Google Google-ACE : Google Associate Cloud Engineer - 2023 Exam Dumps

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Exam Number : Google-ACE
Exam Name : Google Associate Cloud Engineer - 2023
Vendor Name : Google
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Google-ACE Exam Format | Google-ACE Course Contents | Google-ACE Course Outline | Google-ACE Exam Syllabus | Google-ACE Exam Objectives


Length: Two hours

Languages: English, Japanese, Spanish, Indonesian.

Exam format: Multiple choice and multiple select, taken in person at a test center. Locate a test center near you.

Prerequisites: None

Recommended experience: 6 months+ hands-on experience with Google Cloud



An Associate Cloud Engineer deploys applications, monitors operations, and manages enterprise solutions. This individual is able to use Google Cloud Console and the command-line interface to perform common platform-based tasks to maintain one or more deployed solutions that leverage Google-managed or self-managed services on Google Cloud.



The Associate Cloud Engineer exam assesses your ability to:



Set up a cloud solution environment

Plan and configure a cloud solution

Deploy and implement a cloud solution

Ensure successful operation of a cloud solution

Configure access and security



Setting up a cloud solution environment

Setting up cloud projects and accounts. Activities include:



Creating projects

Assigning users to predefined IAM roles within a project

Managing users in Cloud Identity (manually and automated)

Enabling APIs within projects

Provisioning one or more Stackdriver workspaces



Managing billing configuration. Activities include:



Creating one or more billing accounts

Linking projects to a billing account

Establishing billing budgets and alerts

Setting up billing exports to estimate daily/monthly charges



Installing and configuring the command line interface (CLI), specifically the Cloud SDK (e.g., setting the default project).



Planning and configuring a cloud solution

Planning and estimating GCP product use using the Pricing Calculator

Planning and configuring compute resources. Considerations include:



Selecting appropriate compute choices for a given workload (e.g., Compute Engine, Google Kubernetes Engine, App Engine, Cloud Run, Cloud Functions)

Using preemptible VMs and custom machine types as appropriate



Planning and configuring data storage options. Considerations include:



Product choice (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Bigtable)

Choosing storage options (e.g., Standard, Nearline, Coldline, Archive)



Planning and configuring network resources. Tasks include:



Differentiating load balancing options

Identifying resource locations in a network for availability

Configuring Cloud DNS

Deploying and implementing a cloud solution

Deploying and implementing Compute Engine resources. Tasks include:



Launching a compute instance using Cloud Console and Cloud SDK (gcloud) (e.g., assign disks, availability policy, SSH keys)

Creating an autoscaled managed instance group using an instance template

Generating/uploading a custom SSH key for instances

Configuring a VM for Stackdriver monitoring and logging

Assessing compute quotas and requesting increases

Installing the Stackdriver Agent for monitoring and logging



Deploying and implementing Google Kubernetes Engine resources. Tasks include:



Deploying a Google Kubernetes Engine cluster

Deploying a container application to Google Kubernetes Engine using pods

Configuring Google Kubernetes Engine application monitoring and logging

Deploying and implementing App Engine, Cloud Run, and Cloud Functions resources. Tasks include, where applicable:



Deploying an application, updating scaling configuration, versions, and traffic splitting

Deploying an application that receives Google Cloud events (e.g., Cloud Pub/Sub events, Cloud Storage object change notification events)



Deploying and implementing data solutions. Tasks include:



Initializing data systems with products (e.g., Cloud SQL, Cloud Datastore, BigQuery, Cloud Spanner, Cloud Pub/Sub, Cloud Bigtable, Cloud Dataproc, Cloud Dataflow, Cloud Storage)

Loading data (e.g., command line upload, API transfer, import/export, load data from Cloud Storage, streaming data to Cloud Pub/Sub)



Deploying and implementing networking resources. Tasks include:



Creating a VPC with subnets (e.g., custom-mode VPC, shared VPC)

Launching a Compute Engine instance with custom network configuration (e.g., internal-only IP address, Google private access, static external and private IP address, network tags)

