Click Below to Get the Code

Browse, clone, and build from real-world templates powered by Harper.
Blog
GitHub Logo

Nobody Wants to Pick a Data Center (And They Shouldn't Have To)

Harper Fabric simplifies cloud deployment by eliminating the need to choose data centers, automating infrastructure, scaling, and global distribution. Built for Harper’s unified runtime, it enables developers to deploy high-performance, distributed applications quickly without managing complex cloud configurations or infrastructure overhead.
Blog

Nobody Wants to Pick a Data Center (And They Shouldn't Have To)

Bari Jay
Senior Director of Product Management
at Harper
April 17, 2026
Bari Jay
Senior Director of Product Management
at Harper
April 17, 2026
Bari Jay
Senior Director of Product Management
at Harper
April 17, 2026
April 17, 2026
Harper Fabric simplifies cloud deployment by eliminating the need to choose data centers, automating infrastructure, scaling, and global distribution. Built for Harper’s unified runtime, it enables developers to deploy high-performance, distributed applications quickly without managing complex cloud configurations or infrastructure overhead.
Bari Jay
Senior Director of Product Management

I have a confession. I have spent an unreasonable number of hours of my life in rooms where very smart people argue about which data center to deploy to. Region selection. Redundancy factors. Latency targets by geography. Provider-specific networking quirks. And at the end of every single one of those conversations, the goal was always the same: make the application fast for the people using it.

So why are we still making developers do all that work themselves?

This is the question that Harper Fabric exists to answer. And with Harper 5.0 now fully open source and Harper Pro source-available, Fabric is the piece that takes everything we have built and makes it absurdly easy to actually run at scale.

The Problem Is Not Performance. The Problem Is Getting There.

Here is what we hear from developers and engineering leaders constantly: they know what good performance looks like. They can articulate their latency targets, their throughput requirements, their geographic distribution needs. What they cannot do, at least not without a tremendous amount of effort, is translate those goals into the right combination of cloud provider, region, instance type, networking configuration, replication topology, and deployment pipeline.

And honestly? They should not have to.

The traditional cloud deployment experience asks developers to become infrastructure experts. Pick a provider. Pick a region. Pick an instance size. Configure your database separately. Set up your caching layer. Wire up messaging. Manage replication. Coordinate certificates. Hope everything plays nicely together.

Every additional system is another configuration surface, another set of credentials, another potential failure mode. By the time an engineering team has assembled all of these pieces into something resembling a production environment, they have spent weeks or months on infrastructure that has nothing to do with the application they actually set out to build.

Fabric Flips the Question

Harper Fabric does something that I think sounds deceptively simple but is genuinely difficult to pull off: it asks you what you want to achieve instead of how you want to achieve it.

When you create a cluster on Fabric, you are not picking data centers. You are telling us what your workload looks like. How many reads per minute. What regions your users are in. Whether you want colocated infrastructure (multi-tenant, excellent performance, lower cost) or dedicated infrastructure (single-tenant, maximum isolation, even more specialized regions). You pick a performance level. You hit deploy. And in about five minutes, you have a globally distributed Harper cluster that is live, replicating, and ready to serve traffic.

That is it. No Terraform. No Kubernetes manifests. No region-by-region provisioning. Fabric handles orchestration, node placement, replication, certificate management, and traffic routing. The control plane manages all of it so you can focus on your application.

Why This Matters Right Now

I think there is something happening in the market that makes Fabric's approach especially relevant, and it is not just that developers are tired of YAML files (though they are, and rightfully so).

Two things are converging. First, AI agents are generating applications faster than teams can deploy them. We talked about this in our 5.0 launch: the gap is no longer in writing code. The gap is in getting from prototype to production. Fabric closes that gap. An agent building on Harper can deploy to Fabric in the same workflow, because the entire stack is one runtime and the deployment target is already integrated. No multi-service orchestration required.

Second, enterprise buyers are hitting a wall with cloud complexity. Multi-year committed spend agreements, provider lock-in, security architectures built around a single cloud. Engineering leaders are telling us that they do not want another platform that adds to that complexity. They want something that abstracts it away. Fabric does that by design. We handle the infrastructure decisions so their teams can ship.

