Amazon EC2 Construct Library
The aws-cdk-lib/aws-ec2 package contains primitives for setting up networking and
instances.
import aws_cdk.aws_ec2 as ec2
VPC
Most projects need a Virtual Private Cloud to provide security by means of
network partitioning. This is achieved by creating an instance of
Vpc:
vpc = ec2.Vpc(self, "VPC")
All default constructs require EC2 instances to be launched inside a VPC, so you should generally start by defining a VPC whenever you need to launch instances for your project.
Subnet Types
A VPC consists of one or more subnets that instances can be placed into. CDK distinguishes three different subnet types:
Public (
SubnetType.PUBLIC) - public subnets connect directly to the Internet using an Internet Gateway. If you want your instances to have a public IP address and be directly reachable from the Internet, you must place them in a public subnet.Private with Internet Access (
SubnetType.PRIVATE_WITH_EGRESS) - instances in private subnets are not directly routable from the Internet, and you must provide a way to connect out to the Internet. By default, a NAT gateway is created in every public subnet for maximum availability. Be aware that you will be charged for NAT gateways. Alternatively you can setnatGateways:0and provide your own egress configuration (i.e through Transit Gateway)Isolated (
SubnetType.PRIVATE_ISOLATED) - isolated subnets do not route from or to the Internet, and as such do not require NAT gateways. They can only connect to or be connected to from other instances in the same VPC. A default VPC configuration will not include isolated subnets,
A default VPC configuration will create public and private subnets. However, if
natGateways:0 and subnetConfiguration is undefined, default VPC configuration
will create public and isolated subnets. See Advanced Subnet Configuration
below for information on how to change the default subnet configuration.
Constructs using the VPC will “launch instances” (or more accurately, create
Elastic Network Interfaces) into one or more of the subnets. They all accept
a property called subnetSelection (sometimes called vpcSubnets) to allow
you to select in what subnet to place the ENIs, usually defaulting to
private subnets if the property is omitted.
If you would like to save on the cost of NAT gateways, you can use
isolated subnets instead of private subnets (as described in Advanced
Subnet Configuration). If you need private instances to have
internet connectivity, another option is to reduce the number of NAT gateways
created by setting the natGateways property to a lower value (the default
is one NAT gateway per availability zone). Be aware that this may have
availability implications for your application.
Control over availability zones
By default, a VPC will spread over at most 3 Availability Zones available to
it. To change the number of Availability Zones that the VPC will spread over,
specify the maxAzs property when defining it.
The number of Availability Zones that are available depends on the region
and account of the Stack containing the VPC. If the region and account are
specified on
the Stack, the CLI will look up the existing Availability
Zones
and get an accurate count. The result of this operation will be written to a file
called cdk.context.json. You must commit this file to source control so
that the lookup values are available in non-privileged environments such
as CI build steps, and to ensure your template builds are repeatable.
If region and account are not specified, the stack could be deployed anywhere and it will have to make a safe choice, limiting itself to 2 Availability Zones.
Therefore, to get the VPC to spread over 3 or more availability zones, you must specify the environment where the stack will be deployed.
You can gain full control over the availability zones selection strategy by overriding the Stack’s get availabilityZones() method:
// This example is only available in TypeScript
class MyStack extends Stack {
constructor(scope: Construct, id: string, props?: StackProps) {
super(scope, id, props);
// ...
}
get availabilityZones(): string[] {
return ['us-west-2a', 'us-west-2b'];
}
}
Note that overriding the get availabilityZones() method will override the default behavior for all constructs defined within the Stack.
Choosing subnets for resources
When creating resources that create Elastic Network Interfaces (such as
databases or instances), there is an option to choose which subnets to place
them in. For example, a VPC endpoint by default is placed into a subnet in
every availability zone, but you can override which subnets to use. The property
is typically called one of subnets, vpcSubnets or subnetSelection.
The example below will place the endpoint into two AZs (us-east-1a and us-east-1c),
in Isolated subnets:
# vpc: ec2.Vpc
ec2.InterfaceVpcEndpoint(self, "VPC Endpoint",
vpc=vpc,
service=ec2.InterfaceVpcEndpointService("com.amazonaws.vpce.us-east-1.vpce-svc-uuddlrlrbastrtsvc", 443),
subnets=ec2.SubnetSelection(
subnet_type=ec2.SubnetType.PRIVATE_ISOLATED,
availability_zones=["us-east-1a", "us-east-1c"]
)
)
You can also specify specific subnet objects for granular control:
# vpc: ec2.Vpc
# subnet1: ec2.Subnet
# subnet2: ec2.Subnet
ec2.InterfaceVpcEndpoint(self, "VPC Endpoint",
vpc=vpc,
service=ec2.InterfaceVpcEndpointService("com.amazonaws.vpce.us-east-1.vpce-svc-uuddlrlrbastrtsvc", 443),
subnets=ec2.SubnetSelection(
subnets=[subnet1, subnet2]
)
)
Which subnets are selected is evaluated as follows:
subnets: if specific subnet objects are supplied, these are selected, and no other logic is used.subnetType/subnetGroupName: otherwise, a set of subnets is selected by supplying either type or name:subnetTypewill select all subnets of the given type.subnetGroupNameshould be used to distinguish between multiple groups of subnets of the same type (for example, you may want to separate your application instances and your RDS instances into two distinct groups of Isolated subnets).If neither are given, the first available subnet group of a given type that exists in the VPC will be used, in this order: Private, then Isolated, then Public. In short: by default ENIs will preferentially be placed in subnets not connected to the Internet.
availabilityZones/onePerAz: finally, some availability-zone based filtering may be done. This filtering by availability zones will only be possible if the VPC has been created or looked up in a non-environment agnostic stack (so account and region have been set and availability zones have been looked up).availabilityZones: only the specific subnets from the selected subnet groups that are in the given availability zones will be returned.onePerAz: per availability zone, a maximum of one subnet will be returned (Useful for resource types that do not allow creating two ENIs in the same availability zone).
subnetFilters: additional filtering on subnets using any number of user-provided filters which extendSubnetFilter. The following methods on theSubnetFilterclass can be used to create a filter:byIds: chooses subnets from a list of idsavailabilityZones: chooses subnets in the provided list of availability zonesonePerAz: chooses at most one subnet per availability zonecontainsIpAddresses: chooses a subnet which contains any of the listed ip addressesbyCidrMask: chooses subnets that have the provided CIDR netmaskbyCidrRanges: chooses subnets which are inside any of the specified CIDR ranges
Using NAT instances
By default, the Vpc construct will create NAT gateways for you, which
are managed by AWS. If you would prefer to use your own managed NAT
instances instead, specify a different value for the natGatewayProvider
property, as follows:
The construct will automatically selects the latest version of Amazon Linux 2023.
If you prefer to use a custom AMI, use machineImage: MachineImage.genericLinux({ ... }) and configure the right AMI ID for the
regions you want to deploy to.
Warning The NAT instances created using this method will be unmonitored. They are not part of an Auto Scaling Group, and if they become unavailable or are terminated for any reason, will not be restarted or replaced.
By default, the NAT instances will route all traffic. To control what traffic
gets routed, pass a custom value for defaultAllowedTraffic and access the
NatInstanceProvider.connections member after having passed the NAT provider to
the VPC:
# instance_type: ec2.InstanceType
provider = ec2.NatProvider.instance_v2(
instance_type=instance_type,
default_allowed_traffic=ec2.NatTrafficDirection.OUTBOUND_ONLY
)
ec2.Vpc(self, "TheVPC",
nat_gateway_provider=provider
)
provider.connections.allow_from(ec2.Peer.ipv4("1.2.3.4/8"), ec2.Port.HTTP)
You can also customize the characteristics of your NAT instances, including their security group, as well as their initialization scripts:
# bucket: s3.Bucket
user_data = ec2.UserData.for_linux()
user_data.add_commands(
(SpreadElement ...ec2.NatInstanceProviderV2.DEFAULT_USER_DATA_COMMANDS
ec2.NatInstanceProviderV2.DEFAULT_USER_DATA_COMMANDS), "echo \"hello world!\" > hello.txt", f"aws s3 cp hello.txt s3://{bucket.bucketName}")
provider = ec2.NatProvider.instance_v2(
instance_type=ec2.InstanceType("t3.small"),
credit_specification=ec2.CpuCredits.UNLIMITED,
default_allowed_traffic=ec2.NatTrafficDirection.NONE
)
vpc = ec2.Vpc(self, "TheVPC",
nat_gateway_provider=provider,
nat_gateways=2
)
security_group = ec2.SecurityGroup(self, "SecurityGroup", vpc=vpc)
security_group.add_egress_rule(ec2.Peer.any_ipv4(), ec2.Port.tcp(443))
for gateway in provider.gateway_instances:
bucket.grant_write(gateway)
gateway.add_security_group(security_group)
# Configure the `natGatewayProvider` when defining a Vpc
nat_gateway_provider = ec2.NatProvider.instance(
instance_type=ec2.InstanceType("t3.small")
)
vpc = ec2.Vpc(self, "MyVpc",
nat_gateway_provider=nat_gateway_provider,
# The 'natGateways' parameter now controls the number of NAT instances
nat_gateways=2
)
The V1 NatProvider.instance construct will use the AWS official NAT instance AMI, which has already
reached EOL on Dec 31, 2023. For more information, see the following blog post:
Amazon Linux AMI end of life.
# instance_type: ec2.InstanceType
provider = ec2.NatProvider.instance(
instance_type=instance_type,
default_allowed_traffic=ec2.NatTrafficDirection.OUTBOUND_ONLY
)
ec2.Vpc(self, "TheVPC",
nat_gateway_provider=provider
)
provider.connections.allow_from(ec2.Peer.ipv4("1.2.3.4/8"), ec2.Port.HTTP)
Associate Public IP Address to NAT Instance
You can choose to associate public IP address to a NAT instance V2 by specifying associatePublicIpAddress
like the following:
nat_gateway_provider = ec2.NatProvider.instance_v2(
instance_type=ec2.InstanceType("t3.small"),
associate_public_ip_address=True
)
In certain scenarios where the public subnet has set mapPublicIpOnLaunch to false, NAT instances does not
get public IP addresses assigned which would result in non-working NAT instance as NAT instance requires a public
IP address to enable outbound internet connectivity. Users can specify associatePublicIpAddress to true to
solve this problem.
Ip Address Management
The VPC spans a supernet IP range, which contains the non-overlapping IPs of its contained subnets. Possible sources for this IP range are:
You specify an IP range directly by specifying a CIDR
You allocate an IP range of a given size automatically from AWS IPAM
By default the Vpc will allocate the 10.0.0.0/16 address range which will be exhaustively spread across all subnets in the subnet configuration. This behavior can be changed by passing an object that implements IIpAddresses to the ipAddress property of a Vpc. See the subsequent sections for the options.
