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The DOP-C02 certification exam is a rigorous exam that tests the candidate's knowledge and skills in several areas, including continuous delivery and deployment, monitoring and logging, security, infrastructure as code, and automation. DOP-C02 Exam is designed to assess the candidate's ability to design, deploy, and manage highly available, fault-tolerant, and scalable AWS systems.
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Amazon DOP-C02 (AWS Certified DevOps Engineer - Professional) Certification Exam is a comprehensive test that validates the skills and expertise of individuals who work in the DevOps field. AWS Certified DevOps Engineer - Professional certification exam is designed for professionals who have a deep understanding of the principles and practices of DevOps and have experience working with AWS services. DOP-C02 Exam assesses the individual's ability to design, deploy, and manage scalable, highly available, and fault-tolerant systems on the AWS platform.
NEW QUESTION # 172
A company deploys a web application on Amazon EC2 instances that are behind an Application Load Balancer (ALB). The company stores the application code in an AWS CodeCommit repository. When code is merged to the main branch, an AWS Lambda function invokes an AWS CodeBuild project. The CodeBuild project packages the code, stores the packaged code in AWS CodeArtifact, and invokes AWS Systems Manager Run Command to deploy the packaged code to the EC2 instances.
Previous deployments have resulted in defects, EC2 instances that are not running the latest version of the packaged code, and inconsistencies between instances.
Which combination of actions should a DevOps engineer take to implement a more reliable deployment solution? (Select TWO.)
Answer: B,E
Explanation:
Explanation
To implement a more reliable deployment solution, a DevOps engineer should take the following actions:
Create a pipeline in AWS CodePipeline that uses the CodeCommit repository as a source provider.
Configure pipeline stages that run the CodeBuild project in parallel to build and test the application. In the pipeline, pass the CodeBuild project output artifact to an AWS CodeDeploy action. This action will improve the deployment reliability by automating the entire process from code commit to deployment, reducing human errors and inconsistencies. By running the build and test stages in parallel, the pipeline can also speed up the delivery time and provide faster feedback. By using CodeDeploy as the deployment action, the pipeline can leverage the features of CodeDeploy, such as traffic shifting, health checks, rollback, and deployment configuration123 Create an AWS CodeDeploy application and a deployment group to deploy the packaged code to the EC2 instances. Configure the ALB for the deployment group. This action will improve the deployment reliability by using CodeDeploy to orchestrate the deployment across multiple EC2 instances behind an ALB. CodeDeploy can perform blue/green deployments or in-place deployments with traffic shifting, which can minimize downtime and reduce risks. CodeDeploy can also monitor the health of the instances during and after the deployment, and automatically roll back if any issues are detected. By configuring the ALB for the deployment group, CodeDeploy can register and deregister instances from the load balancer as needed, ensuring that only healthy instances receive traffic45 The other options are not correct because they do not improve the deployment reliability or follow best practices. Creating separate pipeline stages that run a CodeBuild project to build and then test the application is not a good option because it will increase the pipeline execution time and delay the feedback loop. Creating individual Lambda functions that use CodeDeploy instead of Systems Manager to run build, test, and deploy actions is not a valid option because it will add unnecessary complexity and cost to the solution. Lambda functions are not designed for long-running tasks such as building or deploying applications. Creating an Amazon S3 bucket and modifying the CodeBuild project to store the packages in the S3 bucket instead of in CodeArtifact is not a necessary option because it will not affect the deployment reliability. CodeArtifact is a secure, scalable, and cost-effective package management service that can store and share software packages for application development67 References:
1: What is AWS CodePipeline? - AWS CodePipeline
2: Create a pipeline in AWS CodePipeline - AWS CodePipeline
3: Deploy an application with AWS CodeDeploy - AWS CodePipeline
4: What is AWS CodeDeploy? - AWS CodeDeploy
5: Configure an Application Load Balancer for your blue/green deployments - AWS CodeDeploy
6: What is AWS Lambda? - AWS Lambda
7: What is AWS CodeArtifact? - AWS CodeArtifact
NEW QUESTION # 173
A company is developing an application that will generate log events. The log events consist of five distinct metrics every one tenth of a second and produce a large amount of data The company needs to configure the application to write the logs to Amazon Time stream The company will configure a daily query against the Timestream table.
Which combination of steps will meet these requirements with the FASTEST query performance? (Select THREE.)
Answer: A,D,E
Explanation:
The correct answer is A, D, and F)
A comprehensive and detailed explanation is:
Option A is correct because using batch writes to write multiple log events in a single write operation is a recommended practice for optimizing the performance and cost of data ingestion in Timestream. Batch writes can reduce the number of network round trips and API calls, and can also take advantage of parallel processing by Timestream. Batch writes can also improve the compression ratio of data in the memory store and the magnetic store, which can reduce the storage costs and improve the query performance1.
Option B is incorrect because writing each log event as a single write operation is not a recommended practice for optimizing the performance and cost of data ingestion in Timestream. Writing each log event as a single write operation would increase the number of network round trips and API calls, and would also reduce the compression ratio of data in the memory store and the magnetic store. This would increase the storage costs and degrade the query performance1.
Option C is incorrect because treating each log as a single-measure record is not a recommended practice for optimizing the query performance in Timestream. Treating each log as a single-measure record would result in creating multiple records for each timestamp, which would increase the storage size and the query latency. Moreover, treating each log as a single-measure record would require using joins to query multiple measures for the same timestamp, which would add complexity and overhead to the query processing2.
Option D is correct because treating each log as a multi-measure record is a recommended practice for optimizing the query performance in Timestream. Treating each log as a multi-measure record would result in creating a single record for each timestamp, which would reduce the storage size and the query latency. Moreover, treating each log as a multi-measure record would allow querying multiple measures for the same timestamp without using joins, which would simplify and speed up the query processing2.
Option E is incorrect because configuring the memory store retention period to be longer than the magnetic store retention period is not a valid option in Timestream. The memory store retention period must always be shorter than or equal to the magnetic store retention period. This ensures that data is moved from the memory store to the magnetic store before it expires out of the memory store3.
Option F is correct because configuring the memory store retention period to be shorter than the magnetic store retention period is a valid option in Timestream. The memory store retention period determines how long data is kept in the memory store, which is optimized for fast point-in-time queries. The magnetic store retention period determines how long data is kept in the magnetic store, which is optimized for fast analytical queries. By configuring these retention periods appropriately, you can balance your storage costs and query performance according to your application needs3.
Reference:
1: Batch writes
2: Multi-measure records vs. single-measure records
3: Storage
NEW QUESTION # 174
A company is examining its disaster recovery capability and wants the ability to switch over its daily operations to a secondary AWS Region. The company uses AWS CodeCommit as a source control tool in the primary Region.
A DevOps engineer must provide the capability for the company to develop code in the secondary Region. If the company needs to use the secondary Region, developers can add an additional remote URL to their local Git configuration.
Which solution will meet these requirements?
Answer: D
Explanation:
The best solution to meet the disaster recovery capability and allow developers to switch over to a secondary AWS Region for code development is option A. This involves creating a CodeCommit repository in the secondary Region and setting up an AWS CodeBuild project to perform a Git mirror operation of the primary Region's CodeCommit repository to the secondary Region's repository. An AWS Lambda function is then created to invoke the CodeBuild project. Additionally, an Amazon EventBridge rule is configured to react to merge events in the primary Region's CodeCommit repository and invoke the Lambda function12. This setup ensures that the secondary Region's repository is always up-to-date with the primary repository, allowing for a seamless transition in case of a disaster recovery event1.
:
AWS CodeCommit User Guide on resilience and disaster recovery1.
AWS Documentation on monitoring CodeCommit events in Amazon EventBridge and Amazon CloudWatch Events2.
NEW QUESTION # 175
A company has developed a serverless web application that is hosted on AWS. The application consists of Amazon S3. Amazon API Gateway, several AWS Lambda functions, and an Amazon RDS for MySQL database. The company is using AWS CodeCommit to store the source code. The source code is a combination of AWS Serverless Application Model (AWS SAM) templates and Python code.
A security audit and penetration test reveal that user names and passwords for authentication to the database are hardcoded within CodeCommit repositories. A DevOps engineer must implement a solution to automatically detect and prevent hardcoded secrets.
What is the MOST secure solution that meets these requirements?
Answer: D
Explanation:
Explanation
https://docs.aws.amazon.com/codecommit/latest/userguide/how-to-amazon-codeguru-reviewer.html
NEW QUESTION # 176
A company runs a web application that extends across multiple Availability Zones. The company uses an Application Load Balancer (ALB) for routing. AWS Fargate (or the application and Amazon Aurora for the application data The company uses AWS CloudFormation templates to deploy the application The company stores all Docker images in an Amazon Elastic Container Registry (Amazon ECR) repository in the same AWS account and AWS Region.
A DevOps engineer needs to establish a disaster recovery (DR) process in another Region. The solution must meet an RPO of 8 hours and an RTO of 2 hours The company sometimes needs more than 2 hours to build the Docker images from the Dockerfile Which solution will meet the RTO and RPO requirements MOST cost-effectively?
Answer: C
Explanation:
Explanation
The most cost-effective solution to meet the RTO and RPO requirements is option B. This option involves copying the CloudFormation templates to an Amazon S3 bucket in the DR Region, configuring Aurora automated backup Cross-Region Replication, and configuring ECR Cross-Region Replication. In the event of a disaster, the CloudFormation template with the most recent Aurora snapshot and the Docker image from the local ECR repository can be used to launch a new CloudFormation stack in the DR Region. This approach avoids the need to build Docker images from the Dockerfile, which can sometimes take more than 2 hours, thus meeting the RTO requirement. Additionally, the use of automated backups and replication ensures that the RPO of 8 hours is met.
References:
* AWS Documentation on Disaster Recovery: Plan for Disaster Recovery (DR) - Reliability Pillar
* AWS Blog on Establishing RPO and RTO Targets: Establishing RPO and RTO Targets for Cloud Applications
* AWS Documentation on ECR Cross-Region Replication: Amazon ECR Cross-Region Replication
* AWS Documentation on Aurora Cross-Region Replication: Replicating Amazon Aurora DB Clusters Across AWS Regions
NEW QUESTION # 177
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