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The New Stack | DevOps, Open Source, and Cloud Native News

Agentic development hinges on verification. For cloud-native software, that is a runtime problem. AI agents need infrastructure: Why Europe’s regional cloud strategy matters Transform your AI coding agent into a deterministic Java Spring expert WeAreDevelopers is coming to the US to give unsung developers a bigger voice Cleaner AI training data, fewer bugs: Sonar’s SonarSweep explained Observability overload is drowning engineers Google’s DiffusionGemma is 4x faster than its other Gemma models Fable 5: Guardrails and burn rate are annoying users, who say it’s still better than Opus 4.8 The Anthropic leader who built Claude Code says he ditched prompting — now he just writes loops. AWS can now mathematically prove your VMs are isolated Microsoft pulled 73 GitHub repos after malware attack — but still won’t say who’s compromised Databricks wants to kill the “email me a file” problem for AI agent skills Ramp bets forward deployed engineers can do what off-the-shelf finance AI can’t Git real: AI agents aren’t just for solo developers anymore Anthropic launches Claude Mythos/Fable 5, but you better try it soon Spring is 23 years old. AI just made it a security emergency. This AI agent startup ditched Anthropic for DeepSeek — and says it’s saving millions When your data model is the bottleneck: lessons from Medium’s feature store How long before we stop reading the code? The tokenmaxxing party is over, and Revenium is mopping up How AI is solving the memory crunch it created Microsoft’s pitch to enterprises: Ditch Azure Repos for GitHub, despite its rocky reliability record Claude Code’s biggest upgrade yet ran 5 agents at once — here’s what happened Why Anthropic just doubled Claude Cowork limits at no charge For years, Apache Cassandra handed this work to your team — 6.0 takes it back “A dangerous combination”: The 2 factors that can “corrupt” AI agent workflows With Foundry, Microsoft bets the enterprise AI battle is about reliability, not capability Microsoft unlocks Visual Studio for developers left behind by its own AI AI teams now deploy 1,000 times a month. Your pipeline wasn’t built for that. Microsoft just made the agent runtime free — and kept everything around it
Snowflake commits $6B to AWS as it pushes deeper into AI
Frederic Lardinois · 2026-05-28 · via The New Stack | DevOps, Open Source, and Cloud Native News

Snowflake is committing $6 billion over five years to Amazon Web Services for Graviton compute and AI infrastructure, the data company’s largest cloud spend commitment to date and a clear sign of its ambitions in the AI space.

This multi-year strategic collaboration agreement, announced by AWS on Wednesday, covers AWS’s ARM-based Graviton processors and GPU-accelerated EC2 instances, which Snowflake will use for AI model training and inference. 

Interestingly, there’s no mention of AWS’s specialized Trainium chips here (though there are accelerated EC2 instances with Trainium chips attached). Since AWS’s announcement specifically refers to “GPU-accelerated” instances, the focus here is likely on Nvidia GPUs.

Given that Snowflake supports a variety of cloud vendors, the company likely doesn’t want to lock itself into a vendor-specific platform (and commit engineering resources to support it). For ARM-based general compute instances, this is far less of a worry at this point.

The deal also expands the two companies’ joint go-to-market through AWS Marketplace, where AWS says Snowflake has now surpassed $7 billion in lifetime sales.

A $6 billion commitment is notable on its own (that’s 6 Instagrams, after all), but what’s maybe just as interesting here is that Snowflake will use AWS’s cost-efficient Graviton instances to help power Snowflake’s traditional data warehousing business — and maybe free up financial resources for the far more expensive AI training and inferencing workload.

Snowflake’s AI pivot

Under CEO Sridhar Ramaswamy, who succeeded Frank Slootman in 2024, Snowflake has been repositioning from a cloud data warehouse into what the company now calls “the platform for the AI era.”

Cortex AI, Snowflake’s suite of AI products, lets customers build and deploy applications for text-to-SQL, summarization, sentiment analysis, and entity extraction directly on governed data inside Snowflake. With Cortex Code, Snowflake also offers an AI coding agent.

“We are moving into the era of the agentic enterprise, where AI systems don’t just answer questions, but help organizations reason over trusted data, coordinate workflows, and drive real business outcomes,” Ramaswamy says in the announcement. “With AWS, we are making it easier for enterprises to bring AI directly to governed data.”

Snowflake expands its AWS region

Snowflake is also expanding its AWS footprint to 10 new regions, including New Zealand, South Africa, Thailand, and the AWS European Sovereign Cloud. The sovereign cloud piece here is especially important, given that enterprises are increasingly dealing with localized data residency requirements (especially in Europe). Support for these is becoming a prerequisite for many companies when choosing a vendor — and not just for AI workloads.

Snowflake Summit

It’s worth noting that Snowflake’s annual Summit conference is happening June 1-4 in San Francisco. It doesn’t take a crystal ball to predict that we will hear more about the company’s AI focus — and how it plans to use all of these compute resources — there.

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