Be aware that if you don’t explicitly reserve subnet groups in subnetConfiguration, the address space will be fully allocated! If you predict you may need to add more subnet groups later, add them early on and set reserved: true (see the “Advanced Subnet Configuration” section for more information).
Specifying a CIDR directly
Use IpAddresses.cidr to define a Cidr range for your Vpc directly in code:
from aws_cdk.aws_ec2 import IpAddresses
ec2.Vpc(self, "TheVPC",
ip_addresses=IpAddresses.cidr("10.0.1.0/20")
)
Space will be allocated to subnets in the following order:
First, spaces is allocated for all subnets groups that explicitly have a
cidrMaskset as part of their configuration (including reserved subnets).Afterwards, any remaining space is divided evenly between the rest of the subnets (if any).
The argument to IpAddresses.cidr may not be a token, and concrete Cidr values are generated in the synthesized CloudFormation template.
Allocating an IP range from AWS IPAM
Amazon VPC IP Address Manager (IPAM) manages a large IP space, from which chunks can be allocated for use in the Vpc. For information on Amazon VPC IP Address Manager please see the official documentation. An example of allocating from AWS IPAM looks like this:
from aws_cdk.aws_ec2 import IpAddresses
# pool: ec2.CfnIPAMPool
ec2.Vpc(self, "TheVPC",
ip_addresses=IpAddresses.aws_ipam_allocation(
ipv4_ipam_pool_id=pool.ref,
ipv4_netmask_length=18,
default_subnet_ipv4_netmask_length=24
)
)
IpAddresses.awsIpamAllocation requires the following:
ipv4IpamPoolId, the id of an IPAM Pool from which the VPC range should be allocated.ipv4NetmaskLength, the size of the IP range that will be requested from the Pool at deploy time.defaultSubnetIpv4NetmaskLength, the size of subnets in groups that don’t havecidrMaskset.
With this method of IP address management, no attempt is made to guess at subnet group sizes or to exhaustively allocate the IP range. All subnet groups must have an explicit cidrMask set as part of their subnet configuration, or defaultSubnetIpv4NetmaskLength must be set for a default size. If not, synthesis will fail and you must provide one or the other.
Dual Stack configuration
To allocate both IPv4 and IPv6 addresses in your VPC, you can configure your VPC to have a dual stack protocol.
ec2.Vpc(self, "DualStackVpc",
ip_protocol=ec2.IpProtocol.DUAL_STACK
)
By default, a dual stack VPC will create an Amazon provided IPv6 /56 CIDR block associated to the VPC. It will then assign /64 portions of the block to each subnet. For each subnet, auto-assigning an IPv6 address will be enabled, and auto-asigning a public IPv4 address will be disabled. An egress only internet gateway will be created for PRIVATE_WITH_EGRESS subnets, and IPv6 routes will be added for IGWs and EIGWs.
Disabling the auto-assigning of a public IPv4 address by default can avoid the cost of public IPv4 addresses starting 2/1/2024. For use cases that need an IPv4 address, the mapPublicIpOnLaunch property in subnetConfiguration can be set to auto-assign the IPv4 address. Note that private IPv4 address allocation will not be changed.
See Advanced Subnet Configuration for all IPv6 specific properties.
Reserving availability zones
There are situations where the IP space for availability zones will
need to be reserved. This is useful in situations where availability
zones would need to be added after the vpc is originally deployed,
without causing IP renumbering for availability zones subnets. The IP
space for reserving n availability zones can be done by setting the
reservedAzs to n in vpc props, as shown below:
vpc = ec2.Vpc(self, "TheVPC",
cidr="10.0.0.0/21",
max_azs=3,
reserved_azs=1
)
In the example above, the subnets for reserved availability zones is not
actually provisioned but its IP space is still reserved. If, in the future,
new availability zones needs to be provisioned, then we would decrement
the value of reservedAzs and increment the maxAzs or availabilityZones
accordingly. This action would not cause the IP address of subnets to get
renumbered, but rather the IP space that was previously reserved will be
used for the new availability zones subnets.
Advanced Subnet Configuration
If the default VPC configuration (public and private subnets spanning the
size of the VPC) don’t suffice for you, you can configure what subnets to
create by specifying the subnetConfiguration property. It allows you
to configure the number and size of all subnets. Specifying an advanced
subnet configuration could look like this:
vpc = ec2.Vpc(self, "TheVPC",
# 'IpAddresses' configures the IP range and size of the entire VPC.
# The IP space will be divided based on configuration for the subnets.
ip_addresses=ec2.IpAddresses.cidr("10.0.0.0/21"),
# 'maxAzs' configures the maximum number of availability zones to use.
# If you want to specify the exact availability zones you want the VPC
# to use, use `availabilityZones` instead.
max_azs=3,
# 'subnetConfiguration' specifies the "subnet groups" to create.
# Every subnet group will have a subnet for each AZ, so this
# configuration will create `3 groups × 3 AZs = 9` subnets.
subnet_configuration=[ec2.SubnetConfiguration(
# 'subnetType' controls Internet access, as described above.
subnet_type=ec2.SubnetType.PUBLIC,
# 'name' is used to name this particular subnet group. You will have to
# use the name for subnet selection if you have more than one subnet
# group of the same type.
name="Ingress",
# 'cidrMask' specifies the IP addresses in the range of of individual
# subnets in the group. Each of the subnets in this group will contain
# `2^(32 address bits - 24 subnet bits) - 2 reserved addresses = 254`
# usable IP addresses.
#
# If 'cidrMask' is left out the available address space is evenly
# divided across the remaining subnet groups.
cidr_mask=24
), ec2.SubnetConfiguration(
cidr_mask=24,
name="Application",
subnet_type=ec2.SubnetType.PRIVATE_WITH_EGRESS
), ec2.SubnetConfiguration(
cidr_mask=28,
name="Database",
subnet_type=ec2.SubnetType.PRIVATE_ISOLATED,
# 'reserved' can be used to reserve IP address space. No resources will
# be created for this subnet, but the IP range will be kept available for
# future creation of this subnet, or even for future subdivision.
reserved=True
)
]
)
The example above is one possible configuration, but the user can use the constructs above to implement many other network configurations.
The Vpc from the above configuration in a Region with three
availability zones will be the following:
| Subnet Name | Type | IP Block | AZ | Features |
|---|---|---|---|---|
| IngressSubnet1 | PUBLIC |
10.0.0.0/24 |
#1 | NAT Gateway |
| IngressSubnet2 | PUBLIC |
10.0.1.0/24 |
#2 | NAT Gateway |
| IngressSubnet3 | PUBLIC |
10.0.2.0/24 |
#3 | NAT Gateway |
| ApplicationSubnet1 | PRIVATE |
10.0.3.0/24 |
#1 | Route to NAT in IngressSubnet1 |
| ApplicationSubnet2 | PRIVATE |
10.0.4.0/24 |
#2 | Route to NAT in IngressSubnet2 |
| ApplicationSubnet3 | PRIVATE |
10.0.5.0/24 |
#3 | Route to NAT in IngressSubnet3 |
| DatabaseSubnet1 | ISOLATED |
10.0.6.0/28 |
#1 | Only routes within the VPC |
| DatabaseSubnet2 | ISOLATED |
10.0.6.16/28 |
#2 | Only routes within the VPC |
| DatabaseSubnet3 | ISOLATED |
10.0.6.32/28 |
#3 | Only routes within the VPC |
Dual Stack Configurations
Here is a break down of IPv4 and IPv6 specifc subnetConfiguration properties in a dual stack VPC:
vpc = ec2.Vpc(self, "TheVPC",
ip_protocol=ec2.IpProtocol.DUAL_STACK,
subnet_configuration=[ec2.SubnetConfiguration(
# general properties
name="Public",
subnet_type=ec2.SubnetType.PUBLIC,
reserved=False,
# IPv4 specific properties
map_public_ip_on_launch=True,
cidr_mask=24,
# new IPv6 specific property
ipv6_assign_address_on_creation=True
)
]
)
The property mapPublicIpOnLaunch controls if a public IPv4 address will be assigned. This defaults to false for dual stack VPCs to avoid inadvertant costs of having the public address. However, a public IP must be enabled (or otherwise configured with BYOIP or IPAM) in order for services that rely on the address to function.
The ipv6AssignAddressOnCreation property controls the same behavior for the IPv6 address. It defaults to true.
Using IPv6 specific properties in an IPv4 only VPC will result in errors.
Accessing the Internet Gateway
If you need access to the internet gateway, you can get its ID like so:
# vpc: ec2.Vpc
igw_id = vpc.internet_gateway_id
For a VPC with only ISOLATED subnets, this value will be undefined.
This is only supported for VPCs created in the stack - currently you’re unable to get the ID for imported VPCs. To do that you’d have to specifically look up the Internet Gateway by name, which would require knowing the name beforehand.
This can be useful for configuring routing using a combination of gateways: for more information see Routing below.
Disabling the creation of the default internet gateway
If you need to control the creation of the internet gateway explicitly,
you can disable the creation of the default one using the createInternetGateway
property:
vpc = ec2.Vpc(self, "VPC",
create_internet_gateway=False,
subnet_configuration=[ec2.SubnetConfiguration(
subnet_type=ec2.SubnetType.PUBLIC,
name="Public"
)]
)
Routing
It’s possible to add routes to any subnets using the addRoute() method. If for
example you want an isolated subnet to have a static route via the default
Internet Gateway created for the public subnet - perhaps for routing a VPN
connection - you can do so like this:
vpc = ec2.Vpc(self, "VPC",
subnet_configuration=[ec2.SubnetConfiguration(
subnet_type=ec2.SubnetType.PUBLIC,
name="Public"
), ec2.SubnetConfiguration(
subnet_type=ec2.SubnetType.PRIVATE_ISOLATED,
name="Isolated"
)]
)
(vpc.isolated_subnets[0]).add_route("StaticRoute",
router_id=vpc.internet_gateway_id,
router_type=ec2.RouterType.GATEWAY,
destination_cidr_block="8.8.8.8/32"
)
Note that we cast to Subnet here because the list of subnets only returns an
ISubnet.
Reserving subnet IP space
There are situations where the IP space for a subnet or number of subnets
will need to be reserved. This is useful in situations where subnets would
need to be added after the vpc is originally deployed, without causing IP
renumbering for existing subnets. The IP space for a subnet may be reserved
by setting the reserved subnetConfiguration property to true, as shown
below:
vpc = ec2.Vpc(self, "TheVPC",
nat_gateways=1,
subnet_configuration=[ec2.SubnetConfiguration(
cidr_mask=26,
name="Public",
subnet_type=ec2.SubnetType.PUBLIC
), ec2.SubnetConfiguration(
cidr_mask=26,
name="Application1",
subnet_type=ec2.SubnetType.PRIVATE_WITH_EGRESS
), ec2.SubnetConfiguration(
cidr_mask=26,
name="Application2",
subnet_type=ec2.SubnetType.PRIVATE_WITH_EGRESS,
reserved=True
), ec2.SubnetConfiguration(
cidr_mask=27,
name="Database",
subnet_type=ec2.SubnetType.PRIVATE_ISOLATED
)
]
)
In the example above, the subnet for Application2 is not actually provisioned
but its IP space is still reserved. If in the future this subnet needs to be
provisioned, then the reserved: true property should be removed. Reserving
parts of the IP space prevents the other subnets from getting renumbered.
