Planning & Configuring Cloud Solutions

• Plan and configure compute resources with specific skills in choosing the relevant compute choices for a specific workload as well as utilizing preemptible virtual machines and custom machine types as relevant;
• Plan and estimate the GCP product use with Pricing Calculator;
• Plan and configure network resources, which include distinguishing load balancing alternatives, configuring the Cloud DNS, establishing resource locations within a network for its availability.
• Plan and configure data storage options with a focus on product choice and selecting storage options;

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Training

While the exam curriculum covers a lot of knowledge and skills, Google offers enough tools to help candidates systematize their preparation process. Self-paced and in-classroom courses as well we lab practice are also available.

So, you can take advantage of Architecting with Google Compute Engine, a three-day course that will introduce you to Google Cloud infrastructure and platform services by focusing on Compute Engine.

Alternatively, candidates can pose their questions to an expert instructor regarding Google Сloud products at a one-day Google Cloud Fundamentals: Core Infrastructure training session that includes lectures, presentations, and lab activities.

In addition, Google recommends that all applicants who want to know more about the format, structure, and topics of the certification exam finish the Preparing for the Associate Cloud Engineer Examination course. It helps applicants to assess their strengths and weaknesses and be fully prepared on the day of the final test.

If you are not confident in your readiness, you can also check your skills by answering sample questions alongside doing self-paced labs offered by the vendor.

The Google Associate Cloud Engineer certification is designed to measure the candidates’ fundamental skills required to perform the deployment, monitoring, and maintenance of projects on Google Cloud. This certificate is a good starting point for those individuals who are new to Cloud and can be used as a stepping stone to the professional-level certifications of this vendor. To get certified, the applicants are required to complete one exam. The qualifying test measures the ability of the specialists to perform the following tasks: setting up the Cloud solution environment; planning and configuring Cloud solutions; deploying and implementing Cloud solutions; ensuring the effective operation of Cloud solutions; and configuring access & security.

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

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 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 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 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 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;