Welcome to AWS re:Post

Earlier this year I switched my RDS database from EC2-Classic to a VPC. While I've been able to read/write to the database through my Localhost connection, I am now in the process of replacing my old EC2 connections (I haven't been hosting a web app, but have used EC2 in the past when I've needed to run long and potentially slow PHP scripts). It took a couple of tries, but I finally created a Linux EC2 instance that went through the VPC and I was able to connect via WinSCP and Putty. I changed the file permissions and transferred my code over. I tried to reconnect via Putty and am getting a "Network error: Connection refused" message. When I try to login to WinSCP, I'm getting a "Network Error Connection to ---- Refused." I tried stopping and restarting my EC2 connection and using the new public IP address and I'm getting the same errors. What do you think changed so that I can no longer access this connection? Should I just try the whole process again from the start?lg...

I have created a docker image which has Entrypoint as processing.py. This script is taking data from /opt/ml/processing/input and after processing putting it /opt/ml/processing/output folder. For processing the data I should put the file in /opt/ml/processing/input from s3 and then pick processed file from /opt/ml/processing/output into S3. Following script in sagemaker is doing it properly: from sagemaker.processing import Processor, ProcessingInput, ProcessingOutput import sagemaker input_data = 's3://sagemaker-ap-south-1-057036842446/sagemaker/Data/Training/Churn_Modelling.csv' output_dir = 's3://sagemaker-ap-south-1-057036842446/sagemaker/Outputs/' image_uri = '057036842446.dkr.ecr.ap-south-1.amazonaws.com/aws-docker-repo:latest' aws_role = sagemaker.get_execution_role() processor = Processor(image_uri= image_uri, role=aws_role, instance_count=1, instance_type="ml.m5.xlarge") processor.run(inputs=[ProcessingInput( source=input_data, destination='/opt/ml/processing/input')], outputs=[ProcessingOutput(source='/opt/ml/processing/output', destination=output_dir)] ) Could someone please guide how this can be executed with lambda function? It is not recognizing sagemaker package, second there is a challenge in placing file before the script execution and pick processed files. I am trying codepipeline to automate this operation.lg...

Hi folks Anyone are experienced lost packets from a ec2 instance in us-east2 region to Colombia? A Bogota endpoint? For example 190.131.203.26 Greetingslg...

