Fernando Valverde
3 min read


  • Crystal
  • crystal-lang
  • crystal lang
  • oss
  • github
  • open source
  • database
  • jennifer.cr
  • worker
  • kemal

This is another post about the Battlesnake project I’ve been working on while diving in Crystal lang.

This time I’m looking into persisting the game data to a database for analysis. This will allow me to review games from each game played by the bot and hopefully improve my spot on the leaderboards by tweaking my strategy.

FYI the code is on GitHub.


imdrasil/jennifer.cr is my ORM of choice, but I’m no longer following the recommended config directory in the root of the project. I’m just stuffing initializers to be required from the main app files (i.e. src/app.cr).

This is what the database initializer can look like:

# src/initializers/database.cr

require "kemal"
require "jennifer"
require "jennifer/adapter/postgres"

Jennifer::Config.configure do |conf|
  conf.from_uri(ENV["DATABASE_URL"]) if ENV.has_key?("DATABASE_URL")
  conf.logger.level = Log::Severity::Debug
  conf.adapter = "postgres"
  conf.pool_size = (ENV["DB_POOL"] ||= "5").to_i

Jennifer docs are great. I found a couple of difficulties along the way, mostly related to configuration details, but made it work with help from kind folks on GitHub.

Migration & Model

It’s not quite like ActiveRecord (maybe nothing is/will be 😅), but IMO it’s great and has lots of incredibly valuable features (i.e. built in migration management, query dsl, etc). Here’s what the migration and model look like:

class CreateTurns < Jennifer::Migration::Base
  def up
    create_table :turns do |t|
      t.string :game_id, {:null => false}
      t.string :snake_id, {:null => false}
      t.text :context, {:null => false}
      t.string :path, {:null => false}
      t.bool :dead, {:null => false, :default => false}

      t.index :game_id
      t.index :path


  def down
    drop_table :turns if table_exists? :turns
# This is a DB record representation of a request from a game for either
# start/move/end request.
# NOTE: https://imdrasil.github.io/jennifer.cr/docs/model_mapping
class Turn < Jennifer::Model::Base

    id: Primary64,
    game_id: String,
    snake_id: String,
    context: String,
    path: String,
    dead: Bool,
    created_at: Time?,
    updated_at: Time?,

With all of this in place I added this macro to src/app.cr and called it from within /start, /move, /end endpoints so the turn data gets persisted in Postgres.

macro persist_turn!
  dead = context.board.snakes.find { |s| s.id == context.you.id }.nil?
    game_id: context.game.id,
    snake_id: context.you.id,
    context: env.params.json.to_json,
    path: env.request.path,
    dead: dead

I left this run through Monday’s leaderboard matches and it worked. You can check out the most recent games persisted by my snake in https://snake.fdo.cr/games

Performance impact

Now that we’re storing (inserting) data to PostgreSQL, which is currently hosted in a low cost server, response times should’ve slowed down a noticeable amount.

OpenTelemetry data on Honeycomb is able to tell me exactly how it performed (read my post about this here).


Server times before DB persist implemented


Server times with DB persist implemented

There’s indeed a penalty in persisting data, likely coming from network latency and the low cost DB server performance being much lower than ideal… I’m saving $$ with that pet (as in “not caddle”) server (droplet on DO) hosting Redis+Postgres maintained by me. This hack saves me ~$25/month and could merit a post in and of itself 😆

Anyways, Battlesnake rules usually work with a 500ms timeout, which means we have time to spare for now.

How to recover/regain performance

I’m not going to start spending money on high performing tiers of hosted Postgres services anytime soon, so I could think of ways to avoid such a costly penatly. One option is to store the Turn data asynchronously.

Redis is better performing than Postgres, so queuing the data to be persisted to DB by a background job instead of synchronously when the request is made might help improve response times again.

I actually already have this implemented with the mosquito shard, but that will be covered in the next post of this series. I’m waiting for at least a day’s worth of leaderboard match data to reliably compare with the results above, so stay tuned if interested I guess.

Pura vida.