Importing an existing VPC
If your VPC is created outside your CDK app, you can use Vpc.fromLookup().
The CDK CLI will search for the specified VPC in the the stack’s region and
account, and import the subnet configuration. Looking up can be done by VPC
ID, but more flexibly by searching for a specific tag on the VPC.
Subnet types will be determined from the aws-cdk:subnet-type tag on the
subnet if it exists, or the presence of a route to an Internet Gateway
otherwise. Subnet names will be determined from the aws-cdk:subnet-name tag
on the subnet if it exists, or will mirror the subnet type otherwise (i.e.
a public subnet will have the name "Public").
The result of the Vpc.fromLookup() operation will be written to a file
called cdk.context.json. You must commit this file to source control so
that the lookup values are available in non-privileged environments such
as CI build steps, and to ensure your template builds are repeatable.
Here’s how Vpc.fromLookup() can be used:
vpc = ec2.Vpc.from_lookup(stack, "VPC",
# This imports the default VPC but you can also
# specify a 'vpcName' or 'tags'.
is_default=True
)
Vpc.fromLookup is the recommended way to import VPCs. If for whatever
reason you do not want to use the context mechanism to look up a VPC at
synthesis time, you can also use Vpc.fromVpcAttributes. This has the
following limitations:
Every subnet group in the VPC must have a subnet in each availability zone (for example, each AZ must have both a public and private subnet). Asymmetric VPCs are not supported.
All VpcId, SubnetId, RouteTableId, … parameters must either be known at synthesis time, or they must come from deploy-time list parameters whose deploy-time lengths are known at synthesis time.
Using Vpc.fromVpcAttributes() looks like this:
vpc = ec2.Vpc.from_vpc_attributes(self, "VPC",
vpc_id="vpc-1234",
availability_zones=["us-east-1a", "us-east-1b"],
# Either pass literals for all IDs
public_subnet_ids=["s-12345", "s-67890"],
# OR: import a list of known length
private_subnet_ids=Fn.import_list_value("PrivateSubnetIds", 2),
# OR: split an imported string to a list of known length
isolated_subnet_ids=Fn.split(",", ssm.StringParameter.value_for_string_parameter(self, "MyParameter"), 2)
)
For each subnet group the import function accepts optional parameters for subnet
names, route table ids and IPv4 CIDR blocks. When supplied, the length of these
lists are required to match the length of the list of subnet ids, allowing the
lists to be zipped together to form ISubnet instances.
Public subnet group example (for private or isolated subnet groups, use the properties with the respective prefix):
vpc = ec2.Vpc.from_vpc_attributes(self, "VPC",
vpc_id="vpc-1234",
availability_zones=["us-east-1a", "us-east-1b", "us-east-1c"],
public_subnet_ids=["s-12345", "s-34567", "s-56789"],
public_subnet_names=["Subnet A", "Subnet B", "Subnet C"],
public_subnet_route_table_ids=["rt-12345", "rt-34567", "rt-56789"],
public_subnet_ipv4_cidr_blocks=["10.0.0.0/24", "10.0.1.0/24", "10.0.2.0/24"]
)
The above example will create an IVpc instance with three public subnets:
| Subnet id | Availability zone | Subnet name | Route table id | IPv4 CIDR | | ——— | —————– | ———– | ————– | ———– | | s-12345 | us-east-1a | Subnet A | rt-12345 | 10.0.0.0/24 | | s-34567 | us-east-1b | Subnet B | rt-34567 | 10.0.1.0/24 | | s-56789 | us-east-1c | Subnet B | rt-56789 | 10.0.2.0/24 |
Restricting access to the VPC default security group
AWS Security best practices recommend that the VPC default security group should
not allow inbound and outbound
traffic.
When the @aws-cdk/aws-ec2:restrictDefaultSecurityGroup feature flag is set to
true (default for new projects) this will be enabled by default. If you do not
have this feature flag set you can either set the feature flag or you can set
the restrictDefaultSecurityGroup property to true.
ec2.Vpc(self, "VPC",
restrict_default_security_group=True
)
If you set this property to true and then later remove it or set it to false
the default ingress/egress will be restored on the default security group.
Allowing Connections
In AWS, all network traffic in and out of Elastic Network Interfaces (ENIs)
is controlled by Security Groups. You can think of Security Groups as a
firewall with a set of rules. By default, Security Groups allow no incoming
(ingress) traffic and all outgoing (egress) traffic. You can add ingress rules
to them to allow incoming traffic streams. To exert fine-grained control over
egress traffic, set allowAllOutbound: false on the SecurityGroup, after
which you can add egress traffic rules.
You can manipulate Security Groups directly:
my_security_group = ec2.SecurityGroup(self, "SecurityGroup",
vpc=vpc,
description="Allow ssh access to ec2 instances",
allow_all_outbound=True
)
my_security_group.add_ingress_rule(ec2.Peer.any_ipv4(), ec2.Port.tcp(22), "allow ssh access from the world")
All constructs that create ENIs on your behalf (typically constructs that create EC2 instances or other VPC-connected resources) will all have security groups automatically assigned. Those constructs have an attribute called connections, which is an object that makes it convenient to update the security groups. If you want to allow connections between two constructs that have security groups, you have to add an Egress rule to one Security Group, and an Ingress rule to the other. The connections object will automatically take care of this for you:
# load_balancer: elbv2.ApplicationLoadBalancer
# app_fleet: autoscaling.AutoScalingGroup
# db_fleet: autoscaling.AutoScalingGroup
# Allow connections from anywhere
load_balancer.connections.allow_from_any_ipv4(ec2.Port.HTTPS, "Allow inbound HTTPS")
# The same, but an explicit IP address
load_balancer.connections.allow_from(ec2.Peer.ipv4("1.2.3.4/32"), ec2.Port.HTTPS, "Allow inbound HTTPS")
# Allow connection between AutoScalingGroups
app_fleet.connections.allow_to(db_fleet, ec2.Port.HTTPS, "App can call database")
Connection Peers
There are various classes that implement the connection peer part:
# app_fleet: autoscaling.AutoScalingGroup
# db_fleet: autoscaling.AutoScalingGroup
# Simple connection peers
peer = ec2.Peer.ipv4("10.0.0.0/16")
peer = ec2.Peer.any_ipv4()
peer = ec2.Peer.ipv6("::0/0")
peer = ec2.Peer.any_ipv6()
peer = ec2.Peer.prefix_list("pl-12345")
app_fleet.connections.allow_to(peer, ec2.Port.HTTPS, "Allow outbound HTTPS")
Any object that has a security group can itself be used as a connection peer:
# fleet1: autoscaling.AutoScalingGroup
# fleet2: autoscaling.AutoScalingGroup
# app_fleet: autoscaling.AutoScalingGroup
# These automatically create appropriate ingress and egress rules in both security groups
fleet1.connections.allow_to(fleet2, ec2.Port.HTTP, "Allow between fleets")
app_fleet.connections.allow_from_any_ipv4(ec2.Port.HTTP, "Allow from load balancer")
Port Ranges
The connections that are allowed are specified by port ranges. A number of classes provide the connection specifier:
ec2.Port.tcp(80)
ec2.Port.HTTPS
ec2.Port.tcp_range(60000, 65535)
ec2.Port.all_tcp()
ec2.Port.all_icmp()
ec2.Port.all_icmp_v6()
ec2.Port.all_traffic()
NOTE: Not all protocols have corresponding helper methods. In the absence of a helper method, you can instantiate
Portyourself with your own settings. You are also welcome to contribute new helper methods.
Default Ports
Some Constructs have default ports associated with them. For example, the listener of a load balancer does (it’s the public port), or instances of an RDS database (it’s the port the database is accepting connections on).
If the object you’re calling the peering method on has a default port associated with it, you can call
allowDefaultPortFrom() and omit the port specifier. If the argument has an associated default port, call
allowDefaultPortTo().
For example:
# listener: elbv2.ApplicationListener
# app_fleet: autoscaling.AutoScalingGroup
# rds_database: rds.DatabaseCluster
# Port implicit in listener
listener.connections.allow_default_port_from_any_ipv4("Allow public")
# Port implicit in peer
app_fleet.connections.allow_default_port_to(rds_database, "Fleet can access database")
Security group rules
By default, security group wills be added inline to the security group in the output cloud formation template, if applicable. This includes any static rules by ip address and port range. This optimization helps to minimize the size of the template.
In some environments this is not desirable, for example if your security group access is controlled
via tags. You can disable inline rules per security group or globally via the context key
@aws-cdk/aws-ec2.securityGroupDisableInlineRules.
my_security_group_without_inline_rules = ec2.SecurityGroup(self, "SecurityGroup",
vpc=vpc,
description="Allow ssh access to ec2 instances",
allow_all_outbound=True,
disable_inline_rules=True
)
# This will add the rule as an external cloud formation construct
my_security_group_without_inline_rules.add_ingress_rule(ec2.Peer.any_ipv4(), ec2.Port.SSH, "allow ssh access from the world")
Importing an existing security group
If you know the ID and the configuration of the security group to import, you can use SecurityGroup.fromSecurityGroupId:
sg = ec2.SecurityGroup.from_security_group_id(self, "SecurityGroupImport", "sg-1234",
allow_all_outbound=True
)
Alternatively, use lookup methods to import security groups if you do not know the ID or the configuration details. Method SecurityGroup.fromLookupByName looks up a security group if the security group ID is unknown.
sg = ec2.SecurityGroup.from_lookup_by_name(self, "SecurityGroupLookup", "security-group-name", vpc)
If the security group ID is known and configuration details are unknown, use method SecurityGroup.fromLookupById instead. This method will lookup property allowAllOutbound from the current configuration of the security group.
sg = ec2.SecurityGroup.from_lookup_by_id(self, "SecurityGroupLookup", "sg-1234")
The result of SecurityGroup.fromLookupByName and SecurityGroup.fromLookupById operations will be written to a file called cdk.context.json. You must commit this file to source control so that the lookup values are available in non-privileged environments such as CI build steps, and to ensure your template builds are repeatable.
Cross Stack Connections
If you are attempting to add a connection from a peer in one stack to a peer in a different stack, sometimes it is necessary to ensure that you are making the connection in a specific stack in order to avoid a cyclic reference. If there are no other dependencies between stacks then it will not matter in which stack you make the connection, but if there are existing dependencies (i.e. stack1 already depends on stack2), then it is important to make the connection in the dependent stack (i.e. stack1).