**Environment:** Greengrass V2 Nucleus (2.9.1) running as Docker container. We developed one `aws.greengrass.generic` component and have successfully published 4 versions (1.0.0, 1.0.1, 1.0.2 and 1.0.3). All three versions are published, displayed in Greengrass V2 console and artifacts correctly available in the S3 bucket. ``` [2022-11-26 17:32:54] INFO - Getting project configuration from gdk-config.json [2022-11-26 17:32:54] INFO - Found component recipe file 'recipe.yaml' in the project directory. [2022-11-26 17:32:54] INFO - Found credentials in shared credentials file: ~/.aws/credentials [2022-11-26 17:32:55] INFO - Using '1.0.3' as the next version of the component '<my-component>' to create. [2022-11-26 17:32:55] INFO - Publishing the component '<my-component>' with the given project configuration. [2022-11-26 17:32:55] INFO - Uploading the component built artifacts to s3 bucket. [2022-11-26 17:32:55] INFO - Uploading component artifacts to S3 bucket: <my-bucket>. If this is your first time using this bucket, add the 's3:GetObject' permission to each core device's token exchange role to allow it to download the component artifacts. For more information, see https://docs.aws.amazon.com/greengrass/v2/developerguide/device-service-role.html. [2022-11-26 17:32:56] INFO - Successfully created the artifacts bucket '<my-bucket>' in region 'us-east-1' [2022-11-26 17:32:58] INFO - Updating the component recipe <my-component>-1.0.3. [2022-11-26 17:32:58] INFO - Creating a new greengrass <my-component>-1.0.3 [2022-11-26 17:32:58] INFO - Created private version '1.0.3' of the component in the account.'<my-component>'. ``` **However**, we apparently can only deploy version `1.0.0` successfully. All other versions fail. ``` 2022-11-26T20:19:01.427Z [INFO] (pool-2-thread-47) com.aws.greengrass.componentmanager.ComponentManager: prepare-package-start. {packageIdentifier=<my-component>-v1.0.0} ``` When we try to deploy *ANY* newer version (e.g. `1.0.3`), we always get this error: ``` 2022-11-26T20:36:10.987Z [ERROR] (pool-2-thread-51) com.aws.greengrass.deployment.DeploymentService: Error occurred while processing deployment. {deploymentId=3a4cb705-db16-4b5b-94b4-30e53f0edc9b, serviceName=DeploymentService, currentState=RUNNING} java.util.concurrent.ExecutionException: com.aws.greengrass.componentmanager.exceptions.NoAvailableComponentVersionException: No local or cloud component version satisfies the requirements Check whether the version constraints conflict and that the component exists in your AWS account with a version that matches the version constraints. If the version constraints conflict, revise deployments to resolve the conflict. Component <my-component> version constraints: thing/<thing-name> requires =1.0.3. ... 2022-11-26T20:36:20.733Z [ERROR] (pool-2-thread-9) com.aws.greengrass.deployment.DeploymentService: Deployment task failed with following errors. {DeploymentId=arn:aws:greengrass:us-east-1:<account-id>:configuration:thing/<my-thing>:5, detailed-deployment-status=FAILED_NO_STATE_CHANGE, deployment-error-types=[REQUEST_ERROR], GreengrassDeploymentId=3a4cb705-db16-4b5b-94b4-30e53f0edc9b, serviceName=DeploymentService, currentState=RUNNING, deployment-error-stack=[DEPLOYMENT_FAILURE, NO_AVAILABLE_COMPONENT_VERSION, COMPONENT_VERSION_REQUIREMENTS_NOT_MET]} com.aws.greengrass.componentmanager.exceptions.NoAvailableComponentVersionException: No local or cloud component version satisfies the requirements Check whether the version constraints conflict and that the component exists in your AWS account with a version that matches the version constraints. If the version constraints conflict, revise deployments to resolve the conflict. Component <my-component> version constraints: thing/<my-thing> requires =1.0.3. at com.aws.greengrass.componentmanager.ComponentManager.negotiateVersionWithCloud(ComponentManager.java:229) at com.aws.greengrass.componentmanager.ComponentManager.resolveComponentVersion(ComponentManager.java:164) at com.aws.greengrass.componentmanager.DependencyResolver.lambda$resolveDependencies$2(DependencyResolver.java:125) at com.aws.greengrass.componentmanager.DependencyResolver.resolveComponentDependencies(DependencyResolver.java:221) at com.aws.greengrass.componentmanager.DependencyResolver.resolveDependencies(DependencyResolver.java:123) at com.aws.greengrass.deployment.DefaultDeploymentTask.lambda$call$2(DefaultDeploymentTask.java:125) ``` As stated, the component is available in Greengrass V2 console and artifacts correctly published in S3.lg...

