py , and save it in a project directory of your choice. I've been guilty of this in my own articles, but it's important to remember that Python is a 'first-class citizen' within AWS and is a great option for writing readable Lambda code. Option 2: Automating Snowpipe with AWS Lambda¶ AWS Lambda is a compute service that runs when triggered by an event and executes code that has been loaded into the system. Write a python handler function to respond to events and interact with other parts of AWS (e. Eg — If your function will be interacting with S3, just give S3 access to its assigned role. Uploading files to AWS S3 using Nodejs By Mukul Jain AWS S3. Lambda gives you a place to just “write and run code on the cloud”. Lack of infrastructure maintenance is the bigger story here. As uploading files to s3 bucket from lambda one-by-one was taking a lot of time, I thought of optimising my code where I'm storing each image. The Solution. The Problem. You can use Boto module also. Looking for an experienced Amazon Web Services and python developer. When to use S3-Select? S3 Select is extremely useful when:. In this post, I will show you how to use Lambda to execute data ingestion from S3 to RDS whenever a new file is created in the source bucket. You will also learn how to use boto3 Python library. But this time I’ve decided to explore more AWS services and turn that script into a Lambda that is triggered by CloudWatch. My task is to copy the most recent backup file from AWS S3 to the local sandbox SQL Server, then do the restore. Host a Custom Skill as an AWS Lambda Function The easiest way to build the cloud-based service for a custom Alexa skill is to use AWS Lambda , an Amazon Web Services offering that runs your code only when it's needed and scales automatically, so there is no need to provision or continuously run servers. A step-by-step process to enable AWS CLI within an AWS Lambda function. Select event source type as s3, select the desired bucket. If you look above, you'll see that this is registered in the service (right at the bottom there) with the name hello. S3 can store any types of objects / files and it may be necessary to access and read the files programatically. So no compilation or 3rd party libraries are required for this function, it can even be written directly into the AWS console. Read File from S3 using Lambda. Following is the lambda function created. A possible solution for these kind of situations is to implement a recursive approach to perform the processing task. image thumbnail generation, metadata extraction, indexing etc). zip to Lambda Layers so we can use that package from now on in all our functions. I wrote a very simple AWS Lambda function to demonstrate how to connect an Oracle database, gather the tablespace usage information, and send these metrics to CloudWatch. RDS and DynamoDB require fixed monthly payments. Connect to AWS RDS (MySQL) Using Lambda (Python) | RDS Tutorial | Lambda Tutorial Appychip. • Worked on AWS EBS, storage service AWS S3. All you need to do is upload your code to AWS or you can write your code in the Lambda in-line editor itself. Today, Qubole is announcing the availability of a working implementation of Apache Spark on AWS Lambda. Lambda is a good option for running any scripts you write if you do not have a dedicated server. The Introduction to AWS Lambda course in qwiklabs. You can do this by going to “Create Policy” , then “Policy Generator”, then checking “allow”, selecting “Amazon S3” as the AWS Service, checking “s3:PutObject” and “s3:PutObjectAcl”, and then entering the ARN number as follows: arn:aws:s3. AWS supports a number of languages including NodeJS, C#, Java, Python and many more that can be used to access and read file. To do this, we’ll simply call the New-S3Bucket command. Amazon Web Services (AWS) Lambda is a usage-based service that can run arbitrary Python 3. 7 in which I want to: 1) Grab an. With lambda you write your code, package it up & send it to AWS using API call. In recent months, I've begun moving some of my analytics functions to the cloud. Every 100 or so megs, write a new file to an s3 bucket. Merely invoke this. While developing this application, you will interact with AWS services such as S3 bucket and AWS Lambda. Write the first response. AWS Lambda is a service that allows you to write Python, Java, or Node. from Node. So, let’s begin. Additionally, it comes with Boto3, the AWS Python SDK that makes interfacing with AWS services a snap. As the function executes, it reads the S3 event data, logs some of the event information to Amazon CloudWatch. Python and AWS Lambda - A match made in heaven September 19, 2017 September 19, 2017 Python Data Data Analytics In recent months, I've begun moving some of my analytics functions to the cloud. Its always preferable to use CloudFormation (or Terraform to be Cloud agnostic) as its easier and better to provision resources as code due to reasons mentioned above mainly speed and ease of deployment. Looking for an experienced Amazon Web Services and python developer. But depending on your use case there might be a similar option. In one corner we have Pandas: Python's beloved data analysis library. You can then set a trigger on colorImage, and the output will be stored in grayscaleImage. Explain what AWS Lambda and API Gateway are and why would would want to use them. Amazon Simple Storage Service is storage for the Internet. Lambda Function. 