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I am exploring the Sagemaker Built-in algorithms, and I am curious to learn more about the details of the algorithms. However, I am surprised that it is hard to find any references for the research background and implementation details in the numerous documents and tutorials for particular algorithms. If such information exists somewhere, I would highly appreciate a pointer. Thanks a lot in advance!

We have app running in 3 AWS accounts (dev, test and production), we want the app to be able to send out transactional sms/voice/email alerts for weather conditions. We would also like it to use a local(ish) numbers based on clients locations, i.e. US clients get sms/voice from US number, UK clients from a UK number etc. Should I use sns/ses/voice directly or should we use pinpoint for this ? In any of these cases should we get the SNS long numbers out of the sandbox and into production first, and then use the same long numbers to get the voice out of the sandbox and into production ? I seem to have got myself into a catch-22 with support at the moment probably down to my understanding of the documentation. Can the long numbers (when in production) be used across 3 AWS accounts or do we need to create the long numbers per account i.e. end up with 3 numbers for US clients one in dev, one in test and one in production ? Thanks

Hi, the framework given by AWS for ESP32-DevkitC based OTA MQTT is crashing when internet disconnects. During crash, 6 out of 5 retry for TLS attempts is seen in serial log. Please suggest how to overcome this. If any other info required please let me know.

In local, I was able to connect to the container through the docker exec command. However, fargate is a serverless service, so I wonder if it can connect to the container.

I am working on a requirement, where we need to do some action (Email Processing (out of scope of this requirement)), whenever we receive an email in Client's Gmail or Outlook account. Since we don't own these domains, so setting up Email Receiving Pipelines via SES (https://aws.amazon.com/getting-started/hands-on/setup-email-receiving-pipeline/faq/) is out of question here. The solution that we thought of for this problem statement is Setting up a Gmail push notifications to hit AWS Api Gateway, which internally would call AWS Lambda for inserting data in SQS. Changes involved are :- AWS: 1. Create an SQS Queue. 2. Create an AWS Lambda inserting data in SQS. 3. Create an API Gateway invoking AWS Lambda. Google Cloud: 1. Create a Pub / Sub topic. 2. Create a subscription for Api Gateway url. 3. Create a watch on Gmail. The watcher would invoke topic on any change in Gmail. Can someone please validate above approach?

I have two different Braket task ARNs that are pending, but they are not appearing on the dashboard. They are region specific, but they are not appearing on that region. Searching for the ARN does not return a result either.

I'm trying to run a dedicated server using Windows Server 2019. When I tell the server application to begin it gets stuck on a loading screen and never starts. Any ideas?

We would like to control which services are available for use in which accounts and regions while still being able to review everything: - Allow ReadOnly across all services in all regions - Allow Write on specified services in certain regions We are aware of the general policy to [restrict actions not in specific regions](https://docs.aws.amazon.com/organizations/latest/userguide/orgs_manage_policies_scps_examples_general.html#example-scp-deny-region) but this is too restrictive and results in unnecessary confusion when users experience permission errors on various service dashboards. Thus far we have been unable to construct an SCP, or combination of SCPs, that provide the intended effect given [the attachment and size limits.](https://docs.aws.amazon.com/organizations/latest/userguide/orgs_reference_limits.html#min-max-values) Is what we are looking for even possible with Service Control Policies alone? We would like to avoid: - Managing this via User/Role Permissions - Having "Bypass" Roles as shown in the documented example above.

Hi Dears, I am building ML model using DeepAR Algorithm. I faced this error while i reached to this point : Error : ClientError: An error occurred (UnknownOperationException) when calling the CreateHyperParameterTuningJob operation: The requested operation is not supported in the called region. ------------------- Code: from sagemaker.tuner import ( IntegerParameter, CategoricalParameter, ContinuousParameter, HyperparameterTuner, ) from sagemaker import image_uris container = image_uris.retrieve(region= 'af-south-1', framework="forecasting-deepar") deepar = sagemaker.estimator.Estimator( container, role, instance_count=1, instance_type="ml.m5.2xlarge", use_spot_instances=True, # use spot instances max_run=1800, # max training time in seconds max_wait=1800, # seconds to wait for spot instance output_path="s3://{}/{}".format(bucket, output_path), sagemaker_session=sess, ) freq = "D" context_length = 300 deepar.set_hyperparameters( time_freq=freq, context_length=str(context_length), prediction_length=str(prediction_length) ) Can you please help in solving the error? I have to do that in af-south-1 region. Thanks Basem hyperparameter_ranges = { "mini_batch_size": IntegerParameter(100, 400), "epochs": IntegerParameter(200, 400), "num_cells": IntegerParameter(30, 100), "likelihood": CategoricalParameter(["negative-binomial", "student-T"]), "learning_rate": ContinuousParameter(0.0001, 0.1), } objective_metric_name = "test:RMSE" tuner = HyperparameterTuner( deepar, objective_metric_name, hyperparameter_ranges, max_jobs=10, strategy="Bayesian", objective_type="Minimize", max_parallel_jobs=10, early_stopping_type="Auto", ) s3_input_train = sagemaker.inputs.TrainingInput( s3_data="s3://{}/{}/train/".format(bucket, prefix), content_type="json" ) s3_input_test = sagemaker.inputs.TrainingInput( s3_data="s3://{}/{}/test/".format(bucket, prefix), content_type="json" ) tuner.fit({"train": s3_input_train, "test": s3_input_test}, include_cls_metadata=False) tuner.wait()