The [AWS documentation](https://docs.aws.amazon.com/systems-manager/latest/userguide/ps-integration-lambda-extensions.html#sample-commands-ps) for the Parameters and Secrets Lambda Extension states: ``` To make a call using the Amazon Resource Name (ARN) for a parameter, make an HTTP GET call similar to the following. GET http://localhost:port/systemsmanager/parameters/get?name=arn:aws:ssm:us-east-1:123456789012:parameter/MyParameter ``` however these requests return a 400 stating the parameter name is invalid. Here's a quick example to demonstrate the successful request using the parameter name, and the failed request using the parameter ARN: ```py import json import os from botocore.vendored import requests def lambda_handler(event, context): name_url = 'http://localhost:2773/systemsmanager/parameters/get?name=test-param' arn_url = 'http://localhost:2773/systemsmanager/parameters/get?name=arn:aws:ssm:us-east-2:{ACCOUNT_ID}:parameter/test-param' headers = {'X-Aws-Parameters-Secrets-Token': os.environ['AWS_SESSION_TOKEN']} name_resp = requests.get(name_url, headers=headers) print(f'NAME RESPONSE: {name_resp.status_code} > {name_resp.text}') arn_resp = requests.get(arn_url, headers=headers) print(f'ARN RESPONSE: {arn_resp.status_code} > {arn_resp.text}') ``` and the output: ``` NAME RESPONSE: 200 > {"Parameter":{"ARN":"arn:aws:ssm:us-east-2:{ACCOUNT_ID}:parameter/test-param","DataType":"text","LastModifiedDate":"2022-11-26T02:25:14.669Z","Name":"test-param","Selector":null,"SourceResult":null,"Type":"SecureString","Value":"AQICAH....=","Version":2},"ResultMetadata":{}} ARN RESPONSE: 400 > an unexpected error occurred while executing request [AWS Parameters and Secrets Lambda Extension] 2022/11/26 18:09:36 ERROR GetParameter request encountered an error: operation error SSM: GetParameter, https response error StatusCode: 400, RequestID: {REQUEST_ID}, api error ValidationException: Invalid parameter name. Please use correct syntax for referencing a version/label <name>:<version/label> ``` The docs also state: ``` When using GET calls, parameter values must be encoded for HTTP to preserve special characters. ``` however the error still occurs whether the ARN colons and/or slash are URL-encoded or not like so: ``` http://localhost:2773/systemsmanager/parameters/get?name=arn%3Aaws%3Assm%3Aus-east-2%3A{ACCOUNT_ID}%3Aparameter/test-param http://localhost:2773/systemsmanager/parameters/get?name=arn%3Aaws%3Assm%3Aus-east-2%3A{ACCOUNT_ID}%3Aparameter%2Ftest-param ``` Am I missing something here or is the documentation incorrect in that an ARN can be used for these requests?lg...

Hi there, I need advice on moving archive MSK topic data to an S3 bucket. I'm currently doing this with MSK connect with Confluence custom plugin running two tasks. We have ~163GB of data in MSK, and for the last 48 hours, it has only copied ~3GB; this will cost us a lot of money if we leave it like this, considering msk connect running cost and S3 PUT charges. Is there a better way to migrate the data that is cost-effective? Below is the msk Connector configuration should in case I missed out anything ``` connector.class=io.confluent.connect.s3.S3SinkConnector s3.region=### flush.size=1 schema.compatibility=NONE tasks.max=2 topics=##### format.class=io.confluent.connect.s3.format.json.JsonFormat partitioner.class=io.confluent.connect.storage.partitioner.DefaultPartitioner value.converter=org.apache.kafka.connect.storage.StringConverter storage.class=io.confluent.connect.s3.storage.S3Storage s3.bucket.name=######### key.converter=org.apache.kafka.connect.storage.StringConverter ``` Thankslg...

When it is all said and done, I will have many Lightsail servers, each with a minimum of 5 TB of transfer quota. Currently I have a 5,6, and 7 TB plans. That is 18 TB total, but the current hosting plans are for more compute power requirements than transfer needs at this time. However, transfers rates are expected to swell. Underpaying for data transfer on some and hugely overpaying on others seems unsportsmanlike! Can’t all these transfer quotas be aggregated / combined so I don’t get clobbered with overages on the public facing server?lg...

From [AWS IoT Greengrass FAQs](https://aws.amazon.com/greengrass/faqs/?nc1=h_ls), it said AWS IoT Greengrass discovery is available on the AWS IoT Device SDK via C++, Node.js, Java, and Python 2.7, 3.7, and 3.8. However, my application is used **JavaScript and React**. Then, I found [aws.greengrass.labs.LocalWebServer](https://github.com/awslabs/aws-greengrass-labs-local-web-server). Is it possible for me to use this aws.greengrass.labs.LocalWebServer deploy the application on Greengrass. Rather than this aws.greengrass.labs.LocalWebServer, **do I have another way to deploy my application on AWS IoT Greengrass**? P.S. I am using Ubuntu, but I am **unable** to download docker. **Thank you very much!**lg...