What Makes Fabric Different

I want to be really clear about what Fabric is and is not.

Fabric is not a generic cloud hosting platform. It is the product experience for deploying and operating Harper. That distinction matters because Fabric is purpose-built for a unified runtime. When you deploy on Fabric, you are not assembling separate services. Your database, cache, messaging, and application logic are already in-process. Fabric is orchestrating the deployment and distribution of that single, integrated system.

This is why Fabric can offer things that generic cloud platforms cannot. Latency estimates at cluster creation time, based on your actual workload and region selection. Automatic replication driven by Harper Pro's transaction-log architecture. A single URL for your entire globally distributed cluster. Real-time scaling without re-architecting.

100% of customers do not want to pick their data centers. They want to be deployed in a way that makes their application as performant as possible. Fabric does that, with redundant deployments that ensure top performance even if a specific data center has issues.

The Free Tier Is Real

One more thing, because I think this matters a lot: you can start on Fabric for free. No credit card. Deploy a cluster, build your application, and see the performance for yourself. If you need more capacity, the pricing is transparent and block-based, designed to scale with you rather than surprise you.

We built Fabric so that more people could experience Harper. To lower the barrier of entry and help developers see their applications deployed and working in a way that actually helps their users. That is the whole point.

If you have been building on Harper locally or evaluating the open-source core, Fabric is how you take it to production without taking on the operational weight of managing distributed infrastructure yourself.

Go deploy something. Tell us what you think. And if you run into anything zany, you know where to find us.

Build with Harper 5.0: https://github.com/HarperFast/harper 

Deploy on Harper Fabric: https://fabric.harper.fast/

Join the Discord: https://discord.com/invite/VzZuaw3Xay

I have a confession. I have spent an unreasonable number of hours of my life in rooms where very smart people argue about which data center to deploy to. Region selection. Redundancy factors. Latency targets by geography. Provider-specific networking quirks. And at the end of every single one of those conversations, the goal was always the same: make the application fast for the people using it.

So why are we still making developers do all that work themselves?

This is the question that Harper Fabric exists to answer. And with Harper 5.0 now fully open source and Harper Pro source-available, Fabric is the piece that takes everything we have built and makes it absurdly easy to actually run at scale.

The Problem Is Not Performance. The Problem Is Getting There.

Here is what we hear from developers and engineering leaders constantly: they know what good performance looks like. They can articulate their latency targets, their throughput requirements, their geographic distribution needs. What they cannot do, at least not without a tremendous amount of effort, is translate those goals into the right combination of cloud provider, region, instance type, networking configuration, replication topology, and deployment pipeline.

And honestly? They should not have to.

The traditional cloud deployment experience asks developers to become infrastructure experts. Pick a provider. Pick a region. Pick an instance size. Configure your database separately. Set up your caching layer. Wire up messaging. Manage replication. Coordinate certificates. Hope everything plays nicely together.

Every additional system is another configuration surface, another set of credentials, another potential failure mode. By the time an engineering team has assembled all of these pieces into something resembling a production environment, they have spent weeks or months on infrastructure that has nothing to do with the application they actually set out to build.

Fabric Flips the Question

Harper Fabric does something that I think sounds deceptively simple but is genuinely difficult to pull off: it asks you what you want to achieve instead of how you want to achieve it.

When you create a cluster on Fabric, you are not picking data centers. You are telling us what your workload looks like. How many reads per minute. What regions your users are in. Whether you want colocated infrastructure (multi-tenant, excellent performance, lower cost) or dedicated infrastructure (single-tenant, maximum isolation, even more specialized regions). You pick a performance level. You hit deploy. And in about five minutes, you have a globally distributed Harper cluster that is live, replicating, and ready to serve traffic.

That is it. No Terraform. No Kubernetes manifests. No region-by-region provisioning. Fabric handles orchestration, node placement, replication, certificate management, and traffic routing. The control plane manages all of it so you can focus on your application.

Why This Matters Right Now

I think there is something happening in the market that makes Fabric's approach especially relevant, and it is not just that developers are tired of YAML files (though they are, and rightfully so).

