mitigations.md

Mitigation Strategies Analysis for ruby-concurrency/concurrent-ruby

Mitigation Strategy: Atomic Operations (using concurrent-ruby)

• Description:

  1. Identify Simple Shared Variables: Find shared variables that are subject to simple, atomic updates (e.g., incrementing a counter, setting a flag).
  2. Use concurrent-ruby Atomic Types: Replace direct access to these variables with concurrent-ruby's atomic primitives:
     • Concurrent::AtomicFixnum: For integer counters.
     • Concurrent::AtomicBoolean: For boolean flags.
     • Concurrent::AtomicReference: For holding references to other objects (use with caution, ensures atomic reference updates, not object mutability). This is crucial for atomically swapping out entire objects.
  3. Understand Atomic Operations: Be aware of the specific atomic operations provided by each type (e.g., increment, decrement, compare_and_set, update). Use the correct operation for your needs. The compare_and_set (CAS) operation is particularly important for implementing more complex lock-free algorithms.
  4. Avoid Non-Atomic Operations: Do not combine atomic operations with non-atomic operations on the same variable. For example, if atomic_counter.value > 0 then atomic_counter.decrement end is not atomic and still needs external synchronization.

• Threats Mitigated:

  • Data Races (Severity: High): Guarantees that simple updates to shared variables are performed atomically, preventing data corruption.
  • Lost Updates (Severity: Medium): Ensures that updates from multiple threads are not lost due to concurrent access.

• Impact:

  • Data Races: Risk significantly reduced for simple variable updates.
  • Lost Updates: Risk significantly reduced.

• Currently Implemented:

  • Concurrent::AtomicFixnum is used to track the number of active requests in the RequestCounter module.

• Missing Implementation:

  • A boolean flag indicating whether the system is in maintenance mode is currently a regular instance variable and is not updated atomically.

Mitigation Strategy: Thread-Safe Data Structures (using concurrent-ruby)

• Description:

  1. Identify Shared Collections: Find shared data structures like arrays, hashes, or maps that are accessed and modified by multiple threads.
  2. Use concurrent-ruby Collections: Replace standard Ruby collections with concurrent-ruby's thread-safe equivalents:
     • Concurrent::Array
     • Concurrent::Hash
     • Concurrent::Map (often the best choice for general-purpose concurrent hash tables)
  3. Read Documentation Carefully: Understand the thread-safety guarantees of each collection and its methods. Some operations might not be fully atomic, particularly those involving multiple steps.
  4. Avoid Check-Then-Act: Be particularly cautious of "check-then-act" sequences (e.g., checking if a key exists in a Concurrent::Map and then inserting a value). These are not atomic and require additional synchronization (often using compute_if_absent or similar methods). Concurrent::Map provides methods like put_if_absent, compute_if_absent, compute_if_present, and merge that can help with these scenarios.

• Threats Mitigated:

  • Data Races (Severity: High): Provides thread-safe access to collections, preventing data corruption.
  • ConcurrentModificationException (Severity: Medium): Eliminates the risk of exceptions caused by modifying a collection while it's being iterated over by another thread.

• Impact:

  • Data Races: Risk significantly reduced for collection operations.
  • ConcurrentModificationException: Risk eliminated.

• Currently Implemented:

  • Concurrent::Map is used to store cached database query results in the QueryCache module.

• Missing Implementation:

  • A list of active user sessions is currently stored in a regular Ruby Array and is accessed by multiple threads without proper synchronization.

Mitigation Strategy: Thread Pool Management (using concurrent-ruby)

• Description:

  1. Avoid Raw Threads: Do not create threads directly using Thread.new unless absolutely necessary. Raw threads offer no management or resource control.
  2. Use concurrent-ruby Thread Pools: Utilize concurrent-ruby's thread pool implementations:
     • Concurrent::ThreadPoolExecutor: The most general-purpose and configurable thread pool.
     • Concurrent::FixedThreadPool: A pool with a fixed number of threads.
     • Concurrent::CachedThreadPool: A pool that creates threads as needed and reuses them, suitable for short-lived tasks.
     • Concurrent::SingleThreadExecutor: Executes tasks sequentially in a single background thread.
     • Concurrent::ImmediateExecutor: Executes tasks immediately in the calling thread (useful for testing or when concurrency is not desired).
  3. Configure Pool Size: Carefully configure the thread pool size based on:
     • The number of available CPU cores.
     • The nature of the tasks (CPU-bound vs. I/O-bound). I/O-bound tasks can often use a larger pool size.
     • Available system memory.
  4. Monitor Resource Usage: Monitor the application's resource usage (CPU, memory, threads) to ensure that the thread pool is not over- or under-provisioned. Use tools like concurrent-ruby's built-in instrumentation or external monitoring systems.
  5. Consider Adaptive Pools: Explore concurrent-ruby's Concurrent::ThreadPoolExecutor with auto-trimming features, which can dynamically adjust the number of threads based on load.
  6. Shutdown Pools Gracefully: When shutting down the application, ensure that thread pools are shut down gracefully using #shutdown and #wait_for_termination. This allows running tasks to complete before the application exits.
  7. Use post method: Use post method to add tasks to the thread pool.