7-compatible runtime to execute your Lambda functions. 5 pycparser==2. You may not realise that you can write AWS Lambda functions in a recursive manner to perform long-running tasks. Our Function. I'm a newbie to the Amazon Lambda/AWS service. Therefore open an editor of your choice, create a file called simple-lambda-authorizer. You could incorporate this logic in a Python module in a bigger system, like a Flask app or a web API. ConcurrentExecutions (integer) --The maximum number of simultaneous function executions. AWS Lambda and the Serverless Framework is the QUICKEST way to get started in the serverless world, to deploy AWS Lambda functions in Amazon Web Services that infinitely scale without managing any servers! This course, unlike others, has an approach that teaches you how to properly deploy AWS Lambda functions from the very first lectures. It works fine from a regular Unix Terminal, but AWS Lambda doesn't seem to work well with Temporary Files. The AWS Lambda blueprint from Loggly is also written in Node. Read access keys from ~/. This then begins a loop (12) to pull each instance name, filtered by using a Python lambda (not AWS Lambda) function. If your Lambda function is using a Python runtime, install the Datadog Lambda Layer to collect and send custom metrics. AWS Lambda is a new, serverless way to build systems in the cloud. In this post, I will show you how to use Lambda to execute data ingestion from S3 to RDS whenever a new file is created in the source bucket. • Monitored the server's performance, CPU Utilization, disk usage etc. Once the lambda function is installed, manually add a trigger on the S3 bucket that contains your S3 logs in the AWS console, in your Lambda, click on S3 in the trigger list: Configure your trigger by choosing the S3 bucket that contains your S3 logs and change the event type to Object Created (All) then click on the add button. ) No underscores (_) - cannot appear at the beginning nor end of the bucket name. Interact with Amazon S3 in various ways, such as creating a bucket and uploading a file. AWS Lambda service will take care of the deployment and all administration related. S3 can store any types of objects / files and it may be necessary to access and read the files programatically. Deploy Go, Java,. The AWS Lambda Python runtime is version 2. Checksum: 5d0b66f2f6f50fe7a199c5f16ca4d3b67ebba5c9. All you need to do is upload your code to AWS or you can write your code in the Lambda in-line editor itself. In this post, we'll learn how Kinesis Firehose captures streaming data and transforms the data, and then sends it to ElasticSearch service. While developing this application, you will interact with AWS services such as S3 bucket and AWS Lambda. Learn how to create objects, upload them to S3, download their contents, and change their attributes directly from your script, all while avoiding common pitfalls. In previous chapter I talked a little what is AWS Lambda and idea behind serverless computing. That is to say, your code sits out there as just a file and AWS keeps a lookout for a trigger event, which you are interested in. You must enter some descriptive information for your question. Python and AWS for simple services. Boto is a Python package that provides interfaces to AWS including Amazon S3. resource again. Today, we’ll go through a very brief introduction of the main AWS Lambda and serverless concepts. There are various classes of storage available, ranging from extremely cost-efficient options to high-performance, high-speed storage mediums. Layers allows you to include additional files or data for your functions. Play with it on. Lambda is a good. Lambda (Serverless) As the name serverless indicates, no servers from your side are required. zip to Lambda Layers so we can use that package from now on in all our functions. (4) AWS Lambda executes the Lambda function. How do I write a Python lambda function to check If my S3 Buckets are Public & Make them Private in my account. AWS Lambda is a service that allows you to write Python, Java, or Node. To have maximum compatibility, the ideal bucket name has: No capital letters (A-Z) No periods (. Serverless ETL on AWS Lambda. Version v2. python-lambda: The Savior of AWS. For our purposes, AWS Lambda is a perfect solution for running user-supplied code quickly, securely, and cheaply. Amazon Simple Storage Service is storage for the Internet. csv files from Phase #1 into a AWS S3 bucket; Run the copy commands to load these. Back then we packaged and depl. I was wondering if I could set up a lambda function for AWS, triggered whenever a new text file is uploaded into an s3 bucket. AWS Lambda to connect to PostgreSQL and execute a function/query using Python Posted on August 15, 2018 by Ramasankar It’s been long time since i wrote a blog post. aws/credentials. AWS