Most Recent Oracle 1Z0-1084-23 Exam Dumps

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.

The correct answer is: 'read only.' The layers of a Docker image are read-only. Once a layer is created, it cannot be modified. Each layer represents a Dockerfile instruction, and it is stacked on top of the previous layer, forming a stack of immutable layers. These layers are designed to be read-only to ensure consistency and integrity of the image. When a Docker image is built, each instruction in the Dockerfile creates a new layer. Each layer represents the changes made by that instruction relative to the previous layer. The layers are stacked on top of each other to form the complete image. This layer-based approach allows for efficient storage and distribution of Docker images. Because the layers are read-only, any changes or modifications to the image result in the creation of new layers rather than modifying the existing ones. This immutability ensures that each layer remains intact and preserves the integrity of the image. It also enables Docker's caching mechanism, where previously built layers can be reused if the corresponding instructions haven't changed, speeding up the image build process. The other options mentioned, such as 'write only,' 'write once,' 'movable,' and 'read mostly,' do not accurately describe the permission associated with Docker image layers. Docker image layers are specifically designed to be read-only.

The correct answer is: 'Resiliency is about recovering from failures without downtime or data loss.' Service resiliency, in the context of cloud-native applications, is the ability of a service or system to recover from failures and continue functioning without downtime or data loss. It involves designing and implementing mechanisms to handle failures, such as network outages, hardware failures, or software errors, in a way that minimizes the impact on the overall system. The goal of resiliency is to ensure that the application or service can continue to operate and provide a certain level of functionality, even in the face of failures. This typically involves techniques such as redundancy, fault tolerance, and graceful degradation. By implementing resiliency measures, a cloud-native application can recover and adapt to failures, maintain availability, and preserve data integrity. The other statements are not accurate regarding service resiliency: Resiliency is not about not bringing a service to a functioning state after a failure. Instead, it is about recovering from failures and ensuring continued functionality. Resiliency is not about avoiding failures entirely. While it is desirable to prevent failures, resiliency focuses on the ability to handle and recover from failures when they do occur. Resiliency testing is not limited to a test environment. It is important to test and validate the resiliency measures in both test environments and production environments to ensure the application can effectively handle failures in real-world scenarios.

The correct value for the 'type' field in the API deployment specification is 'STOCK_RESPONSE_BACKEND'. By setting the 'type' to 'STOCK_RESPONSE_BACKEND', you are indicating that the backend for the specified route should return a pre-defined response. This type of backend is commonly used when you want a specific response to be returned consistently, regardless of the actual backend service implementation. In this case, the API deployment specification is configured to have a single route with the path '/hello' and the method 'GET'. The backend section specifies the type as 'STOCK_RESPONSE_BACKEND'. Additionally, it defines the response status code as 200, sets the 'Content-Type' header to 'application/json', and provides the JSON content in the 'body' field. Using this configuration, any request to the '/hello' path with the 'GET' method will always receive a consistent JSON response with the content '{'myjson': 'consistent response'}'.

The strategy that involves exposing new functionality or features to only a small set of users is called Canary Deployment. Canary deployment is a technique used in software development and deployment where a new version of an application or feature is released to a small subset of users or a specific group of servers. This allows for testing and gathering feedback on the new functionality in a controlled and limited environment before making it available to a wider audience. In a canary deployment, a small portion of the traffic is routed to the new version while the majority of the traffic still goes to the stable version. This allows for monitoring and evaluation of the new functionality in real-world conditions while minimizing the impact of any potential issues or bugs. If the new version performs well and meets the desired criteria, it can then be gradually rolled out to a larger user base or all servers. By exposing the new functionality or features to a small set of users initially, canary deployment helps in identifying any unforeseen issues, gathering feedback, and ensuring the stability and reliability of the application before a full deployment.