Scaling Strategies

Coming Soon

This lesson will teach you advanced scaling strategies to handle millions of concurrent users on your chat server. You’ll learn how to:

• Design horizontal scaling architectures
• Implement data sharding and partitioning
• Build multi-layer caching strategies
• Integrate CDN for global content delivery
• Optimize for massive concurrent connections

What You’ll Build

By the end of this lesson, you’ll have implemented:

• Horizontal scaling with automatic node provisioning
• Data sharding across multiple database instances
• Multi-layer caching (L1, L2, distributed cache)
• CDN integration for static content delivery
• Load balancing with session affinity

Key Concepts Preview

% Sharding strategy
get_shard_node(UserId) ->
    ShardId = erlang:phash2(UserId) rem get_shard_count(),
    maps:get(ShardId, get_shard_map()).

% Distributed caching
cache_get(Key) ->
    case ets:lookup(l1_cache, Key) of
        [{Key, Value}] -> {ok, Value};
        [] ->
            case distributed_cache:get(Key) of
                {ok, Value} ->
                    ets:insert(l1_cache, {Key, Value}),
                    {ok, Value};
                not_found -> not_found
            end
    end.

% Auto-scaling triggers
monitor_load() ->
    case get_current_load() of
        Load when Load > 0.8 -> trigger_scale_up();
        Load when Load < 0.3 -> trigger_scale_down();
        _ -> ok
    end.

This lesson builds on the advanced security from Lesson 30 and prepares you for the operations and DevOps practices we’ll explore in Lesson 32.

This lesson is currently under development. Check back soon for the complete content!