Deploying Agents: AWS vs Azure vs GCP (Real-World Decision Guide) Agentic AI

Which cloud should you use for deploying agents?

I get this question every week.

The answer: It depends less on the clouds and more on your constraints.

Complete comparison:

🔹 AWS

• Strengths: Most mature, best docs, Lambda + Bedrock
• Weaknesses: Pricing complexity
• Cost: $1,127/month (100K requests)
• Best for: Startups, general use

🔹 Azure

• Strengths: Enterprise integration, OpenAI exclusive
• Weaknesses: Service naming confusing
• Cost: $843/month (100K requests)
• Best for: Enterprises, Microsoft shops

🔹 GCP

• Strengths: Clean APIs, best for ML, fast cold starts
• Weaknesses: Fewer enterprise features
• Cost: $1,140/month (100K requests)
• Best for: ML-heavy workloads

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📊 KEY INSIGHTS:

Cost difference: 25% max

• Not 2x or 10x
• LLM tokens = 70-90% of cost
• Infrastructure = 10-30%

Choose based on:

1. Existing infrastructure
2. Team expertise
3. LLM requirements
4. Compliance needs
5. Geographic distribution
6. Budget model

Don't migrate unless:

• Saving >30% on $50K+/month
• LLM requirements force it
• Acquisition/merger