I am trying to create a nested topology from 4 existing templates. These templates do the following:
1: deploys a policy and a role.
2: deploys an EC2 instance.
3: deploys an ELB.
4: deploys an RDS instance.
All of them are "linked" by using outputs. All of the parameters are also contained within these.
Now I want to create a fifth template (master) and treat the other 4 templates as child.
However I am not too sure about the minimum code that I need in the master template:
Parameters: these are defined within the child so I don't need them here, do I?
Resources: point to the 4 child templates by providing the S3 URL where they're stored.
DependsOn clause: I need this as the child templates need to be deployed in sequential order.
Outputs: not too sure what to include here, shall I leave the outputs on the child and define here only the master's?
The master I think it should be small but not too sure if I am missing something. Another question, do I need to change anything on the child templates?
Any help would be much appreciated.
A handful of questions here, so I'll address what I can :)
For the master, or parent template, I'd recommend including all Parameters that the child stacks will need.
When you want to make any updates in the future to any of the child stacks, you'll want to initiate that from the parent stack.
According to the docs:
Certain stack operations, such as stack updates, should be initiated
from the root stack rather than performed directly on nested stacks
themselves.
So your parent template could have a lot of parameters depending on how many parameters need to be passed directly to the child templates.
Depending on how the child stacks use the Outputs from the other child stacks, you may not need to use the DependsOn to enforce ordering, since Cloudformation is smart enough to figure out Implicit Dependencies (see docs discussing DependsOn). It certainly won't hurt to include these, but the DependsOn attribute isn't needed for most situations.
You'll want to make sure the child stacks have an Outputs section so that other child stacks can use them. Pay close attention to the Return values for AWS::CloudFormation::Stack
If you have many dependent stacks, it is much easier to run everything for example from Ansible. Add outputs in each CF template, then just write simple playbook that will run your templates in desired order. Please take a look at https://docs.ansible.com/ansible/devel/modules/cloudformation_module.html
Related
I'm creating tag templates programmatically and it doesn't appear in the section "Tag Templates" (the creation of each tag template was successful because I can attach it in each table), but when I create those tag templates by hand, they appear as a list.
Btw I'm trying to list the tag templates that I created, with the following sentence:
tag_list = datacatalog.list_tags(parent=f"projects/{project_id}/locations/{location}")
but when I print it says
google.api_core.exceptions.InvalidArgument: 400 Malformed Data Catalog resource name projects/sybogames-analytics-dev/locations/us.
anyone knows why?
thanks in advance.
I'm unfamiliar with the Data Catalog service but, looking at the possible methods in APIs Explorer, I think (!?) you may need to terminate parent with /entrygroup/{entrygroup}.
There are 2 (!?) possible methods for list_tags:
entryGroups.entries.tag_list
entryGroup.tags.list
Both define parent similarly and require /entryGroups/{entrygroup}:
The resource can be an Entry or an EntryGroup (without /entries/{entries} at the end). It takes the form projects/{project}/locations/{location}/entryGroups/{entrygroup}/entries/{entries}.
You can use APIs Explorer to invoke either method to test it.
You can also use gcloud data-catalog tags list and, if you append --log-http to it, you'll be able to see exactly what underlying REST call is being made.
My application currently intakes cloudformation jsons/yamls and create stacks out of them. Currently, the struggles we are having are concerning the updating, since it's impossible to update a stack that contains custom-named resources.
My question is the following: is there a clean/smart way to remove custom names from those templates, and either service-aware or service-agnostic?
I've considered some regex/replacement but I wanted to see if there were a smarter way.
TIA
In CloudFormation we have the ability to output some values from a template so that they can be retrieved by other processes, stacks, etc. This is typically the name of something, maybe a URL or something generated during stack creation (deployment), etc.
We also have the ability to 'export' from a template. What is the difference between returning a value as an 'output' vs as an 'export'?
