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Initial smoke test pass, dialyzer clean, 20 pass/0 fail
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.github/workflows/elixir.yaml

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# Define workflow that runs when changes are pushed to the
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# `main` branch or pushed to a PR branch that targets the `main`
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# branch. Change the branch name if your project uses a
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# different name for the main branch like "master" or "production".
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on:
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push:
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branches: [ "main" ] # adapt branch for project
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pull_request:
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branches: [ "main" ] # adapt branch for project
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# Sets the ENV `MIX_ENV` to `test` for running tests
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env:
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MIX_ENV: test
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permissions:
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contents: read
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jobs:
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test:
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# Set up a Postgres DB service. By default, Phoenix applications
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# use Postgres. This creates a database for running tests.
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# Additional services can be defined here if required.
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services:
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# db:
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# image: postgres:12
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# ports: ['5432:5432']
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# env:
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# POSTGRES_PASSWORD: postgres
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# options: >-
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# --health-cmd pg_isready
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# --health-interval 10s
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# --health-timeout 5s
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# --health-retries 5
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runs-on: ubuntu-latest
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name: Test on OTP ${{matrix.otp}} / Elixir ${{matrix.elixir}}
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strategy:
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# Specify the OTP and Elixir versions to use when building
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# and running the workflow steps.
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matrix:
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otp: ['25.0.4'] # Define the OTP version [required]
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elixir: ['1.14.1'] # Define the elixir version [required]
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steps:
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# Step: Setup Elixir + Erlang image as the base.
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- name: Set up Elixir
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uses: erlef/setup-beam@v1
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with:
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otp-version: ${{matrix.otp}}
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elixir-version: ${{matrix.elixir}}
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# Step: Check out the code.
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- name: Checkout code
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uses: actions/checkout@v3
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# Step: Define how to cache deps. Restores existing cache if present.
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- name: Cache deps
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id: cache-deps
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uses: actions/cache@v3
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env:
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cache-name: cache-elixir-deps
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with:
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path: deps
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key: ${{ runner.os }}-mix-${{ env.cache-name }}-${{ hashFiles('**/mix.lock') }}
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restore-keys: |
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${{ runner.os }}-mix-${{ env.cache-name }}-
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# Step: Define how to cache the `_build` directory. After the first run,
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# this speeds up tests runs a lot. This includes not re-compiling our
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# project's downloaded deps every run.
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- name: Cache compiled build
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id: cache-build
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uses: actions/cache@v3
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env:
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cache-name: cache-compiled-build
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with:
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path: _build
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key: ${{ runner.os }}-mix-${{ env.cache-name }}-${{ hashFiles('**/mix.lock') }}
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restore-keys: |
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${{ runner.os }}-mix-${{ env.cache-name }}-
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${{ runner.os }}-mix-
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# Step: Conditionally bust the cache when job is re-run.
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# Sometimes, we may have issues with incremental builds that are fixed by
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# doing a full recompile. In order to not waste dev time on such trivial
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# issues (while also reaping the time savings of incremental builds for
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# *most* day-to-day development), force a full recompile only on builds
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# that are retried.
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- name: Clean to rule out incremental build as a source of flakiness
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if: github.run_attempt != '1'
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run: |
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mix deps.clean --all
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mix clean
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shell: sh
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# Step: Download project dependencies. If unchanged, uses
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# the cached version.
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- name: Install dependencies
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run: mix deps.get
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# Step: Compile the project treating any warnings as errors.
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# Customize this step if a different behavior is desired.
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- name: Compiles without warnings
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run: mix compile --warnings-as-errors
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# Step: Check that the checked in code has already been formatted.
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# This step fails if something was found unformatted.
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# Customize this step as desired.
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- name: Check Formatting
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run: mix format --check-formatted
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# Step: Execute the tests.
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- name: Run tests
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run: mix test

HOW_TO_HANDLE_ERRORS.md

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## Key Points for Robust Error Handling in Large-Scale Elixir Applications
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* **Standardized Error Formats:** Research suggests using standardized error formats, like atoms with maps, for reliability and clarity.
