Reviewers see Google Cloud Platform as a strong, developer-friendly cloud for shipping and scaling apps, APIs, data pipelines, and AI workloads. Users especially praise Cloud Run, BigQuery, Cloud Storage, and the broad managed-service lineup, saying they reduce the need for extra infrastructure. Makers of Greta, Needle, and Fabraix also highlight reliable compute, smooth service integration, and useful AI tooling. Main complaints are harder-to-predict pricing, complex IAM permissions, uneven docs, and some gaps versus AWS maturity.

+193

Summarized with AI

Pros

robust infrastructure (26)

scalability (20)

AI/ML capabilities (11)

startup program credits (10)

easy to use (5)

enterprise-grade security (5)

seamless integration with Google services (4)

Cloud Storage (3)

data analytics tools (3)

global reach (3)

Pros

Cons

Reviews

All Reviews

Most Informative

•11 reviews

What's great

robust infrastructure (26)

Google Cloud Platform has been my go-to cloud provider for deploying Python applications, APIs, data pipelines, and AI workloads. Cloud Run makes deployments simple, BigQuery is excellent for analytics, and Cloud Storage integrates seamlessly with the rest of the platform. The breadth of services means I rarely need third-party infrastructure, and everything scales well as projects grow.

What needs improvement

The platform is extremely capable, but pricing can become difficult to estimate across multiple services. IAM permissions are also quite complex for new users, and some products have documentation that could be more consistent. Better cost forecasting and simpler permission management would make the platform even easier to adopt.

vs Alternatives

I evaluated AWS, Azure, and DigitalOcean. I chose Google Cloud because Cloud Run, BigQuery, and the overall developer experience fit my workflow better. For AI projects, data engineering, and containerized applications, GCP provides a strong balance between ease of use, scalability, and managed services.

Ratings

Ease of use

Reliability

Value for money

Customization

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10 views26d 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 (20)enterprise-grade security (5)robust infrastructure (26)AI/ML capabilities (11)

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37 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.

What's great

easy to use (5)free tier (1)scalability (20)global reach (3)robust infrastructure (26)AI/ML capabilities (11)

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29 views1yr ago

used Google Cloud Platform to build SimplAI

•3 reviews

Google Cloud Platform (GCP) stands out due to its superior AI/ML capabilities, high-performance networking, and seamless integration with Google’s ecosystem. Its global fiber network ensures low-latency connectivity, while BigQuery and Vertex AI make data analytics and machine learning more accessible

What's great

seamless integration with Google services (4)AI/ML capabilities (11)Vertex AI (2)high-performance networking (2)BigQuery (2)

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16 views1yr ago

used Google Cloud Platform to build ittybit

•5 reviews

There’s merits to all the hyperscale clouds but we’ve chosen GCP for several of our core services. They get containers right with Cloud Run, we use PubSub heavily for async workflows, and Gemini has first-class models at a range of price points.

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8 views1yr ago

used Google Cloud Platform to build PRISM by Block Convey

•3 reviews

As part of the Google for Startups program, we gained access to technical mentorship, cloud credits, and a global network of innovators. This collaboration allowed us to refine PRISM’s architecture, optimize costs, and fast-track integrations with critical fintech ecosystems. While we’re proud to leverage Google’s infrastructure and resources, Block Convey operates independently—ensuring our solutions remain unbiased, flexible, and tailored to fintech’s unique needs.

What's great

global reach (3)startup program credits (10)robust infrastructure (26)

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6 views1yr ago

used Google Cloud Platform to build Pebbles Ai

•3 reviews

GCP is our AI infrastructure backbone. We didn't choose it just for scale – though it handles that too. Being part of the Google for Startups program gives us personal extended access to the tools and support that actually matter at our stage. For a B2B product like ours, data containment and tenant isolation are non-negotiable. Our customers trust us with sensitive GTM data, and GCP's security model gives us the architecture to honour that promise. Our CASA 2 certification backs that up – our security posture has been independently validated, not self-declared. On top of that, the native AI/ML tooling – Vector DB, inference, RAG – means we're building on primitives that are genuinely production-ready, not bolted-on afterthoughts.

Alternatives Considered

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8d ago

used Google Cloud Platform to build Proxy 1.0

•3 reviews

Google Cloud Platform has been essential to our infrastructure. Their robust cloud services helped us build and scale efficiently, while their powerful compute options enabled rapid development and deployment. The comprehensive documentation and enterprise-grade security made GCP a natural choice for building reliable systems at scale.

What's great

scalability (20)enterprise-grade security (5)robust infrastructure (26)

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6 views1yr ago

•6 reviews

Amazing for the most bit, I do feel like they are not as advance as AWS. Even their product offerings arent as mature as AWS. For example AWS has their own SMTP offering which you can use to build an email notification system. With GCP you are forced to go through a third party like SendGrid.

What needs improvement

less mature product offerings compared to AWS (1)

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8 views1yr ago

used Google Cloud Platform to build Needle

•8 reviews

We use Google Cloud Platform and love how thoughtfully their services are designed. The pieces fit together naturally, letting us build powerful software systems. Whether going serverless, containerized, or hybrid - GCP makes our lives easier. Solid engineering! 🚀

What's great

easy to use (5)

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3 views1yr ago

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