defmodule JidoSystem.EventBus do
  @moduledoc """
  Unified event system that bridges all event sources.
  """
  
  # Single publishing interface
  def publish(event_type, data, metadata \\ %{}) do
    event = build_event(event_type, data, metadata)
    
    # Publish to all subscribers
    :ok = dispatch_to_subscribers(event)
    
    # Store in event store
    :ok = EventStore.append(event)
    
    # Emit telemetry
    :ok = emit_telemetry(event)
    
    # Forward to external systems if configured
    :ok = forward_external(event)
  end
  
  # Unified subscription
  def subscribe(pattern, handler, opts \\ []) do
    Registry.register(EventBus.Registry, pattern, {handler, opts})
  end
  
  # Event sourcing support
  def replay(stream, from: position, to: handler) do
    EventStore.read_stream(stream, from: position)
    |> Stream.each(&handler.(&1))
    |> Stream.run()
  end
end

defmodule JidoSystem.Config do
  @moduledoc """
  Centralized configuration with validation and hot reload.
  """
  
  use JidoSystem.Config.Schema
  
  config_schema do
    section :platform do
      field :cluster_name, :string, required: true
      field :environment, :atom, default: :production
      field :deployment_type, :atom, default: :kubernetes
    end
    
    section :agents do
      field :default_timeout, :timeout, default: 30_000
      field :max_queue_size, :pos_integer, default: 10_000
      field :supervision_strategy, :atom, default: :one_for_one
    end
    
    section :infrastructure do
      field :cache_backend, :atom, default: :redis
      field :event_store_backend, :atom, default: :postgresql
      field :circuit_breaker_threshold, :pos_integer, default: 5
    end
  end
  
  # Runtime configuration updates
  def update(path, value) do
    with :ok <- validate_update(path, value),
         :ok <- apply_update(path, value) do
      broadcast_update(path, value)
    end
  end
end

defmodule JidoSystem.Security do
  @moduledoc """
  Capability-based security and access control.
  """
  
  defmodule Capability do
    defstruct [:name, :constraints, :granted_by, :expires_at]
  end
  
  def grant_capability(agent, capability, constraints \\ %{}) do
    cap = %Capability{
      name: capability,
      constraints: constraints,
      granted_by: self(),
      expires_at: expiry_time(constraints)
    }
    
    Registry.update_value(agent, fn state ->
      update_in(state.capabilities, &[cap | &1])
    end)
  end
  
  def check_capability(agent, capability, context \\ %{}) do
    with {:ok, caps} <- get_capabilities(agent),
         {:ok, cap} <- find_valid_capability(caps, capability),
         :ok <- verify_constraints(cap, context) do
      {:ok, cap}
    else
      _ -> {:error, :unauthorized}
    end
  end
end

defmodule JidoSystem.AgentSupervisor do
  @moduledoc """
  Intelligent agent supervision with resource awareness.
  """
  
  use DynamicSupervisor
  
  def start_agent(agent_spec, opts \\ []) do
    # Check resource availability
    with {:ok, resources} <- ResourceManager.reserve(agent_spec.resources),
         {:ok, placement} <- PlacementStrategy.decide(agent_spec, opts) do
      
      # Start with resource limits
      spec = %{
        agent_spec | 
        resources: resources,
        node: placement.node,
        metadata: build_metadata(agent_spec, placement)
      }
      
      DynamicSupervisor.start_child(__MODULE__, spec)
    end
  end
  
  # Automatic scaling based on load
  def handle_info({:scale_request, agent_type, count}, state) do
    scale_agents(agent_type, count)
    {:noreply, state}
  end
end

defmodule JidoSystem.AgentState do
  @moduledoc """
  Distributed agent state management with persistence.
  """
  
  defmacro __using__(opts) do
    quote do
      use Jido.Agent
      
      # Automatic state persistence
      def handle_state_change(old_state, new_state) do
        StateStore.persist(self(), new_state)
        super(old_state, new_state)
      end
      
      # State recovery on restart
      def init(args) do
        case StateStore.recover(self()) do
          {:ok, state} -> {:ok, state}
          :not_found -> super(args)
        end
      end
      
      # Distributed state sync
      def handle_info({:state_sync, from_node}, state) do
        sync_state_with_node(from_node, state)
        {:noreply, state}
      end
    end
  end
end

defmodule JidoSystem.Discovery do
  @moduledoc """
  Multi-strategy service discovery.
  """
  
  def discover(criteria, opts \\ []) do
    strategy = Keyword.get(opts, :strategy, :adaptive)
    
    case strategy do
      :local -> discover_local(criteria)
      :cluster -> discover_cluster(criteria)
      :global -> discover_global(criteria)
      :adaptive -> discover_adaptive(criteria, opts)
    end
  end
  
  # Adaptive discovery based on criteria
  defp discover_adaptive(criteria, opts) do
    cond do
      local_sufficient?(criteria) -> discover_local(criteria)
      cluster_sufficient?(criteria) -> discover_cluster(criteria)
      true -> discover_global(criteria)
    end
  end
  