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* **Supervision Trees and "Let It Crash":** It seems likely that supervision trees and the "let it crash" philosophy are essential for fault tolerance.
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* **Monitoring and Testing:** The evidence leans toward integrating monitoring tools and testing for failures to ensure scalability.
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* **Exceptions vs. Tuples:** There is some debate on whether to use exceptions or tuples, but tuples are generally preferred for expected errors.
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-----
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## Overview
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For enterprise, large-scale Elixir applications, robust error handling is crucial to ensure reliability and scalability. Here’s a simple guide to help you implement effective strategies, keeping things approachable and open to complexity.
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### Standardized Error Formats
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Start by using a consistent way to represent errors. Research suggests using atoms (like `:not_found`) for error codes, combined with maps for details, such as `{:error, %{code: :not_found, message: "User not found...", details: %{user_id: 1234}}}`. This makes errors easy to match and debug. Libraries like `ErrorMessage` can standardize this across your app, which is great for large teams.
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### Leverage Elixir’s Built-in Tools
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Elixir’s design, built on the Erlang VM, supports fault tolerance. Use `{:ok, result}` and `{:error, reason}` tuples for expected errors, like invalid inputs, and reserve exceptions for rare cases, like configuration issues. Use `try/rescue` to catch exceptions and `try/after` to clean up resources, ensuring your app stays stable.
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### Supervision and Fault Tolerance
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For large-scale apps, organize processes into supervision trees. The "let it crash" philosophy means processes fail fast on unexpected errors, and supervisors restart them, maintaining system uptime. This is key for handling high traffic or distributed systems.
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### Advanced Strategies for Scale
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For enterprise needs, add circuit breakers to manage external service failures, preventing system overload. Integrate monitoring tools like Prometheus for metrics and test for failures to catch issues early. Document your strategies and use structured logging for easier debugging in production.
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### Why It Matters
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These strategies ensure your app is reliable, scalable, and maintainable, meeting enterprise demands. They help handle errors gracefully, keeping users happy and systems running smoothly.
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-----
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## Survey Note: Comprehensive Analysis of Robust Error Handling in Large-Scale Elixir Applications
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This note provides a detailed exploration of robust error handling strategies for enterprise, large-scale Elixir applications, expanding on the direct answer with additional context and depth. The analysis is informed by authoritative sources and community discussions, ensuring a comprehensive understanding suitable for professional implementation.
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### Introduction
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Elixir, built on the Erlang VM (BEAM), is renowned for its fault tolerance and scalability, making it ideal for enterprise applications. However, as applications grow in scale, robust error handling becomes critical to ensure reliability, maintainability, and user satisfaction. This section outlines key strategies, supported by practical examples and best practices, to address the complexities of error management in large-scale Elixir systems.
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### Standardized Error Representation
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One of the foundational strategies for robust error handling is ensuring errors are represented in a consistent, machine-readable, and human-understandable format. Research suggests avoiding strings for errors due to their fragility in pattern matching, as they can lead to runtime errors if not handled carefully. Instead, the evidence leans toward using atoms for error codes, which are more reliable and support pattern matching effectively. For example, the `File.ls` function returns atoms like `:eexist` or `:eacces` for specific error conditions.
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To enhance clarity, combine atoms with maps to include detailed error information. A common pattern is:
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```elixir
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{:error, %{code: :not_found, message: "User not found...", details: %{user_id: 1234}}}
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```
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This approach allows developers to match on the atom for control flow while providing a human-readable message and additional context for debugging. The `ErrorMessage` library exemplifies this, offering a standardized structure for error representation. For instance:
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```elixir
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ErrorMessage.not_found("No user found...", %{user_id: 1234})
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```
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This returns a structured error like `%ErrorMessage{code: :not_found, message: "...", details: %{user_id: 1234}}`, which has been battle-tested in production environments like Blitz for over four years and is used by companies like Requis and CheddarFlow. Integrating such libraries with Phoenix APIs and logs enhances debugging capabilities, as seen in projects like EctoShorts and ElixirCache.