Two things are converging. First, AI agents are generating applications faster than teams can deploy them. We talked about this in our 5.0 launch: the gap is no longer in writing code. The gap is in getting from prototype to production. Fabric closes that gap. An agent building on Harper can deploy to Fabric in the same workflow, because the entire stack is one runtime and the deployment target is already integrated. No multi-service orchestration required.

Second, enterprise buyers are hitting a wall with cloud complexity. Multi-year committed spend agreements, provider lock-in, security architectures built around a single cloud. Engineering leaders are telling us that they do not want another platform that adds to that complexity. They want something that abstracts it away. Fabric does that by design. We handle the infrastructure decisions so their teams can ship.

What Makes Fabric Different

I want to be really clear about what Fabric is and is not.

Fabric is not a generic cloud hosting platform. It is the product experience for deploying and operating Harper. That distinction matters because Fabric is purpose-built for a unified runtime. When you deploy on Fabric, you are not assembling separate services. Your database, cache, messaging, and application logic are already in-process. Fabric is orchestrating the deployment and distribution of that single, integrated system.

This is why Fabric can offer things that generic cloud platforms cannot. Latency estimates at cluster creation time, based on your actual workload and region selection. Automatic replication driven by Harper Pro's transaction-log architecture. A single URL for your entire globally distributed cluster. Real-time scaling without re-architecting.

100% of customers do not want to pick their data centers. They want to be deployed in a way that makes their application as performant as possible. Fabric does that, with redundant deployments that ensure top performance even if a specific data center has issues.

The Free Tier Is Real

One more thing, because I think this matters a lot: you can start on Fabric for free. No credit card. Deploy a cluster, build your application, and see the performance for yourself. If you need more capacity, the pricing is transparent and block-based, designed to scale with you rather than surprise you.

We built Fabric so that more people could experience Harper. To lower the barrier of entry and help developers see their applications deployed and working in a way that actually helps their users. That is the whole point.

If you have been building on Harper locally or evaluating the open-source core, Fabric is how you take it to production without taking on the operational weight of managing distributed infrastructure yourself.

Go deploy something. Tell us what you think. And if you run into anything zany, you know where to find us.

Build with Harper 5.0: https://github.com/HarperFast/harper 

Deploy on Harper Fabric: https://fabric.harper.fast/

Join the Discord: https://discord.com/invite/VzZuaw3Xay

Harper Fabric simplifies cloud deployment by eliminating the need to choose data centers, automating infrastructure, scaling, and global distribution. Built for Harper’s unified runtime, it enables developers to deploy high-performance, distributed applications quickly without managing complex cloud configurations or infrastructure overhead.

Download

White arrow pointing right
Harper Fabric simplifies cloud deployment by eliminating the need to choose data centers, automating infrastructure, scaling, and global distribution. Built for Harper’s unified runtime, it enables developers to deploy high-performance, distributed applications quickly without managing complex cloud configurations or infrastructure overhead.

Download

White arrow pointing right
Harper Fabric simplifies cloud deployment by eliminating the need to choose data centers, automating infrastructure, scaling, and global distribution. Built for Harper’s unified runtime, it enables developers to deploy high-performance, distributed applications quickly without managing complex cloud configurations or infrastructure overhead.

Download

White arrow pointing right

Explore Recent Resources

Tutorial
GitHub Logo

Introducing Structon: Random-Access Binary Encoding for JavaScript

Deserializing entire records to read one field is a bottleneck at scale. Structon stores objects in a binary format where any field is reachable by byte offset, with lazy getters that never allocate until you access a property. It's the encoding Harper has used internally for years, now a standalone package.
JavaScript
Tutorial
Deserializing entire records to read one field is a bottleneck at scale. Structon stores objects in a binary format where any field is reachable by byte offset, with lazy getters that never allocate until you access a property. It's the encoding Harper has used internally for years, now a standalone package.
Person with very short blonde hair wearing a light gray button‑up shirt, standing with arms crossed and smiling outdoors with foliage behind.
Kris Zyp
SVP of Engineering
Tutorial