  # Rich capability matching
  def match_capabilities(required, provided) do
    score = calculate_capability_score(required, provided)
    constraints_met? = verify_constraints(required, provided)
    
    if constraints_met? and score > 0 do
      {:ok, score}
    else
      {:error, :no_match}
    end
  end
end

defmodule JidoSystem.Choreography do
  @moduledoc """
  Distributed choreography for agent coordination.
  """
  
  defmodule Choreography do
    defstruct [:id, :participants, :steps, :state, :context]
  end
  
  def start_choreography(definition, participants) do
    choreography = %Choreography{
      id: generate_id(),
      participants: participants,
      steps: parse_definition(definition),
      state: :initiated,
      context: %{}
    }
    
    # Notify all participants
    broadcast_to_participants(choreography, :choreography_started)
    
    # Start execution
    execute_next_step(choreography)
  end
  
  # Distributed state machine
  def handle_participant_event(choreography_id, participant, event) do
    with {:ok, choreography} <- get_choreography(choreography_id),
         :ok <- validate_event(choreography, participant, event) do
      
      updated = update_choreography_state(choreography, participant, event)
      
      if next_step?(updated) do
        execute_next_step(updated)
      else
        complete_choreography(updated)
      end
    end
  end
end

defmodule JidoSystem.Cache do
  @moduledoc """
  Multi-tier distributed cache with consistency guarantees.
  """
  
  def get(key, opts \\ []) do
    consistency = Keyword.get(opts, :consistency, :eventual)
    
    case consistency do
      :eventual -> get_from_nearest(key)
      :strong -> get_from_primary(key)
      :bounded -> get_with_staleness(key, opts[:max_staleness])
    end
  end
  
  def put(key, value, opts \\ []) do
    ttl = Keyword.get(opts, :ttl)
    replicas = Keyword.get(opts, :replicas, 3)
    
    # Write to primary
    :ok = write_primary(key, value, ttl)
    
    # Async replication
    Task.async(fn ->
      replicate_to_nodes(key, value, ttl, replicas)
    end)
    
    :ok
  end
  
  # Multi-tier architecture
  defp get_from_nearest(key) do
    # L1: Process cache
    with :miss <- ProcessCache.get(key),
         # L2: Node cache  
         :miss <- NodeCache.get(key),
         # L3: Distributed cache
         {:ok, value} <- DistributedCache.get(key) do
      
      # Populate upper tiers
      warm_caches(key, value)
      {:ok, value}
    end
  end
end

defmodule JidoSystem.ResourcePool do
  @moduledoc """
  Intelligent resource pooling with fairness.
  """
  
  def acquire(pool_name, opts \\ []) do
    priority = Keyword.get(opts, :priority, :normal)
    timeout = Keyword.get(opts, :timeout, 5_000)
    
    request = %ResourceRequest{
      pool: pool_name,
      priority: priority,
      requester: self(),
      constraints: opts[:constraints] || %{}
    }
    
    case ResourceScheduler.schedule(request, timeout) do
      {:ok, resource} ->
        monitor_ref = Process.monitor(self())
        track_allocation(resource, monitor_ref)
        {:ok, resource}
        
      {:error, :timeout} ->
        handle_timeout(request, opts)
    end
  end
  
  # Fair scheduling with priorities
  defmodule ResourceScheduler do
    def schedule(request, timeout) do
      queue = get_queue(request.pool)
      
      # Priority queue with fairness
      position = calculate_position(request, queue)
      
      wait_for_resource(request, position, timeout)
    end
  end
end

defmodule MyApp.DataProcessor do
  use JidoSystem.Platform.Agent
  
  agent do
    name "data_processor"
    description "Processes incoming data streams"
    
    capabilities do
      processing [:stream, :batch]
      formats [:json, :csv, :parquet]
      throughput {1000, :per_second}
    end
    
    resources do
      memory "512MB"
      cpu {2, :cores}
      storage "10GB"
    end
    
    lifecycle do
      startup_timeout 30_000
      shutdown_grace_period 60_000
      
      on_start :initialize_connections
      on_terminate :cleanup_resources
    end
    
    resilience do
      circuit_breaker threshold: 5, timeout: 30_000
      retry_policy :exponential, max_attempts: 3
      bulkhead max_concurrent: 100
    end
    
    observability do
      metrics [:throughput, :latency, :error_rate]
      tracing sample_rate: 0.1
      logging level: :info
    end
  end
  
  action process_stream(data) do
    with {:ok, parsed} <- parse_data(data),
         {:ok, validated} <- validate_data(parsed),
         {:ok, result} <- transform_data(validated) do
      {:ok, result}
    end
  end
end

defmodule MyApp.OrderWorkflow do
  use JidoSystem.Platform.Workflow
  
  workflow do
    name "order_processing"
    description "End-to-end order processing"
    
