AWS Lambda | AWS Lambda functions Flashcards
What AWS regions are available for AWS Lambda?
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Please refer to the AWS Global Infrastructure Region Table.
What is an AWS Lambda function?
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The code you run on AWS Lambda is uploaded as a “Lambda function”. Each function has associated configuration information, such as its name, description, entry point, and resource requirements. The code must be written in a “stateless” style i.e. it should assume there is no affinity to the underlying compute infrastructure. Local file system access, child processes, and similar artifacts may not extend beyond the lifetime of the request, and any persistent state should be stored in Amazon S3, Amazon DynamoDB, or another Internet-available storage service. Lambda functions can include libraries, even native ones.
Will AWS Lambda reuse function instances?
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To improve performance, AWS Lambda may choose to retain an instance of your function and reuse it to serve a subsequent request, rather than creating a new copy. To learn more about how Lambda reuses function instances, visit our documentation. Your code should not assume that this will always happen.
What if I need scratch space on disk for my AWS Lambda function?
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Each Lambda function receives 500MB of non-persistent disk space in its own /tmp directory.
Why must AWS Lambda functions be stateless?
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Keeping functions stateless enables AWS Lambda to rapidly launch as many copies of the function as needed to scale to the rate of incoming events. While AWS Lambda’s programming model is stateless, your code can access stateful data by calling other web services, such as Amazon S3 or Amazon DynamoDB.
Can I use threads and processes in my AWS Lambda function code?
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Yes. AWS Lambda allows you to use normal language and operating system features, such as creating additional threads and processes. Resources allocated to the Lambda function, including memory, execution time, disk, and network use, must be shared among all the threads/processes it uses. You can launch processes using any language supported by Amazon Linux.
What restrictions apply to AWS Lambda function code?
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Lambda attempts to impose as few restrictions as possible on normal language and operating system activities, but there are a few activities that are disabled: Inbound network connections are blocked by AWS Lambda, and for outbound connections only TCP/IP sockets are supported, and ptrace (debugging) system calls are blocked. TCP port 25 traffic is also blocked as an anti-spam measure.
How do I create an AWS Lambda function using the Lambda console?
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If you are using Node.js or Python, you can author the code for your function using code editor in the AWS Lambda console which lets you author and test your functions, and view the results of function executions in a robust, IDE-like environment. Go to the console to get started.
You can also package the code (and any dependent libraries) as a ZIP and upload it using the AWS Lambda console from your local environment or specify an Amazon S3 location where the ZIP file is located. Uploads must be no larger than 50MB (compressed). You can use the AWS Eclipse plugin to author and deploy Lambda functions in Java. You can use the Visual Studio plugin to author and deploy Lambda functions in C#, and Node.js.
How do I create an AWS Lambda function using the Lambda CLI?
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You can package the code (and any dependent libraries) as a ZIP and upload it using the AWS CLI from your local environment, or specify an Amazon S3 location where the ZIP file is located. Uploads must be no larger than 50MB (compressed). Visit the Lambda Getting Started guide to get started.
Does AWS Lambda support environment variables?
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Yes. You can easily create and modify environment variables from the AWS Lambda Console, CLI or SDKs. To learn more about environment variables, see the documentation.
Can I store sensitive information in environment variables?
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For sensitive information, such as database passwords, we recommend you use client-side encryption using AWS Key Management Service and store the resulting values as ciphertext in your environment variable. You will need to include logic in your AWS Lambda function code to decrypt these values.
How can I manage my AWS Lambda functions?
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You can easily list, delete, update, and monitor your Lambda functions using the dashboard in the AWS Lambda console. You can also use the AWS CLI and AWS SDK to manage your Lambda functions. Visit the Lambda Developers Guide to learn more.
How do I monitor an AWS Lambda function?
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AWS Lambda automatically monitors Lambda functions on your behalf, reporting real-time metrics through Amazon CloudWatch, including total requests, account-level and function-level concurrency usage, latency, error rates, and throttled requests. You can view statistics for each of your Lambda functions via the Amazon CloudWatch console or through the AWS Lambda console. You can also call third-party monitoring APIs in your Lambda function.
Visit Troubleshooting CloudWatch metrics to learn more. Standard charges for AWS Lambda apply to use Lambda’s built-in metrics.
How do I troubleshoot failures in an AWS Lambda function?
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AWS Lambda automatically integrates with Amazon CloudWatch logs, creating a log group for each Lambda function and providing basic application lifecycle event log entries, including logging the resources consumed for each use of that function. You can easily insert additional logging statements into your code. You can also call third-party logging APIs in your Lambda function. Visit Troubleshooting Lambda functions to learn more. Amazon CloudWatch Logs rates will apply.
How do I scale an AWS Lambda function?
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You do not have to scale your Lambda functions – AWS Lambda scales them automatically on your behalf. Every time an event notification is received for your function, AWS Lambda quickly locates free capacity within its compute fleet and runs your code. Since your code is stateless, AWS Lambda can start as many copies of your function as needed without lengthy deployment and configuration delays. There are no fundamental limits to scaling a function. AWS Lambda will dynamically allocate capacity to match the rate of incoming events.