Whenever you make a connections function call, the ingress and egress security group rules will be added to the stack that the calling object exists in.
So if you are doing something like peer1.connections.allowFrom(peer2), then the security group rules (both ingress and egress) will be created in peer1’s Stack.
As an example, if we wanted to allow a connection from a security group in one stack (egress) to a security group in a different stack (ingress), we would make the connection like:
If Stack1 depends on Stack2
# Stack 1
# stack1: Stack
# stack2: Stack
sg1 = ec2.SecurityGroup(stack1, "SG1",
allow_all_outbound=False, # if this is `true` then no egress rule will be created
vpc=vpc
)
# Stack 2
sg2 = ec2.SecurityGroup(stack2, "SG2",
allow_all_outbound=False, # if this is `true` then no egress rule will be created
vpc=vpc
)
# `connections.allowTo` on `sg1` since we want the
# rules to be created in Stack1
sg1.connections.allow_to(sg2, ec2.Port.tcp(3333))
In this case both the Ingress Rule for sg2 and the Egress Rule for sg1 will both be created
in Stack 1 which avoids the cyclic reference.
If Stack2 depends on Stack1
# Stack 1
# stack1: Stack
# stack2: Stack
sg1 = ec2.SecurityGroup(stack1, "SG1",
allow_all_outbound=False, # if this is `true` then no egress rule will be created
vpc=vpc
)
# Stack 2
sg2 = ec2.SecurityGroup(stack2, "SG2",
allow_all_outbound=False, # if this is `true` then no egress rule will be created
vpc=vpc
)
# `connections.allowFrom` on `sg2` since we want the
# rules to be created in Stack2
sg2.connections.allow_from(sg1, ec2.Port.tcp(3333))
In this case both the Ingress Rule for sg2 and the Egress Rule for sg1 will both be created
in Stack 2 which avoids the cyclic reference.
Machine Images (AMIs)
AMIs control the OS that gets launched when you start your EC2 instance. The EC2 library contains constructs to select the AMI you want to use.
Depending on the type of AMI, you select it a different way. Here are some examples of images you might want to use:
# Pick the right Amazon Linux edition. All arguments shown are optional
# and will default to these values when omitted.
amzn_linux = ec2.MachineImage.latest_amazon_linux(
generation=ec2.AmazonLinuxGeneration.AMAZON_LINUX,
edition=ec2.AmazonLinuxEdition.STANDARD,
virtualization=ec2.AmazonLinuxVirt.HVM,
storage=ec2.AmazonLinuxStorage.GENERAL_PURPOSE,
cpu_type=ec2.AmazonLinuxCpuType.X86_64
)
# Pick a Windows edition to use
windows = ec2.MachineImage.latest_windows(ec2.WindowsVersion.WINDOWS_SERVER_2019_ENGLISH_FULL_BASE)
# Read AMI id from SSM parameter store
ssm = ec2.MachineImage.from_ssm_parameter("/my/ami", os=ec2.OperatingSystemType.LINUX)
# Look up the most recent image matching a set of AMI filters.
# In this case, look up the NAT instance AMI, by using a wildcard
# in the 'name' field:
nat_ami = ec2.MachineImage.lookup(
name="amzn-ami-vpc-nat-*",
owners=["amazon"]
)
# For other custom (Linux) images, instantiate a `GenericLinuxImage` with
# a map giving the AMI to in for each region:
linux = ec2.MachineImage.generic_linux({
"us-east-1": "ami-97785bed",
"eu-west-1": "ami-12345678"
})
# For other custom (Windows) images, instantiate a `GenericWindowsImage` with
# a map giving the AMI to in for each region:
generic_windows = ec2.MachineImage.generic_windows({
"us-east-1": "ami-97785bed",
"eu-west-1": "ami-12345678"
})
NOTE: The AMIs selected by
MachineImage.lookup()will be cached incdk.context.json, so that your AutoScalingGroup instances aren’t replaced while you are making unrelated changes to your CDK app.To query for the latest AMI again, remove the relevant cache entry from
cdk.context.json, or use thecdk contextcommand. For more information, see Runtime Context in the CDK developer guide.
MachineImage.genericLinux(),MachineImage.genericWindows()will useCfnMappingin an agnostic stack.
Special VPC configurations
VPN connections to a VPC
Create your VPC with VPN connections by specifying the vpnConnections props (keys are construct ids):
from aws_cdk import SecretValue
vpc = ec2.Vpc(self, "MyVpc",
vpn_connections={
"dynamic": ec2.VpnConnectionOptions( # Dynamic routing (BGP)
ip="1.2.3.4",
tunnel_options=[ec2.VpnTunnelOption(
pre_shared_key_secret=SecretValue.unsafe_plain_text("secretkey1234")
), ec2.VpnTunnelOption(
pre_shared_key_secret=SecretValue.unsafe_plain_text("secretkey5678")
)
]),
"static": ec2.VpnConnectionOptions( # Static routing
ip="4.5.6.7",
static_routes=["192.168.10.0/24", "192.168.20.0/24"
])
}
)
To create a VPC that can accept VPN connections, set vpnGateway to true:
vpc = ec2.Vpc(self, "MyVpc",
vpn_gateway=True
)
VPN connections can then be added:
vpc.add_vpn_connection("Dynamic",
ip="1.2.3.4"
)
By default, routes will be propagated on the route tables associated with the private subnets. If no
private subnets exist, isolated subnets are used. If no isolated subnets exist, public subnets are
used. Use the Vpc property vpnRoutePropagation to customize this behavior.
VPN connections expose metrics (cloudwatch.Metric) across all tunnels in the account/region and per connection:
# Across all tunnels in the account/region
all_data_out = ec2.VpnConnection.metric_all_tunnel_data_out()
# For a specific vpn connection
vpn_connection = vpc.add_vpn_connection("Dynamic",
ip="1.2.3.4"
)
state = vpn_connection.metric_tunnel_state()
VPC endpoints
A VPC endpoint enables you to privately connect your VPC to supported AWS services and VPC endpoint services powered by PrivateLink without requiring an internet gateway, NAT device, VPN connection, or AWS Direct Connect connection. Instances in your VPC do not require public IP addresses to communicate with resources in the service. Traffic between your VPC and the other service does not leave the Amazon network.
Endpoints are virtual devices. They are horizontally scaled, redundant, and highly available VPC components that allow communication between instances in your VPC and services without imposing availability risks or bandwidth constraints on your network traffic.
# Add gateway endpoints when creating the VPC
vpc = ec2.Vpc(self, "MyVpc",
gateway_endpoints={
"S3": cdk.aws_ec2.GatewayVpcEndpointOptions(
service=ec2.GatewayVpcEndpointAwsService.S3
)
}
)
# Alternatively gateway endpoints can be added on the VPC
dynamo_db_endpoint = vpc.add_gateway_endpoint("DynamoDbEndpoint",
service=ec2.GatewayVpcEndpointAwsService.DYNAMODB
)
# This allows to customize the endpoint policy
dynamo_db_endpoint.add_to_policy(
iam.PolicyStatement( # Restrict to listing and describing tables
principals=[iam.AnyPrincipal()],
actions=["dynamodb:DescribeTable", "dynamodb:ListTables"],
resources=["*"]))
# Add an interface endpoint
vpc.add_interface_endpoint("EcrDockerEndpoint",
service=ec2.InterfaceVpcEndpointAwsService.ECR_DOCKER
)
By default, CDK will place a VPC endpoint in one subnet per AZ. If you wish to override the AZs CDK places the VPC endpoint in,
use the subnets parameter as follows:
# vpc: ec2.Vpc
ec2.InterfaceVpcEndpoint(self, "VPC Endpoint",
vpc=vpc,
service=ec2.InterfaceVpcEndpointService("com.amazonaws.vpce.us-east-1.vpce-svc-uuddlrlrbastrtsvc", 443),
# Choose which availability zones to place the VPC endpoint in, based on
# available AZs
subnets=ec2.SubnetSelection(
availability_zones=["us-east-1a", "us-east-1c"]
)
)
Per the AWS documentation, not all
VPC endpoint services are available in all AZs. If you specify the parameter lookupSupportedAzs, CDK attempts to discover which
AZs an endpoint service is available in, and will ensure the VPC endpoint is not placed in a subnet that doesn’t match those AZs.
These AZs will be stored in cdk.context.json.
# vpc: ec2.Vpc
ec2.InterfaceVpcEndpoint(self, "VPC Endpoint",
vpc=vpc,
service=ec2.InterfaceVpcEndpointService("com.amazonaws.vpce.us-east-1.vpce-svc-uuddlrlrbastrtsvc", 443),
# Choose which availability zones to place the VPC endpoint in, based on
# available AZs
lookup_supported_azs=True
)
Pre-defined AWS services are defined in the InterfaceVpcEndpointAwsService class, and can be used to create VPC endpoints without having to configure name, ports, etc. For example, a Keyspaces endpoint can be created for use in your VPC:
# vpc: ec2.Vpc
ec2.InterfaceVpcEndpoint(self, "VPC Endpoint",
vpc=vpc,
service=ec2.InterfaceVpcEndpointAwsService.KEYSPACES
)
Security groups for interface VPC endpoints
By default, interface VPC endpoints create a new security group and all traffic to the endpoint from within the VPC will be automatically allowed.
Use the connections object to allow other traffic to flow to the endpoint:
# my_endpoint: ec2.InterfaceVpcEndpoint
my_endpoint.connections.allow_default_port_from_any_ipv4()
Alternatively, existing security groups can be used by specifying the securityGroups prop.
VPC endpoint services
A VPC endpoint service enables you to expose a Network Load Balancer(s) as a provider service to consumers, who connect to your service over a VPC endpoint. You can restrict access to your service via allowed principals (anything that extends ArnPrincipal), and require that new connections be manually accepted. You can also enable Contributor Insight rules.
# network_load_balancer1: elbv2.NetworkLoadBalancer
# network_load_balancer2: elbv2.NetworkLoadBalancer
ec2.VpcEndpointService(self, "EndpointService",
vpc_endpoint_service_load_balancers=[network_load_balancer1, network_load_balancer2],
acceptance_required=True,
allowed_principals=[iam.ArnPrincipal("arn:aws:iam::123456789012:root")],
contributor_insights=True
)
You can also include a service principal in the allowedPrincipals property by specifying it as a parameter to the ArnPrincipal constructor.
The resulting VPC endpoint will have an allowlisted principal of type Service, instead of Arn for that item in the list.
