Penanganan Kesalahan dan Percobaan Ulang
Terapkan penanganan kesalahan yang andal, antrean surat mati, dan mekanisme percobaan ulang untuk aplikasi tanpa server yang tangguh.
Penanganan Kesalahan dan Percobaan Ulang adalah pelajaran Serverless Backend with AWS Lambda & API Gateway gratis di CoddyKit. Ini adalah pelajaran 3 dari 4. Kamu bisa membaca pelajaran lengkapnya di bawah secara gratis — lalu praktikkan langsung di browser dengan editor kode bawaan dan tutor AI 24/7. Ini adalah bagian dari jalur belajar Serverless Backend with AWS Lambda & API Gateway, dan progresmu tersinkronisasi di web dan aplikasi CoddyKit. Kursus Serverless Backend with AWS Lambda & API Gateway mencakup 4 pelajaran total.
Bagian dari pelajaran ini belum diterjemahkan dan ditampilkan dalam bahasa Inggris.
Build Resilient Serverless Apps
In serverless architectures, things can go wrong. Network issues, service outages, or bugs in your code can all lead to failures.
Building resilient applications means they can recover gracefully from these issues, minimizing impact on users and preventing data loss. Error handling and retries are key to this.
Lambda Invocation Types
How Lambda handles errors and retries depends on how your function is invoked. There are two main types:
- Synchronous: The caller waits for a response (e.g., API Gateway, ALB).
- Asynchronous: The caller doesn't wait; Lambda queues the event (e.g., S3, SNS, SQS, EventBridge).
Each type has different retry behaviors by default.
Synchronous Invocation Retries
When a Lambda function is invoked synchronously and returns an error (or times out), Lambda does NOT automatically retry the function.
It's up to the service or client that invoked Lambda (e.g., API Gateway, your mobile app) to implement its own retry logic. Lambda simply passes the error back to the caller.
Asynchronous Invocation Retries
For asynchronous invocations, Lambda has built-in retry mechanisms. If your function fails due to an unhandled error or times out, Lambda will automatically retry the invocation twice.
This means a total of three attempts (initial + two retries) are made, with an exponential backoff between retries. This helps overcome transient issues.
Handling Errors in Code
Beyond Lambda's automatic retries, you should always implement error handling *within* your function code. This allows you to:
- Gracefully manage expected errors (e.g., missing input).
- Log specific details for debugging.
- Return custom error messages to callers.
In Python, the try-except block is your best friend for this.
Python Error Handling Example
This Python Lambda function uses try-except to handle potential KeyError if an expected key is missing, or ZeroDivisionError if a value is zero. Try running it with different inputs!
import json
def lambda_handler(event, context):
try:
# Expecting 'value' key in the event
num = event['value']
result = 100 / num
return {
'statusCode': 200,
'body': json.dumps(f'Result: {result}')
}
except KeyError:
print("Error: 'value' key missing in event.")
return {
'statusCode': 400,
'body': json.dumps('Input Error: Missing \'value\' in event.')
}
except ZeroDivisionError:
print("Error: Cannot divide by zero.")
return {
'statusCode': 400,
'body': json.dumps('Input Error: Cannot divide by zero.')
}
except Exception as e:
print(f"An unexpected error occurred: {e}")
return {
'statusCode': 500,
'body': json.dumps(f'Server Error: {str(e)}')
}
# Example of how to run locally for testing
if __name__ == "__main__":
# Test case 1: Missing key
print("\n--- Test Case 1 (Missing Key) ---")
print(lambda_handler({}, None))
# Test case 2: Zero division
print("\n--- Test Case 2 (Zero Division) ---")
print(lambda_handler({'value': 0}, None))
# Test case 3: Success
print("\n--- Test Case 3 (Success) ---")
print(lambda_handler({'value': 25}, None))
# Test case 4: Non-numeric value (unhandled, falls to generic exception)
print("\n--- Test Case 4 (Type Error) ---")
print(lambda_handler({'value': 'abc'}, None))Dead-Letter Queues (DLQs)
What happens if an asynchronous Lambda invocation fails even after all retries? This is where Dead-Letter Queues (DLQs) come in!
