Deploying Dart functions to AWS Lambda enables you to utilize them not only within AWS Lambda but also integrate them with services like Amazon API Gateway, allowing you to leverage them in Flutter applications as well. This unified codebase in Dart offers great convenience. - Source: dev.to / about 1 month ago

Moreover, integrating rate limiting can thwart DDoS attacks, and schema validation can prevent malformed requests, ensuring only legitimate and well-formed traffic reaches your serverless functions. Tools like Amazon API Gateway, Azure API Management, and Google Cloud Endpoints offer these capabilities, allowing you to set up custom authorization workflows and request validation rules that align with your security... - Source: dev.to / 2 months ago

Amazon API Gateway is a fully managed service by Amazon Web Services that provides customers with the capability to create, publish, maintain, monitor, and secure APIs at any scale. API Gateway is using regional endpoints that can be deployed in multi-AWS Regions to enable reduced latency. - Source: dev.to / 2 months ago

Amazon API Gateway receives the message from the WhatsApp webhook (previously authenticated). - Source: dev.to / 3 months ago

This is where we turn to the tried and true Amazon API Gateway and its many integrations. Using API Gateway, we can use services like AWS Lambda or AWS Step Functions to run logic against the payload that we receive. We can also use these integrations to return responses back to the user. - Source: dev.to / 7 months ago

Infrastructure as code (IaC) allows DevOps teams to define the end state of the required infrastructure and deploy it using a template-based approach. Public cloud platforms each provide proprietary IaC tools, such as Azure (ARM Templates and Bicep), AWS (CloudFormation), and GCP (Deployment Manager). - Source: dev.to / 12 months ago

Start with the google docs https://cloud.google.com/deployment-manager/docs. Source: about 1 year ago

Cloud Deployment Manager: Templated infrastructure deployment 🔗Link 🔗Link. - Source: dev.to / almost 2 years ago

When exploring options on how to deploy the architecture we briefly considered Google Cloud Deployment Manager. Upon further investigation we were led to use Terraform instead. It was evident that Cloud Deployment Manager did not have the necessary support for the resource types that we were trying to create. Many of the supported resource types were still listed in beta. - Source: dev.to / almost 2 years ago

Deployment Manager templates give declarative language choices rather than imperative ones; this means that DevOps teams may tell Deployment Manager what a final deployment should look like, and GCP will automatically utilize the tools and procedures. When an excellent deployment method is created, it is saved so that it may be repeated and scaled on demand. Source: almost 2 years ago