# network_load_balancer: elbv2.NetworkLoadBalancer
ec2.VpcEndpointService(self, "EndpointService",
vpc_endpoint_service_load_balancers=[network_load_balancer],
allowed_principals=[iam.ArnPrincipal("ec2.amazonaws.com")]
)
Endpoint services support private DNS, which makes it easier for clients to connect to your service by automatically setting up DNS in their VPC. You can enable private DNS on an endpoint service like so:
from aws_cdk.aws_route53 import PublicHostedZone, VpcEndpointServiceDomainName
# zone: PublicHostedZone
# vpces: ec2.VpcEndpointService
VpcEndpointServiceDomainName(self, "EndpointDomain",
endpoint_service=vpces,
domain_name="my-stuff.aws-cdk.dev",
public_hosted_zone=zone
)
Note: The domain name must be owned (registered through Route53) by the account the endpoint service is in, or delegated to the account. The VpcEndpointServiceDomainName will handle the AWS side of domain verification, the process for which can be found here
Client VPN endpoint
AWS Client VPN is a managed client-based VPN service that enables you to securely access your AWS resources and resources in your on-premises network. With Client VPN, you can access your resources from any location using an OpenVPN-based VPN client.
Use the addClientVpnEndpoint() method to add a client VPN endpoint to a VPC:
vpc.add_client_vpn_endpoint("Endpoint",
cidr="10.100.0.0/16",
server_certificate_arn="arn:aws:acm:us-east-1:123456789012:certificate/server-certificate-id",
# Mutual authentication
client_certificate_arn="arn:aws:acm:us-east-1:123456789012:certificate/client-certificate-id",
# User-based authentication
user_based_authentication=ec2.ClientVpnUserBasedAuthentication.federated(saml_provider)
)
The endpoint must use at least one authentication method:
Mutual authentication with a client certificate
User-based authentication (directory or federated)
If user-based authentication is used, the self-service portal URL is made available via a CloudFormation output.
By default, a new security group is created, and logging is enabled. Moreover, a rule to authorize all users to the VPC CIDR is created.
To customize authorization rules, set the authorizeAllUsersToVpcCidr prop to false
and use addAuthorizationRule():
endpoint = vpc.add_client_vpn_endpoint("Endpoint",
cidr="10.100.0.0/16",
server_certificate_arn="arn:aws:acm:us-east-1:123456789012:certificate/server-certificate-id",
user_based_authentication=ec2.ClientVpnUserBasedAuthentication.federated(saml_provider),
authorize_all_users_to_vpc_cidr=False
)
endpoint.add_authorization_rule("Rule",
cidr="10.0.10.0/32",
group_id="group-id"
)
Use addRoute() to configure network routes:
endpoint = vpc.add_client_vpn_endpoint("Endpoint",
cidr="10.100.0.0/16",
server_certificate_arn="arn:aws:acm:us-east-1:123456789012:certificate/server-certificate-id",
user_based_authentication=ec2.ClientVpnUserBasedAuthentication.federated(saml_provider)
)
# Client-to-client access
endpoint.add_route("Route",
cidr="10.100.0.0/16",
target=ec2.ClientVpnRouteTarget.local()
)
Use the connections object of the endpoint to allow traffic to other security groups.
Instances
You can use the Instance class to start up a single EC2 instance. For production setups, we recommend
you use an AutoScalingGroup from the aws-autoscaling module instead, as AutoScalingGroups will take
care of restarting your instance if it ever fails.
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
# Amazon Linux 2
ec2.Instance(self, "Instance2",
vpc=vpc,
instance_type=instance_type,
machine_image=ec2.MachineImage.latest_amazon_linux2()
)
# Amazon Linux 2 with kernel 5.x
ec2.Instance(self, "Instance3",
vpc=vpc,
instance_type=instance_type,
machine_image=ec2.MachineImage.latest_amazon_linux2(
kernel=ec2.AmazonLinux2Kernel.KERNEL_5_10
)
)
# Amazon Linux 2023
ec2.Instance(self, "Instance4",
vpc=vpc,
instance_type=instance_type,
machine_image=ec2.MachineImage.latest_amazon_linux2023()
)
# Graviton 3 Processor
ec2.Instance(self, "Instance5",
vpc=vpc,
instance_type=ec2.InstanceType.of(ec2.InstanceClass.C7G, ec2.InstanceSize.LARGE),
machine_image=ec2.MachineImage.latest_amazon_linux2023(
cpu_type=ec2.AmazonLinuxCpuType.ARM_64
)
)
Latest Amazon Linux Images
Rather than specifying a specific AMI ID to use, it is possible to specify a SSM
Parameter that contains the AMI ID. AWS publishes a set of public parameters
that contain the latest Amazon Linux AMIs. To make it easier to query a
particular image parameter, the CDK provides a couple of constructs AmazonLinux2ImageSsmParameter,
AmazonLinux2022ImageSsmParameter, & AmazonLinux2023SsmParameter. For example
to use the latest al2023 image:
# vpc: ec2.Vpc
ec2.Instance(self, "LatestAl2023",
vpc=vpc,
instance_type=ec2.InstanceType.of(ec2.InstanceClass.C7G, ec2.InstanceSize.LARGE),
machine_image=ec2.MachineImage.latest_amazon_linux2023()
)
Warning Since this retrieves the value from an SSM parameter at deployment time, the value will be resolved each time the stack is deployed. This means that if the parameter contains a different value on your next deployment, the instance will be replaced.
It is also possible to perform the lookup once at synthesis time and then cache the value in CDK context. This way the value will not change on future deployments unless you manually refresh the context.
# vpc: ec2.Vpc
ec2.Instance(self, "LatestAl2023",
vpc=vpc,
instance_type=ec2.InstanceType.of(ec2.InstanceClass.C7G, ec2.InstanceSize.LARGE),
machine_image=ec2.MachineImage.latest_amazon_linux2023(
cached_in_context=True
)
)
# or
ec2.Instance(self, "LatestAl2023",
vpc=vpc,
instance_type=ec2.InstanceType.of(ec2.InstanceClass.C7G, ec2.InstanceSize.LARGE),
# context cache is turned on by default
machine_image=ec2.AmazonLinux2023ImageSsmParameter()
)
Kernel Versions
Each Amazon Linux AMI uses a specific kernel version. Most Amazon Linux generations come with an AMI using the “default” kernel and then 1 or more AMIs using a specific kernel version, which may or may not be different from the default kernel version.
For example, Amazon Linux 2 has two different AMIs available from the SSM parameters.
/aws/service/ami-amazon-linux-latest/amzn2-ami-hvm-x86_64-ebsThis is the “default” kernel which uses
kernel-4.14
/aws/service/ami-amazon-linux-latest/amzn2-ami-kernel-5.10-hvm-x86_64-ebs
If a new Amazon Linux generation AMI is published with a new kernel version,
then a new SSM parameter will be created with the new version
(e.g. /aws/service/ami-amazon-linux-latest/amzn2-ami-kernel-5.15-hvm-x86_64-ebs),
but the “default” AMI may or may not be updated.
If you would like to make sure you always have the latest kernel version, then either specify the specific latest kernel version or opt-in to using the CDK latest kernel version.
# vpc: ec2.Vpc
ec2.Instance(self, "LatestAl2023",
vpc=vpc,
instance_type=ec2.InstanceType.of(ec2.InstanceClass.C7G, ec2.InstanceSize.LARGE),
# context cache is turned on by default
machine_image=ec2.AmazonLinux2023ImageSsmParameter(
kernel=ec2.AmazonLinux2023Kernel.KERNEL_6_1
)
)
CDK managed latest
# vpc: ec2.Vpc
ec2.Instance(self, "LatestAl2023",
vpc=vpc,
instance_type=ec2.InstanceType.of(ec2.InstanceClass.C7G, ec2.InstanceSize.LARGE),
# context cache is turned on by default
machine_image=ec2.AmazonLinux2023ImageSsmParameter(
kernel=ec2.AmazonLinux2023Kernel.CDK_LATEST
)
)
# or
ec2.Instance(self, "LatestAl2023",
vpc=vpc,
instance_type=ec2.InstanceType.of(ec2.InstanceClass.C7G, ec2.InstanceSize.LARGE),
machine_image=ec2.MachineImage.latest_amazon_linux2023()
)
When using the CDK managed latest version, when a new kernel version is made
available the LATEST will be updated to point to the new kernel version. You
then would be required to update the newest CDK version for it to take effect.
Configuring Instances using CloudFormation Init (cfn-init)
CloudFormation Init allows you to configure your instances by writing files to them, installing software
packages, starting services and running arbitrary commands. By default, if any of the instance setup
commands throw an error; the deployment will fail and roll back to the previously known good state.
The following documentation also applies to AutoScalingGroups.
For the full set of capabilities of this system, see the documentation for
AWS::CloudFormation::Init.
Here is an example of applying some configuration to an instance:
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
# machine_image: ec2.IMachineImage
ec2.Instance(self, "Instance",
vpc=vpc,
instance_type=instance_type,
machine_image=machine_image,
# Showing the most complex setup, if you have simpler requirements
# you can use `CloudFormationInit.fromElements()`.
init=ec2.CloudFormationInit.from_config_sets(
config_sets={
# Applies the configs below in this order
"default": ["yumPreinstall", "config"]
},
configs={
"yum_preinstall": ec2.InitConfig([
# Install an Amazon Linux package using yum
ec2.InitPackage.yum("git")
]),
"config": ec2.InitConfig([
# Create a JSON file from tokens (can also create other files)
ec2.InitFile.from_object("/etc/stack.json", {
"stack_id": Stack.of(self).stack_id,
"stack_name": Stack.of(self).stack_name,
"region": Stack.of(self).region
}),
# Create a group and user
ec2.InitGroup.from_name("my-group"),
ec2.InitUser.from_name("my-user"),
# Install an RPM from the internet
ec2.InitPackage.rpm("http://mirrors.ukfast.co.uk/sites/dl.fedoraproject.org/pub/epel/8/Everything/x86_64/Packages/r/rubygem-git-1.5.0-2.el8.noarch.rpm")
])
}
),
init_options=ec2.ApplyCloudFormationInitOptions(
# Optional, which configsets to activate (['default'] by default)
config_sets=["default"],
# Optional, how long the installation is expected to take (5 minutes by default)
timeout=Duration.minutes(30),
# Optional, whether to include the --url argument when running cfn-init and cfn-signal commands (false by default)
include_url=True,
# Optional, whether to include the --role argument when running cfn-init and cfn-signal commands (false by default)
include_role=True
)
)
InitCommand can not be used to start long-running processes. At deploy time,
cfn-init will always wait for the process to exit before continuing, causing
the CloudFormation deployment to fail because the signal hasn’t been received
within the expected timeout.
Instead, you should install a service configuration file onto your machine InitFile,
and then use InitService to start it.