Lambda is a compute service which can run your code without provisioning any Infrastructure or servers. Before you get started building your Lambda function, you must first create an IAM role which Lambda will use to work with S3 and to write logs to CloudWatch. Let’s start with creating AWS Lambda. Login to your AWS account. I have tried to use lambda function to write a file to S3, then test shows "succeeded" ,but nothing appeared in my S3 bucket. # ##### AWSTemplateFormatVersion: 2010-09-09 Description: (SO0070) - The AWS cloud formation template for the deployment of machine-to-cloud-connectivity-framework. You must enter some descriptive information for your question. Use Amazon S3 for larger files. In this tutorial you understood and created your own server-less API using AWS S3, Lambda and API Gateway. Skip to content. AWS Lambda is a server less computing platform. Our Lambda functions will be written in Python 3, and we will be using Python in the scripts used to deploy and update our AWS Infrastructure. By the end of this tutorial you will be able to…. Choose Skip to skip the blueprint selection. Writing Your Lambda with Python Since Python is a scripting language, you can create the script directly within the AWS console. Get started working with Python, Boto3, and AWS S3. 7 function that takes a basic string input from CloudFormation, concatenates it with another string and returns it. Amazon S3 can send an event to a Lambda function when an object is created or deleted. Clean and transform some fields of a csv file, join with a xls, load DynamoDB table. In this post, I will show you how to use Lambda to execute data ingestion from S3 to RDS whenever a new file is created in the source bucket. The FunctionName in the Lambda Permission configuration needs to match the logical ID generated for the target Lambda function as determined by the Serverless naming convention. Here is what I figured out so far:. Mike’s discussion is excellent: clear, straight-forward, with useful illustrative examples. How to use AWS Fargate and Lambda for long-running processes in a Serverless app. I have an S3 bucket. It helped me — finally — to grok lambda, and led me to write yet another lambda tutorial. To create the project just right click on Project explorer and create a new Project and select AWS Lambda Java Project as type of project. (Lambda architecture is distinct from and should not be confused with the AWS Lambda compute service. Sign in Sign up. In November 2018, Amazon released toolkits for the IntelliJ software suite (including PyCharm) to communicate directly with AWS. So here I am going to write about the basics of AWS Lambda and how to trigger it with an API Gateway so that an image can be uploaded on an S3 Bucket. And the underlying systems Lambda writes to (DDB, SQS, etc. Working with Lambda is relatively easy, but the process of bundling and deploying your code is not as simple as it could be. This can be Python modules, code snippets, binary files or anything. Boto is the Amazon Web Services (AWS) SDK for Python. CloudWatch: Lambda logs events to CloudWatch where you can view errors and console statements. If you haven't heard about it, it's a cloud resource that can run Java(nodejs/Python) scripts for free in the cloud. Skills: Amazon Web Services, Aws Lambda, Python. Select Python 2. AWS Lambda encrypts and stores your code in S3. Lambda functions need an entry point handler that accepts the arguments event and context. AWS Lambda guide part I - Import your Python application to Lambda I lately started playing with AWS Lambda for few reasons. To save objects we need permission to execute the s3:PutObject action. Parameters: ExistingGreengrassGroup: Description: Do you want to use an existing greengrass group as the default group of the solution?. import boto3 s3 = boto3. Write the CSV file to local file system (/tmp) and then use boto3's put_object() method. The last lines check for S3 events, and you have to add some logic to deal with the specific s3 events you need. Make sure the path is correct in step 4. S3() If we take a look at our AWS Lambda code, before processing a chunk, we need to forward the stream to point. The maximum size of a deployment package when it's uploaded directly to AWS Lambda. Once you have a handle on S3 and Lambda you can build a Python application that will upload files to the S3 bucket. AWS Lambda is the glue that binds many AWS services together, including S3, API Gateway, and DynamoDB. 