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### Leveraging Elixir’s Built-in Error Handling Mechanisms
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Elixir provides robust mechanisms for error handling, which are particularly effective for large-scale applications. The standard convention is to use `{:ok, result}` and `{:error, reason}` tuples for functions that can fail, such as file operations or database queries. This allows for pattern matching to handle both success and failure cases, as shown in:
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```elixir
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case File.read("example.txt") do
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{:ok, content} -> IO.puts(content)
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{:error, reason} -> IO.puts("Error: #{reason}")
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end
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```
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This approach is preferred for expected errors, such as invalid input or resource unavailability, and is widely adopted in the Elixir community.
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For exceptional cases, such as configuration errors or bugs, exceptions should be used. The `try/rescue` construct is ideal for catching these, allowing developers to specify which exceptions to handle. For example:
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```elixir
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try do
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# Code that might raise an exception
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rescue
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File.Error -> IO.puts("File operation failed")
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KeyError -> IO.puts("Key not found")
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end
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```
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Additionally, `try/after` ensures cleanup actions, such as closing files or database connections, are executed regardless of whether an exception occurs, similar to Ruby’s `begin/rescue/ensure` or Java’s `try/catch/finally`. For instance:
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```elixir
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try do
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File.open("example.txt", [:write])
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after
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File.close("example.txt")
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end
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```
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Custom exceptions can also be defined using `defexception/1` for specific error cases, enhancing the granularity of error handling. For example:
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```elixir
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defmodule ExampleError do
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defexception message: "Something went wrong"
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end
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raise ExampleError
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```
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However, there is some debate in the community about the use of `throw/catch` and `exit`, with modern Elixir favoring supervisors for process exits instead, as discussed in community forums like Elixir Forum.
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### Supervision and Fault Tolerance
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For large-scale applications, fault tolerance is critical, and Elixir’s supervision trees are a cornerstone of this. Supervisors monitor and manage the lifecycle of worker processes, restarting them if they crash. This is facilitated by the "let it crash" philosophy, where processes are designed to fail fast on unexpected events, simplifying code by offloading error recovery to supervisors. For example, a supervisor might use a `one_for_one` strategy to restart a failed worker:
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```elixir
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children = [
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{MyWorker, []}
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]
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Supervisor.start_link(children, strategy: :one_for_one)
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```
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This approach ensures the system remains operational, which is essential for handling high traffic or distributed systems. The supervision strategy can be customized (e.g., `one_for_all` for restarting all children if one fails), depending on the application’s needs.
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### Advanced Patterns for Large-Scale Applications
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As applications scale, additional patterns are necessary to manage complexity and ensure reliability. Circuit breakers are particularly useful for handling failures in external services, such as APIs or databases. A circuit breaker temporarily stops requests to a failing service, preventing cascading failures. While specific implementations vary, libraries like Hystrix (in other ecosystems) inspire similar patterns in Elixir, often implemented using `GenServer`s or libraries like Fuse.
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Monitoring and telemetry are also vital for proactive issue detection. Tools like Prometheus can be integrated for metrics, and telemetry libraries can track error rates and system health. For example, the `Telemetry` library allows developers to emit events for monitoring:
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```elixir
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:telemetry.execute([:my_app, :error], %{count: 1}, %{reason: "Database timeout"})
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```
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Testing for failures is another critical aspect, ensuring the application behaves correctly under exceptional conditions. This includes unit tests, integration tests, and property-based tests using tools like ExUnit and PropEr. For instance:
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```elixir
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test "handles database connection failure" do
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assert {:error, :timeout} = MyApp.database_operation()
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end
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```
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### Best Practices for Development and Maintenance
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To ensure maintainability, document error-handling strategies clearly, especially in large teams. Structured logging is essential for diagnosing production issues, using libraries like Logger to include error codes, messages, and context. For example:
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```elixir
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Logger.error("Failed to process request, code: :not_found, details: %{user_id: 1234}")
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```
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Over time, convert unexpected errors into expected ones to enhance system resilience. For instance, if a database query fails due to a timeout, handle it as an expected error with a meaningful message rather than letting the process crash.
