About

This repo contains scripts designed to automate Blockscout deployment builds. Currently it supports only AWS as a cloud provider.

In the root folder you can find an Ansible Playbooks that will create all necessary infrastructure and deploy BlockScout. Please refer to the following sections of the README for details:

1. Deploying the Infrastructure. This section describes all the steps to deploy the virtual hardware that is required for production instance of BlockScout. Skip this section if you do have an infrastructure and simply want to install or update your BlockScout.
2. Deploying BlockScout. Follow this section to install or update your BlockScout.
3. Destroying Provisioned Infrastructure. Refer to this section if you want to destroy your BlockScout installation.

Also you may want to refer to the lambda folder which contains a set of scripts that may be useful in your BlockScout infrastructure.

Prerequisites

Playbooks relies on Terraform under the hood, which is the stateful infrastructure-as-a-code software tool. It allows to keep a hand on your infrastructure - modify and recreate single and multiple resources depending on your needs.

This version of playbooks supports the multi-hosts deployment, which means that test BlockScout instances can be built on remote machines. In that case, you will need to have the Ansible, installed on jumpbox (controller) and all the prerequisites, that are described below, installed on runners.

Prerequisites for deploying infrastructure

Dependency name	Installation method
Terraform >=0.11.11	Installation guide
Python >=2.6.0	apt install python
Python-pip	apt install python-pip
boto & boto3 & botocore python modules	pip install boto boto3 botocore

Prerequisites for deploying BlockScout

Dependency name	Installation method
Terraform >=0.11.11	Installation guide
Python >=2.6.0	apt install python
Python-pip	apt install python-pip
boto & boto3 & botocore python modules	pip install boto boto3 botocore
AWS CLI	pip install awscli
All BlockScout prerequisites	Check it here

AWS permissions

During deployment you will have to provide credentials to your AWS account. Deployment process requires a wide set of permissions to do the job, so it would work best of all if you specify the administrator account credentials.

However, if you want to restrict the permissions as much possible, here is the list of resources which are created during the deployment process:

• An S3 bucket to keep Terraform state files;
• DynamoDB table to manage Terraform state files leases;
• An SSH keypair (or you can choose to use one which was already created), this is used with any EC2 hosts;
• A VPC containing all of the resources provisioned;
• A public subnet for the app servers, and a private subnet for the database (and Redis for now);
• An internet gateway to provide internet access for the VPC;
• An ALB which exposes the app server HTTPS endpoints to the world;
• A security group to lock down ingress to the app servers to 80/443 + SSH;
• A security group to allow the ALB to talk to the app servers;
• A security group to allow the app servers access to the database;
• An internal DNS zone;
• A DNS record for the database;
• An autoscaling group and launch configuration for each chain;
• A CodeDeploy application and deployment group targeting the corresponding autoscaling groups.

Each configured chain will receive its own ASG (autoscaling group) and deployment group, when application updates are pushed to CodeDeploy, all autoscaling groups will deploy the new version using a blue/green strategy. Currently, there is only one EC2 host to run, and the ASG is configured to allow scaling up, but no triggers are set up to actually perform the scaling yet. This is something that may come in the future.

The deployment process goes in two stages. First, Ansible creates S3 bucket and DynamoDB table that are required for Terraform state management. It is needed to ensure that Terraforms state is stored in a centralized location, so that multiple people can use Terraform on the same infra without stepping on each others toes. Terraform prevents this from happening by holding locks (via DynamoDB) against the state data (stored in S3).

Configuration

There are three groups of variables required to build BlockScout. Furst is required to create infrastructure, second is required to build BlockScout instances and the third is the one that is required both for infra and BS itself. For your convenience we have divided variable templates into three files accordingly - infrastructure.yml.example, blockscout.yml.example and all.yml.example . Also we have divided those files to place them in group_vars and in host_vars folder, so you will not have to repeat some of the variables for each host/group.