A DLQ is an Amazon SQS queue or SNS topic where Lambda sends events it couldn't process successfully after all retry attempts. It's a crucial mechanism for:
- Preventing data loss.
- Debugging persistent issues.
- Manual reprocessing of failed events.
Configuring a DLQ
To set up a DLQ for your Lambda function:
- Create an SQS queue or SNS topic: This will be your DLQ.
- Grant Permissions: Ensure your Lambda function has permission to publish messages to the chosen SQS queue or SNS topic.
- Configure Lambda: In your Lambda function's configuration (under 'Asynchronous invocation'), specify the ARN of your SQS queue or SNS topic as the DLQ.
This ensures failed events have a safe landing spot.
DLQ Behavior in Action
It's important to understand *when* an event is sent to a DLQ:
- Only for asynchronous invocations.
- After all automatic retry attempts (initial + two retries) have failed.
- If the event's maximum age is exceeded, or the maximum retry attempts are exhausted.
The original event payload, along with some metadata, is sent to the DLQ.
DLQ Understanding
Let's check your understanding of Dead-Letter Queues!
Recap: Error Handling & Retries
You've learned how to make your serverless applications more robust!
- Synchronous vs. Asynchronous: Different invocation types have different default retry behaviors.
- In-code Error Handling: Use
try-exceptto catch and manage errors within your Lambda code. - Dead-Letter Queues (DLQs): A critical mechanism for capturing and inspecting events that fail after all automatic retries, preventing data loss for async invocations.
These practices are essential for building reliable serverless systems!
Pertanyaan yang Sering Diajukan
Apakah pelajaran “Penanganan Kesalahan dan Percobaan Ulang” gratis?
Ya — teks lengkap “Penanganan Kesalahan dan Percobaan Ulang” gratis dibaca di sini di web. Untuk praktiknya secara interaktif (editor kode bawaan dan tutor AI 24/7) dan buka sisa kursus Serverless Backend with AWS Lambda & API Gateway, upgrade ke CoddyKit PRO. Kursus Serverless Backend with AWS Lambda & API Gateway mencakup 4 pelajaran total.
Apa yang akan aku pelajari di “Penanganan Kesalahan dan Percobaan Ulang”?
Terapkan penanganan kesalahan yang andal, antrean surat mati, dan mekanisme percobaan ulang untuk aplikasi tanpa server yang tangguh. Kamu berlatih Serverless Backend with AWS Lambda & API Gateway dengan kode praktik yang langsung kamu jalankan di browser, dan tutor AI 24/7 menjawab pertanyaanmu saat kamu mengerjakan pelajaran ini.
Apakah aku perlu pengalaman untuk memulai Serverless Backend with AWS Lambda & API Gateway?
Tidak diperlukan pengalaman sebelumnya. Serverless Backend with AWS Lambda & API Gateway di CoddyKit dirancang untuk pemula hingga pelajar tingkat lanjut, jadi kamu bisa memulai di sini atau dari awal dan belajar sesuai kecepatan kamu sendiri. Ini adalah pelajaran 3 dari 4.
Berapa lama pelajaran “Penanganan Kesalahan dan Percobaan Ulang” memakan waktu?
Sebagian besar pelajaran CoddyKit memakan waktu sekitar 5–10 menit. Setiap pelajaran ringkas dan interaktif, jadi kamu membuat kemajuan stabil dan melanjutkan dari tempat kamu tinggalkan di web dan aplikasi.
Bisakah aku menulis dan menjalankan kode dalam pelajaran Serverless Backend with AWS Lambda & API Gateway ini?
Ya. Setiap pelajaran Serverless Backend with AWS Lambda & API Gateway menyertakan editor kode bawaan, jadi kamu menulis dan menjalankan kode nyata langsung di browser dan mendapatkan umpan balik AI instan — tidak diperlukan penyiapan lokal.
Semua pelajaran dalam kursus ini
- Cold Start dan Strategi Pemanasan
- Teknik Optimasi Biaya
- Penanganan Kesalahan dan Percobaan Ulang
- Keteramatan dengan Pencatatan Terstruktur dan Pelacakan