.us-east-1.eks-auth
Private Hosted Zone: eks-auth.us-east-1.api.aws
Zone Record (A alias): eks-auth.us-east-1.api.aws

Exception 2. Endpoint Service Name doesn’t start with com.amazonaws

Endpoint Service Name: aws.sagemaker.us-east-1.notebook
Private Hosted Zone: notebook.us-east-1.sagemaker.aws
Zone Record (A alias): notebook.us-east-1.sagemaker.aws

Exception 3. Two A-records are required under the same PHZ

Endpoint Service Name: com.amazonaws.us-east-1.ecr.dkr
Private Hosted Zone: dkr.ecr.us-east-1.amazonaws.com
Zone Record (A alias): dkr.ecr.us-east-1.amazonaws.com and *.dkr.ecr.us-east-1.amazonaws.com

Exception 4. Two PHZs are required:

Endpoint Service Name: com.amazonaws.us-east-1.ec2
Private Hosted Zone: ec2.us-east-1.amazonaws.com and ec2.us-east-1.api.aws
Zone Record (A alias): ec2.us-east-1.amazonaws.com and ec2.us-east-1.api.aws

The infrastructure code that handles interface endpoints should be able to take care of the exceptions.

Security Constructs

AWS Network firewall is a configuration under VPC. You associate a Network Firewall with one or more subnets in the VPC. You also associate the Network Firewall with Firewall Policies. Each policy consists of rule groups. Each rule blocks or filters traffic. The log can be published to CloudWatch or S3 via Kinesis. Usecases of AWS Network firewall include:

inspect VPC-to-VPC traffic;
filter outbound traffic;
prevent inbound internet traffic;
secure AWS Direct Connect and VPN traffic

When you associate a firewall to your VPC, you must provide a subnet for each Availability Zone where you want to place a firewall endpoint to filter traffic

There are many points of configuration for firewall rules in AWS. AWS Firewall Manager is a place for central management. It connects with other services such as:

AWS WAF (L7)
AWS Network Firewall (L4)
AWS Shield (DDos)
Amazon Route 53 Resolver DNS Firewall
Security Groups
Third party firewall support

IAM Identity Center (previously AWS SSO) is for logging into AWS portal, giving each identity from an external identity store (such as AD) an identity on an AWS account. It addresses several challenges as a result of having multiple AWS accounts.

First, a user from AD needs to access multiple accounts. Second, in each account with access, s/he needs to have an IAM role. These IAM roles are based on attributes of his/her external identity, and can be different per AWS account. With Permission Set IAM Identity Center:

Allow you to login on different AWS account using the same credential
Allow you to federate with external identity store( e.g. using SAML)
Manage permission set for each account.

This video has a good walk-through of how to configure Azure AD as identity store, and tie it to specific AWS accounts and specify permission set.

Note that IAM Identity Center has a different purpose than Cognito. Cognito is to connect your app with an IdP. Your app can be an EC2-hosted application, serverless application on API gateway, or container-based application on Kubernetes, as long as the support open identity standards (e.g. OAuth 2.0, SAML 2.0 and OIDC). Cognito has two pools:

User pool for authentication. With a user pool, your app
Identity pool for authorization

So Cognito is for AuthN & AuthZ to your own app’s endpoint (business traffic) and it supports a number of standards. IAM Identity Center is for AuthN & AuthZ to your AWS account (management traffic). If you use it for your own application, your application user will have direct access your AWS resources. It mainly supports SAML (and OIDC but less used) and is commonly connected with Active Directory (Microsoft or AWS).

One can use AWS Directory Service to host a compatible and managed directory service. AWS Directory Service supports four modes:

AWS managed Microsoft AD: actual Microsoft Active Directory in AWS Cloud
Simple AD, powered by Linux-Samba Active Directory-compatible server
AD Connector: a proxy for redirecting directory request to your existing Microsoft AD without caching any information in the cloud
Cognito user pools

If you combine two AD domains, you will need domain trust.

Other security services

In addition to the core services above, LZA involves the following four services as well.

AWS Macie is a fully managed data security and privacy service based on ML and pattern matching. It continually evaluates your S3 environments to discovery PII and act on them. It also reports alerts on unencrypted buckets, publicly accessible buckets, etc.

AWS GuardDuty continuously analyze S3, container & instance workloads, user and accounts for potential threads, across account, based on ML for intelligent threat detection. In addition, GuardDuty also acts on findings.

AWS Config is an essential service that traces resource inventory, their changes and monitors for compliance:

When you turn on AWS Config, it first discovers the supported AWS resources in your account and generates a configuration item (poin-in-time view of attributes) for each resource. AWS Config also generates configuration items when the configuration of a resource changes, and it maintains historical records of the configuration items of your resources from the time you start the configuration recorder.
On an ongoing basis, AWS Config keeps track of all changes to your resources, whether or not it is initiated by the API
If you are using AWS Config rules, AWS Config continuously evaluates your AWS resource configurations for desired settings. You can deploy several related rules in a pre-built compliance pack.

As you may have noticed, there are many AWS services related to firewall, security and compliance. AWS Security Hub aims to be a a consolidated view of your security status in AWS. You can automate security checks, manage security findings, and identify the highest priority security issues across accounts in client environment. It can also:

consolidate security findings from GuardDuty, Inspector (vulnerability scanner and management), Macie, Config, Systems Manager, Firewall Manager, IAM Access Analyzer and other Integrated APN solutions
Check findings against best practices
Client can take action: i.e. investigate findings or take response and remediation actions

Summary

Landing zone deployment can take numerous iterations to finalize the requirement. It is important to have a vision of the client’s cloud operating model, which is usually discussed prior to implementation. At the implementation phase, I discuss the topic on two more separate posts on control tower and landing zone accelerator.