In order to deploy BlockScout, you will have to setup the following set of files for each instance:

/
| - group_vars
|   | - group.yml (combination of [blockscout+infrastructure+all].yml.example)
|   | - all.yml (optional, one for all instances)
| - host_vars
|   | - host.yml (combination of [blockscout+infrastructure+all].yml.example)
| - hosts (one for all instances)

Common variables

• ansible_host - is an address where BlockScout will be built. If this variable is set to localhost, also set ansible_connection to local for better performance.
• chain variable set the name of the network (Kovan, Core, xDAI, etc.). Will be used as part of the infrastructure resource names.
• env_vars represents a set of environment variables used by BlockScout. You can see the description of this variables at POA Forum.
  • Also One can define BULD_* set of the variables, where asterisk stands for any environment variables. All variables defined with BUILD_* will override default variables while building the dev server.
• aws_access_key and aws_secret_key is a credentials pair that provides access to AWS for the deployer; You can use the aws_profile instead. In that case, AWS CLI profile will be used. Also, if none of the access key and profile provided, the default AWS profile will be used. The aws_region should be left at us-east-1 as some of the other regions fail for different reasons;
• backend variable defines whether deployer should keep state files remote or locally. Set backend variable to true if you want to save state file to the remote S3 bucket;
• upload_config_to_s3 - set to true if you want to upload config all.yml file to the S3 bucket automatically after the deployment. Will not work if backend is set to false;
• upload_debug_info_to_s3 - set to true if you want to upload full log output to the S3 bucket automatically after the deployment. Will not work if backend is set to false. IMPORTANT: Locally logs are stored at log.txt which is not cleaned automatically. Please, do not forget to clean it manually or using the clean.yml playbook;
• bucket represents a globally unique name of the bucket where your configs and state will be stored. It will be created automatically during the deployment;

Note: a chain name shouldn't be more than 5 characters. Otherwise, it causing the error, because the aws load balancer name should not be greater than 32 characters.

Infrastructure related variables

• terraform_location is an address of the Terraform binary on the builder;

• dynamodb_table represents the name of table that will be used for Terraform state lock management;

• If ec2_ssh_key_content variable is not empty, Terraform will try to create EC2 SSH key with the ec2_ssh_key_name name. Otherwise, the existing key with ec2_ssh_key_name name will be used;

• instance_type defines a size of the Blockscout instance that will be launched during the deployment process;

• vpc_cidr, public_subnet_cidr, db_subnet_cidr represents the network configuration for the deployment. Usually you want to leave it as is. However, if you want to modify it, please, expect that db_subnet_cidr represents not a single network, but a group of networks started with defined CIDR block increased by 8 bits. Example: Number of networks: 2 db_subnet_cidr: "10.0.1.0/16" Real networks: 10.0.1.0/24 and 10.0.2.0/24

• An internal DNS zone withdns_zone_name name will be created to take care of BlockScout internal communications;

• The root_block_size is the amount of storage on your EC2 instance. This value can be adjusted by how frequently logs are rotated. Logs are located in /opt/app/logs of your EC2 instance;

• Each of the db_* variables configures the database for each chain. Each chain will have the separate RDS instance;

• instance_type represent the size of the EC2 instance to be deployed in production;

• use_placement_group determines whether or not to launch BlockScout in a placement group.

Blockscout related variables

• blockscout_repo - a direct link to the Blockscout repo;
• branch - maps branch at blockscout_repo to each chain;
• Specify the merge_commit variable if you want to merge any of the specified chains with the commit in the other branch. Usually may be used to update production branches with the releases from master branch;
• skip_fetch - if this variable is set to true , BlockScout repo will not be cloned and the process will start from building the dependencies. Use this variable to prevent playbooks from overriding manual changes in cloned repo;
• ps_* variables represents a connection details to the test Postgres database. This one will not be installed automatically, so make sure ps_* credentials are valid before starting the deployment;

Database Storage Required

The configuration variable db_storage can be used to define the amount of storage allocated to your RDS instance. The chart below shows an estimated amount of storage that is required to index individual chains. The db_storage can only be adjusted 1 time in a 24 hour period on AWS.

Chain	Storage (GiB)
POA Core	200
POA Sokol	400
Ethereum Classic	1000
Ethereum Mainnet	4000
Kovan Testnet	800
Ropsten Testnet	1500

Deploying the Infrastructure

1. Ensure all the infrastructure prerequisites are installed and has the right version number;
2. Create the AWS access key and secret access key for user with sufficient permissions;
3. Create hosts file from hosts.example (mv hosts.example hosts) and adjust to your needs. Each host should represent each BlockScout instance you want to deploy. Note, that each host name should belong exactly to one group. Also, as per Ansible requirements, hosts and groups names should be unique.