If your Linux OS is using SystemD (like Amazon Linux 2 or higher), the CDK has
helpers to create a long-running service using CFN Init. You can create a
SystemD-compatible config file using InitService.systemdConfigFile(), and
start it immediately. The following examples shows how to start a trivial Python
3 web server:
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
ec2.Instance(self, "Instance",
vpc=vpc,
instance_type=instance_type,
machine_image=ec2.MachineImage.latest_amazon_linux2023(),
init=ec2.CloudFormationInit.from_elements(
# Create a simple config file that runs a Python web server
ec2.InitService.systemd_config_file("simpleserver",
command="/usr/bin/python3 -m http.server 8080",
cwd="/var/www/html"
),
# Start the server using SystemD
ec2.InitService.enable("simpleserver",
service_manager=ec2.ServiceManager.SYSTEMD
),
# Drop an example file to show the web server working
ec2.InitFile.from_string("/var/www/html/index.html", "Hello! It's working!"))
)
You can have services restarted after the init process has made changes to the system.
To do that, instantiate an InitServiceRestartHandle and pass it to the config elements
that need to trigger the restart and the service itself. For example, the following
config writes a config file for nginx, extracts an archive to the root directory, and then
restarts nginx so that it picks up the new config and files:
# my_bucket: s3.Bucket
handle = ec2.InitServiceRestartHandle()
ec2.CloudFormationInit.from_elements(
ec2.InitFile.from_string("/etc/nginx/nginx.conf", "...", service_restart_handles=[handle]),
ec2.InitSource.from_s3_object("/var/www/html", my_bucket, "html.zip", service_restart_handles=[handle]),
ec2.InitService.enable("nginx",
service_restart_handle=handle
))
You can use the environmentVariables or environmentFiles parameters to specify environment variables
for your services:
ec2.InitConfig([
ec2.InitFile.from_string("/myvars.env", "VAR_FROM_FILE=\"VAR_FROM_FILE\""),
ec2.InitService.systemd_config_file("myapp",
command="/usr/bin/python3 -m http.server 8080",
cwd="/var/www/html",
environment_variables={
"MY_VAR": "MY_VAR"
},
environment_files=["/myvars.env"]
)
])
Bastion Hosts
A bastion host functions as an instance used to access servers and resources in a VPC without open up the complete VPC on a network level. You can use bastion hosts using a standard SSH connection targeting port 22 on the host. As an alternative, you can connect the SSH connection feature of AWS Systems Manager Session Manager, which does not need an opened security group. (https://aws.amazon.com/about-aws/whats-new/2019/07/session-manager-launches-tunneling-support-for-ssh-and-scp/)
A default bastion host for use via SSM can be configured like:
host = ec2.BastionHostLinux(self, "BastionHost", vpc=vpc)
If you want to connect from the internet using SSH, you need to place the host into a public subnet. You can then configure allowed source hosts.
host = ec2.BastionHostLinux(self, "BastionHost",
vpc=vpc,
subnet_selection=ec2.SubnetSelection(subnet_type=ec2.SubnetType.PUBLIC)
)
host.allow_ssh_access_from(ec2.Peer.ipv4("1.2.3.4/32"))
As there are no SSH public keys deployed on this machine, you need to use EC2 Instance Connect
with the command aws ec2-instance-connect send-ssh-public-key to provide your SSH public key.
EBS volume for the bastion host can be encrypted like:
host = ec2.BastionHostLinux(self, "BastionHost",
vpc=vpc,
block_devices=[ec2.BlockDevice(
device_name="/dev/sdh",
volume=ec2.BlockDeviceVolume.ebs(10,
encrypted=True
)
)]
)
Placement Group
Specify placementGroup to enable the placement group support:
# instance_type: ec2.InstanceType
pg = ec2.PlacementGroup(self, "test-pg",
strategy=ec2.PlacementGroupStrategy.SPREAD
)
ec2.Instance(self, "Instance",
vpc=vpc,
instance_type=instance_type,
machine_image=ec2.MachineImage.latest_amazon_linux2023(),
placement_group=pg
)
Block Devices
To add EBS block device mappings, specify the blockDevices property. The following example sets the EBS-backed
root device (/dev/sda1) size to 50 GiB, and adds another EBS-backed device mapped to /dev/sdm that is 100 GiB in
size:
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
# machine_image: ec2.IMachineImage
ec2.Instance(self, "Instance",
vpc=vpc,
instance_type=instance_type,
machine_image=machine_image,
# ...
block_devices=[ec2.BlockDevice(
device_name="/dev/sda1",
volume=ec2.BlockDeviceVolume.ebs(50)
), ec2.BlockDevice(
device_name="/dev/sdm",
volume=ec2.BlockDeviceVolume.ebs(100)
)
]
)
It is also possible to encrypt the block devices. In this example we will create an customer managed key encrypted EBS-backed root device:
from aws_cdk.aws_kms import Key
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
# machine_image: ec2.IMachineImage
kms_key = Key(self, "KmsKey")
ec2.Instance(self, "Instance",
vpc=vpc,
instance_type=instance_type,
machine_image=machine_image,
# ...
block_devices=[ec2.BlockDevice(
device_name="/dev/sda1",
volume=ec2.BlockDeviceVolume.ebs(50,
encrypted=True,
kms_key=kms_key
)
)
]
)
To specify the throughput value for gp3 volumes, use the throughput property:
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
# machine_image: ec2.IMachineImage
ec2.Instance(self, "Instance",
vpc=vpc,
instance_type=instance_type,
machine_image=machine_image,
# ...
block_devices=[ec2.BlockDevice(
device_name="/dev/sda1",
volume=ec2.BlockDeviceVolume.ebs(100,
volume_type=ec2.EbsDeviceVolumeType.GP3,
throughput=250
)
)
]
)
EBS Optimized Instances
An Amazon EBS–optimized instance uses an optimized configuration stack and provides additional, dedicated capacity for Amazon EBS I/O. This optimization provides the best performance for your EBS volumes by minimizing contention between Amazon EBS I/O and other traffic from your instance.
Depending on the instance type, this features is enabled by default while others require explicit activation. Please refer to the documentation for details.
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
# machine_image: ec2.IMachineImage
ec2.Instance(self, "Instance",
vpc=vpc,
instance_type=instance_type,
machine_image=machine_image,
ebs_optimized=True,
block_devices=[ec2.BlockDevice(
device_name="/dev/xvda",
volume=ec2.BlockDeviceVolume.ebs(8)
)]
)
Volumes
Whereas a BlockDeviceVolume is an EBS volume that is created and destroyed as part of the creation and destruction of a specific instance. A Volume is for when you want an EBS volume separate from any particular instance. A Volume is an EBS block device that can be attached to, or detached from, any instance at any time. Some types of Volumes can also be attached to multiple instances at the same time to allow you to have shared storage between those instances.
A notable restriction is that a Volume can only be attached to instances in the same availability zone as the Volume itself.
The following demonstrates how to create a 500 GiB encrypted Volume in the us-west-2a availability zone, and give a role the ability to attach that Volume to a specific instance:
# instance: ec2.Instance
# role: iam.Role
volume = ec2.Volume(self, "Volume",
availability_zone="us-west-2a",
size=Size.gibibytes(500),
encrypted=True
)
volume.grant_attach_volume(role, [instance])
Instances Attaching Volumes to Themselves
If you need to grant an instance the ability to attach/detach an EBS volume to/from itself, then using grantAttachVolume and grantDetachVolume as outlined above
will lead to an unresolvable circular reference between the instance role and the instance. In this case, use grantAttachVolumeByResourceTag and grantDetachVolumeByResourceTag as follows:
# instance: ec2.Instance
# volume: ec2.Volume
attach_grant = volume.grant_attach_volume_by_resource_tag(instance.grant_principal, [instance])
detach_grant = volume.grant_detach_volume_by_resource_tag(instance.grant_principal, [instance])
Attaching Volumes
The Amazon EC2 documentation for Linux Instances and Windows Instances contains information on how to attach and detach your Volumes to/from instances, and how to format them for use.
The following is a sample skeleton of EC2 UserData that can be used to attach a Volume to the Linux instance that it is running on:
# instance: ec2.Instance
# volume: ec2.Volume
volume.grant_attach_volume_by_resource_tag(instance.grant_principal, [instance])
target_device = "/dev/xvdz"
instance.user_data.add_commands("TOKEN=$(curl -SsfX PUT \"http://169.254.169.254/latest/api/token\" -H \"X-aws-ec2-metadata-token-ttl-seconds: 21600\")", "INSTANCE_ID=$(curl -SsfH \"X-aws-ec2-metadata-token: $TOKEN\" http://169.254.169.254/latest/meta-data/instance-id)", f"aws --region {Stack.of(this).region} ec2 attach-volume --volume-id {volume.volumeId} --instance-id $INSTANCE_ID --device {targetDevice}", f"while ! test -e {targetDevice}; do sleep 1; done")
Tagging Volumes
You can configure tag propagation on volume creation.
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
# machine_image: ec2.IMachineImage
ec2.Instance(self, "Instance",
vpc=vpc,
machine_image=machine_image,
instance_type=instance_type,
propagate_tags_to_volume_on_creation=True
)
Throughput on GP3 Volumes
You can specify the throughput of a GP3 volume from 125 (default) to 1000.
ec2.Volume(self, "Volume",
availability_zone="us-east-1a",
size=Size.gibibytes(125),
volume_type=ec2.EbsDeviceVolumeType.GP3,
throughput=125
)
Configuring Instance Metadata Service (IMDS)
Toggling IMDSv1
You can configure EC2 Instance Metadata Service options to either allow both IMDSv1 and IMDSv2 or enforce IMDSv2 when interacting with the IMDS.
To do this for a single Instance, you can use the requireImdsv2 property.
The example below demonstrates IMDSv2 being required on a single Instance:
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
# machine_image: ec2.IMachineImage
ec2.Instance(self, "Instance",
vpc=vpc,
instance_type=instance_type,
machine_image=machine_image,
# ...
require_imdsv2=True
)
You can also use the either the InstanceRequireImdsv2Aspect for EC2 instances or the LaunchTemplateRequireImdsv2Aspect for EC2 launch templates
to apply the operation to multiple instances or launch templates, respectively.