Hi everyone. I am using node to programmatically create segments in pinpoint.. sdk of createImportJob method needs parameter S3 ("S3 file localed")..however I would like to upload directly without uploading to S3 first like console interface does.. Is there some option? Thanks

Since today we are having this error, the DBT/SQL was not touched I'm receiving errors in many processes with this same message. A full refresh on DBT clears it, but when the first incremental runs, it starts to fail again with the same error, "context" is not helping. I ran the query manually and had no trouble at all. It's a query that creates a table, a delete on the destination table (with a where), and inserts into it (managed by DBT that wasn't modified for more than 6 months, the query runs daily and also wasn't changed on the last months). The only thing that I think changed was the Redshift version via an auto-maintenance yesterday, but can't do a rollback to validate, or can I? I was in "current" version on maintenance, just switched to "trailing", now I'm on 1.0.38361, and can't find the changelog for that version. ``` 20:26:44 | 20:26:44 | 1 of 1 START incremental model xxxxxx......... [RUN] 20:26:51 | 1 of 1 ERROR creating incremental model xxxxxx [ERROR in 6.44s] 20:26:51 | 20:26:51 | Finished running 1 incremental model in 8.55s. Completed with 1 error and 0 warnings: Database Error in model xxxxx (models/xxxxx.sql) Assert DETAIL: ----------------------------------------------- error: Assert code: 1000 context: size >= 0 - size=-2, 0=0. query: 62706875 location: tbl_trans.cpp:867 process: padbmaster [pid=70356] ----------------------------------------------- compiled SQL at target/run/xxxxx/xxxxx.sql Done. PASS=0 WARN=0 ERROR=1 SKIP=0 TOTAL=1 ``` Any idea of what can be happening? Thanks!

I set up an AWS connect instance, claimed a number and set up users and queues with a caller Id. When an agent makes a call the customer doesn't see the specified caller id, instead gets "Suspected Spam". The calls are made to Australia, either from Australia or from the Philippines.

I'm unable to delete the snapshot of a terminated instance. The instance is a very old t1.micro for which the Volume has also been deleted. How do I get rid of the snapshot so that this instance incurs no additional charges?

Hi, After I upgraded the lambda runtime to nodejs16 and run AWS codepipeline which failed with the following error: Resource handler returned message: "Invalid request provided: The function timeout is larger than the maximum allowed for functions that are triggered by a CloudFront event: 60 Max allowed: 30 Function: arn:aws:lambda:us-east-1:xxxxxxxxxxxx:function:doc-check:55 (Service: CloudFront, Status Code: 400, Request ID: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx)" (RequestToken: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxx, HandlerErrorCode: InvalidRequest) Can anyone help me fix it please? Many thanks Del

We are interested to use AWS FSx for Windows plus install FSx File Gateway at our main site. There will be multiple users using the File System, some from within the site and others will be accessing FSx directly from the internet. Our concern is whether a change made from a user on-site will be synchronized immediately and be visible to other users, or if there is a delay. What is the minimum time does the FSx Gateway send its changes to the main AWS FSx? Is it near real-time, or more (like minutes)? Does a "write" stay on the FSx Gateway cache for a while or is it written immediately to the FSx? Thanks in advance.

Has anyone experienced their **ACCOUNT BEING HACKED and CHARGED for it by AWS?** I experienced a major breech, and suddenly got a bill for over $18,000!!! I was reassured by AWS the entire time that I will not be paying this while spending HOURS following all their steps for securing my account, only to be sent an email MONTHS later that **I need to pay over $4,000**. I am in total shock over this, and wondering if anyone has experienced something similar - what did you do?

I have some IoT devices that send raw data which I am planning to store in Kafka and then process it with the consumer and save it to a database. Scenario: IoT devices send sensor data in form of packets (1 packet per sec) and you need 10 raw packets to decode its value (I have a C binary that takes 10 packets, I can enforce in IoT to send 10 packets combined as a single packet but I want IoT to focus on single packet only so that in future I can modify the algorithm to work for 20, 30 packets on the cloud). If I use the same topic for all IoT then consumers have to wait until it has received 10 packets to start processing, which I am thinking can cause some problems. (Problem of filtering packet of IoT, as single packets, can mix up in single topic) Issues: Initially, I thought of creating a single topic with partitions for each IoT device, but Kafka doesn't support dynamic partitions. (More IoT devices can be added or removed during runtime.) Another solution can be to create a topic for each IoT device with 1 partition. Also, the above approach of 1 topic for each IoT device may enforce to use of one consumer for each IoT device added (can this be improved?) I am looking for a better and more efficient implementation if possible for this problem. The number of IoT devices is dynamic and can go up to 100+.

### Purpose & Context I am trying to enable https for my lightsail instance, to do it I am following this "how to" document: https://lightsail.aws.amazon.com/ls/docs/en_us/articles/amazon-lightsail-enabling-https-on-wordpress ### Problem When bncert-tool ask me about the domain, I enter it and it shows me: Warning: The domain 'mydomain.com' does not resolve, please fix its DNS entries or remove it. when I enter my domain in the navigator it works: it jumps into my wordpress instance. ### Question What am I missing? What should I do to fix it? many thanks in advance