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An automation framework for spinning up cloud infrastructure to run BlockScout
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README.md

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.

Prerequisites for deploying infrastructure

Dependency name Installation method
Ansible >= 2.6 Installation guide
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
Ansible >= 2.7.3 Installation guide
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

The single point of configuration in this script is a group_vars/all.yml file. First, copy it from group_vars/all.yml.example template by executing cp group_vars/all.yml.example group_vars/all.yml command and then modify it via any text editor you want (vim example - vim group_vars/all.yml). The subsections describe the variable you may want to adjust.

Common variables

  • aws_access_key and aws_secret_key is a credentials pair that provides access to AWS for the deployer;
  • 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;
  • prefix - is a unique tag to use for provisioned resources (5 alphanumeric chars or less);
  • chains - maps chains to the URLs of HTTP RPC endpoints, an ordinary blockchain node can be used;
  • The region should be left at us-east-1 as some of the other regions fail for different reasons;

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

  • 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 name of a IAM key pair to use for EC2 instances, if you provide a name which already exists it will be used, otherwise it will be generated for you;
  • If use_ssl is set to false, SSL will be forced on Blockscout. To configure SSL, use alb_ssl_policy and alb_certificate_arn variables;
  • 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;
  • The pool_size defines the number of connections allowed by the RDS instance;
  • secret_key_base is a random password used for BlockScout internally. It is highly recommended to gernerate your own secret_key_base before the deployment. For instance, you can do it via openssl rand -base64 64 | tr -d '\n' command;
  • new_relic_app_name and new_relic_license_key should usually stay empty unless you want and know how to configure New Relic integration;
  • elixir_version - is an Elixir version used in BlockScout release;
  • chain_trace_endpoint - maps chains to the URLs of HTTP RPC endpoints, which represents a node where state pruning is disabled (archive node) and tracing is enabled. If you don't have a trace endpoint, you can simply copy values from chains variable;
  • chain_ws_endpoint - maps chains to the URLs of HTTP RPCs that supports websockets. This is required to get the real-time updates. Can be the same as chains if websocket is enabled there (but make sure to usews(s) instead of htpp(s) protocol);
  • chain_jsonrpc_variant - a client used to connect to the network. Can be parity, geth, etc;
  • chain_logo - maps chains to the it logos. Place your own logo at apps/block_scout_web/assets/static and specify a relative path at chain_logo variable;
  • chain_coin - a name of the coin used in each particular chain;
  • chain_network - usually, a name of the organization keeping group of networks, but can represent a name of any logical network grouping you want;
  • chain_subnetwork - a name of the network to be shown at BlockScout;
  • chain_network_path - a relative URL path which will be used as an endpoint for defined chain. For example, if we will have our BlockScout at blockscout.com domain and place core network at /poa/core, then the resulting endpoint will be blockscout.com/poa/core for this network.
  • chain_network_icon - maps the chain name to the network navigation icon at apps/block_scout_web/lib/block_scout_web/templates/icons without .eex extension
  • chain_graphiql_transaction - is a variable that maps chain to a random transaction hash on that chain. This hash will be used to provide a sample query in the GraphIQL Playground.
  • chain_block_transformer - will be clique for clique networks like Rinkeby and Goerli, and base for the rest;
  • chain_heart_beat_timeout, chain_heart_command - configs for the integrated heartbeat. First describes a timeout after the command described at the second variable will be executed;
  • Each of the chain_db_* variables configures the database for each chain. Each chain will have the separate RDS instance.
  • chain_blockscout_version - is a text at the footer of BlockScout instance. Usually represents the current BlockScout version.

Blockscout related variables

  • blockscout_repo - a direct link to the Blockscout repo;
  • chain_branch - maps branch at blockscout_repo to each chain;
  • Specify the chain_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;
  • chain_custom_environment - is a map of variables that should be overrided when deploying the new version of Blockscout. Can be omitted.

Note: chain_custom_environment variables will not be propagated to the Parameter Store at production servers and need to be set there manually.

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. Merge infrastructure and all config template files into single config file:

cat group_vars/infrastructure.yml.example group_vars/all.yml.example > group_vars/all.yml
  1. Set the variables at group_vars/all.yml config template file as described at the corresponding part of instruction;

  2. 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

  1. Ensure all the BlockScout prerequisites are installed and has the right version number;
  2. Merge blockscout and all config template files into single config file:
cat group_vars/blockscout.yml.example group_vars/all.yml.example > group_vars/all.yml

Note! All three configuration files are compatible to each other, so you can simply cat group_vars/blockscout.yml.example >> group_vars/all.yml if you already do have the all.yml file after the deploying of infrastructure.

  1. Set the variables at group_vars/all.yml config template file as described at the corresponding part of instruction; Note! Use chain_custom_environment to update the variables in each deployment. Map each deployed chain with variables as they should appear at the Parameter Store. Check the example at group_vars/blockscout.yml.example config file. chain_* variables will be ignored during BlockScout software deployment.

  2. 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. Run ansible-playbook deploy_software.yml;
  2. 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.
  3. When server is ready to be deployed simply press enter and deployer will upload Blockscout to the appropriate S3.
  4. 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.
  5. 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

chain_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.

You can’t perform that action at this time.