Introducing Structon: Random-Access Binary Encoding for JavaScript

Deserializing entire records to read one field is a bottleneck at scale. Structon stores objects in a binary format where any field is reachable by byte offset, with lazy getters that never allocate until you access a property. It's the encoding Harper has used internally for years, now a standalone package.
Kris Zyp
Jun 2026
Tutorial

Introducing Structon: Random-Access Binary Encoding for JavaScript

Deserializing entire records to read one field is a bottleneck at scale. Structon stores objects in a binary format where any field is reachable by byte offset, with lazy getters that never allocate until you access a property. It's the encoding Harper has used internally for years, now a standalone package.
Kris Zyp
Tutorial

Introducing Structon: Random-Access Binary Encoding for JavaScript

Deserializing entire records to read one field is a bottleneck at scale. Structon stores objects in a binary format where any field is reachable by byte offset, with lazy getters that never allocate until you access a property. It's the encoding Harper has used internally for years, now a standalone package.
Kris Zyp
Livestream
GitHub Logo

1.5 Hour Build - Vibe Coding a Full Personal Site: Design to Deployment in One Session

Watch Austin rebuild his personal website live using Claude AI and Harper, including a custom Markdown CMS, GraphQL schema design, React scaffolding, and full deployment. A real-time pair coding session from design to launch.
Livestream
Watch Austin rebuild his personal website live using Claude AI and Harper, including a custom Markdown CMS, GraphQL schema design, React scaffolding, and full deployment. A real-time pair coding session from design to launch.
Person with short hair wearing a light blue patterned shirt, smiling widely outdoors with blurred greenery and trees in the background.
Austin Akers
Head of Developer Relations
Livestream

1.5 Hour Build - Vibe Coding a Full Personal Site: Design to Deployment in One Session

Watch Austin rebuild his personal website live using Claude AI and Harper, including a custom Markdown CMS, GraphQL schema design, React scaffolding, and full deployment. A real-time pair coding session from design to launch.
Austin Akers
May 2026
Livestream

1.5 Hour Build - Vibe Coding a Full Personal Site: Design to Deployment in One Session

Watch Austin rebuild his personal website live using Claude AI and Harper, including a custom Markdown CMS, GraphQL schema design, React scaffolding, and full deployment. A real-time pair coding session from design to launch.
Austin Akers
Livestream

1.5 Hour Build - Vibe Coding a Full Personal Site: Design to Deployment in One Session

Watch Austin rebuild his personal website live using Claude AI and Harper, including a custom Markdown CMS, GraphQL schema design, React scaffolding, and full deployment. A real-time pair coding session from design to launch.
Austin Akers
Blog
GitHub Logo

The Old Product Loop Is the New Bottleneck

AI has made it dramatically cheaper to get software to a working version, but most companies still plan like building is the expensive part. The new bottleneck is the product loop: forming sharp hypotheses, living inside the user experience, fixing friction as it appears, and feeding evidence back into the roadmap faster than ticket-based planning allows.
Blog
AI has made it dramatically cheaper to get software to a working version, but most companies still plan like building is the expensive part. The new bottleneck is the product loop: forming sharp hypotheses, living inside the user experience, fixing friction as it appears, and feeding evidence back into the roadmap faster than ticket-based planning allows.
Person with short dark hair and moustache, wearing a colorful plaid shirt, smiling outdoors in a forested mountain landscape.
Aleks Haugom
Senior Manager of GTM
Blog

The Old Product Loop Is the New Bottleneck

AI has made it dramatically cheaper to get software to a working version, but most companies still plan like building is the expensive part. The new bottleneck is the product loop: forming sharp hypotheses, living inside the user experience, fixing friction as it appears, and feeding evidence back into the roadmap faster than ticket-based planning allows.
Aleks Haugom
May 2026
Blog

The Old Product Loop Is the New Bottleneck

AI has made it dramatically cheaper to get software to a working version, but most companies still plan like building is the expensive part. The new bottleneck is the product loop: forming sharp hypotheses, living inside the user experience, fixing friction as it appears, and feeding evidence back into the roadmap faster than ticket-based planning allows.
Aleks Haugom
Blog

