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Cross account deployments using a Customer Managed KMS key

Xebia

In my previous blog I wrote about application pipelines. In this blog I will explain how you can achieve this. AWS::Region}.amazonaws.com AWS::Region}.amazonaws.com Action: kms:Decrypt Effect: Allow Principal: AWS: "*" Resource: "*" Condition: StringEquals: aws:PrincipalOrgID: !Ref

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Getting High Availability for IBM Db2 on AWS with Db2 Pacemaker Using Overlay IP – Part 2

Datavail

Now that we’ve covered what Pacemaker is and why it’s an excellent solution for IBM Db2 HA/DR in the cloud in Part 1 of this blog post, it’s time to talk about how to set it up. This example demonstrates the Pacemaker deployment process on AWS using overlay IP. Created db2_db2test2_eth0 resource. ls -alL /usr/lib/ocf/resource.d/heartbeat/db2*

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Using Vault to generate dynamic IAM users in AWS with Cloud Playground

Linux Academy

Vault manages secrets and protects sensitive data by providing a central location to store, access, and distribute secrets such as API keys, AWS IAM/STS credentials, SQL/NoSQL databases, certificates, SSH credentials, and more — all through a user interface, CLI, or HTTP API. Configure Vault and your AWS credentials. region=us-east-1.

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How ACG and LA Built the Future of Cloud Training

Linux Academy

” I know, because the ACG instructor I ate lunch with during the AWS Summit said so. November 2012: Linux Academy is Founded by Anthony James. What began as a humble blog in 2011, quickly transformed into a community of learners sharing resources. Aug 11, 2014: First AWS Live!Lab. That’s right.

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Scheduling Amazon DynamoDB Backups with Lambda, Python, and Boto3

Linux Academy

A simple way to achieve this is to use an Amazon CloudWatch Events rule to trigger an AWS Lambda function daily. In this hands-on AWS lab, you will write a Lambda function in Python using the Boto3 library. We’ll be using the AWS Management Console for this task. Select type of trusted entity: AWS service.

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Transform one-on-one customer interactions: Build speech-capable order processing agents with AWS and generative AI

AWS Machine Learning - AI

In addition to Amazon Bedrock, you can use other AWS services like Amazon SageMaker JumpStart and Amazon Lex to create fully automated and easily adaptable generative AI order processing agents. In this post, we show you how to build a speech-capable order processing agent using Amazon Lex, Amazon Bedrock, and AWS Lambda.

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Cloud assessment: an interview with CGS Cloud-Practice experts

Capgemini

Age may be indicative of a heavily customized application (COTS or in-house developed) that requires extensive resources and specialized expertise to maintain. Carl Forde: We partner with leading CSPs including Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, and others. Future blogs will explore our work further.

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