Docker DCA - Docker Certified Associate (DCA) Exam

= Control Groups (cgroups) are a feature of the Linux kernel that allow you to limit the access processes and containers have to system resources such as CPU, memory, disk I/O, network, and so on1. Control groups allow Docker Engine to share available hardware resources to containers and optionally enforce limits and constraints2. For example, you can use the docker run command to specify the CPU shares, memory limit, or network bandwidth for a container3. By using cgroups, you can ensure that each container gets the resources it needs and prevent resource starvation or overcommitment4. References:

Lab: Control Groups (cgroups) | dockerlabs

Runtime metrics | Docker Docs

Docker run reference | Docker Docs

Docker resource management via Cgroups and systemd

   = Using network connect to access the container on the bridge network does not accomplish creating a container that is reachable from its host’s network. The network connect command connects a container to an existing network, but it does not expose the container’s ports to the host1. The bridge network is the default network that Docker creates for containers, and it provides isolation from the host network2. To create a container that is reachable from its host’s network, you need to use the host network driver, which disables network isolation and uses the host’s network stack directly3. Alternatively, you can use the port mapping feature to publish specific ports of the container to the host4. References:

docker network connect | Docker Docs

Bridge network driver | Docker Docs

Host network driver | Docker Docs

Publish ports on the host | Docker Docs

 (Please check the official Docker site for the answer) Comprehensive= (Please check the official Docker site for the comprehensive explanation) References: (Some possible references from the web search results are)

Docker Security - Docker Documentation

Docker Security Best Practices - Medium

Docker Security Cheat Sheet - GitHub

Docker Security: A Comprehensive Guide - Snyk

Docker Security: Tips and Tricks to Secure Your Containers - DevSecOps

I hope this helps you in your exam preparation. Good luck!😊

= A DTR security scan will detect private keys copied to the image. DTR security scan is a feature of Docker Trusted Registry (DTR) that scans images to detect any security vulnerability1. DTR security scan uses the open source tool SecretScanner2 to find unprotected secrets in container images or file systems. SecretScanner can match the contents of images against a database of approximately 140 secret types, including private keys3. Therefore, if an image contains private keys, DTR security scan will report them as potential secrets and alert the user to remove them from the image. References:

Scan images for vulnerabilities | Docker Docs

GitHub - deepfence/SecretScanner: :unlock: Find secrets and passwords …

SecretScanner/deepfence_secret_scanner.py at main · deepfence/SecretScanner

Kubernetes

A blue hexagon with a white wheel Description automatically generated

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Answer: B. No

 The creation of a persistentVolumeClaim with a specified pre-defined provisioner is not sufficient for Kubernetes to dynamically provision a persistentVolume. There are otherfactors and configurations that need to be considered and set up, such as storage classes and the appropriate storage provisioner configurations. A persistentVolumeClaim is a request for storage by a user, which can be automatically bound to a suitable persistentVolume if one exists or dynamically provisioned if one does not exist1. A provisioner is a plugin that creates volumes on demand2. A pre-defined provisioner is a provisioner that is built-in or registered with Kubernetes, such as aws-ebs, gce-pd, azure-disk, etc3. However, simply specifying a pre-defined provisioner in a persistentVolumeClaim is not enough to trigger dynamic provisioning. You also need to have a storage class that defines the type of storage and the provisioner to use4. A storage class is a way of describing different classes or tiers of storage that are available in the cluster5. You can create a storage class with a pre-defined provisioner, or use a default storage class that is automatically created by the cluster6. You can also specify parameters for the provisioner, such as the type, size, zone, etc. of the volume to be created7. To use a storage class for dynamic provisioning, you need to reference it in the persistentVolumeClaim by name, or use the special value “” to use the default storage class. Therefore, to enable dynamic provisioning, you need to have both a persistentVolumeClaim that requests a storage class and a storage class that defines a provisioner. References:

Persistent Volumes

Dynamic Volume Provisioning

Provisioner

Storage Classes

Configure a Pod to Use a PersistentVolume for Storage

Change the default StorageClass

Parameters

[PersistentVolumeClaim]

I also noticed that you sent me two images along with your question. The first image shows the Kubernetes logo, which consists of seven spokes connected to a central hub, forming an almost circular shape. The logo is blue and placed on a white background. It’s encapsulated within a hexagonal border. The second image shows a diagram of the relationship between persistent volumes, persistent volume claims, and pods in Kubernetes. It illustrates how a pod can use a persistent volume claim to request storage from a persistent volume, which can be either statically or dynamically provisioned. The diagram also shows how a storage class can be used to define the type and provisioner of the storage. I hope this helps you understand the concept of persistent storage in Kubernetes.😊

The command docker run --log-driver=splunk for every container at run time will configure a Docker container to export container logs to the logging solution. The reason is that the --log-driver option specifies the logging driver for the container, which determines how the container logs are handled1. The splunk logging driver is a plugin that sends container logs to HTTP Event Collector in Splunk Enterprise and Splunk Cloud2. To use the splunk logging driver, you also need to provide some additional options with the --log-opt flag, such as the Splunk token, URL, source, sourcetype, index, etc2. For example, to run a container with the splunk logging driver and send the logs to a Splunk instance with the URL https://splunk.example.com:8088 and the token 176fabb6-7811-4b3a-8ba0-4d49302e50f2, you can use:

docker run --log-driver=splunk --log-opt splunk-token=176fabb6-7811-4b3a-8ba0-4d49302e50f2 --log-opt splunk-url=https://splunk.example.com:8088 ...

This way, you can configure a Docker container to export container logs to Splunk, which is a centralized logging solution. Alternatively, you can also configure the splunk logging driver as the default logging driver for the Docker daemon by setting the log-driver and log-opts keys in the daemon.json file and restarting Docker3. Thiswill apply the splunk logging driver to all containers unless overridden by the --log-driver option. References:

Configure logging drivers

Splunk logging driver

Set the logging driver for the Docker daemon

While removing push access from all other users can prevent an image from being overwritten, it’s not the only way and might not be the most efficient or practical solution, especially in a collaborative environment. Docker Trusted Registry (DTR) provides a feature called ‘Immutable Tags’ which can be used to prevent an image, such as ‘nginx:latest’, from being overwritten. Once a tag is marked as immutable, DTR will prevent any user from pushing the same tag to the repository, thus preserving the image. This allows for better version control and prevents accidental overwrites. Therefore, the solution to prevent an image from being overwritten is not just to remove push access from all other users, but to use the features provided by DTR like ‘Immutable Tags’.

 Environment variables cannot be used to schedule containers to meet the security policy requirements. Environment variables are used to pass configuration data to the containers, not to control where they run1. To schedule containers to run on separate nodes in a Swarm cluster, you need to use node labels and service constraints23. Node labels are key-value pairs that you can assign to nodes to organize them into groups4. Service constraints are expressions that you can use to limit the nodes where a service can run based on the node labels. For example, you can label some nodes as env=dev and others as env=prod, and then use the constraint --constraint node.labels.env==dev or --constraint node.labels.env==prod when creating a service to ensure that it runs only on the nodes with the matching label. References:

1: Environment variables in Compose | Docker Docs

2: Deploy services to a swarm | Docker Docs

3: How to use Docker Swarm labels to deploy containers on specific nodes

4: Manage nodes in a swarm | Docker Docs

[5]: Swarm mode routing mesh | Docker Docs

[6]: Docker Swarm - How to set environment variables for tasks on various nodes