1 argon2-cffi==18. Learn to write, run, and deploy Lambda functions in the AWS cloud. We will use Python 3. In the other, AWS: the unstoppable cloud provider we're obligated to use for all eternity. Now that I had my files in S3, I needed some way for Twitter to read them. AWS Lambda is AWS’s serverless platform. The classifier will be stored in a S3 bucket and a lambda function will used to make classifications, finally an Amazon API Gateway will be used to trigger the lambda function. AWS Lambda starts running your code within milliseconds of an event such as an image upload, in-app activity, website click, or output from a connected device. In November 2018, Amazon released toolkits for the IntelliJ software suite (including PyCharm) to communicate directly with AWS. Image source : Getting Started with Amazon Simple Storage Service Amazon S3 has a simple web services interface that we can use to store and retrieve any amount of data, at. Building AWS Lambda with Python, S3 and serverless July 24, 2017 Cloud-native revolution pointed out the fact that the microservice is the new building block and your best friends now are Containers, AWS, GCE, Openshift, Kubernetes, you-name-it. We can always execute Lambda function manually either from web panel or using CLI. This Layer is 100% Bash and handles all communication with the Lambda Runtime API. zip to Lambda Layers so we can use that package from now on in all our functions. 2 (153 ratings) Course Ratings are calculated from individual students' ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately. Use Amazon S3 for larger files. Uploading files to AWS S3 using Nodejs By Mukul Jain AWS S3. yml will look like: Given this configuration file, we now have to provide a python module user. This is a sample python AWS lambda script to load data into a Snowflake database. Mike’s discussion is excellent: clear, straight-forward, with useful illustrative examples. I want to be able to write a text file to S3 and have read many tutorials about how to integrate with S3. Its always preferable to use CloudFormation (or Terraform to be Cloud agnostic) as its easier and better to provision resources as code due to reasons mentioned above mainly speed and ease of deployment. So, let's get started with AWS Lambda Amazon S3 Invocation. This is an example of "push" model where Amazon S3 invokes the Lambda function. People often call Lambda as Lambda Functions. Amazon Web Services is a cloud services provider which owns and maintains the network-connected hardware required for these application services. Therefore open an editor of your choice, create a file called simple-lambda-authorizer. The hands on labs will show you how to write Lambda functions that: Run when files change in S3 (eg. It is up to you to choose the type of events, however, here are some examples of the kinds of. Lambda functions can contain the application logic and use DynamoDB or RDS for persistent data. Topics covered include: AWS Lambda functions, Python. it to deploying it on AWS Lambda. You can write and attach a event for your AWS s3 directory which will call a Lambda function to unzip. You will feel much more confident going forward if you spend some time understanding the AWS services you wish to use and the serverless framework concepts. The application records the event in its log file. 2nd lambda is an event listener on the bucket. But depending on your use case there might be a similar option. Back-end tasks like analyzing a new document or processing requests from a mobile app are easy to implement. We can trigger AWS Lambda on S3 when there are any file uploads in S3 buckets. The lambda compute service can process the data from S3, Dynamodb, SQS etc without provisioning the required compute explicitly. AWS Chalice allows you to quickly create and deploy applications that use Amazon API Gateway and AWS Lambda. Data produced on EC2 instances or AWS lambda servers often end up in Amazon S3 storage. Boto is the Amazon Web Services (AWS) SDK for Python. Introduction to AWS Lambda. Go to Lambda -> Functions -> Create a Lambda Function. Interact with Amazon S3 in various ways, such as creating a bucket and uploading a file. aws/credentials. Finally, it invokes the desired lambda function which works on the object which has been uploaded to the S3 bucket. This blog post addresses that and provides fully working code, including scripts for some of the steps described in their tutorial. Now, we are going to use the python library boto to facilitate our work. Example use cases:. Below is an example lambda function to to get started. In this article, we will focus on how to use Amazon S3 for regular file handling operations using Python and Boto library. Even though this post will largely be focused on Python, a lot of the core lessons are extensible to other languages supported by AWS as well. You will also learn how to use boto3 Python library. We can upload an image directly on S3 Bucket. According to AWS, when you invoke a function asynchronously, the Lambda sends the event to the SQS queue. Lambda is running stock Python 2. Once again, Chathura was the mastermind behind SigmaTrail. As shown below, type s3 into the Filter field to narrow down the list of. Looking for an experienced Amazon Web Services and python developer. GitHub Gist: instantly share code, notes, and snippets. Then, the Lambda function can read the image object from the source bucket and create a thumbnail image target. py , and save it in a project directory of your choice. There are a lot of tutorials for Python’s lambda out there. It enables Python developers to create, configure, and manage AWS services, such as EC2 and S3. When writing a Lambda piece by piece, it really helps to have a logs pane next