Regular output values can't be references from other stacks. They can be useful when you chain or nest your stacks and their scope/visibility is local. Exported outputs are visible globally within account and region, and can be used by any future stack you are going to deploy.
Chaining
When you chain your stacks, you deploy one stack, take it outputs, and use as input parameters to the second stack you are going to deploy.
For example, let's say you have two templates called instance.yaml and eip.yaml. The instance.yaml outputs its instance-id (no export), while eip.yaml takes instance id as an input parameter.
To deploy them both, you have to chain them:
Deploy instance.yaml and wait for its completion.
Note it outputs values (i.e. instance-id) - usually done programmatically, not manually.
Deploy eip.yaml and pass instance-id as its input parameter.
Nesting
When you nest stacks you will have a parent template and a child template. Child stack will be created from inside of the parent stack. In this case the child stack will produce some outputs (not exports) for the parent stack to use.
For example, lets use again instance.yaml and eip.yaml. But this time eip.yaml will be parent and instance.yaml will be child. Also eip.yaml does not take any input parameters, but instance.yaml outputs its instance-id (not export)
In this case, to deploy them you do the following:
Upload parrent template (eip.yaml) to s3
In eip.yaml create the child instance stack using AWS::CloudFormation::Stack and the s3 url from step 1.
This way eip.yaml will be able to access the instance-id from the outputs of the nested stack using GetAtt.
Cross-referencing
When you cross-reference stacks, you have one stack that exports it outputs so that they can be used by any other stack in the same region and account.
For example, lets use again instance.yaml and eip.yaml. instance.yaml is going to export its output (instance-id). To use the instance-id eip.yaml will have to use ImportValue in its template without the need for any input parameters or nested stacks.
In this case, to deploy them you do the following:
Deploy instance.yaml and wait till it completes.
Deploy eip.yaml which will import the instance-id.
Altough cross-referencing seems very useful, it has one major issue, which is that its very difficult to update or delete cross-referenced stacks:
After another stack imports an output value, you can't delete the stack that is exporting the output value or modify the exported output value. All of the imports must be removed before you can delete the exporting stack or modify the output value.
This is very problematic if you are starting your design and your templates can change often.
When to use which?
Use cross-references (exported values) when you have some global resources that are going to be shared among many stacks in a given region and account. Also they should not change often as they are difficult to modify. Common examples are: a global bucket for centralized logging location, a VPC.
Use nested stack (not exported outputs) when you have some common components that you often deploy, but each time they can be a bit different. Examples are: ALB, a bastion host instance, vpc interface endpoint.
Finally, chained stacks (not exported outputs) are useful for designing loosely-coupled templates, where you can mix and match templates based on new requirements.
Short answer from here, use export between stacks, and use output with nested stacks.
Export
To share information between stacks, export a stack's output values.
Other stacks that are in the same AWS account and region can import
the exported values.
Output
With nested stacks, you deploy and manage all resources from a single
stack. You can use outputs from one stack in the nested stack group as
inputs to another stack in the group. This differs from exporting
values.
I have been trying this example provided in the Google's Deployment Manager GitHub project.
It works, yet I am not sure what is the purpose of creating three instances named instance_create, instance_update and instance_delete.
For example, taken from the link:
instance_create = {
'name':
'instance_create',
'action':
'gcp-types/bigtableadmin-v2:bigtableadmin.projects.instances.create',
'properties': {
'parent': project_path,
'instanceId': instance_name,
'clusters': copy.deepcopy(initial_cluster),
'instance': context.properties['instance']
},
'metadata': {
'runtimePolicy': ['CREATE']
}
}
What is the purpose of `action` and `metadata`.`runtimePolicy`? I have tried to find it in the documentation but failed miserably.
Why there are three `BigTable` instances there?
You are right, the documentation is missing the information, which would answer your questions regarding these parameters.
However, it helps knowing what's going on in the Depoyment Manager example you linked.
First of all, the following line in the config.yaml is where the things get tricky:
resources:
- name: my-bigtable
type: bigtable.py
This line will do a call to the bigtable.py python file, which sets the resource type of the deployment to that which are in it, under the GenerateConfig function. See how this is done here.
