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Design (LLD) Alarm OR Alert Service for AWS - Machine Coding

Design (LLD) Alarm OR Alert Service for AWS - Machine Coding

Jan 17, 2025·

3 min read

Features Required

  1. Create and Manage Alarms

    • Users can create alarms with conditions (e.g., CPU > 80%, Memory < 20%).

    • Alarms can be configured to monitor metrics across AWS services.

    • Support recurring or one-time alarms.

  2. Multi-Metric Monitoring

    • Monitor multiple metrics for an alarm (e.g., both CPU and Memory).

    • Composite alarms to evaluate combined conditions.

  3. Notification Mechanism

    • Notify via email, SMS, or push notifications when an alarm triggers.

    • Integrate with AWS SNS (Simple Notification Service).

  4. State Management

    • Maintain states like OK, ALARM, and INSUFFICIENT_DATA for alarms.
  5. Custom Actions

    • Allow users to specify actions when alarms trigger (e.g., terminate an instance, scale a service).
  6. Persistence

    • Store alarm configurations in a database (e.g., DynamoDB).
  7. Scalability

    • Support a high number of alarms with minimal latency.

Design Patterns

  1. Observer Pattern

    • Used for the notification mechanism where alarms notify multiple subscribers when triggered.
  2. Builder Pattern

    • Used for creating complex alarm configurations, ensuring immutability and a readable syntax.
  3. State Pattern

    • Used for managing alarm states like OK, ALARM, and INSUFFICIENT_DATA.
  4. Strategy Pattern

    • Used for evaluating alarm conditions with different algorithms.
  5. Repository Pattern

    • Used for persisting and retrieving alarm configurations from the database.
  6. Singleton Pattern

    • Used for managing shared components like NotificationManager and StateManager.

Algorithms Involved (we will not cover this)

  1. Threshold Evaluation Algorithm

    • Compare metrics against thresholds to determine alarm state.
  2. Composite Condition Evaluation

    • Use logical operators (AND, OR) to evaluate conditions across multiple metrics.

Code (Java)

Code is given in Below IDE

The above implementation is single-threaded and does not inherently utilize the full potential of an EC2 server with multiple cores. For this service to take full advantage of a multi-core EC2 instance, multithreading or asynchronous processing must be introduced. Let’s break this down:

Current Behavior (Single-Threaded)

  • The service handles one task (e.g., notifying subscribers, evaluating alarm conditions) at a time.

  • All operations run on the main thread, resulting in under-utilization of CPU cores, especially on high-core EC2 instances.

  • Notifications and alarm evaluations are processed sequentially, potentially causing delays when handling a high number of alarms.

Improving with Multithreading

Why Multithreading?

  • EC2 instances with multiple cores can handle concurrent tasks more efficiently.

  • Notifications can be processed in parallel for multiple subscribers.

  • Alarm evaluations can be distributed across threads to improve response time.

How to Introduce Multithreading?

  1. ExecutorService
    Use Java's ExecutorService to manage a thread pool for parallel execution of tasks.

  2. Parallel Notification
    Notifications can be dispatched to subscribers concurrently.

  3. Concurrent Alarm Evaluation
    Use separate threads to evaluate alarms for different metrics or conditions.

Updated Implementation with Multithreading

We will be covering more details in our course.