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(2026)",{"type":14,"tag":23,"props":24,"children":25},"p",{},[26],{"type":20,"value":27},"Amazon S3 is the world's default object store; IronShard is governed, S3-compatible storage built specifically for AI agents. The short answer: choose S3 for petabyte-scale training data and deep AWS integration; choose IronShard when agents are first-class users of your storage and you need agent self-provisioning, zero-egress reads, isolated forks of production data, and a signed audit record. Because IronShard speaks the S3 API and Mirror keeps a governed, continuously synced copy of production S3, this is not always an either/or decision.",{"type":14,"tag":23,"props":29,"children":30},{},[31,33,40],{"type":20,"value":32},"Comparing more providers? See the ",{"type":14,"tag":34,"props":35,"children":37},"a",{"href":36},"/compare/object-storage-comparison",[38],{"type":20,"value":39},"six-way comparison",{"type":20,"value":41}," covering R2, GCS, Azure Blob, and MinIO as well.",{"type":14,"tag":43,"props":44,"children":46},"h2",{"id":45},"at-a-glance",[47],{"type":20,"value":48},"At a glance",{"type":14,"tag":50,"props":51,"children":52},"table",{},[53,75],{"type":14,"tag":54,"props":55,"children":56},"thead",{},[57],{"type":14,"tag":58,"props":59,"children":60},"tr",{},[61,65,70],{"type":14,"tag":62,"props":63,"children":64},"th",{},[],{"type":14,"tag":62,"props":66,"children":67},{},[68],{"type":20,"value":69},"Amazon 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It offers eleven nines of durability, objects up to 5TB, storage classes from Express One Zone to Glacier Deep Archive, and the deepest IAM ecosystem available. If your AI stack is built on Bedrock or SageMaker, S3 is the path of least resistance, and at petabyte scale it remains the safest choice.",{"type":14,"tag":43,"props":312,"children":314},{"id":313},"what-is-ironshard",[315],{"type":20,"value":316},"What is IronShard?",{"type":14,"tag":23,"props":318,"children":319},{},[320,322,328],{"type":20,"value":321},"IronShard is the governed data layer for AI agents: an S3-compatible bucket agents connect to over MCP, with a live fork of production they can safely work on, zero-egress reads by default, per-agent access control, and a signed record of everything they touch. It also runs a public MCP server for object storage, which is how agents provision and operate buckets on their own. Under the hood it fragments, encrypts, and distributes data across multiple storage providers, so no single provider holds a complete file; this is also the basis of its ",{"type":14,"tag":34,"props":323,"children":325},{"href":324},"/docs/gdpr-everywhere",[326],{"type":20,"value":327},"GDPR-everywhere",{"type":20,"value":329}," posture. IronShard is in early access.",{"type":14,"tag":43,"props":331,"children":333},{"id":332},"can-an-ai-agent-create-its-own-storage-bucket",[334],{"type":20,"value":335},"Can an AI agent create its own storage bucket?",{"type":14,"tag":23,"props":337,"children":338},{},[339,341,347,349,354,356,362],{"type":20,"value":340},"On S3, no. A human or a deploy pipeline must create the bucket, author the IAM policy, and mint credentials before an agent can store a single byte. On IronShard, yes: an agent connects to the public Agent MCP server at ",{"type":14,"tag":124,"props":342,"children":344},{"className":343},[],[345],{"type":20,"value":346},"https://mcp.agent.ironshard.ai/mcp",{"type":20,"value":348}," and calls ",{"type":14,"tag":124,"props":350,"children":352},{"className":351},[],[353],{"type":20,"value":129},{"type":20,"value":355},". No authentication, no existing account, and no human approval are required for creation. The agent receives a real, governed bucket with bucket-scoped credentials and policy-defined limits, and can then store objects, take snapshots, branch, and inspect its own audit log through the same MCP tools. The ",{"type":14,"tag":34,"props":357,"children":359},{"href":358},"/docs/agent-buckets",[360],{"type":20,"value":361},"Agent Buckets documentation",{"type":20,"value":363}," has the full specification.",{"type":14,"tag":23,"props":365,"children":366},{},[367],{"type":20,"value":368},"This difference matters more than it looks. On S3, the provisioning ceremony is where scoping discipline dies: the path of least resistance is one broad key shared by every agent. When the scoped credential is what provisioning hands out by default, least privilege stops being aspirational.",{"type":14,"tag":43,"props":370,"children":372},{"id":371},"what-does-egress-cost-for-ai-agent-workloads",[373],{"type":20,"value":374},"What