Creating ingress and egress firewall rules for a VPC (e.g., IP subnets, tags, service accounts)

Creating a VPN between a Google VPC and an external network using Cloud VPN

Creating a load balancer to distribute application network traffic to an application (e.g., Global HTTP(S) load balancer, Global SSL Proxy load balancer, Global TCP Proxy load balancer, regional network load balancer, regional internal load balancer)



Deploying a solution using Cloud Marketplace. Tasks include:



Browsing Cloud Marketplace catalog and viewing solution details

Deploying a Cloud Marketplace solution

Deploying application infrastructure using Cloud Deployment Manager. Tasks include:



Developing Deployment Manager templates

Launching a Deployment Manager template



Ensuring successful operation of a cloud solution

Managing Compute Engine resources. Tasks include:



Managing a single VM instance (e.g., start, stop, edit configuration, or delete an instance)

SSH/RDP to the instance

Attaching a GPU to a new instance and installing CUDA libraries

Viewing current running VM inventory (instance IDs, details)

Working with snapshots (e.g., create a snapshot from a VM, view snapshots, delete a snapshot)

Working with images (e.g., create an image from a VM or a snapshot, view images, delete an image)

Working with instance groups (e.g., set autoscaling parameters, assign instance template, create an instance template, remove instance group)

Working with management interfaces (e.g., Cloud Console, Cloud Shell, GCloud SDK)



Managing Google Kubernetes Engine resources. Tasks include:



Viewing current running cluster inventory (nodes, pods, services)

Browsing the container image repository and viewing container image details

Working with node pools (e.g., add, edit, or remove a node pool)

Working with pods (e.g., add, edit, or remove pods)

Working with services (e.g., add, edit, or remove a service)

Working with stateful applications (e.g. persistent volumes, stateful sets)

Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)



Managing App Engine and Cloud Run resources. Tasks include:



Adjusting application traffic splitting parameters

Setting scaling parameters for autoscaling instances

Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)



Managing storage and database solutions. Tasks include:



Moving objects between Cloud Storage buckets

Converting Cloud Storage buckets between storage classes

Setting object life cycle management policies for Cloud Storage buckets

Executing queries to retrieve data from data instances (e.g., Cloud SQL, BigQuery, Cloud Spanner, Cloud Datastore, Cloud Bigtable)

Estimating costs of a BigQuery query

Backing up and restoring data instances (e.g., Cloud SQL, Cloud Datastore)

Reviewing job status in Cloud Dataproc, Cloud Dataflow, or BigQuery

Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)



Managing networking resources. Tasks include:



Adding a subnet to an existing VPC

Expanding a subnet to have more IP addresses

Reserving static external or internal IP addresses

Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)



Monitoring and logging. Tasks include:



Creating Stackdriver alerts based on resource metrics

Creating Stackdriver custom metrics

Configuring log sinks to export logs to external systems (e.g., on-premises or BigQuery)

Viewing and filtering logs in Stackdriver

Viewing specific log message details in Stackdriver

Using cloud diagnostics to research an application issue (e.g., viewing Cloud Trace data, using Cloud Debug to view an application point-in-time)

Viewing Google Cloud Platform status

Working with management interfaces (e.g., Cloud Console, Cloud Shell, Cloud SDK)



Configuring access and security

Managing identity and access management (IAM). Tasks include:



Viewing IAM role assignments

Assigning IAM roles to accounts or Google Groups

Defining custom IAM roles



Managing service accounts. Tasks include:



Managing service accounts with limited privileges

Assigning a service account to VM instances

Granting access to a service account in another project



Viewing audit logs for project and managed services.



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Google 2023 exam success

 

Snigel Earns Prestigious Google Certified Publishing Partner Status

DUBLIN, June 12, 2023 /PRNewswire/ -- Snigel, an award-winning advertising technology company, is excited to announce that it has been recognized as a Google Certified Publishing Partner (GCPP). This certification solidifies Snigel's position as a longstanding Google partner and showcases its proficiency across a variety of Google advertising products like Google Ad Manager. The partnership signifies Snigel's dedication to working hand-in-hand with publishers, fostering growth, and unlocking new opportunities in a highly competitive landscape.

The GCPP certification process involved a rigorous evaluation of Snigel's ability to deliver exceptional service, uphold the highest performance standards, and consistently meet and exceed publisher expectations. The accomplishment highlights Snigel's commitment to empowering online publishers to maximize ad revenue with Google's suite of advanced tools.

GCPP partners stay ahead of the curve by working directly with Google. With access to training and product updates, Partners stay on top of the latest Google products and features by passing Google-administered certification exams every year. The GCPP certification bolsters Snigel's collaboration with Google and reaffirms its commitment to providing publishers with cutting-edge strategies and advanced monetization technologies that maximize results.

Since it was founded in 2012 by two former Google executives, Snigel has steadily built a reputation as an innovative and dependable monetization partner for over 200 of the world's largest websites. This recognition, combined with its extensive technical know-how, has led to market-leading growth, landing Snigel on both 'Deloitte's Technology Fast 50' and the 'FT 1000: Europe's Fastest Growing Companies' lists in consecutive years.

At the heart of Snigel's success is its technology platform, AdEngine. Powered by Machine Learning, AdEngine optimally matches ads with available impressions, delivering superior results for publishers and advertisers. Snigel continues to innovate by introducing AI-powered ad setup optimization tools, automated UI customization, and robust data analytics capabilities.

Snigel provides each publisher with a dedicated Ad Operations specialist who not only implements a customized ad strategy and ad setup for the website but also activates new ad technologies including next-gen ad formats as they emerge and ensures the website's user consent management is compliant with the multitude of emerging global regulations.

Christian Jeschko and Ben Rycroft, Co-CEOs of Snigel, commented, "Becoming a Google Certified Publishing Partner is an important milestone for Snigel. This recognition further validates our expertise and dedication to helping publishers maximize their ad revenue. We are proud to partner with Google and look forward to continuing our work in delivering exceptional results for our clients."

About Snigel:

Snigel is an award-winning advertising technology company that empowers online publishers to maximize their ad revenue through programmatic advertising. Since its inception in 2012, Snigel has consistently ranked among Europe's fastest-growing companies. Over 200 of the world's largest websites rely on Snigel's market-leading monetization technology, supported by its seasoned team of ad operations experts. With headquarters in Dublin and teams located throughout Europe, Snigel remains at the forefront of ad tech innovation.

For further information, visit www.snigel.com

Media inquiries: Ira Nikolaou Head of Marketing ira@snigel.com

View original content:https://www.prnewswire.com/news-releases/snigel-earns-prestigious-google-certified-publishing-partner-status-301848071.html

SOURCE Snigel

© 2023 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.


Opinion: Jim Martin: To minimize risks and maximize benefits, AI must be developed responsibly

Artificial Intelligence poses a human-extinction risk equally dangerous as a nuclear war, tech leaders warn. 

One danger is that it could undermine the fabric of our society because people no longer will be able to tell the difference between what’s real and what’s not. The effects on the 2024 presidential election may be profound.

Jim Martin for the Camera Jim Martin for the Camera

The late, legendary physicist Stephen Hawking shared this ominous warning: “Success in creating effective AI could be the biggest event in the history of our civilization. Or the worst. We just don’t know. So we cannot know if we will be infinitely helped by AI, or ignored by it and side-lined, or conceivably destroyed by it.”

In March, more than 1,000 technology leaders and researchers working in AI signed an open letter warning that AI technologies present “profound risks to society and humanity,” according to The New York Times. Many of the leaders appeared before a Senate subcommittee hearing on May 16, and they all were in agreement that regulations were needed before it is too late.

Meanwhile, AI recently grabbed our attention. It’s vital that we know what it is, and that we respect and fear its capabilities.

That’s because ChatGPT (Generative Pre-Trained Transformer) released an AI chatbot in November. That triggered a new global race in AI that involves Microsoft, Google and other tech giants that are desperately trying to catch up. (An AI chatbot is a computer program designed to simulate conversation with human users, especially over the internet.)

The rapid growth of ChatGPT has been shocking, whether you are asking it simple or complicated questions. In addition, a newer, more powerful version of ChatGPT has just been released — and it shows early signs of developing something like human reasoning.

AI is a fast-growing field of technology that is transforming the way we live and work. From self-driving cars to voice assistants, AI is already a part of our daily lives, and its potential applications are nearly limitless.

It can process vast amounts of data, learn from experience and make predictions and decisions based on that data. As AI evolves, it has the potential to bring many benefits to the human race, such as improving health care, transportation and communication systems, as well as making work more efficient and less repetitive.

AI’s knowledge base seems to have no boundaries. AI has the ability to transform educational systems at all levels. Almost 30% of college students already use ChatGPT, mainly to research and write term papers and more — even for poetry. AI is now outperforming human test scores on SAT, ACT, LSAT and MCAT exams. It can have conversations on almost any topic, generate lyrics in the style, for example, of Taylor Swift or Billy Joel, and suggest edits to computer programming code.

ChatGPT can write resumes, compose song lyrics and poetry, and plan a party or an event. AI can translate written material such as reports and term papers into Spanish and other languages. It’ll even tell you what to pack for a vacation or what to wear or do on a first date and so much more.

Besides showing early signs of something like human reasoning, experts fear AI could become sentient, which could enable it to think, feel and perceive the physical world around it, just as humans do.    

Geoffrey Hinton, who’s considered the godfather of AI, caused a stir when he announced his resignation from Google, saying he regretted his work in developing AI. Other experts also are speaking out about AI’s negative side.

Extreme risks will include job displacement and the concentration of power in the hands of a few entities that will create an imbalance in society and pose extreme risk to our democratic principles.

A new report from Goldman Sachs forecasted that AI could eventually replace a quarter of the full-time jobs in the United States and Europe.

Other risks include the expansion of existing human biases, privacy concerns, surveillance potential, the danger of overuse of facial recognition capabilities and the ability to process large amounts of information, which can have significant privacy risks. AI also can create smart systems that threaten our electrical grid, finance industry, our elections and so much more.

This may sound grim, but all is not lost. AI has huge potential for positive results as well.

AI is in the beginning stages where we can spot lung cancer faster than any other existing method and also can predict pancreatic cancer three years earlier than current technology. 

The Biden administration recently announced steps, including $140 million in new research efforts, to promote responsible AI innovation and to protect people’s rights and safety.

Scientists warn of AI’s dangers and not all agree on the solutions.

ChatGPT provided some solutions to AI-created problems:

Both the tech industry and Congress agree that regulations on the development of more AI are needed soon.

Now is the time to: 

• Develop AI responsibility and encourage transparency, accountability and ethical considerations in AI research and development.

• Promote AI education and retooling: Invest in education and training programs that equip individuals with skills needed for jobs in an AI-driven economy.

• Address bias and discrimination: Implement guidelines and regulations to ensure AI systems are developed and deployed in ways that minimize bias and promote fairness.

• Strengthen data privacy: Establish a robust data protection framework and encourage the development of privacy-preserving AI technology.

• Establish international cooperation: Foster global collaboration on AI policy and regulation to address shared risk and ensure benefits are distributed equitably.

By addressing these concerns, we can work to ensure that AI develops in a way that is beneficial and safe for society.

Ultimately, AI’s impact on people will depend on how it is developed, deployed and regulated. By ensuring that AI is developed in a responsible and ethical manner, and that its benefits are distributed fairly, we can maximize the potential benefits of this technology while minimizing its risks.

Hinton, the godfather of AI, gets the final word: “Humanity’s survival is threatened when smart things can outsmart us.” 

Jim Martin can be reached at jimmartinesq@gmail.com.


 




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