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Azure Container Instances (ACI) is a serverless service that runs containers without requiring you to manage any underlying virtual machines. It is designed for isolated workloads that need to start quickly and scale on demand. The deployment process begins with storing your container image in an Azure Container Registry. To securely access this registry without embedding passwords, you can use managed identities, which are automatically handled credentials assigned to your VM or AKS cluster.
A key benefit of ACI is its ability to provide strong security boundaries. Confidential containers offer enhanced protection by running within a hardware-backed Trusted Execution Environment (TEE), such as those provided by AMD EPYC™ processors. This environment ensures data and code integrity through full guest attestation and secure policy enforcement. For data encryption, you can use customer-managed keys stored in Azure Key Vault, giving you control over the encryption keys for your container resources.
When creating a container instance, you define its basic properties, including a unique name, the operating system type, and the source of the container image. You must allocate CPU cores and memory appropriately to match your application's needs. For private images stored in an Azure Container Registry, you must provide registry credentials so ACI can pull the image. You can also pass environment variables to the container at startup, which is the preferred method for injecting dynamic configuration like API endpoints without hardcoding them into the image.
Networking determines how your container is accessed. You can assign a public IP address and a DNS name label to give your container a public-facing web address. You must also open specific ports, such as TCP port 80 for web traffic, to allow communication. For more secure deployments, ACI supports virtual network integration, which places the container inside your private Azure network so it can communicate with other resources like databases without exposing them to the internet.
Because containers are stateless, any data written inside is lost when the container stops. To persist data, you mount an Azure File Share as a volume within the container instance. This allows the application to read and write files that survive container restarts or deletions. For security, you can enable a managed identity (either system-assigned or user-assigned) on the container, allowing it to authenticate to services like Azure Key Vault without handling secrets in your code.
To maintain a healthy application, you configure liveness probes and readiness probes. These checks tell Azure if the container is running correctly and ready to accept traffic, triggering restarts if necessary. You can also deploy container groups into specific availability zones to protect against failures within a single data center. Monitoring is done by viewing container logs directly in the Azure portal or by sending them to a log analytics workspace.
The cornerstone of security is using managed identities to grant your container access to other Azure services. This follows the principle of least privilege and eliminates the need to store passwords in your code or configuration. For storing sensitive data like connection strings, you should use Azure Key Vault. The container uses its managed identity to retrieve these secrets at runtime. When you must use environment variables, you should configure them as secure environment variables in your deployment to prevent them from being displayed in plain text.
Azure Monitor is the primary tool for tracking container performance and activity. It collects logs from the container's standard output and error streams. By enabling Log Analytics, you can run detailed queries to audit activity and detect anomalies. You must configure diagnostic settings to send these logs to a workspace for long-term analysis. The Diagnose and solve problems tool in the portal provides automated troubleshooting for common configuration issues.
To prevent unauthorized access, you can deploy container instances into an Azure Virtual Network. This isolates them from the public internet and allows communication only through private endpoints. It is also critical to set resource limits for CPU and memory on your container groups. This prevents a single misbehaving container from consuming all available host resources and affecting other workloads, ensuring system stability and fair resource governance.
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