does egress cost for AI agent workloads?",{"type":14,"tag":23,"props":376,"children":377},{},[378],{"type":20,"value":379},"S3 bills roughly $0.09/GB for data leaving AWS. Human-scale workloads absorb that; agent-scale workloads do not. A retrieval pipeline that re-reads its corpus on every run, or a fleet of agents fetching context hundreds of times an hour, turns egress into an unbounded line item. AWS's own answer is to keep compute inside AWS, which is a fine answer if that is where your compute lives.",{"type":14,"tag":23,"props":381,"children":382},{},[383,385,391],{"type":20,"value":384},"IronShard reads are zero-egress by default: read-heavy agents stay on a zero-egress storage mix, with ",{"type":14,"tag":34,"props":386,"children":388},{"href":387},"/trim",[389],{"type":20,"value":390},"Trim",{"type":20,"value":392}," routing data to the cheapest compatible provider for the workload, and automated reads never run up a bill. Latency-sensitive credentials can tune toward speed instead, trading away from the zero-egress provider mix; each credential sets its own point on the dial. Pricing is a flat per-TB rate, so internal placement optimizations never show up as billing surprises.",{"type":14,"tag":43,"props":394,"children":396},{"id":395},"will-my-s3-tools-work-with-ironshard",[397],{"type":20,"value":398},"Will my S3 tools work with IronShard?",{"type":14,"tag":23,"props":400,"children":401},{},[402],{"type":20,"value":403},"Yes. IronShard implements the AWS S3 API, so boto3, the AWS CLI, rclone, s3fs, Terraform, Airflow, LangChain, MLflow, PyTorch, and Spark connect by changing the endpoint URL. Existing data imports over the S3 API. There is no SDK swap and no pipeline rewrite; if your tools speak S3, they already speak IronShard.",{"type":14,"tag":43,"props":405,"children":407},{"id":406},"how-do-agents-work-on-production-data-without-risking-production",[408],{"type":20,"value":409},"How do agents work on production data without risking production?",{"type":14,"tag":23,"props":411,"children":412},{},[413],{"type":20,"value":414},"On S3, the honest answer is copies: replicate the bucket, hand the copy to the agent, reconcile later. Versioning protects individual objects after the fact, and Object Lock prevents deletion, but neither gives an agent an isolated, writable view of current production data. Copies go stale in hours and double your storage.",{"type":14,"tag":23,"props":416,"children":417},{},[418,420,426,428,434],{"type":20,"value":419},"IronShard has a fork primitive. 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The failure mode shifts from \"agent corrupted production\" to \"agent corrupted its own branch,\" which is not an incident.",{"type":14,"tag":43,"props":437,"children":439},{"id":438},"how-does-per-agent-access-control-compare",[440],{"type":20,"value":441},"How does per-agent access control compare?",{"type":14,"tag":23,"props":443,"children":444},{},[445,447,453],{"type":20,"value":446},"S3's IAM is the most powerful policy engine in the industry, and that power is exactly the problem at agent scale: someone has to author, test, and rotate a policy per agent, and in practice most teams fall back to a handful of shared keys. IronShard's ",{"type":14,"tag":34,"props":448,"children":450},{"href":449},"/agents",[451],{"type":20,"value":452},"AI Agent Storage",{"type":20,"value":454}," issues each agent its own credentials with policy-defined scopes (read-only, write-only, or custom), enforced at the storage layer and updatable without redeploying the agent. 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Agents call ",{"type":14,"tag":124,"props":583,"children":585},{"className":584},[],[586],{"type":20,"value":129},{"type":20,"value":588}," on the public Agent MCP server at ",{"type":14,"tag":124,"props":590,"children":592},{"className":591},[],[593],{"type":20,"value":346},{"type":20,"value":595}," with no authentication, account, or approval, and receive a governed bucket with bucket-scoped credentials. On S3 this is not possible; a human must provision first. See the ",{"type":14,"tag":34,"props":597,"children":598},{"href":358},[599],{"type":20,"value":361},{"type":20,"value":601},".",{"type":14,"tag":23,"props":603,"children":604},{},[605,610],{"type":14,"tag":87,"props":606,"children":607},{},[608],{"type":20,"value":609},"Is IronShard cheaper than Amazon S3?",{"type":20,"value":611},"\nFor read-heavy and egress-heavy AI workloads, typically yes, because IronShard reads are zero-egress by default and pricing is a flat per-TB rate. 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