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You can deploy a modern web application by choosing a hosting model, preparing the app and its data, automating deployment, configuring its domain and security, then verifying and monitoring the live service. These five steps are a planning framework—not a shared workflow across AWS, Azure, and Google Cloud. Commands, service settings, pricing, and security defaults depend on the provider and workload.
1. Choose a hosting model that fits the application
Start by identifying what you are deploying and how much infrastructure you want to operate. A static site, a conventional web application, and a containerized service have different hosting needs. Also decide whether you need direct control over servers or would rather use a managed platform.
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Google Cloud documents options ranging from static hosting and virtual machines to Kubernetes and serverless Cloud Run. AWS App Runner can deploy from source code or a supplied container image, while Azure App Service can host supported code or containers. These are different services and operating models, not interchangeable steps. Google Cloud’s overview, last reviewed February 18, 2026, advises newcomers to start with technology they already know: Google Cloud hosting options.
- Static assets: Consider static hosting when the site is made up of files that do not need a continuously running application server.
- Managed application platform: Consider a service such as App Runner or App Service when you want to deploy supported code or a container without managing every server detail.
- Containers, Kubernetes, or virtual machines: These may suit workloads that need their respective deployment or control models, but bring their own operational responsibilities.
Before selecting a service, note the runtime, traffic expectations, region and availability needs, data sensitivity, and whether the app requires durable file storage or a database. Estimate cost only after choosing a service, region, resource configuration, and expected usage; Google Cloud notes that costs vary by implementation and points users to service pricing and its calculator.
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2. Prepare the application and its data
Make the app’s build and run requirements explicit before connecting it to a cloud service. Confirm the supported runtime or container image, build command, start command, configuration values, and any database, object storage, or other service the app needs. Separate environment-specific settings from source code so development and production do not accidentally share inappropriate values.
Plan data persistence separately from application compute. Cloud Run containers are ephemeral, so files written to a container’s local filesystem should not be treated as durable application data. Google Cloud identifies services such as Cloud Storage, Firestore, and Cloud SQL as options for persistent data, depending on what the application needs. Azure’s App Service example likewise connects the app to SQL Database through configured application settings: Microsoft’s basic App Service web application architecture.
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- Use a database for structured records and an appropriate object or file storage service for durable uploads.
- Confirm how the app obtains credentials and connection settings without embedding secrets in the repository.
- Check that database networking, permissions, and schema setup are compatible with the deployment environment.
Azure describes its basic architecture as intended for learning and evaluation, not as a production deployment blueprint. Treat any tutorial topology as a starting point, then design for the application’s actual data, availability, and security requirements.
3. Automate deployment and define infrastructure
Choose a repeatable path from application changes to a deployed release. Depending on the service, you may connect a source repository for provider-managed builds, or publish a built container image to a registry and deploy that image. Decide whether releases should happen automatically when code changes or only after an explicit approval.
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AWS App Runner supports deployment from source code or a container image, and can automatically deploy changes from a connected repository. Azure recommends introducing CI/CD early and using infrastructure templates so environments can be recreated consistently. For AWS CDK deployments, credentials and a bootstrapped environment are prerequisites; cdk synth synthesizes the app’s infrastructure definition and can help validate it before deployment. See the provider documentation for the workflow that applies to your setup: AWS App Runner overview, Azure App Service architecture, and AWS CDK bootstrapping.
- Connect the repository or image source supported by the selected service.
- Configure the build, runtime, environment settings, and deployment trigger.
- Represent repeatable infrastructure—such as the app service, network settings, and dependencies—in the provider’s deployment tooling where practical.
- Deploy to a non-production environment first when the application or its data warrants validation before release.
Automation reduces ad hoc release steps, but it does not by itself make a deployment safe. Keep production credentials protected, restrict who can approve or change releases, and establish a recovery path appropriate to the service.
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4. Configure the domain, HTTPS, and secrets
After the service is available, connect the domain by creating the DNS records required by that provider. An A record maps a name to an IP address; a CNAME points one name to another hostname. Which record to use, and the exact target value, depend on the hosting service and DNS provider. Google Cloud explains these record roles in its DNS records documentation.
Enable the service’s supported TLS certificate and test the public HTTPS route, including any redirect from HTTP. Microsoft recommends TLS 1.2 or higher for Azure App Service applications. Do not assume the certificate is active merely because DNS changes have been saved: verify resolution and certificate validity from the public hostname. Azure’s guidance is in TLS/SSL in Azure App Service.
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Keep passwords, API keys, and connection secrets out of source control and build logs. Azure recommends storing sensitive values in Key Vault and using managed identities to access them, rather than distributing long-lived credentials in application settings. See Key Vault references for App Service. Other providers have their own secret-management services and identity configuration; follow the selected service’s current guidance.
5. Verify, observe, and harden the live service
A successful deployment means more than a build that completes. Check the public route and the application’s important dependencies, then make sure failures are visible to whoever operates the service.
- Open the HTTPS domain and confirm the expected page or API response.
- Exercise an important user flow, including a database read or write if the app depends on one.
- Review application and platform logs for startup errors, failed requests, and dependency failures.
- Configure a health check or equivalent signal and alerts for failures that require action.
Azure documents health checks and telemetry for requests and database dependencies; Google Cloud documents Cloud Run request and container logs alongside Cloud Monitoring. The implementation and available signals differ by service. See Azure’s App Service architecture guidance and Google Cloud Run logging.
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Before treating a proof of concept as production-ready, review capacity and scaling, redundancy and availability, identity permissions, network exposure, backups or recovery needs, and the limits of the selected plan. The appropriate safeguards depend on workload, data sensitivity, and availability targets; a basic tutorial configuration cannot establish those requirements for every application.
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