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Google Cloud Platform

A suite of cloud computing services
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What is Google Cloud Platform?

It helps you build what's next with secure infrastructure, developer tools, APIs, data analytics and machine learning. It is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube.
Google Cloud Platform is a tool in the Cloud Hosting category of a tech stack.

Who uses Google Cloud Platform?

8547 companies reportedly use Google Cloud Platform in their tech stacks, including CRED, Snapchat, and Revolut.

10537 developers on StackShare have stated that they use Google Cloud Platform.

Google Cloud Platform Integrations

Google App Engine, Contentful, Dapr, CanvasJS , and Google Cloud Load Balancing are some of the popular tools that integrate with Google Cloud Platform. Here's a list of all 50 tools that integrate with Google Cloud Platform.
Pros of Google Cloud Platform
1 year free trial credit USD300
Good app Marketplace for Beginner and Advanced User
Premium tier IP address
Live chat support
Decisions about Google Cloud Platform

Here are some stack decisions, common use cases and reviews by companies and developers who chose Google Cloud Platform in their tech stack.

I am currently working on a long term mobile app project. Current stack: Frontend: Dart/Flutter Backend: Go, AWS Resources (AWS Lambda, Amazon DynamoDB, etc.) Since there are only two developers and we have limited time and resources, we are looking for a BAAS like Firebase or AWS Amplify to handle auth and push notifications for now. We are prioritizing developing speed so we can iterate quickly. The only problem is that AWS amplify support for flutter is in developer preview and has limited capabilities (We have tested it out in our app). Firebase is the more mature option. It has great support for flutter and has more than we need for auth, notifications, etc. My question is that, if we choose firebase, we would be stuck with using two different cloud providers. Is this bad, or is this even a problem? I am willing to change anything on the backend architecture wise, so any suggestions would be greatly appreciated as I am somewhat unfamiliar with Google Cloud Platform. Thank you.

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Hello Everyone, My motive is to build an MLOps pipeline that is 100% independent from Cloud services like AWS, Google Cloud Platform, and Microsoft Azure. I have a project for a client in a production factory and would like to build a Camera based Object Tracking ML service for them. I want to build this pipeline in my own server or (on-premise computer). I am really confused about what stacks I should use. I keep ending up with a Cloud component based solution. It would be great to get some advice on what are the components that I can use and preferably open source.

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Sumit Singh Chauhan
Data Scientist at Entropik · | 6 upvotes · 23.1K views

I have started using AWS Batch for some long ML inference jobs. So far it's working well and giving a decent performance. Since it is fully managed, it saves a lot of extra work as well. But Batch takes a good amount of time to create a new cluster and then load the job based on the priority of the queue. Going forward would love to put effort into something which is fast to start and give more flexibility as well. What other tools you would suggest for long-running backend jobs which can scale well. I am not looking for something fully managed so ignore the options similar to batch in Google Cloud Platform or Microsoft Azure, Looking for open-source alternatives here. Do you think Kubernetes, RabbitMQ/Kafka will be a good fit or just overkill for my problem. Usually w we get 1000s of requests in parallel and each job might take 20-30 mins in a 2 vCPU system.

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Shared insights
Google Cloud PlatformGoogle Cloud Platform

I am new to the cloud platforms. I am trying to figure out which Google Cloud product would be the best fit for my needs. Here are the requirements I am trying to meet:

  1. Store data in Google Cloud Platform.
  2. Support potentially thousands of concurrent users running analytical queries.
  3. The data volumes would be moderate (as far as Google is concerned) - we are talking 10's of GB up to potentially 100s of GB.
  4. The data needs to be updated once a day (but ideally a few times a day).
  5. Perhaps my biggest goal is the following: I am trying to avoid having to build a traditional data warehouse with star-schema and ETL process. I have experience with these projects, and they end up being very costly, error-prone, hard to troubleshoot, and rigid (hard to deploy changes). Instead, I am hoping to just copy my OLTP tables to GCP and query them from there, relying on GCP horsepower. I appreciate any feedback.
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Jenil Calcuttawala
Software Engineer at Servian · | 5 upvotes · 3.9K views

Hello folks, we are making a company internal google chatbot system hosted on Google Cloud Platform. The backend is being written in ExpressJS + TypeScript, we are planning to use Cloud SQL to store basic entities like Users, Spaces, Connections(use-case specific).

The question I have is which tool is recommended for this basic use case where we want to query some data and perform CRUD operations. Also, how we should be handling the DB version control & migrations?

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Blog Posts

Sep 29 2020 at 7:36PM


PythonSlackG Suite+17

Google Cloud Platform's Features

  • Scales automatically
  • No server management

Google Cloud Platform Alternatives & Comparisons

What are some alternatives to Google Cloud Platform?
Microsoft Azure
Azure is an open and flexible cloud platform that enables you to quickly build, deploy and manage applications across a global network of Microsoft-managed datacenters. You can build applications using any language, tool or framework. And you can integrate your public cloud applications with your existing IT environment.
Go Daddy makes registering Domain Names fast, simple, and affordable. It is a trusted domain registrar that empowers people with creative ideas to succeed online.
Google App Engine
Google has a reputation for highly reliable, high performance infrastructure. With App Engine you can take advantage of the 10 years of knowledge Google has in running massively scalable, performance driven systems. App Engine applications are easy to build, easy to maintain, and easy to scale as your traffic and data storage needs grow.
Amazon Web Services
It provides on-demand cloud computing platforms to individuals, companies and governments. It offers reliable, scalable, and inexpensive cloud computing services.
Google Compute Engine
Google Compute Engine is a service that provides virtual machines that run on Google infrastructure. Google Compute Engine offers scale, performance, and value that allows you to easily launch large compute clusters on Google's infrastructure. There are no upfront investments and you can run up to thousands of virtual CPUs on a system that has been designed from the ground up to be fast, and to offer strong consistency of performance.
See all alternatives

Google Cloud Platform's Followers
8525 developers follow Google Cloud Platform to keep up with related blogs and decisions.