Can I build a react web app on AWS Lambda? What should I configure so that I can host the web and see it on the web browser?lg...

How to package and automate License software and do versioning based on License software or free software in Windows Ec2 instance with AWS? **Tools Example** like: AWS Image Builder, HASI Corp Packer. I see very less example on Windows Instance on License software Packaging and versioning. ******Please advise****.** with Step by step documents and videos. **Reference Link**: **Packer**: https://developer.hashicorp.com/packer/tutorials/integrations/aws-windows-image **AWS Image Builder:- ** https://aws.amazon.com/image-builder/lg...

I have developed a react project run by npm start and I would like to deploy it to AWS Iot greengrass. I initialized my component with the component template,and configure the gdk-config and recipe. But when I am building the component of my web application by gdk component build, it said the artifact file is not found. I have placed my project in the s3 bucket with a pth similar to this artifacts/componentName/componentVersion/ and tried placing my project in the src directory and a artifacts directory, but the problem consist. How can I solve this problem? lg...

How to publish a component and for a JS web project run by npm start? I tried upload my project.zip to AWS S3 and create the component using gdk component init --template HelloWorld --language python but the deploment failed. What can be the problem? And if the deployment success,where will be the web hosted? lg...

I can't change configuration. Can't clone. Can't reboot. I was able to reboot the individual EC2 instances but that didn't helplg...

Two questions: 1) When an EC2 instance is started, what actually provides the IP addresses that are assigned to it? 2) How can I see the public IP address assigned to an EC2 instance, from within (i.e. after connecting) the EC2 instance? When an EC2 is started, I can see the public IP address that is assigned to it, simply by looking in the Management Console. I can also see the Private IP assigned to that same EC2 instance, once I connect to it, and issue the "ip a s" command - I'm running a RHEL OS. Is there a command that I can run/execute within Linux that will display the public IP address associated with that EC2 instance?lg...

have created an Amazon EC2 instance with AMI - Ubuntu Server 22.04 LTS (Free Tier) and try to install AWS CodeDeploy Agent into it. I am following the official documentation from Amazon to install CodeDeploy agent into the Ubuntu server. [https://docs.aws.amazon.com/codedeploy/latest/userguide/codedeploy-agent-operations-install-ubuntu.html](AWS Documentation Link) I have connected the EC2 instance with SSH Keypairs and run the following commands: ``` sudo apt update sudo apt install ruby-full sudo apt install wget wget https://aws-codedeploy-ap-south-1.s3.ap-south-1.amazonaws.com/latest/install chmod +x ./install sudo ./install auto ``` In the last command, I got the following error message: ``` I, [2022-11-25T20:22:45.262298 #4303] INFO -- : Starting Ruby version check. E, [2022-11-25T20:22:45.262740 #4303] ERROR -- :Current running Ruby version for root is 3.0.2, but Ruby version 2.x needs to be installed. E, [2022-11-25T20:22:45.262959 #4303] ERROR -- : If you already have the proper Ruby version installed, please either create a symlink to /usr/bin/ruby2.x, E, [2022-11-25T20:22:45.263173 #4303] ERROR -- : or run this install script with right interpreter. Otherwise please install Ruby 2.x for root user. E, [2022-11-25T20:22:45.263378 #4303] ERROR -- : You can get more information by running the script with --help option. ``` Please let me know if there is any other hacks, I should employ to install AWS CodeDeploy agent in the EC2 instance with with AMI - Ubuntu Server 22.04 LTS (Free Tier). Thanks in advance!!lg...