The simplest hosts file with one BlockScout instance will look like:

[group]
host

Where [group] is a group name, which will be interpreted as a prefix for all created resources and host is a name of BlockScout instance.

4. For each host merge infrastructure.yml.example and all.yml.example config template files in host_vars folder into single config file with the same name as in hosts file:

cat host_vars/infrastructure.yml.example host_vars/all.yml.example > host_vars/host.yml

5. For each group merge infrastructure.yml.example and all.yml.example config template files in group_vars folder into single config file with the same name as group name in hosts file:

cat group_vars/infrastructure.yml.example group_vars/all.yml.example > group_vars/group.yml

6. Adjust the variables at group_vars and host_vars. Note - you can move variables between host and group vars depending on if variable should be applied to the host or to the entire group. The list of the variables you can find at the corresponding part of instruction; Also, if you need to distribute variables accross all the hosts/groups, you can add these variables to the group_vars/all.yml file. Note about variable precedence => Official Ansible Docs.

7. Run ansible-playbook deploy_infra.yml;

• During the deployment the "diffs didn't match" error may occur, it will be ignored automatically. If Ansible play recap shows 0 failed plays, then the deployment was successful despite the error.
• Optionally, you may want to check the variables the were uploaded to the Parameter Store at AWS Console.

Deploying BlockScout

0. (optional) This step is for mac OS users. Please skip it, if this is not your case.

To avoid the error

TASK [main_software : Fetch environment variables] ************************************
objc[12816]: +[__NSPlaceholderDate initialize] may have been in progress in another thread when fork() was called.
objc[12816]: +[__NSPlaceholderDate initialize] may have been in progress in another thread when fork() was called. We cannot safely call it or ignore it in the fork() child process. Crashing instead. Set a breakpoint on objc_initializeAfterForkError to debug.

error and crashing of Python follow the next steps:

• Open terminal: nano .bash_profile;
• Add the following line to the end of the file: export OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES;
• Save, exit, close terminal and re-open the terminal. Check to see that the environment variable is now set: env

(source: https://stackoverflow.com/questions/50168647/multiprocessing-causes-python-to-crash-and-gives-an-error-may-have-been-in-progr);

1. Ensure all the BlockScout prerequisites are installed and has the right version number;
2. Create the AWS access key and secret access key for user with sufficient permissions;
3. Create hosts file from hosts.example (mv hosts.example hosts) and adjust to your needs. Each host should represent each BlockScout instance you want to deploy. Note, that each host name should belong exactly to one group. Also, as per Ansible requirements, hosts and groups names should be unique.

The simplest hosts file with one BlockScout instance will look like:

[group]
host

Where [group] is a group name, which will be interpreted as a prefix for all created resources and host is a name of BlockScout instance.

4. For each host merge blockscout.yml.example and all.yml.example config template files in host_vars folder into single config file with the same name as in hosts file:

cat host_vars/blockscout.yml.example host_vars/all.yml.example > host_vars/host.yml

If you have already merged infrastructure.yml.example and all.yml while deploying the BlockScout infrastructure, you can simply add the blockscout.yml.example to the merged file: cat host_vars/blockscout.yml.example >> host_vars/host.yml

5. For each group merge blockscout.yml.example and all.yml.example config template files in group_vars folder into single config file with the same name as group name in hosts file:

cat group_vars/blockscout.yml.example group_vars/all.yml.example > group_vars/group.yml

If you have already merged infrastructure.yml.example and all.yml while deploying the BlockScout infrastructure, you can simply add the blockscout.yml.example to the merged file: cat group_vars/blockscout.yml.example >> group_vars/host.yml

6. Adjust the variables at group_vars and host_vars. Note - you can move variables between host and group vars depending on if variable should be applied to the host or to the entire group. The list of the variables you can find at the corresponding part of instruction; Also, if you need to distribute variables accross all the hosts/groups, you can add these variables to the group_vars/all.yml file. Note about variable precedence => Official Ansible Docs.

7. Run ansible-playbook deploy_software.yml;

8. When the prompt appears, check that server is running and there is no visual artifacts. The server will be launched at port 4000 at the same machine where you run the Ansible playbooks. If you face any errors you can either fix it or cancel the deployment by pressing Ctrl+C and then pressing A when additionally prompted.

