[DATE] - [ARCHITECTURE_DECISION_NAME]
===

## Motivation

<!--
  Motivation Example
  ===

  Our database is heavy on read operations than write operations. After users is growing, we need to optimize read performance to ensure low latency and high availability.

  ### Stackholder

    - **Users**: Expect fast response times when accessing data.
    - **Developers**: Need to maintain and scale the database efficiently.

  ### Problem Statement

    The current database setup is struggling to handle the increasing read load, leading to slow response times and potential downtime during peak usage periods.
-->

[DESCRIPTION_OF_THE_DECISION_PROBLEM]

### Stakeholders

- [STAKEHOLDER_1]: [ROLE_AND_INTEREST]
- [STAKEHOLDER_2]: [ROLE_AND_INTEREST]

### Problem Statement

[DETAILED_DESCRIPTION_OF_THE_PROBLEM]

## Proposed Solution

<!--
    Proposed Solution Example
    ===

    We have considered the following solutions to address the read performance issue:

    ### Redis Caching

    Implementing Redis as an in-memory caching layer to store frequently accessed data. This will reduce the load on the primary database and speed up read operations.

    ### Read Replicas

    Setting up read replicas of the primary database to distribute read traffic. This will help in balancing the load and improving read performance.
-->

### [SOLUTION_NAME]

[DESCRIPTION_OF_SOLUTION]

### [SOLUTION_NAME]

[DESCRIPTION_OF_SOLUTION]

## Decision

<!--
    Decision Example
    ===

    After evaluating the proposed solutions, we have decided to implement Redis Caching because it provides a significant performance boost for read operations with relatively low complexity and cost.
-->

After evaluating the proposed solutions, we have decided to implement [CHOSEN_SOLUTION_NAME] because [REASON_FOR_CHOICE].

## Consequences

<!--

    Consequences Example
    ===

    Implementing Redis Caching will have the following consequences:

    ### Positive Consequences

    - Improved read performance, leading to faster response times for users.
    - Reduced load on the primary database, enhancing overall system stability.

    ### Negative Consequences

    - Additional infrastructure to manage and maintain (Redis server).
    - Potential data consistency issues if cache is not properly invalidated.
-->

### Positive Consequences

- [POSITIVE_CONSEQUENCE_1]
- [POSITIVE_CONSEQUENCE_2]

### Negative Consequences

- [NEGATIVE_CONSEQUENCE_1]
- [NEGATIVE_CONSEQUENCE_2]