Below configuration about all the services necessary to deploy on AWS are outlined. There is an experimental CloudFront deploy script maintained by the community as an alternative.
Walking through all the different AWS resources and configuration that must be in place before deploying Spoke.
Spoke needs a domain to run on. In order to configure the API Gateway with this domain we first need to create a certificate.
Waiting for verification for a certificate may take a while so we will start that now. Go to the Certificate Manager service. Request a certificate. Select "public." Add a domain name spoke.campaign.com
. Choose a validation method (generally the DNS method). Add the verification DNS records to your domain. Wait for the DNS update to propagate and continue with the setup.
Create a private S3 bucket by choosing all the default values as you go through the setup wizard. We will call this textforcampaign
.
We will create a VPC with two groups of subnets, one publicly accessible one for the RDS instance and one private one for our AWS Lambda function (don't worry, the API Gateway created later will expose the function via the domain you created a certificate for). Each group will have two subnets for redundancy.
Getting the VPC right is pretty tricky. Start by launching the VPC creation wizard and choosing "VPC with a Single Public Subnet". Give the VPC a name, TextForCampaign
, and change the name of the subnet to Public - 1
. Click create.
One subnet was already created for us. Take a note of the availability region this was created in. Now create a second public subnet in a different availability region with IPv4 CIDR 10.0.1.0/24
.
Create the two private subnets with CIDR blocks 10.0.2.0/24
and 10.0.3.0/24
. It is important that the private subnets are in different availability regions from each other, but they do not need to be different from the public subnets.
A NAT Gateway is required to allow the private AWS Lambda function to talk to the outside world (Twilio, Mailgun, etc.).
Create a NAT Gateway in one of the two public subnets. Create a new Elastic IP address to use with it using the provided button.
You should have two route tables for your Spoke VPC at this point. Give the name Spoke - Private
the one marked Main and Spoke - Public
to the other one.
Double check that Spoke - Public
's routes are configured to use the internet gateway created with the VPC:
| Destination | Target |
|-------------|-------------------|
| 10.0.0.0/16 | local |
| 0.0.0.0/0 | igw-xxxxxxxxxxxxx |
Then, edit Spoke - Private
's routes to connect to the NAT you just created:
| Destination | Target |
|-------------|-------------------|
| 10.0.0.0/16 | local |
| 0.0.0.0/0 | nat-xxxxxxxxxxxxx |
Security groups give you fine grained access control for resources.
Create a security group called Spoke - Lambda
and description Security group for Lambda function access
. Copy the security group ID sg-xxxxx
of this new group. Edit the inbound rules to allow web access:
| Type | Protocol | Port Range | Source | Description |
|-------------|----------|------------|----------|-----------------------|
| HTTP (80) | TCP (6) | 80 | sg-xxxxx | Web traffic |
| HTTPS (443) | TCP (6) | 443 | sg-xxxxx | Encrypted web traffic |
Create another security group called Spoke - RDS
and description Security group for RDS access
. Edit the inbound rules to allow web access:
| Type | Protocol | Port Range | Source | Description |
|-------------------|----------|------------|-----------|-----------------------|
| PostgreSQL (5432) | TCP (6) | 5432 | 0.0.0.0/0 | Allow all DB access |
We will use the AWS RDS service for our Postgres database.
Create a subnet group called spoke_rds_group
. Choose the TextForCampaign
VPC. Add our two public subnets to the group.
Create an RDS instance running Postgres 10.4 with the following settings:
Config name | Config value |
---|---|
Nickname | spoke_prod |
Database name | spoke_prod |
Username | spoke |
Password | [something secret] |
Publically exposed | yes |
Claudia is command line tool for serverless Node.js applications on AWS.
- First make sure you are running node 10.x (compatible with AWS Lambda)
nvm install 10; nvm use
- Install Claudia js:
npm install -g claudia
- Create an admin user on AWS selecting programmatic access. Add that profile to
~/.aws/credentials
giving it a nickname to use later in shell commands:[your_profile_nickname] aws_access_key_id = XXXXXXXXXXXXXXXXXXX aws_secret_access_key = XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX
- Install the AWS CLI
- See instructions at AWS Command Line Interface Version 2
- On a mac, you can also use homebrew command
brew install aws-cli
Create a file based on the template in ./deploy/lambda-env.json
, called something like ./production-env.json
locally (whatever you call it, replace the path in the commands below with it) in the form:
{
"JSONVAR1": "JSONVAR1 VALUE",
...
}
(all values must be strings)
The main variables you will require set in a lambda environment beyond the regularly documented ones:
Do NOT set:
PORT
: The whole application is called as a library, rather than running a process on a portDEV_APP_PORT
AWS_ACCESS_KEY_ID
: amazon forbids this variable -- access should be granted through the "role" for the Lambda functionAWS_SECRET_ACCESS_KEY
DO Set:
"SUPPRESS_SEED_CALLS": "1",
: This stops Spoke from trying to connect to the database every startup point. You will need to run the seed call once, directly to the database rather than through Lambda (or send us a PR to make it easy to do this and other jobs in Lambda :-)"JOBS_SAME_PROCESS": "1",
: This makes jobs get called semi-synchronously (as async in code, but triggered directly from the same Lambda instance as the originating web request"JOB_RUNNER": "lambda-async",
: This dispatches asynchronous tasks that occur after a web response to another Lambda invocation which improves performance and completion."AWS_ACCESS_AVAILABLE": "1",
: This replaces the AWS_ key variables for S3 bucket supportSTATIC_BASE_URL
: You will need to upload your ASSETS_DIR to an S3 bucket (or other static file site) and then set this to something like:"https://s3.amazonaws.com/YOUR_BUCKET_AND_PATH/"
(don't forget the trailing '/')S3_STATIC_PATH
: This will be the aws s3 upload path that corresponds to STATIC_BASE_URL. So ifSTATIC_BASE_URL=https://s3.amazon.com/spoke.example.com/static/
thenS3_STATIC_PATH=s3://spoke.example.com/static/
You will also need a ~/.s3cfg file that has the s3 upload credentials. Seepackage.json
's postinstall script and more specificallyprod-static-upload
."LAMBDA_DEBUG_LOG": "1",
: (ONLY FOR DEBUGGING) This will send more details of requests to the CloudWatch log. However, it will include the full request details, e.g. so do not use this in production."ASSETS_DIR_PREBUILT"
: should be the absolute path (runpwd
from command line) of your spoke deploy directory suffixed by/build/client
. This complements--no-optional-dependencies
claudia deploy arguments (below) so that the client-only libraries are not included in the packaged server file (which would be too big for a Lambda upload)
For large production environments, it might also be a good idea to add "SUPPRESS_MIGRATIONS": "1"
so that any time you update the schema with a version upgrade,
you can manually run the migration (see below) rather than it accidentally trigger on multiple lambdas at once.
AWS Lambda has a maximum size limit for all environment variable data of 4K -- this should generally be harmless. However, some environment variables like BASE64_GOOGLE_SECRET for script import can be quite large. In this case, create another file (does not have to be located in your Spoke project directory) in the same format as production-env.json with BASE64_GOOGLE_SECRET as a top-level JSON key (currently, no other variables are supported from this file).
Then set the variable in production-env.json CONFIG_FILE
: "/absolute/path/to/configfile.json" -- during deployment (below),
this file will be copied into the lambda function zip file and get deployed with the rest of the code.
DEVELOPER NOTE: Now that GOOGLE_SECRET is set in Base64, this may no longer be an issue. Please open a ticket if a problem occurs.
To create the AWS Lambda function and the API Gateway to access it, run the following being sure to substitute in the correct values:
$ ASSETS_DIR=./build/client/assets ASSETS_MAP_FILE=assets.json NODE_ENV=production yarn prod-build-client
$ AWS_PROFILE=[your_profile_nickname] claudia create --handler lambda.handler \
--deploy-proxy-api \
--set-env-from-json ./production-env.json \
--region [YOUR_DESIRED_REGION] \
--security-group-ids [SPOKE_LAMBDA_SECURITY_GROUP_ID] \
--subnet-ids [PRIVATE_SUBNET_1_ID],[PRIVATE_SUBNET_2_ID] \
--role SpokeOnLambda \
--use-s3-bucket [YOUR_S3_BUCKET] \
--memory 512 --timeout 300
--no-optional-dependencies
Notes:
- You'll want a timeout that corresponds with the scheduled jobs -- this is 5 minutes which should be the same as below
- The memory requirement can probably be lower, but that will affect the maximum contact upload file you can send in and process.
After Claudia.js does an 'npm install' essentially of your directory (which will filter out files in .gitignore, etc), It runs package.json
's postinstall
script which does the building necessary for production. The environment variables included in your env-from-json file will also be set during build.
Because seed calls are suppressed, you will need to seed the database manually. The current best way to do this is to run Spoke locally using the RDS database credentials. In your .env
file the relevant lines will look like:
DB_HOST=spokeprod.xxxxxxxxxxxx.us-east-1.rds.amazonaws.com
DB_PORT=5432
DB_NAME=spoke_prod
DB_USER=spoke
DB_PASSWORD=[something secret]
DB_TYPE=pg
DB_USE_SSL=true
PGSSLMODE=require
$ AWS_PROFILE=[your_profile_nickname] claudia add-scheduled-event \
--name spoke-job-runner \
--schedule 'rate(5 minutes)' \
--event ./deploy/lambda-scheduled-event.json
Migrations are created with knex[https://knexjs.org/#Migrations].
You can trigger migration updates with the following command:
$ AWS_PROFILE=[your_profile_nickname] claudia test-lambda --event ./deploy/lambda-migrate-database.js
(Note: the migration will probably take much less than the 5 minutes or whatever your lambda timeout is, however it will look like test-lambda
is still running/doing something. If you've confirmed on the DB side that the migration completed, it's safe to Ctrl + c
)
For major database changes on large database instances, you should probably disable the web interface so that web requests triggering database calls are not made. In AWS, the easiest way to do this is:
- In the API Gateway Custom Domains (see below) section, add an
invalid prefix (like
/xxx
) to the domain. - Then in the Lambda AWS Console, you can disable any CloudWatch event triggers
Once Claudia has created an API Gateway we can add a subdomain to access Spoke. Add the custom domain you created the certificate for, selecting that certificate. Add a mapping with a blank path and spoke
:latest
for the destination and path.
(if you are using nvm, make sure to run nvm use
first to use the correct node version)
$ ASSETS_DIR=./build/client/assets ASSETS_MAP_FILE=assets.json NODE_ENV=production yarn prod-build-client
$ AWS_PROFILE=[your_profile_nickname] claudia update \
--use-s3-bucket [YOUR_S3_BUCKET] \
--set-env-from-json ./production-env.json
--no-optional-dependencies