9. When server is ready to be deployed simply press enter and deployer will upload Blockscout to the appropriate S3.

10. Two other prompts will appear to ensure your will on updating the Parameter Store variables and deploying the BlockScout through the CodeDeploy. Both yes and true will be interpreted as the confirmation.

11. (optional) If the deployment fails, you can use the following tags to repeat the particular steps of the deployment:

• build
• update_vars
• deploy

12. Monitor and manage your deployment at CodeDeploy service page at AWS Console.

Destroying Provisioned Infrastructure

First of all you have to remove autoscaling groups (ASG) deployed via CodeDeploy manually since Terraform doesn't track them and will miss them during the automatic destroy process. Once ASG is deleted you can use ansible-playbook destroy.yml playbook to remove the rest of generated infrastructure. Make sure to check the playbook output since in some cases it might not be able to delete everything. Check the error description for details.

Note! While Terraform is stateful, Ansible is stateless, so if you modify bucket or dynamodb_table variables and run destroy.yml or deploy_infra.yml playbooks, it will not alter the current S3/Dynamo resources names, but create a new resources. Moreover, altering bucket variable will make Terraform to forget about existing infrastructure and, as a consequence, redeploy it. If it absolutely necessary for you to alter the S3 or DynamoDB names you can do it manually and then change the appropriate variable accordingly.

Also note, that changing backend variable will force Terraform to forget about created infrastructure also, since it will start searching the current state files locally instead of remote.

Useful information

Cleaning Deployment cache

Despite the fact that Terraform cache is automatically cleared automatically before each deployment, you may also want to force the cleaning process manually. To do this simply run the ansible-playbook clean.yml command, and Terraform cache will be cleared.

Migrating deployer to another machine

You can easily manipulate your deployment from any machine with sufficient prerequisites. If upload_debug_info_to_s3 variable is set to true, the deployer will automatically upload your all.yml file to the s3 bucket, so you can easily download it to any other machine. Simply download this file to your group_vars folder and your new deployer will pick up the current deployment instead of creating a new one.

Attaching the existing RDS instance to the current deployment

In some cases you may want not to create a new database, but to add the existing one to use within the deployment. In order to do that configure all the proper values at group_vars/all.yml including yours DB ID and name and execute the ansible-playbook attach_existing_rds.yml command. This will add the current DB instance into Terraform-managed resource group. After that run ansible-playbook deploy_infra.yml as usually.

Note 1: while executing ansible-playbook attach_existing_rds.yml the S3 and DynamoDB will be automatically created (if backend variable is set to true) to store Terraform state files.

Note 2: the actual name of your resource must include prefix that you will use in this deployment.

Example:

Real resource: tf-poa

prefix variable: tf

db_id variable: poa

Note 3: make sure MultiAZ is disabled on your database.

Note 4: make sure that all the variables at group_vars/all.yml are exactly the same as at your existing DB.

Common Errors and Questions

S3: 403 error during provisioning

Usually appears if S3 bucket already exists. Remember, S3 bucket has globally unique name, so if you don't have it, it doesn't mean, that it doesn't exists at all. Login to your AWS console and try to create S3 bucket with the same name you specified at bucket variable to ensure.

Error Applying Plan (diffs didn't match)

If you see something like the following:

Error: Error applying plan:

1 error(s) occurred:

* module.stack.aws_autoscaling_group.explorer: aws_autoscaling_group.explorer: diffs didn't match during apply. This is a bug with Terraform and should be reported as a GitHub Issue.

Please include the following information in your report:

    Terraform Version: 0.11.11
    Resource ID: aws_autoscaling_group.explorer
    Mismatch reason: attribute mismatch: availability_zones.1252502072

This is due to a bug in Terraform, however the fix is to just rerun ansible-playbook deploy_infra.yml again, and Terraform will pick up where it left off. This does not always happen, but this is the current workaround if you see it.

Server doesn't start during deployment

Even if server is configured correctly, sometimes it may not bind the appropriate 4000 port due to unknown reason. If so, simply go to the appropriate nested blockscout folder, kill and rerun server. For example, you can use the following command: pkill beam.smp && pkill node && sleep 10 && mix phx.server.