• Threats Mitigated:

  • Resource Exhaustion (Severity: Medium): Prevents the creation of too many threads, which can lead to resource exhaustion (memory, CPU, file descriptors).
  • Thread Starvation (Severity: Low): Helps ensure that tasks are executed in a timely manner by managing the allocation of threads.

• Impact:

  • Resource Exhaustion: Risk significantly reduced.
  • Thread Starvation: Risk moderately reduced.

• Currently Implemented:

  • A Concurrent::FixedThreadPool is used for handling background tasks related to email sending.

• Missing Implementation:

  • Several parts of the application still create threads directly using Thread.new, without any resource management.
  • The Concurrent::FixedThreadPool for email sending is not properly shut down when the application exits.

Mitigation Strategy: Exception Handling with Future and Promise (using concurrent-ruby)

• Description:

  1. Use Future or Promise: Wrap asynchronous operations in Concurrent::Future or Concurrent::Promise objects. These provide a way to manage the result of an asynchronous computation.
  2. Use rescue: Use the #rescue method (or its alias #rescue_with) on the Future or Promise to handle exceptions that occur during the asynchronous execution. This is essential for preventing unhandled exceptions from silently terminating threads.
     • future.rescue { |reason| ... }
  3. Chain Operations: Use methods like #then, #chain, and #flat_map to chain together asynchronous operations and handle their results (and potential errors) in a controlled manner.
  4. Handle Results: Use #value to get result of the Future or Promise. Use #wait method before getting the value.

• Threats Mitigated:

  • Silent Thread Termination (Severity: High): Prevents asynchronous tasks from failing silently due to unhandled exceptions.
  • Inconsistent Application State (Severity: Medium): Allows for graceful handling of errors in asynchronous operations, preventing the application from entering an inconsistent state.

• Impact:

  • Silent Thread Termination: Risk significantly reduced.
  • Inconsistent Application State: Risk moderately reduced.

• Currently Implemented:

  • Future objects are used in some parts of the code for fetching data from external APIs, but their rescue methods are not consistently used.

• Missing Implementation:

  • Comprehensive exception handling using #rescue is missing in several Future implementations.

Mitigation Strategy: Using ThreadPoolExecutor#error_callback (using concurrent-ruby)

• Description:

1. Use ThreadPoolExecutor: Ensure you are using Concurrent::ThreadPoolExecutor for managing your thread pool.
2. Set error_callback: When creating the ThreadPoolExecutor, set the error_callback option to a lambda or a method that will be invoked whenever a task submitted to the pool raises an unhandled exception.

   executor = Concurrent::ThreadPoolExecutor.new(
     # ... other options ...
     error_callback: ->(job, reason) {
       Rails.logger.error("Error in thread pool task: #{reason}, job: #{job.inspect}")
       # Potentially notify an error tracking service
     }
   )

3. Handle the Exception: Within the error_callback, you have access to the task (job) and the exception (reason). Log the error, potentially notify an error tracking service, and decide whether to take any corrective action.

• Threats Mitigated:

  • Silent Task Failures (Severity: High): Prevents tasks submitted to a ThreadPoolExecutor from failing silently due to unhandled exceptions.
  • Loss of Diagnostic Information (Severity: Medium): Provides a centralized place to log and handle exceptions from background tasks, improving debugging and monitoring.

• Impact:

  • Silent Task Failures: Risk significantly reduced.
  • Loss of Diagnostic Information: Risk significantly reduced.

• Currently Implemented:

  • Not currently implemented. The existing FixedThreadPool does not have an error_callback.

• Missing Implementation:

  • The ThreadPoolExecutor used for background tasks does not have an error_callback configured. This is a critical missing piece for robust error handling.

Mitigation Strategy: Actor Model (using concurrent-ruby)

• Description:

  1. Identify Concurrency Problems: Determine if the Actor model is a good fit for your problem. It excels in situations with complex interactions between concurrent entities.
  2. Define Actors: Define your actors using Concurrent::Actor::Context. Each actor encapsulates its own state and behavior.
  3. Message Passing: Actors communicate exclusively through message passing. Define the messages that each actor can receive and how it should respond to them. Use ! (tell) to send messages asynchronously.
  4. Avoid Shared State: Actors should not share mutable state. All communication should happen through messages.
  5. Supervision: Consider using Concurrent::Actor::Supervisor to manage the lifecycle of your actors and handle failures.
  6. Use ask method: Use ask method to send message and receive result.

• Threats Mitigated:

  • Data Races (Severity: High): Eliminates shared mutable state by design, preventing data races.
  • Deadlocks (Severity: High): Reduces the risk of deadlocks by avoiding explicit locking.
  • Complexity (Severity: Medium): Can simplify reasoning about concurrency by providing a higher-level abstraction.

• Impact:

  • Data Races: Risk significantly reduced (near elimination).
  • Deadlocks: Risk significantly reduced.
  • Complexity: Can increase initial complexity but reduce long-term complexity for suitable problems.

• Currently Implemented:

  • Not currently used.

• Missing Implementation:

  • The Actor model could be a good fit for managing user sessions and handling concurrent requests for the same user, replacing the current mutable Session object. This would require a significant refactoring.