Google Cloud Platform

Name: Google Cloud Platform
Rating: 4.98 (169 reviews)

A suite of cloud computing services by Google

5.0•169 reviews•

1.8K followers

A suite of cloud computing services by Google

5.0•169 reviews•

1.8K followers

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Cloud Computing Platforms

Build with generative AI, deploy apps fast, and analyze data in seconds with Google-grade security.

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Google Cloud Platform Launches

Google Cloud RunBringing serverless to containers

Launched on April 15th, 2019

Cloud Composer, by GoogleA fully managed workflow orchestration service

Launched on May 1st, 2018

Google Cloud Text-To-SpeechText to speech conversion powered by machine learning

Launched on March 28th, 2018

Google Cloud TPUsBuild and train machine learning models with Google

Launched on May 17th, 2017

Google Cloud PostgreSQLFully-managed database service

Launched on March 9th, 2017

View all Google Cloud Platform launches

5.0

Based on 169 reviews

Review Google Cloud Platform?

Reviewers mostly see Google Cloud Platform as reliable, easy to scale, and practical for shipping products without managing too much infrastructure. Makers of products like Greta, ClawMetry, and Claro - Research Agents say its compute, AI, data, and managed services help them move faster, handle global traffic, and reduce operational overhead. Still, the only direct user review adds a note of caution: compared with AWS, some offerings feel less mature, with gaps that can push teams to third-party tools.

+168

Summarized with AI

Pros

robust infrastructure (25)

scalability (22)

AI/ML capabilities (11)

startup program credits (10)

easy to use (7)

enterprise-grade security (7)

seamless integration with Google services (4)

Cloud Storage (3)

data analytics tools (3)

global reach (3)

Pros

Cons

Reviews

All Reviews

Most Informative

used Google Cloud Platform to build Claro - Research Agents

•3 reviews

Claro runs on Google Cloud. BigQuery is our analytical backbone, we store and query millions of rows of supplier data, enrichment history, and confidence metadata there. On top of that, the full data science stack (Vertex AI, notebooks, model training environments) is where our team runs experiments, benchmarks new validation approaches, and iterates on scoring logic. GCP gives us the throughput for parallel LLM calls (multi-model consensus), the storage for customer knowledge bases, and the flexibility to orchestrate long-running enrichment jobs across thousands of rows.

Alternatives Considered

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1 view6d ago

used Google Cloud Platform to build GyftPro

•3 reviews

We chose Google Cloud Platform (GCP) for GyftPro due to its unmatched reliability, scalability, and extensive range of tools that empower our app's development and operations. GCP’s powerful data processing and AI capabilities integrate seamlessly with our AI-driven gift recommendation engine, ensuring efficient and accurate performance. Compared to alternatives, GCP offers top-tier security, robust infrastructure, and innovative machine learning services that enhance our ability to provide personalized gift suggestions and support a seamless user experience. With GCP, GyftPro can scale effortlessly, meeting user demands during peak times like holidays, ensuring reliability and responsiveness.

What's great

scalability (22)enterprise-grade security (7)robust infrastructure (25)AI/ML capabilities (11)

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30 views1yr ago

used Google Cloud Platform to build PageTest.AI

•6 reviews

GCP offers fast, scalable infrastructure with easy-to-integrate APIs and strong support for AI and machine learning workloads. It gave us the flexibility to build PageTest.AI quickly, with global reliability and cost efficiency—ideal for a bootstrapped launch. Alternatives considered: AWS, Azure Why we chose GCP: GCP struck the right balance between performance, pricing, and ease of use—especially with strong AI/ML tooling and generous free tiers for getting started quickly.