The Old Product Loop Is the New Bottleneck

AI has made it dramatically cheaper to get software to a working version, but most companies still plan like building is the expensive part. The new bottleneck is the product loop: forming sharp hypotheses, living inside the user experience, fixing friction as it appears, and feeding evidence back into the roadmap faster than ticket-based planning allows.
Aleks Haugom
Livestream
GitHub Logo

2 Hour Build - Live Stream for Non-Developers

A non-developer's live stream walkthrough of building Flow State, a Colorado river-flow app for rafters, in two hours using ChatGPT dictation, Claude Code, Claude Design, and Harper. Scaffold with npm create harper@latest and deploy to Harper Fabric. No coding background required.
Livestream
A non-developer's live stream walkthrough of building Flow State, a Colorado river-flow app for rafters, in two hours using ChatGPT dictation, Claude Code, Claude Design, and Harper. Scaffold with npm create harper@latest and deploy to Harper Fabric. No coding background required.
Person with short dark hair and moustache, wearing a colorful plaid shirt, smiling outdoors in a forested mountain landscape.
Aleks Haugom
Senior Manager of GTM
Livestream

2 Hour Build - Live Stream for Non-Developers

A non-developer's live stream walkthrough of building Flow State, a Colorado river-flow app for rafters, in two hours using ChatGPT dictation, Claude Code, Claude Design, and Harper. Scaffold with npm create harper@latest and deploy to Harper Fabric. No coding background required.
Aleks Haugom
May 2026
Livestream

2 Hour Build - Live Stream for Non-Developers

A non-developer's live stream walkthrough of building Flow State, a Colorado river-flow app for rafters, in two hours using ChatGPT dictation, Claude Code, Claude Design, and Harper. Scaffold with npm create harper@latest and deploy to Harper Fabric. No coding background required.
Aleks Haugom
Livestream

2 Hour Build - Live Stream for Non-Developers

A non-developer's live stream walkthrough of building Flow State, a Colorado river-flow app for rafters, in two hours using ChatGPT dictation, Claude Code, Claude Design, and Harper. Scaffold with npm create harper@latest and deploy to Harper Fabric. No coding background required.
Aleks Haugom
Tutorial
GitHub Logo

Production Quality at Vibe Code Velocity: Dispatched Agent Teams with Harper

Harper enables production-grade agentic engineering by collapsing database, cache, runtime, and messaging into one process, reducing agent complexity and review burden. A multi-model dispatch workflow lets specialized agents plan, code, QA, and review in parallel while humans retain control over critical decisions.
Tutorial
Harper enables production-grade agentic engineering by collapsing database, cache, runtime, and messaging into one process, reducing agent complexity and review burden. A multi-model dispatch workflow lets specialized agents plan, code, QA, and review in parallel while humans retain control over critical decisions.
Person with very short hair and a goatee wearing a plaid button‑up shirt over a white undershirt, smiling outdoors with leafy greenery behind.
Jeff Darnton
SVP, Professional Services & Customer Success
Tutorial

Production Quality at Vibe Code Velocity: Dispatched Agent Teams with Harper

Harper enables production-grade agentic engineering by collapsing database, cache, runtime, and messaging into one process, reducing agent complexity and review burden. A multi-model dispatch workflow lets specialized agents plan, code, QA, and review in parallel while humans retain control over critical decisions.
Jeff Darnton
May 2026
Tutorial

Production Quality at Vibe Code Velocity: Dispatched Agent Teams with Harper

Harper enables production-grade agentic engineering by collapsing database, cache, runtime, and messaging into one process, reducing agent complexity and review burden. A multi-model dispatch workflow lets specialized agents plan, code, QA, and review in parallel while humans retain control over critical decisions.
Jeff Darnton
Tutorial

Production Quality at Vibe Code Velocity: Dispatched Agent Teams with Harper

Harper enables production-grade agentic engineering by collapsing database, cache, runtime, and messaging into one process, reducing agent complexity and review burden. A multi-model dispatch workflow lets specialized agents plan, code, QA, and review in parallel while humans retain control over critical decisions.
Jeff Darnton