    participants do
      validator: {ValidationAgent, constraints: %{region: :us}}
      processor: {ProcessingAgent, min_count: 2}
      notifier: {NotificationAgent, optional: true}
    end
    
    flow do
      parallel do
        step :validate_order, agent: :validator
        step :check_inventory, agent: :processor
      end
      
      step :process_payment, agent: :processor,
        timeout: 30_000,
        compensation: :refund_payment
      
      conditional on: :payment_success do
        true ->
          step :fulfill_order, agent: :processor
          step :send_confirmation, agent: :notifier
          
        false ->
          step :cancel_order, agent: :processor
          step :notify_failure, agent: :notifier
      end
    end
    
    error_handling do
      on_error :validation_failed, retry: 3
      on_error :payment_failed, compensate: true
      on_timeout :alert_operator
    end
  end
end

defmodule JidoSystem.Cluster do
  @moduledoc """
  Automatic cluster formation and management.
  """
  
  def form_cluster(strategy, opts \\ []) do
    case strategy do
      :kubernetes -> form_k8s_cluster(opts)
      :dns -> form_dns_cluster(opts)
      :consul -> form_consul_cluster(opts)
      :static -> form_static_cluster(opts)
    end
  end
  
  # Kubernetes native clustering
  defp form_k8s_cluster(opts) do
    namespace = Keyword.get(opts, :namespace, "default")
    selector = Keyword.get(opts, :selector, "app=jido-system")
    
    # Use Kubernetes API to discover peers
    {:ok, endpoints} = K8s.Client.list_endpoints(namespace, selector)
    
    # Form cluster
    connect_nodes(endpoints)
  end
  
  # Health-aware clustering
  def handle_node_event(:nodedown, node) do
    # Redistribute work from failed node
    redistribute_agents(node)
    
    # Update routing tables
    update_routing(node, :down)
    
    # Alert operators
    emit_alert(:node_down, %{node: node})
  end
end

defmodule JidoSystem.Migration do
  @moduledoc """
  Zero-downtime agent migration.
  """
  
  def migrate_agent(agent_pid, target_node, opts \\ []) do
    strategy = Keyword.get(opts, :strategy, :checkpoint_restore)
    
    case strategy do
      :checkpoint_restore ->
        checkpoint_restore_migration(agent_pid, target_node)
        
      :state_transfer ->
        state_transfer_migration(agent_pid, target_node)
        
      :dual_write ->
        dual_write_migration(agent_pid, target_node)
    end
  end
  
  defp checkpoint_restore_migration(agent_pid, target_node) do
    # Pause agent
    :ok = Agent.pause(agent_pid)
    
    # Checkpoint state
    {:ok, checkpoint} = Agent.checkpoint(agent_pid)
    
    # Start on target
    {:ok, new_pid} = rpc(target_node, Agent, :restore, [checkpoint])
    
    # Update routing
    :ok = Router.update_routes(agent_pid, new_pid)
    
    # Resume on new node
    :ok = Agent.resume(new_pid)
    
    # Stop old instance
    :ok = Agent.stop(agent_pid)
    
    {:ok, new_pid}
  end
end

defmodule JidoSystem.Observability do
  @moduledoc """
  Comprehensive observability with OpenTelemetry.
  """
  
  def setup do
    # Metrics
    setup_metrics_collection()
    
    # Tracing  
    setup_distributed_tracing()
    
    # Logging
    setup_structured_logging()
    
    # Custom dashboards
    setup_dashboards()
  end
  
  defp setup_metrics_collection do
    # System metrics
    :telemetry.attach_many(
      "jido-system-metrics",
      [
        [:jido, :agent, :*],
        [:jido, :action, :*],
        [:jido, :workflow, :*]
      ],
      &handle_metric/4,
      nil
    )
    
    # Export to Prometheus
    Prometheus.setup()
  end
  
  defp setup_distributed_tracing do
    # OpenTelemetry configuration
    OpenTelemetry.register_tracer(:jido_system, "1.0.0")
    
    # Auto-instrumentation
    OpenTelemetry.attach_auto_instrumentation()
  end
end

defmodule JidoSystem.Chaos do
  def inject_fault(type, target, duration) do
    case type do
      :network_delay -> inject_network_delay(target, duration)
      :node_failure -> inject_node_failure(target, duration)
      :resource_exhaustion -> inject_resource_exhaustion(target, duration)
    end
  end
end

defmodule JidoSystem.Canary do
  def deploy_canary(agent_module, percentage) do
    # Route percentage of traffic to new version
    Router.add_canary_route(agent_module, percentage)
    
    # Monitor metrics
    monitor_canary_metrics(agent_module)
  end
end

defmodule JidoSystem.Features do
  def enabled?(feature, context \\ %{}) do
    FeatureStore.check(feature, context)
  end
  
  def with_feature(feature, context, do: enabled_fn, else: disabled_fn) do
    if enabled?(feature, context) do
      enabled_fn.()
    else
      disabled_fn.()
    end
  end
end