The resources are returned as {'resources': resources} at the end of it, being the resources variable a list of templates created there.
These templates have different name identifiers, which are set by the "name" tag.
So you are not creating three different instances with the name of instance_create, instance_update and instance_delete in this file, but you are creating three templates with those names, that will later be appended to the resources list, and later returned to the config.yaml resources.type tag.
These templates then will be sequentially build and executed by the deployment manager, once the create command is used. Note that they might appear out of order, this is due not using a schema.
It's easier to see this structure in a .yaml file format, for example, built with jinja, the template you posted would be:
resources:
- action: gcp-types/bigtableadmin-v2:bigtableadmin.projects.instances.create
name: instance_create
metadata:
runtimePolicy:
- CREATE
properties:
clusters:
initial:
defaultStorageType: HDD
location: projects/<PROJECT_ID>/locations/<PROJECT_LOCATION>
serveNodes: 4
instance:
displayName: My BigTable Instance.
type: PRODUCTION
instanceId: my-instance
parent: projects/<PROJECT_ID>
Notice that the parameters under properties are the fields in the request body to bigtableadmin.projects.instances.create (which is nesting a clusters object parameters and a instance object parameters). Note that the InstanceId under properties is always the same, hence the BigTable instance, on which the templates do the calls, is always the same one.
The thing is that, not only the example you linked creates various templates to be run in the same script, but that the resource type for each template is a call to the BigTable API.
Normally the template resources are specified with the type tag, but since you are calling a resource that is directly running an API call (i.e. instead of just specifying gcp-types/bigtableadmin-v2, you are specifying bigtableadmin-v2:bigtableadmin.projects.instances.create), the action tag is used. I haven't found this difference on usage documented anywhere, but it needs to be specified like that.
You will know if you are calling an API 'endpoint' directly if the resource ends with either create/update/delete.
Finally, the I have investigated in my side, and the metadata.runtimePolicy is tied to the fact that the resource type is an API call (like in the previous point). Once again, I haven't found this documented anywhere.
However, since this is a requirement, you will always have to set the correct value in this field. It basically boils down to have metadata.runtimePolicy set to this values, depending on which type of API call you do:
create -> ['CREATE']
update -> ['UPDATE_ON_CHANGE']
delete -> ['DELETE']
Summarizing:
You are not creating three different instances, but three different templates, which do the work on the same BigTable instance.
You need to change the resource type flag to action if you are calling an API endpoint (create/update/delete), instead of just naming the base API.
The metadata.runtimePolicy value is a requirement when doing a call to one of the aforenamed endpoints.
Would like know if CFT API's or logs from Cloudtrail can provide any intermediate CFT before or while creating the resources. When I mean intermediate CFT(s) , We know the CFT can be kind of dynamic in the form of parameters /condition/mappings/functions those are to be evaluated at run time. I would like to know if this CFT can generate the processed CFT (with all the processed rules/parameters from input/functions...) as though it looks like static for the resource creation process. This approach really helps us in validating the real CFT that is going to be executed with all the values replaced. I'm just looking for the another CFT API. something like ,
String staticCFT = cftClient.getActualCFT("cft_location\cft.json","parameters"...);
If this feature is available , it really saves time and don't have to wait until all the resources are created with wrong values because of wrong logic in CFT.
What you can actually create is what I call a "dummy template". I use it at work as a stand-in to an actual template with real resources which would take time to execute. The dummy template has only one resource which does not actually do anything. I use a CustomResource to invoke a "HelloWorld" Lambda function. This is to get around the restriction that a CFT must have at least one resource. The template also has a bunch of parameters and all those parameters are simply supplied directly to the Outputs section. The execution of this template will hardly take a few seconds and based on the parameters and outputs, you can figure out whether your top-level template is passing in the expected values of the parameters. You can invoke the dummy template from within the top-level template.