to your code window. With this setup, the data flow is something like this: An application receives an event or performs some operation in response to user input. Additionally, it comes with Boto3, the AWS Python SDK that makes interfacing with AWS services a snap. ) also have invocation and write limits. Run aws configure and write your credentials and your default region; In order for you to execute the Lambda, you need to use the aws command to create and set the appropriate permissions for the roles and policies and then upload the zip archive containing our python environment. The Connectors framework provided a way to transform, buffer, filter, and emit the Amazon Kinesis records to S3 with ease (among other specified AWS services). Make the most of AWS Lambda functions to build scalable and cost-efficient systems. Learn how to create objects, upload them to S3, download their contents, and change their attributes directly from your script, all while avoiding common pitfalls. 2 (153 ratings) Course Ratings are calculated from individual students' ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately. Before proceeding to work on creating a Lambda function in AWS, we need AWS toolkit support for Python. Navigate to the Lambda Management Console -> Layers -> Create Layer. I have a Node 4. You can highlight the text above to change formatting and highlight code. This is how I set up my Lambda instance. How to use AWS API Gateway endpoint with Python AWS Lambda backend to allow uploads of binary files to your cloud environment. The Lambda service provided by Amazon makes it easy to execute code when a AWS event occurs from a supported AWS service. import boto3 s3 = boto3. • Monitored the server's performance, CPU Utilization, disk usage etc. This is the bucket that is going to trigger the lambda function. Though AWS Lambda is a service that is quick to get started, there is value in learning more about the AWS Lambda computing environment and how to take advantage of deeper performance and cost optimization strategies with the AWS Lambda runtime. Today, Qubole is announcing the availability of a working implementation of Apache Spark on AWS Lambda. Now you specify an IAM role that defines what permissions your lambda function has. All same account. Lambda gives you a place to just “write and run code on the cloud”. To do that at a regular time interval, I decided on using an AWS Lambda function (not to be confused with Python lambda functions, a completely different animal. The Solution. With AWS Lambda, you write your code and upload it to the AWS cloud. AWS Lambda guide part I - Import your Python application to Lambda I lately started playing with AWS Lambda for few reasons. Read File from S3 using Lambda. py , and save it in a project directory of your choice. 6 code in response to developer-defined events. (5) From the event data it receives, the Lambda function knows the source bucket name and object key name. S3 buckets to store files and serve the website. It can also be used to trigger code in response to HTTP requests by using AWS API Gateway. AWS Lambda is a service which performs serverless computing, which involves computing without any server. This is a python 2. This is an example of how to make an AWS Lambda Snowflake database data loader. Mocking AWS Services: FakeS3 Moto. Js, Java and Python Programming language. Join us in this video tutorial we walk through step-by-step how to write AWS Lambda functions in Python to interact with S3 and DynamoDB. Loading Configuration from S3 in Python AWS Lambda June 17, 2016. Naming buckets. It runs in under 100 ms, so the execution time charged for each run is 100 ms. Amazon Web Services (AWS) Lambda is a "serverless" compute service that executes arbitrary Python code in response to developer-defined events, such as inbound API calls or file uploads to AWS S3. AWS Lambda is a compute service which can run your code without provisioning any Infrastructure or servers. Lambda gives you a place to just “write and run code on the cloud”. Play with it on. Managing Amazon S3 files in Python with Boto Amazon S3 (Simple Storage Service) allows users to store and retrieve content (e. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author's boto library. This allows you to run full Bash scripts and commands inside of AWS Lambda. AWS Lambda is a service that allows you to write Python, Java, or Node. Christopher H. AWS Lambda is a function-as-a-service platform that stores and executes your code when triggered by an Amazon Web Service (AWS) event. Read File from S3 using Lambda. With this setup, the data flow is something like this: An application receives an event or performs some operation in response to user input. 