Hello, I have created sagemaker endpoint by following https://github.com/huggingface/notebooks/blob/main/sagemaker/20_automatic_speech_recognition_inference/sagemaker-notebook.ipynb and this is failing with error ""An error occurred (ModelError) when calling the InvokeEndpoint operation: Received client error (413) from primary and could not load the entire response body"". The predict function returning me following error but CW log does not have any error details for the endpoint. ``` ModelError Traceback (most recent call last) /tmp/ipykernel_16248/2846183179.py in 2 # audio_path = "s3://ml-backend-sales-call-audio/sales-call-audio/1279881599154831602.playback.mp3" 3 audio_path = "/home/ec2-user/SageMaker/finetune-deploy-bert-with-amazon-sagemaker-for-hugging-face/1279881599154831602.playback.mp3" ## AS OF NOW have stored locally in notebook instance ----> 4 res = predictor.predict(data=audio_path) 5 print(res) ~/anaconda3/envs/amazonei_pytorch_latest_p37/lib/python3.7/site-packages/sagemaker/predictor.py in predict(self, data, initial_args, target_model, target_variant, inference_id) 159 data, initial_args, target_model, target_variant, inference_id 160 ) --> 161 response = self.sagemaker_session.sagemaker_runtime_client.invoke_endpoint(**request_args) 162 return self._handle_response(response) 163 ~/anaconda3/envs/amazonei_pytorch_latest_p37/lib/python3.7/site-packages/botocore/client.py in _api_call(self, *args, **kwargs) 493 ) 494 # The "self" in this scope is referring to the BaseClient. --> 495 return self._make_api_call(operation_name, kwargs) 496 497 _api_call.name = str(py_operation_name) ~/anaconda3/envs/amazonei_pytorch_latest_p37/lib/python3.7/site-packages/botocore/client.py in _make_api_call(self, operation_name, api_params) 912 error_code = parsed_response.get("Error", {}).get("Code") 913 error_class = self.exceptions.from_code(error_code) --> 914 raise error_class(parsed_response, operation_name) 915 else: 916 return parsed_response ModelError: An error occurred (ModelError) when calling the InvokeEndpoint operation: Received client error (413) from primary and could not load the entire response body. See https://us-east-1.console.aws.amazon.com/cloudwatch/home?region=us-east-1#logEventViewer:group=/aws/sagemaker/Endpoints/asr-facebook-wav2vec2-base-960h-2022-11-25-19-27-19 in account xxxx for more information. ` ```lg...

