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Duet AI by Google is an amazing tool for app developers. It uses advanced AI to make coding easier. You can talk to it like you talk to a friend, and it helps you write code, fix problems, and learn coding tricks. It's great for both experienced developers and beginners. Duet AI makes coding feel like a chat, making complex tasks simple and enjoyable.
This article guides you through leveraging Duet AI for the following tasks:
Automating AWS Load Balancers is essential for managing cloud infrastructure efficiently. This article delves into the importance of automation using the AWS Load Balancer controller and Ingress template. Whether you're new or experienced, grasping these configurations is vital to streamlining Load Balancer settings on Amazon Web Services, ensuring a smoother and more effective setup.
A high-level illustration of AWS Application Load Balancer with Kubernetes cluster
ExternalDNS is a handy tool in the Kubernetes world, making it easy to coordinate Services and Ingresses with different DNS providers. This tool automates the process, allowing users to manage DNS records dynamically using Kubernetes resources. Instead of being tied to a specific provider, ExternalDNS works seamlessly with various providers. ExternalDNS intelligently determines the desired DNS records, paving the way for effortless DNS management.
In this article, we'll explore what ExternalDNS is all about and why it's useful. Focusing on a specific situation — imagine a Kubernetes cluster getting updated and using Route 53 in AWS — we'll walk you through how ExternalDNS can automatically create DNS records in Route 53 whenever Ingresses are added. Come along for a simplified journey into DNS management and automation with ExternalDNS.
This article describes the steps involved in setting up Lambda Functions for accessing AWS S3 in a Cross Account scenario. The configuration process for this integration will be explained in detail, providing a comprehensive guide. By following these instructions, readers can gain an understanding of the requirements for Cross Account access to S3 using Lambda Functions. This article is aimed at AWS developers who are looking to improve their knowledge of Cross Account S3 access and want to learn how to configure Lambda Functions for this purpose. 
To create this solution, you must have the following prerequisites:
This article describes the design and creation of Amazon Virtual Private Network (VPC) using the VPC Designer tool and Cloud Formation templates. It also provides details of VPC Components such as Subnets, Route tables, Security Groups, Internet Gateway, NAT Gateway, VPC endpoints, Network Interfaces, Network Access Control Lists (ACLs), and VPC Peering.
Amazon Virtual Private Cloud (VPC) enables you to create your own dedicated, logically isolated virtual private network in your AWS account. This virtual network closely resembles a traditional network that you operate in your own data center (on-premises). It provides the ability to define and have full control over the virtual network environment, including security, connectivity, and resource deployment. VPC spans multiple availability zones in an AWS Region.
This article describes steps to automate AWS Aurora Global Database services using Cloud Formation, Lambda, and State Function. It also provides detailed steps to create a Global Database with sample code snippets. Some of the features detailed in the article are:
Amazon Aurora Global Database is designed for globally distributed cloud applications in AWS. It provides high availability and database resiliency by way of its ability to fail over to another AWS region. It allows a database to span multiple regions (AWS limits regions to a maximum of six), and it consists of one primary and up to five secondary regions in a global database cluster. Primary region can perform read and write operations, whereas the second region can perform read operations only. The way AWS facilitates this feature is by activating writer endpoints in the primary region and deactivating writer endpoints in secondary regions. Furthermore, Aurora replicates data from primary region to secondary regions, usually under a second.