aws rds create-db-cluster-parameter-group\--db-cluster-parameter-group-name pg14-blue-green\--db-parameter-group-family aurora-postgresql14\--description"Parameter group that contains logical replication settings for Aurora PG 14"aws rds modify-db-cluster-parameter-gro...
The Magma service deployment on AWS can be torn down by destroying the underlying infrastructure resources as well as all the CI/CD pipelines. This can be done via a single API call and it has been implemented using AWS Step Functions, where in the execution input you have the optio...
STEPFUNCTIONS_LAMBDA_ENDPOINT: URL to use as the Lambda service endpoint in Step Functions. By default this is the LocalStack Lambda endpoint. Use default to select the original AWS Lambda endpoint. LAMBDA_EXECUTOR: Method to use for executing Lambda functions. Possible values are: local: run La...
To use SQS, a fully managed distributed message queuing service, on LocalStack, run:% awslocal sqs create-queue --queue-name sample-queue { "QueueUrl": "http://sqs.us-east-1.localhost.localstack.cloud:4566/000000000000/sample-queue" }Learn more about LocalStack AWS services and using them ...
Amazon Translate is able to generate events into EventBridge upon job completion or failure. We use this capability to invoke a post-processing AWS Step Functions workflow. For instance, some customers must flag machine translated segments within an XLIFF file, so their translators can...
trainingacross multiple GPUs in multiple machines. For all of these activities, the deep learning desktop is preconfigured to use SageMaker. You can usejupyter-labnotebooks running on the desktop to launch SageMaker training jobs for distributed training in infrastructure automatically...
Again, one API call is all that it takes: I simply create a monitoring schedule for my endpoint, passing the constraints and statistics file for the baseline data set. Optionally, I could also pass preprocessing and postprocessing functions, should I want to tweak data a...
Sensitive data access can be managed throughout your organization by utilizing tags. This integration enables organizations to make data-driven decisions using Amazon Aurora with Privacera to enhance data access governance. Privacera is an AWS Data and Analytics Competency Partner and is available in...
Sensitive data access can be managed throughout your organization by utilizing tags. This integration enables organizations to make data-driven decisions using Amazon Aurora with Privacera to enhance data access governance. Privacera is an AWS Data and Analytics Competency Partner and is available in...
trainingacross multiple GPUs in multiple machines. For all of these activities, the deep learning desktop is preconfigured to use SageMaker. You can usejupyter-labnotebooks running on the desktop to launch SageMaker training jobs for distributed training in infrastructure automatically man...