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Ensuring Operation Success of a Cloud Solution
- 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.
- 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 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 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 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;
- 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;
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Deploying & Implementing Cloud Solutions
To answer the questions related to this domain, the examinees need to show that they know how to deploy and implement Compute Engine resources, Google Kubernetes Engine resources, App Engine resources, Cloud Run resources, and Cloud Functions resources. Moreover, they should have a good understanding of how to deploy and implement data solutions as well as networking resources. They also need to have the capacity to perform the deployment of a solution with the help of Cloud Marketplace. Additionally, their ability to perform the deployment of application infrastructure with the help of Cloud Deployment Manager is required.
About the Exam
The Associate Cloud Engineer exam is 2-hour long, contains 50 multiple-choice and multiple-select questions, and is available in three languages: English, Spanish, and Japanese. You have the choice of taking the exam online or sit for it at one test center located near your area. This exam has a registration fee of $125 and no prerequisites. However, it is recommended that you have at least six months of practical experience working with Google Cloud before taking this test.
After you have passed the exam, you will be issued a digital badge and certificate upon completion of the Google verification. Each certificate contains a sequential number that reflects its position among the list of Google-certified individuals.
Moreover, the Google Associate Cloud Engineer certification is valid for only two years from the date you obtain it. Then, you have to recertify to maintain your certification status. That’s why you will be receiving notifications for renewals 90, 60, and 30 days before the expiration date.
Deploying & Implementing Cloud 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;
- 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 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 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 data solutions: the applicants should be able to initialize data systems with Google products and load data;
- 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.
Reference: https://cloud.google.com/certification/cloud-engineer
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