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Google Associate Cloud Engineer Exam

An associated cloud engineer distributes applications, monitors operations and manages business solutions. This person can use the Google Cloud Console and the command-line interface to perform common platform-based activities to maintain one or more distributed solutions that take advantage of services managed or self-managed by Google in Google Cloud

The Google Cloud Certification Program offers Google Cloud users, customers and partners a way to demonstrate their technical skills in a specific role or technology. People are evaluated using a variety of rigorously developed standard methods to determine if they meet Google Cloud competition standards. The cost of certification exams varies. if you do not pass an exam, you can repeat it after 14 days. If you do not take it a second time, you must wait 60 days before you can take it a third time. If it fails a third time, you must wait a year before resuming it. You can try the test in several languages, but each attempt, regardless of language, counts the total number of attempts allowed and the waiting period between attempts remains valid. Payment is required each time an exam is taken. Avoiding this recovery policy by registering with a different name or any other means constitutes a violation of the terms and conditions of the exam and will result in the denial or revocation of a certification. Exams are designed to determine only if a person meets a minimum standard of approval or not. They are not meant to be diagnostic or spread people on a capacity scale. For this reason, numerical scores are not significant for the candidate and can be misunderstood. Google Cloud Certification Program recognizes that some other exam providers provide section comments on their exams. Google doesn't do it because it makes no sense and could be misleading. Google Cloud Certification tests are not designed to diagnose strengths and weaknesses. Google Cloud Certification exam sections are very broad categories of topics, and the range of specific questions that can be received for each section in a single exam session is extremely small in comparison. Based on such a small amount of data, there are no significant comments at the section level that we can provide responsibly. We follow the procedures accepted by the industry to ensure that our exams are valid and accurate. Our exam development process includes the following steps: A task analysis (JTA) is a formal study that begins with the identification of role representatives, technology experts and stakeholders. These experts are interviewed and interviewed in a seminar to obtain information about what people do in a particular job or role and what skills distinguish the skills. These skills are defined in the exam guides that we write on the web. Our question authors are subject matter experts who worked in the certified role. The question editors are trained in the exam standards and conventions that we apply to our exams. All questions are examined to determine if they meet the standards and are technically accurate. Once the questions have passed all warnings and approvals, they are published in a beta test. The purpose of the beta exam is to collect performance statistics related to the exam questions to determine which ones are the most effective. We review the statistics and comments on the questions and eliminate questions that do not meet our standards. The minimum score for each exam is reserved. It is determined by a group of internal and external experts in the field, following a process of setting standards accepted by the sector. The minimum score applies equally to all candidates. It is reevaluated when changes are made to the content of the exam. The delivery method for an exam depends on its format.

Deploying & Implementing Cloud Solutions

• Deploy and implement compute engine resources: the skills required for this area include launching compute instances with Cloud SDK and Cloud Console; creating auto-scaled managed instance groups with instance templates; uploading/generating custom SSH keys for instances; configuring virtual machines or Stackdriver logging and monitoring. It also requires that the students can assess compute quotas and request for increases; install a Stackdriver Agent for logging and monitoring;
• Deploy and implement networking resources: this will measure your ability to launch Compute Engine instances using custom network configuration; create egress and ingress firewall rule or VPC; create VPNs between the external network and Google VPC with Cloud VPN; create the load balancer to allocate the application network traffic for apps;
• Deploy and implement Google Kubernetes Engine Resources: this domain includes skills in deploying Google Kubernetes Engine cluster, container application to Google Kubernetes Engine with pods, and configuring Google Kubernetes Engine Application logging and monitoring;
• Deploy an application infrastructure with Cloud Deployment Manager with a focus on the development and launch of Deployment Manager templates.
• Deploy and implement data solutions: the applicants should be able to initialize data systems with Google products and load data;
• Deploy solutions with Cloud Marketplace: the candidates must demonstrate the ability to browse the Cloud Marketplace catalog to check solution details; deploy Cloud Marketplace solutions;
• Deploy and implement App Engine, Cloud Functions, and Cloud Run resources: the learners will be required to demonstrate their skills in the deployment of applications, traffic splitting, updating scaling configuration, as well as deployment of applications that accept Google Cloud events;

Reference: https://cloud.google.com/certification/cloud-engineer

Only need to practice for 20 to 30 hours

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Ensuring Operation Success of a Cloud Solution

• Manage App Engine and Cloud Run resources: the individuals should be able to adjust application traffic splitting parameters; set scaling parameters for auto-scaling instances; work with management interfaces;
• Manage Google Kubernetes Engine resources: this requires one’s competence in viewing on-going running cluster inventory; browsing container image depository and viewing the details of container images; working with pods, node pools, services, stateful applications, and management interfaces;
• Manage network resources: this part requires the capability to add subnets to existing VPCs; expand subnets to include more IP addresses; reserve static internal or external IP address; work with management interfaces;
• Manage database and storage solutions: this area requires your competence in setting object lifecycle management policies for Cloud Storage buckets; moving different objects between Cloud Storage buckets; estimating costs for BigQuery; executing queries for the retrieval of data from data instances. It also requires your capability to backup and restores data instances; review a job status in BigQuery, Cloud Dataflow, or Cloud Dataproc; work with management interfaces;
• Manage Compute Engine resources: the test takers should demonstrate their capability to manage single VM instances; RDP/SSH to instance; attack GPU to new instances and install CUDA libraries; view on-going running virtual machine inventory; work with snapshots, images, management interfaces, and instance groups;
• Monitor and log: this subject includes the examinees’ ability to create Stackdriver custom metrics and Stackdriver alerts according to resource metrics; use Cloud diagnostics to analyze application issues; check and filter logs within Stackdriver; configure log sinks for the exportation of logs into external systems; view the status of Google Cloud Platform.

Google Associate-Cloud-Engineer Exam Syllabus Topics: