Chevron Left
返回到 Reliable Google Cloud Infrastructure: Design and Process

学生对 Google 云端平台 提供的 Reliable Google Cloud Infrastructure: Design and Process 的评价和反馈

4.7
4,960 个评分
512 条评论

课程概述

This course equips students to build highly reliable and efficient solutions on Google Cloud using proven design patterns. It is a continuation of the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine courses and assumes hands-on experience with the technologies covered in either of those courses. Through a combination of presentations, design activities, and hands-on labs, participants learn to define and balance business and technical requirements to design Google Cloud deployments that are highly reliable, highly available, secure, and cost-effective. This course teaches participants the following skills: ● Apply a tool set of questions, techniques, and design considerations ● Define application requirements and express them objectively as KPIs, SLOs and SLIs ● Decompose application requirements to find the right microservice boundaries ● Leverage Google Cloud developer tools to set up modern, automated deployment pipelines ● Choose the appropriate Cloud Storage services based on application requirements ● Architect cloud and hybrid networks ● Implement reliable, scalable, resilient applications balancing key performance metrics with cost ● Choose the right Google Cloud deployment services for your applications ● Secure cloud applications, data, and infrastructure ● Monitor service level objectives and costs using Google Cloud tools Prerequisites ● Completion of prior courses in the Architecting with Google Cloud Platform Specialization, Architecting with Google Kubernetes Engine or have equivalent experience ● Basic proficiency with command-line tools and Linux operating system environments ● Systems Operations experience including deploying and managing applications, either on-premises or in a public cloud environment...

热门审阅

RI

Aug 28, 2019

It was a wonderful course were I got to understand principles involved in business logic, determining youreaSLA, SLI and SLO and so many other design principles relevant for an end product scale.

ZJ

Oct 26, 2018

The course consists of up-to-date, rigorous, and interesting concepts. It is well-structured and well-narrated. I am excited and ready to try another specialization with Google Cloud.

筛选依据:

476 - Reliable Google Cloud Infrastructure: Design and Process 的 500 个评论(共 511 个)

创建者 Muhammad A N

Feb 06, 2019

Good

创建者 Ying K N

Jul 15, 2018

Good

创建者 Vishwa S

Mar 04, 2019

Good informative, but too long compared to previous courses. I recommended breaking it into 3 weeks instead of 2. Would like to see Jason Baker speak a little slow without talking too fast. I had to watch few times to grasp the all the information. However, the slides are really good. The challenges and that logging application idea gives a good understanding. The lab is kind of disappointing, I expected it to have more content with better organization.

创建者 Henrik H

Oct 04, 2019

The course was good. Good content, but there was so many errors and corrections in the slide decks, transcript errors and video errors. I find this unprofessional considering this is a recorded course and there should have been so many opportunities to correct those.

Also so many anecdotes that just made this course longer than necessary.

创建者 Marko V

Jan 03, 2019

Jason Baker is a great teacher. Finally a course in this certification that had a real teacher instead of human robots. Other instructors in the this course were just another robots making noise and not really contributing or teaching much.

创建者 Zlatan B

Apr 26, 2019

A lot of technical problems, the sound volume between two speakers is 80% off, the first quicklab makes no sense, does not let you move forward, the lectures are kind of butchered etc.

创建者 Ranjith K

Oct 09, 2019

this course was the most boring of all. All the other courses were nice and flawless. I had much interest throughout other courses in this specialization but this one held me back.

创建者 hleb v

Feb 16, 2019

one trainer is speaking too quietly. another one is speaking in a hurry, swallowing sound and words, making mistakes. without subtitles it's impossible to understand them.

创建者 John E

Jul 12, 2018

If you went through the other five courses, the lectures and lab here are overlap.Also the labs are harder to follow in this module that the prior 5.

创建者 Qingsheng L

Oct 01, 2019

It's too fast... I know you guys want to zip in as much information as possible but this course is really too hard to catch up with.

创建者 Marco M

Apr 29, 2019

Some labs were not working at the time I tried... issue seemed resolved by the time I reached the end of the course.

创建者 Aakash K

Oct 22, 2019

This course is not good as other than in which we are not able to under stand quick lab what he is want in his lab

创建者 Nishant

Jun 07, 2018

Lab3 deployment didn't work. Followed the lab. Gives me something to troubleshoot later if I use that template.

创建者 Giovanni V

Mar 22, 2020

Useful because it's a summary of the first four courses.

The LAB activities are very trivial, not so interesting.

创建者 Weikang S

Feb 21, 2019

course content could be refined and edited; currently it is more of a presentation.

创建者 Dhruv S

Aug 29, 2019

This course is cool but labs and practical learnings could have been more better!!

创建者 Davit B

Dec 08, 2019

It should have more practice, but turned out to be more theory.

创建者 Ammar B

Feb 25, 2019

instructor seems knowledgeable and fun, but he'd speak slower .

创建者 Denis Z

Jan 06, 2020

not that comprehensive and structured as I expected

创建者 Filipe G

Dec 03, 2019

not as good as the others in the series

创建者 Anjang P

Oct 31, 2019

too many video, less lab

创建者 Shaiju P

Mar 31, 2019

little bit boring

创建者 Vinothkumar D

Nov 25, 2018

Good

创建者 Mathieu M

Apr 05, 2020

Hello,

Second time for a coffee :)

Please review all the labs of the present course to fit with the specialization labs format. Simplify, go toward essential. I find there is a kinda repetition during the specialization, it's the second time I implement a logbook application. Missing a global specialization timeline. A lack of coherence between theoretical course and practical.

The labs could be so much more practicals, you discussed during all the theoretical course about an application which we never had the possibility to exploit/deploy, how frustrating.

In my opinion, the first lab could be:

OK we don't have the application from the dev, but we they gave us the format of data we can expect + a dataset, first guide the student to generate a

simple mockup of frontend based on Google functions+pub-sub to simulate the calls (Via G console). With templates & provided really deploy the dev part of the application that was described with the first limitation.

Then each labs would start by getting the last iteration corrected of the previous lab from a bucket you provide, first application delivered will have a a poor design which will be modified at each iteration.

Introduce the log management proposed each time and show the student where to find lead to point at the current solution problem (ex: generating fake logs during the first steps), then show how to modify the current deployment template to circumvent the limitation.

Each time add verification steps with pre-named resources like in other courses labs which ensure the progression of the student and do not generate frustration over deployment failure.

We do not need to have a high consuming application, but it should be a lite version of what was discussed.

I hope my reviews won't be too much a bother, I just hope to be able to help you to improve the quality of your course ;) Have a good day.

Regards

创建者 Alvin P E

Oct 30, 2018

repeated labs and material more of deployment manager labs and notes which was already covered. very less of solution discussion. the whole course felt unnesccesary. mostly all covered direcly or indirecly in other course in the series. It would be great if the course had most common solutions like java jee spring/python djaogo production scale or serverles ETL end to end or datawarehouse analytics solution covering all design concpets of resilient high availaility etcc on such projects and covering labs for the same.