1z0-1084-24 Reviews Questions

Explanation

Which TWO statements are correct regarding Docker images and containers? (Choose two.) Writing and building a new Dockerfile is the only way you can create new Docker images. A container can exist without an image but an image cannot exist without a container. Only one container can be spawned from a given image at a time. If multiple containers are spawned from the same image, then they all use the same copy of that image in memory. (Correct) An image is a collection of immutable layers whereas a container is a running instance of an image. (Correct) ChatGPT The correct statements regarding Docker images and containers are: If multiple containers are spawned from the same image, then they all use the same copy of that image in memory. This statement is correct. When multiple containers are created from the same Docker image, they share the underlying layers of the image in memory. Each container has its own isolated filesystem and runtime environment, but they all use the same base image, which helps in efficient resource utilization. An image is a collection of immutable layers whereas a container is a running instance of an image. This statement is also correct. Docker images are composed of multiple layers, with each layer representing a specific change or addition to the previous layer. These layers are read-only and can be shared among multiple containers. On the other hand, a container is a lightweight and isolated runtime instance created from a specific image. It is a running process that has its own filesystem, network, and runtime configuration. The statements "Writing and building a new Dockerfile is the only way you can create new Docker images" and "A container can exist without an image but an image cannot exist without a container" are incorrect. Docker images can be created in various ways, including using Dockerfiles, importing from existing images, or pulling from registries. Additionally, a container requires an image to run, so an image must exist before a container can be created from it.

Explanation

The best answer is: "Use the OCI Logging service and enable VCN flow logs." To meet the requirement of analyzing network communication between two services deployed in different Container Engine for Kubernetes (OKE) clusters within the same Virtual Cloud Network (VCN) in a cost-effective way, you can use the OCI Logging service and enable VCN flow logs. The VCN flow logs feature in OCI allows you to capture and log network traffic information for your VCN resources. By enabling VCN flow logs, you can monitor and analyze the network communication between your services without the need for additional third-party logging services or tools. Enabling VCN flow logs provides visibility into the network traffic, including source and destination IP addresses, ports, protocols, and other relevant details. This information can be collected and stored in the OCI Logging service, where you can analyze and gain insights into the network communication patterns between your services. By leveraging the built-in capabilities of the OCI Logging service and enabling VCN flow logs, you can fulfill the security team's requirement for network communication analysis in a cost-effective manner. This eliminates the need for deploying additional third-party logging services or tools, reducing complexity and potential costs associated with their setup and maintenance. The other options mentioned are not the most cost-effective or suitable solutions for analyzing network communication in this scenario: Deploying a third-party logging service and aggregating the network flow logs would introduce additional costs and complexity, which may not be necessary considering the built-in capabilities provided by OCI. Rewriting the application to send logs to an outside log aggregator would not directly address the requirement of analyzing network communication between the services. It would focus more on application-level logs rather than network-level analysis. Deploying Wireshark and intercepting packets would require additional infrastructure setup and maintenance, which may not be the most cost-effective approach for network analysis in this scenario.

Idle-timeout is the parameter that is used to configure the time period during which an idle function will remain in memory before Oracle Functions removes its container image from memory2. The idle-timeout parameter is specified in seconds and can be set when creating or updating a function2. The default value for idle-timeout is 30 seconds and the maximum value is 900 seconds (15 minutes)2. If a function has the --provisioned-concurrency option enabled, the idle-timeout parameter is ignored and the function instances are always kept in memory3. Verified References: Creating Functions, Provisioned Concurrency