따라서 별도로 Boto3를 AWS Lambda에 업로드 하지 않아도 AWS의 다양한 기능을 이용할 수 있다는 장점이 있습니다. Snowflake database is a cloud platform suited to working with large amounts of data for data warehousing and analysis. Of course, all of these objects can be managed with Python and the boto3 library. I'll describe how I use my local workstation to develop the functionality and how to configure the AWS Identity and Access Management roles to configure the Lambda function's authorized access. Read access keys from ~/. How to build a Hugo website in AWS Lambda and deploy it to S3. (5) From the event data it receives, the Lambda function knows the source bucket name and object key name. Right now I have this script to spit out a csv file onto my desktop. Amazon Web Services 18,267 views. In this tutorial you understood and created your own server-less API using AWS S3, Lambda and API Gateway. But depending on your use case there might be a similar option. A more elegant solution is to use AWS Lambda to run the two as a set of functions. Looking for an experienced Amazon Web Services and python developer. Eg — If your function will be interacting with S3, just give S3 access to its assigned role. To have maximum compatibility, the ideal bucket name has: No capital letters (A-Z) No periods (. S3 uploads can generate events which can be used to perform tasks such as getting the path of the file in S3 and making API calls to a 3rd party service. Setting up the Lambda S3 Role When executed, Lambda needs to have permission to access your S3 bucket and optionally to CloudWatch if you intend to log Lambda activity. In this post, we take a look at some code to handle this. AWS re:Invent is in full swing, with AWS announcing a slew of new features. CloudWatch: Lambda logs events to CloudWatch where you can view errors and console statements. It runs code in response to events that trigger it. Phase #2 will be about Python and AWS Boto3 libraries and wrapping this tool all together to push the data through all the way to AWS Redshift. The lambda service can listen to S3 and can process the file as it is put into the S3 bucket. Name the bucket as per your choice. AWS re:Invent 2014 | (DEV307) Introduction to Version 3 of the AWS SDK for Python (Boto) - Duration: 36:42. Snowflake database is a cloud platform suited to working with large amounts of data for data warehousing and analysis. Suppose you want to create a thumbnail for each image file that is uploaded to a bucket. 2) Store it in a temp location. Play with it on. Our Lambda functions will be written in Python 3, and we will be using Python in the scripts used to deploy and update our AWS Infrastructure. Deploy Go, Java,. スケジュール起動も可能。. The lambda service can listen to S3 and can process the file as it is put into the S3 bucket. Java is a little different, so while the test case approach will be the same with both of the examples above, we're going to need to package our Lambda into a JAR and upload it to the console. Combining Lambda with the API Gateway , we can build microservices that can be accessed from outside the AWS ecosystem. I am currently rewriting some recurring background tasks as AWS Lambda functions. Create a new directory in which you can add Python files. AWS targets starting a Lambda instance within milliseconds of an event. Combine various services to build powerful applications that have the ability to automatically scale up and down and run in a highly available configuration with no servers to manage. A very helpful one is Mike Driscoll’s discussion of lambda on the Mouse vs Python blog. One method to accomplish this task would be to drag and drop the files and folders into the bucket manually via the AWS Management Console. To instantly track and visualize the performance of any AWS Lambda invocation, get started with IOpipe for free today. I have an S3 bucket. The -BucketName parameter is the only required parameter, although there are some other useful parameters available. Note that we cannot trigger Lambda from CloudTrail. js, Java, Python, and C#. All gists Back to GitHub. The Solution. AWS Lambda supports Python, and includes the Python API for AWS. You don’t need to configure a virtual server and environment to run an application you have written. Data produced on EC2 instances or AWS lambda servers often end up in Amazon S3 storage. How can I create a text file in S3 from Lambda using node? Is this. S3() If we take a look at our AWS Lambda code, before processing a chunk, we need to forward the stream to point. For example, when a user uploads a photo to a bucket, you might want Amazon S3 to invoke your Lambda function so that it reads the image and creates a thumbnail for the photo. def function_name(event, context): some statements return some_value. Deploy Go, Java,. It works fine from a regular Unix Terminal, but AWS Lambda doesn't seem to work well with Temporary Files. However, all of them are about how to call Lambda functions after writing to S3. NET Core) and Go. Go to the Triggers tab and make sure you've got that setup correctly and make sure your lambda function and S3 bucket are in the same region. I have a role associated with the lambda function to give it access to the bucket but it does not seem to work. Boto is a Python package that provides interfaces to AWS including Amazon S3. With the recent announcement of built-in support for Python in AWS Lambda functions (and upcoming access to VPC resources from Lambda), we’ve started considering increased use of Lambda for a number of applications.