The following example demonstrates how to use the InstanceRequireImdsv2Aspect to require IMDSv2 for all EC2 instances in a stack:
aspect = ec2.InstanceRequireImdsv2Aspect()
Aspects.of(self).add(aspect)
Associating a Public IP Address with an Instance
All subnets have an attribute that determines whether instances launched into that subnet are assigned a public IPv4 address. This attribute is set to true by default for default public subnets. Thus, an EC2 instance launched into a default public subnet will be assigned a public IPv4 address. Nondefault public subnets have this attribute set to false by default and any EC2 instance launched into a nondefault public subnet will not be assigned a public IPv4 address automatically. To automatically assign a public IPv4 address to an instance launched into a nondefault public subnet, you can set the associatePublicIpAddress property on the Instance construct to true. Alternatively, to not automatically assign a public IPv4 address to an instance launched into a default public subnet, you can set associatePublicIpAddress to false. Including this property, removing this property, or updating the value of this property on an existing instance will result in replacement of the instance.
vpc = ec2.Vpc(self, "VPC",
cidr="10.0.0.0/16",
nat_gateways=0,
max_azs=3,
subnet_configuration=[ec2.SubnetConfiguration(
name="public-subnet-1",
subnet_type=ec2.SubnetType.PUBLIC,
cidr_mask=24
)
]
)
instance = ec2.Instance(self, "Instance",
vpc=vpc,
vpc_subnets=ec2.SubnetSelection(subnet_group_name="public-subnet-1"),
instance_type=ec2.InstanceType.of(ec2.InstanceClass.T3, ec2.InstanceSize.NANO),
machine_image=ec2.AmazonLinuxImage(generation=ec2.AmazonLinuxGeneration.AMAZON_LINUX_2),
detailed_monitoring=True,
associate_public_ip_address=True
)
Specifying a key pair
To allow SSH access to an EC2 instance by default, a Key Pair must be specified. Key pairs can
be provided with the keyPair property to instances and launch templates. You can create a
key pair for an instance like this:
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
key_pair = ec2.KeyPair(self, "KeyPair",
type=ec2.KeyPairType.ED25519,
format=ec2.KeyPairFormat.PEM
)
instance = ec2.Instance(self, "Instance",
vpc=vpc,
instance_type=instance_type,
machine_image=ec2.MachineImage.latest_amazon_linux2023(),
# Use the custom key pair
key_pair=key_pair
)
When a new EC2 Key Pair is created (without imported material), the private key material is automatically stored in Systems Manager Parameter Store. This can be retrieved from the key pair construct:
key_pair = ec2.KeyPair(self, "KeyPair")
private_key = key_pair.private_key
If you already have an SSH key that you wish to use in EC2, that can be provided when constructing the
KeyPair. If public key material is provided, the key pair is considered “imported” and there
will not be any data automatically stored in Systems Manager Parameter Store and the type property
cannot be specified for the key pair.
key_pair = ec2.KeyPair(self, "KeyPair",
public_key_material="ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIB7jpNzG+YG0s+xIGWbxrxIZiiozHOEuzIJacvASP0mq"
)
Using an existing EC2 Key Pair
If you already have an EC2 Key Pair created outside of the CDK, you can import that key to your CDK stack.
You can import it purely by name:
key_pair = ec2.KeyPair.from_key_pair_name(self, "KeyPair", "the-keypair-name")
Or by specifying additional attributes:
key_pair = ec2.KeyPair.from_key_pair_attributes(self, "KeyPair",
key_pair_name="the-keypair-name",
type=ec2.KeyPairType.RSA
)
Using IPv6 IPs
Instances can be given IPv6 IPs by launching them into a subnet of a dual stack VPC.
vpc = ec2.Vpc(self, "Ip6VpcDualStack",
ip_protocol=ec2.IpProtocol.DUAL_STACK,
subnet_configuration=[ec2.SubnetConfiguration(
name="Public",
subnet_type=ec2.SubnetType.PUBLIC,
map_public_ip_on_launch=True
), ec2.SubnetConfiguration(
name="Private",
subnet_type=ec2.SubnetType.PRIVATE_ISOLATED
)
]
)
instance = ec2.Instance(self, "MyInstance",
instance_type=ec2.InstanceType.of(ec2.InstanceClass.T2, ec2.InstanceSize.MICRO),
machine_image=ec2.MachineImage.latest_amazon_linux2(),
vpc=vpc,
vpc_subnets=ec2.SubnetSelection(subnet_type=ec2.SubnetType.PUBLIC),
allow_all_ipv6_outbound=True
)
instance.connections.allow_from(ec2.Peer.any_ipv6(), ec2.Port.all_icmp_v6(), "allow ICMPv6")
Note to set mapPublicIpOnLaunch to true in the subnetConfiguration.
Additionally, IPv6 support varies by instance type. Most instance types have IPv6 support with exception of m1-m3, c1, g2, and t1.micro. A full list can be found here: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/using-eni.html#AvailableIpPerENI.
Specifying the IPv6 Address
If you want to specify the number of IPv6 addresses to assign to the instance, you can use the ipv6AddresseCount property:
# dual stack VPC
# vpc: ec2.Vpc
instance = ec2.Instance(self, "MyInstance",
instance_type=ec2.InstanceType.of(ec2.InstanceClass.M5, ec2.InstanceSize.LARGE),
machine_image=ec2.MachineImage.latest_amazon_linux2(),
vpc=vpc,
vpc_subnets=ec2.SubnetSelection(subnet_type=ec2.SubnetType.PUBLIC),
# Assign 2 IPv6 addresses to the instance
ipv6_address_count=2
)
Credit configuration modes for burstable instances
You can set the credit configuration mode for burstable instances (T2, T3, T3a and T4g instance types):
# vpc: ec2.Vpc
instance = ec2.Instance(self, "Instance",
instance_type=ec2.InstanceType.of(ec2.InstanceClass.T3, ec2.InstanceSize.MICRO),
machine_image=ec2.MachineImage.latest_amazon_linux2(),
vpc=vpc,
credit_specification=ec2.CpuCredits.STANDARD
)
It is also possible to set the credit configuration mode for NAT instances.
nat_instance_provider = ec2.NatProvider.instance(
instance_type=ec2.InstanceType.of(ec2.InstanceClass.T4G, ec2.InstanceSize.LARGE),
machine_image=ec2.AmazonLinuxImage(),
credit_specification=ec2.CpuCredits.UNLIMITED
)
ec2.Vpc(self, "VPC",
nat_gateway_provider=nat_instance_provider
)
Note: CpuCredits.UNLIMITED mode is not supported for T3 instances that are launched on a Dedicated Host.
Shutdown behavior
You can specify the behavior of the instance when you initiate shutdown from the instance (using the operating system command for system shutdown).
# vpc: ec2.Vpc
ec2.Instance(self, "Instance",
vpc=vpc,
instance_type=ec2.InstanceType.of(ec2.InstanceClass.T3, ec2.InstanceSize.NANO),
machine_image=ec2.AmazonLinuxImage(generation=ec2.AmazonLinuxGeneration.AMAZON_LINUX_2),
instance_initiated_shutdown_behavior=ec2.InstanceInitiatedShutdownBehavior.TERMINATE
)
Enabling Nitro Enclaves
You can enable AWS Nitro Enclaves for
your EC2 instances by setting the enclaveEnabled property to true. Nitro Enclaves is a feature of
AWS Nitro System that enables creating isolated and highly constrained CPU environments known as enclaves.
# vpc: ec2.Vpc
instance = ec2.Instance(self, "Instance",
instance_type=ec2.InstanceType.of(ec2.InstanceClass.M5, ec2.InstanceSize.XLARGE),
machine_image=ec2.AmazonLinuxImage(),
vpc=vpc,
enclave_enabled=True
)
NOTE: You must use an instance type and operating system that support Nitro Enclaves. For more information, see Requirements.
Enabling Termination Protection
You can enable Termination Protection for
your EC2 instances by setting the disableApiTermination property to true. Termination Protection controls whether the instance can be terminated using the AWS Management Console, AWS Command Line Interface (AWS CLI), or API.
# vpc: ec2.Vpc
instance = ec2.Instance(self, "Instance",
instance_type=ec2.InstanceType.of(ec2.InstanceClass.M5, ec2.InstanceSize.XLARGE),
machine_image=ec2.AmazonLinuxImage(),
vpc=vpc,
disable_api_termination=True
)
Enabling Instance Hibernation
You can enable Instance Hibernation for
your EC2 instances by setting the hibernationEnabled property to true. Instance Hibernation saves the
instance’s in-memory (RAM) state when an instance is stopped, and restores that state when the instance is started.
# vpc: ec2.Vpc
instance = ec2.Instance(self, "Instance",
instance_type=ec2.InstanceType.of(ec2.InstanceClass.M5, ec2.InstanceSize.XLARGE),
machine_image=ec2.AmazonLinuxImage(),
vpc=vpc,
hibernation_enabled=True,
block_devices=[ec2.BlockDevice(
device_name="/dev/xvda",
volume=ec2.BlockDeviceVolume.ebs(30,
volume_type=ec2.EbsDeviceVolumeType.GP3,
encrypted=True,
delete_on_termination=True
)
)]
)
NOTE: You must use an instance and a volume that meet the requirements for hibernation. For more information, see Prerequisites for Amazon EC2 instance hibernation.
VPC Flow Logs
VPC Flow Logs is a feature that enables you to capture information about the IP traffic going to and from network interfaces in your VPC. Flow log data can be published to Amazon CloudWatch Logs and Amazon S3. After you’ve created a flow log, you can retrieve and view its data in the chosen destination. (https://docs.aws.amazon.com/vpc/latest/userguide/flow-logs.html).
By default, a flow log will be created with CloudWatch Logs as the destination.
You can create a flow log like this:
# vpc: ec2.Vpc
ec2.FlowLog(self, "FlowLog",
resource_type=ec2.FlowLogResourceType.from_vpc(vpc)
)
Or you can add a Flow Log to a VPC by using the addFlowLog method like this:
vpc = ec2.Vpc(self, "Vpc")
vpc.add_flow_log("FlowLog")
You can also add multiple flow logs with different destinations.
vpc = ec2.Vpc(self, "Vpc")
vpc.add_flow_log("FlowLogS3",
destination=ec2.FlowLogDestination.to_s3()
)
# Only reject traffic and interval every minute.
vpc.add_flow_log("FlowLogCloudWatch",
traffic_type=ec2.FlowLogTrafficType.REJECT,
max_aggregation_interval=ec2.FlowLogMaxAggregationInterval.ONE_MINUTE
)
To create a Transit Gateway flow log, you can use the fromTransitGatewayId method:
# tgw: ec2.CfnTransitGateway
ec2.FlowLog(self, "TransitGatewayFlowLog",
resource_type=ec2.FlowLogResourceType.from_transit_gateway_id(tgw.ref)
)
To create a Transit Gateway Attachment flow log, you can use the fromTransitGatewayAttachmentId method:
# tgw_attachment: ec2.CfnTransitGatewayAttachment
ec2.FlowLog(self, "TransitGatewayAttachmentFlowLog",
resource_type=ec2.FlowLogResourceType.from_transit_gateway_attachment_id(tgw_attachment.ref)
)
For flow logs targeting TransitGateway and TransitGatewayAttachment, specifying the trafficType is not possible.
Custom Formatting
You can also custom format flow logs.
vpc = ec2.Vpc(self, "Vpc")
vpc.add_flow_log("FlowLog",
log_format=[ec2.LogFormat.DST_PORT, ec2.LogFormat.SRC_PORT
]
)
# If you just want to add a field to the default field
vpc.add_flow_log("FlowLog",
log_format=[ec2.LogFormat.VERSION, ec2.LogFormat.ALL_DEFAULT_FIELDS
]
)
# If AWS CDK does not support the new fields
vpc.add_flow_log("FlowLog",
log_format=[ec2.LogFormat.SRC_PORT,
ec2.LogFormat.custom("${new-field}")
]
)
By default, the CDK will create the necessary resources for the destination. For the CloudWatch Logs destination it will create a CloudWatch Logs Log Group as well as the IAM role with the necessary permissions to publish to the log group. In the case of an S3 destination, it will create the S3 bucket.