Following along with this [blog post](https://aws.amazon.com/blogs/big-data/develop-and-test-aws-glue-version-3-0-jobs-locally-using-a-docker-container/) I'm attempting to debug/breakpoint my glue tasks running in VS Code using `amazon/aws-glue-libs:glue_libs_3.0.0_image_01`. I can get up to the point where the job executes and I can step through the code right up until the point I try and connect to RDS to fetch data. As soon as I do I get back ``` An error occurred while calling o47.getDynamicFrame. : java.lang.ClassNotFoundException: com.mysql.cj.jdbc.Driver at java.net.URLClassLoader.findClass(URLClassLoader.java:387) at java.lang.ClassLoader.loadClass(ClassLoader.java:418) at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352) at java.lang.ClassLoader.loadClass(ClassLoader.java:351) at java.lang.Class.forName0(Native Method) at java.lang.Class.forName(Class.java:264) at com.amazonaws.services.glue.util.JDBCUtils.loadDriver(JDBCUtils.scala:214) at com.amazonaws.services.glue.util.JDBCUtils.loadDriver$(JDBCUtils.scala:212) at com.amazonaws.services.glue.util.MySQLUtils$.loadDriver(JDBCUtils.scala:490) at com.amazonaws.services.glue.util.JDBCWrapper.getRawConnection(JDBCUtils.scala:746) at com.amazonaws.services.glue.JDBCDataSource.getPrimaryKeys(DataSource.scala:1006) at com.amazonaws.services.glue.JDBCDataSource.$anonfun$getJdbcJobBookmark$1(DataSource.scala:878) at scala.collection.MapLike.getOrElse(MapLike.scala:131) at scala.collection.MapLike.getOrElse$(MapLike.scala:129) at scala.collection.AbstractMap.getOrElse(Map.scala:63) at com.amazonaws.services.glue.JDBCDataSource.getJdbcJobBookmark(DataSource.scala:878) at com.amazonaws.services.glue.JDBCDataSource.getDynamicFrame(DataSource.scala:953) at com.amazonaws.services.glue.DataSource.getDynamicFrame(DataSource.scala:99) at com.amazonaws.services.glue.DataSource.getDynamicFrame$(DataSource.scala:99) at com.amazonaws.services.glue.SparkSQLDataSource.getDynamicFrame(DataSource.scala:714) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:282) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:238) at java.lang.Thread.run(Thread.java:750) ``` I'm not sure how to solve this problem. I see in the blog post its mentioned that I can pass in extra libraries, however when I look in `/home/glue_user/aws-glue-libs/jars` I can see a jar named `mssql-jdbc-7.0.0.jre8.jar` so I'm not so sure thats the problem. I should mention this job runs without a problem when deployed to AWS. I'm currently starting up the `amazon/aws-glue-libs:glue_libs_3.0.0_image_01` using a very basic docker-compose file ``` version: "3.8" services: glue: container_name: "glue-local-development" image: amazon/aws-glue-libs:glue_libs_3.0.0_image_01 ports: - "4040:4040" - "18080:18080" environment: - DISABLE_SSL=true - AWS_PROFILE=my_profile volumes: - ~/.aws:/home/glue_user/.aws - ${PWD}:/home/glue_user/workspace/ stdin_open: true ``` Then connecting as per the blog post. Is there something else I have to do here? I don't think I should have to manually load in the mysql jars? I've been stuck at this point for awhile so would really appreciate any help or suggestions people have Edit: Interestingly when I attempt to run `amazon/aws-glue-libs:glue_libs_2.0.0_image_01` it fails with a very similar but different error ``` : An error occurred while calling o49.getDynamicFrame. : java.io.FileNotFoundException: (No such file or directory) at java.io.FileInputStream.open0(Native Method) at java.io.FileInputStream.open(FileInputStream.java:195) at java.io.FileInputStream.<init>(FileInputStream.java:138) at com.amazonaws.glue.jdbc.commons.CustomCertificateManager.importCustomJDBCCert(CustomCertificateManager.java:127) at com.amazonaws.services.glue.util.JDBCWrapper$.connectionProperties(JDBCUtils.scala:947) at com.amazonaws.services.glue.util.JDBCWrapper.connectionProperties$lzycompute(JDBCUtils.scala:734) at com.amazonaws.services.glue.util.JDBCWrapper.connectionProperties(JDBCUtils.scala:734) at com.amazonaws.services.glue.util.JDBCWrapper.getRawConnection(JDBCUtils.scala:747) at com.amazonaws.services.glue.JDBCDataSource.getPrimaryKeys(DataSource.scala:996) at com.amazonaws.services.glue.JDBCDataSource$$anonfun$33.apply(DataSource.scala:868) at com.amazonaws.services.glue.JDBCDataSource$$anonfun$33.apply(DataSource.scala:868) at scala.collection.MapLike$class.getOrElse(MapLike.scala:128) at scala.collection.AbstractMap.getOrElse(Map.scala:59) at com.amazonaws.services.glue.JDBCDataSource.getJdbcJobBookmark(DataSource.scala:868) at com.amazonaws.services.glue.JDBCDataSource.getDynamicFrame(DataSource.scala:943) at com.amazonaws.services.glue.DataSource$class.getDynamicFrame(DataSource.scala:97) at com.amazonaws.services.glue.SparkSQLDataSource.getDynamicFrame(DataSource.scala:707) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:282) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:238) at java.lang.Thread.run(Thread.java:750) ```lg...

Has anyone found where Amazon Connect historical and real-time reports are stored, S3 or otherwise? For example, I have a historical report for agents status that runs every 30 minutes, and stores what state the agent was in i.e. available, after call for every 30 minutes. This is exactly what I want in Athena to build an every 30 minute query. However, currently my reporting is based on CTR and agent status changes via Kinesis and Quicksight into Athena, meaning I can't build a report every 30 minutes if say in a 2hr block four agents were online yet no calls came in and they never changed their status. Yet, in my historical report that data is there, but I don't see an S3 bucket where this is stored. Johnlg...