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### Additional Considerations for Enterprise Applications
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For enterprise applications, scalability and reliability are paramount. Ensure error handling does not introduce bottlenecks, such as overly complex logic that slows down the application. Integration with Phoenix, a popular web framework for Elixir, is common, and error handling should seamlessly integrate with Phoenix’s plug system and API responses. Using `ErrorMessage` with Phoenix can standardize API error responses, enhancing user experience.
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In distributed systems, account for node failures and network partitions. Elixir’s distribution features, built on Erlang, support this, and distributed supervisors can manage processes across nodes. For example, use `Node.connect/1` to connect nodes and ensure supervisors handle failures across the cluster.
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### Summary of Strategies
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To organize the strategies discussed, the following table summarizes key approaches and their relevance:
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| Strategy | Description | Relevance for Large-Scale Apps |
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| :-------------------------- | :-------------------------------------------------------------------------- | :--------------------------------------------------------------- |
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| Standardized Error Formats | Use atoms with maps, leverage `ErrorMessage` for uniformity. | Enhances debugging, maintainability, and team collaboration. |
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| Built-in Error Handling | Use tuples for expected errors, exceptions for rare cases, `try/rescue/after`. | Ensures graceful error handling, resource cleanup. |
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| Supervision Trees | Organize processes, use "let it crash" philosophy, customize restart strategies. | Critical for fault tolerance, high availability. |
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| Circuit Breakers | Handle external service failures, prevent cascading issues. | Prevents system overload, ensures reliability. |
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| Monitoring and Telemetry | Use tools like Prometheus, emit telemetry events for proactive detection. | Enables early issue detection, system health tracking. |
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| Testing for Failures | Include unit, integration, and property-based tests for failure scenarios. | Ensures resilience under exceptional conditions. |
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| Documentation and Logging | Document strategies, use structured logging for production debugging. | Improves maintainability, diagnostics in production. |
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This table highlights the comprehensive nature of error handling in Elixir, addressing both technical and operational needs for enterprise applications.
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### Conclusion
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Robust error handling in enterprise, large-scale Elixir applications requires a combination of standardized error representation, leveraging built-in mechanisms, supervision for fault tolerance, and advanced patterns like circuit breakers and monitoring. By following these strategies, developers can build applications that are resilient, scalable, and maintainable, meeting the demands of enterprise-level deployments. The integration of community-tested libraries and thorough testing ensures these strategies are practical and effective in real-world scenarios.
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### Key Citations
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* [Safer Error Systems In Elixir guide](https://www.google.com/search?q=https://elixir-lang.org/getting-started/error-handling/safer-error-systems.html)
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* [Error Handling lesson at Elixir School](https://www.google.com/search?q=https://elixirschool.com/lessons/basics/error-handling/)
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* [Best practices for error handling and fault tolerance in Elixir](https://www.google.com/search?q=https://www.cultivatehq.com/blog/error-handling-and-fault-tolerance-in-elixir/)
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* [ErrorMessage library documentation](https://hexdocs.pm/error_message/ErrorMessage.html)
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* [Prometheus monitoring tool](https://prometheus.io/)
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* [Telemetry library documentation](https://www.google.com/search?q=https://hexdocs.pm/telemetry/Telemetry.html)
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* [ExUnit testing framework](https://hexdocs.pm/ex_unit/ExUnit.html)
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* [Requis company website](https://requis.com/)
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* [CheddarFlow company website](https://cheddarflow.com/)
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* [EctoShorts GitHub repository](https://www.google.com/search?q=https://github.com/dorgan/ectoshorts)
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* [ElixirCache GitHub repository](https://www.google.com/search?q=https://github.com/dorgan/elixir_cache)

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