If you want to customize any of the destination resources you can provide your own as part of the destination.
CloudWatch Logs
# vpc: ec2.Vpc
log_group = logs.LogGroup(self, "MyCustomLogGroup")
role = iam.Role(self, "MyCustomRole",
assumed_by=iam.ServicePrincipal("vpc-flow-logs.amazonaws.com")
)
ec2.FlowLog(self, "FlowLog",
resource_type=ec2.FlowLogResourceType.from_vpc(vpc),
destination=ec2.FlowLogDestination.to_cloud_watch_logs(log_group, role)
)
S3
# vpc: ec2.Vpc
bucket = s3.Bucket(self, "MyCustomBucket")
ec2.FlowLog(self, "FlowLog",
resource_type=ec2.FlowLogResourceType.from_vpc(vpc),
destination=ec2.FlowLogDestination.to_s3(bucket)
)
ec2.FlowLog(self, "FlowLogWithKeyPrefix",
resource_type=ec2.FlowLogResourceType.from_vpc(vpc),
destination=ec2.FlowLogDestination.to_s3(bucket, "prefix/")
)
Kinesis Data Firehose
import aws_cdk.aws_kinesisfirehose as firehose
# vpc: ec2.Vpc
# delivery_stream: firehose.CfnDeliveryStream
vpc.add_flow_log("FlowLogsKinesisDataFirehose",
destination=ec2.FlowLogDestination.to_kinesis_data_firehose_destination(delivery_stream.attr_arn)
)
When the S3 destination is configured, AWS will automatically create an S3 bucket policy
that allows the service to write logs to the bucket. This makes it impossible to later update
that bucket policy. To have CDK create the bucket policy so that future updates can be made,
the @aws-cdk/aws-s3:createDefaultLoggingPolicy feature flag can be used. This can be set
in the cdk.json file.
{
"context": {
"@aws-cdk/aws-s3:createDefaultLoggingPolicy": true
}
}
User Data
User data enables you to run a script when your instances start up. In order to configure these scripts you can add commands directly to the script or you can use the UserData’s convenience functions to aid in the creation of your script.
A user data could be configured to run a script found in an asset through the following:
from aws_cdk.aws_s3_assets import Asset
# instance: ec2.Instance
asset = Asset(self, "Asset",
path="./configure.sh"
)
local_path = instance.user_data.add_s3_download_command(
bucket=asset.bucket,
bucket_key=asset.s3_object_key,
region="us-east-1"
)
instance.user_data.add_execute_file_command(
file_path=local_path,
arguments="--verbose -y"
)
asset.grant_read(instance.role)
Persisting user data
By default, EC2 UserData is run once on only the first time that an instance is started. It is possible to make the user data script run on every start of the instance.
When creating a Windows UserData you can use the persist option to set whether or not to add
<persist>true</persist> to the user data script. it can be used as follows:
windows_user_data = ec2.UserData.for_windows(persist=True)
For a Linux instance, this can be accomplished by using a Multipart user data to configure cloud-config as detailed in: https://aws.amazon.com/premiumsupport/knowledge-center/execute-user-data-ec2/
Multipart user data
In addition, to above the MultipartUserData can be used to change instance startup behavior. Multipart user data are composed
from separate parts forming archive. The most common parts are scripts executed during instance set-up. However, there are other
kinds, too.
The advantage of multipart archive is in flexibility when it’s needed to add additional parts or to use specialized parts to
fine tune instance startup. Some services (like AWS Batch) support only MultipartUserData.
The parts can be executed at different moment of instance start-up and can serve a different purpose. This is controlled by contentType property.
For common scripts, text/x-shellscript; charset="utf-8" can be used as content type.
In order to create archive the MultipartUserData has to be instantiated. Than, user can add parts to multipart archive using addPart. The MultipartBody contains methods supporting creation of body parts.
If the very custom part is required, it can be created using MultipartUserData.fromRawBody, in this case full control over content type,
transfer encoding, and body properties is given to the user.
Below is an example for creating multipart user data with single body part responsible for installing awscli and configuring maximum size
of storage used by Docker containers:
boot_hook_conf = ec2.UserData.for_linux()
boot_hook_conf.add_commands("cloud-init-per once docker_options echo 'OPTIONS=\"${OPTIONS} --storage-opt dm.basesize=40G\"' >> /etc/sysconfig/docker")
setup_commands = ec2.UserData.for_linux()
setup_commands.add_commands("sudo yum install awscli && echo Packages installed らと > /var/tmp/setup")
multipart_user_data = ec2.MultipartUserData()
# The docker has to be configured at early stage, so content type is overridden to boothook
multipart_user_data.add_part(ec2.MultipartBody.from_user_data(boot_hook_conf, "text/cloud-boothook; charset=\"us-ascii\""))
# Execute the rest of setup
multipart_user_data.add_part(ec2.MultipartBody.from_user_data(setup_commands))
ec2.LaunchTemplate(self, "",
user_data=multipart_user_data,
block_devices=[]
)
For more information see Specifying Multiple User Data Blocks Using a MIME Multi Part Archive
Using add*Command on MultipartUserData
To use the add*Command methods, that are inherited from the UserData interface, on MultipartUserData you must add a part
to the MultipartUserData and designate it as the receiver for these methods. This is accomplished by using the addUserDataPart()
method on MultipartUserData with the makeDefault argument set to true:
multipart_user_data = ec2.MultipartUserData()
commands_user_data = ec2.UserData.for_linux()
multipart_user_data.add_user_data_part(commands_user_data, ec2.MultipartBody.SHELL_SCRIPT, True)
# Adding commands to the multipartUserData adds them to commandsUserData, and vice-versa.
multipart_user_data.add_commands("touch /root/multi.txt")
commands_user_data.add_commands("touch /root/userdata.txt")
When used on an EC2 instance, the above multipartUserData will create both multi.txt and userdata.txt in /root.
Importing existing subnet
To import an existing Subnet, call Subnet.fromSubnetAttributes() or
Subnet.fromSubnetId(). Only if you supply the subnet’s Availability Zone
and Route Table Ids when calling Subnet.fromSubnetAttributes() will you be
able to use the CDK features that use these values (such as selecting one
subnet per AZ).
Importing an existing subnet looks like this:
# Supply all properties
subnet1 = ec2.Subnet.from_subnet_attributes(self, "SubnetFromAttributes",
subnet_id="s-1234",
availability_zone="pub-az-4465",
route_table_id="rt-145"
)
# Supply only subnet id
subnet2 = ec2.Subnet.from_subnet_id(self, "SubnetFromId", "s-1234")
Launch Templates
A Launch Template is a standardized template that contains the configuration information to launch an instance. They can be used when launching instances on their own, through Amazon EC2 Auto Scaling, EC2 Fleet, and Spot Fleet. Launch templates enable you to store launch parameters so that you do not have to specify them every time you launch an instance. For information on Launch Templates please see the official documentation.
The following demonstrates how to create a launch template with an Amazon Machine Image, security group, and an instance profile.
# vpc: ec2.Vpc
role = iam.Role(self, "Role",
assumed_by=iam.ServicePrincipal("ec2.amazonaws.com")
)
instance_profile = iam.InstanceProfile(self, "InstanceProfile",
role=role
)
template = ec2.LaunchTemplate(self, "LaunchTemplate",
launch_template_name="MyTemplateV1",
version_description="This is my v1 template",
machine_image=ec2.MachineImage.latest_amazon_linux2023(),
security_group=ec2.SecurityGroup(self, "LaunchTemplateSG",
vpc=vpc
),
instance_profile=instance_profile
)
And the following demonstrates how to enable metadata options support.
ec2.LaunchTemplate(self, "LaunchTemplate",
http_endpoint=True,
http_protocol_ipv6=True,
http_put_response_hop_limit=1,
http_tokens=ec2.LaunchTemplateHttpTokens.REQUIRED,
instance_metadata_tags=True
)
And the following demonstrates how to add one or more security groups to launch template.
# vpc: ec2.Vpc
sg1 = ec2.SecurityGroup(self, "sg1",
vpc=vpc
)
sg2 = ec2.SecurityGroup(self, "sg2",
vpc=vpc
)
launch_template = ec2.LaunchTemplate(self, "LaunchTemplate",
machine_image=ec2.MachineImage.latest_amazon_linux2023(),
security_group=sg1
)
launch_template.add_security_group(sg2)
To use AWS Systems Manager parameters instead of AMI IDs in launch templates and resolve the AMI IDs at instance launch time:
launch_template = ec2.LaunchTemplate(self, "LaunchTemplate",
machine_image=ec2.MachineImage.resolve_ssm_parameter_at_launch("parameterName")
)
Please note this feature does not support Launch Configurations.
Detailed Monitoring
The following demonstrates how to enable Detailed Monitoring for an EC2 instance. Keep in mind that Detailed Monitoring results in additional charges.
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
ec2.Instance(self, "Instance1",
vpc=vpc,
instance_type=instance_type,
machine_image=ec2.MachineImage.latest_amazon_linux2023(),
detailed_monitoring=True
)
Connecting to your instances using SSM Session Manager
SSM Session Manager makes it possible to connect to your instances from the AWS Console, without preparing SSH keys.
To do so, you need to:
Use an image with SSM agent installed and configured. Many images come with SSM Agent preinstalled, otherwise you may need to manually put instructions to install SSM Agent into your instance’s UserData or use EC2 Init).
Create the instance with
ssmSessionPermissions: true.
If these conditions are met, you can connect to the instance from the EC2 Console. Example:
# vpc: ec2.Vpc
# instance_type: ec2.InstanceType
ec2.Instance(self, "Instance1",
vpc=vpc,
instance_type=instance_type,
# Amazon Linux 2023 comes with SSM Agent by default
machine_image=ec2.MachineImage.latest_amazon_linux2023(),
# Turn on SSM
ssm_session_permissions=True
)
Managed Prefix Lists
Create and manage customer-managed prefix lists. If you don’t specify anything in this construct, it will manage IPv4 addresses.
You can also create an empty Prefix List with only the maximum number of entries specified, as shown in the following code. If nothing is specified, maxEntries=1.
ec2.PrefixList(self, "EmptyPrefixList",
max_entries=100
)
maxEntries can also be omitted as follows. In this case maxEntries: 2, will be set.
ec2.PrefixList(self, "PrefixList",
entries=[ec2.CfnPrefixList.EntryProperty(cidr="10.0.0.1/32"), ec2.CfnPrefixList.EntryProperty(cidr="10.0.0.2/32", description="sample1")
]
)
For more information see Work with customer-managed prefix lists