How Altara’s infrastructure stays optimized in a rapidly evolving ecosystem

Altara brings cutting-edge AI to companies in IP-sensitive, security-conscious industries. Whether we’re working with a semiconductor manufacturer or a battery cell developer, data is sensitive, proprietary, and tightly controlled. Our AI systems are routinely trusted with some of the world's most confidential intellectual property, making how and where our systems actually run critical to earning our customers’ trust.

Our customers hold us to strict standards: data has to stay properly isolated, integrations often need to happen inside their Virtual Private Cloud (VPC) rather than ours, every action needs to be auditable, and costs need to stay predictable. These requirements become especially difficult to meet given each customer has their own security requirements, cloud infrastructure, and data permissioning.

The infrastructure underneath our product – specifically, the systems that let AI agents safely execute tasks – is a direct constraint on who we can serve and how much responsibility they can safely hand us.

Sandboxes are controlled environments where an AI agent can execute code, use tools, or take actions without direct access to production systems, files, or the broader internet. Over the past year, sandboxes have become the default standard for running parallel, asynchronous, and long-running agent workloads. With the emergence of OpenClaw-like harnesses and the rapid improvement of cloud agents, companies offering hosted sandboxes spiked in relevance and quickly entered a race with each other to optimize pricing and margins, speed and reliability, and feature delivery in order to lock in a rapidly growing market.

Early on, we evaluated E2B, agent-sandbox, AWS Lambda MicroVMs, and custom solutions, spending countless engineering hours searching for the 'perfect fit.' We soon realized no single provider satisfied every customer requirement – each introduced distinct capabilities and tradeoffs.

This isn’t a problem isolated to just sandboxes or Altara. The past 20 years have trained enterprises to choose the ‘best’ solution for a given task or the SaaS application with the most features. Software engineers toggle between Cursor, Claude Code, and Codex; HR teams migrate from Workday to Rippling or Gusto; sales teams jump from ZoomInfo to Clay or Apollo. Companies end up spending more employee time and money on implementing and adapting to new architecture than on their core job function.

When infrastructure moves this quickly, teams fall into a trap that we call “infinite churn.” We spend so much time evaluating every option that we end up paralyzed by them.

Plug-and-Play Architecture

Not all industries experience infinite churn. Intermodal shipping containers share universal dimensions regardless of cargo. Standardized outlets deliver power whether you plug in a toaster or a laptop.

While developer tools frequently claim to be "plug-and-play," very few truly are. They’re like the chargers of old - only compatible with their subset of devices. A Lightning cable won’t charge an Android phone, and a Micro-USB cable is useless on an iPhone. These vendors were not going to come out with a universal “USB-C” equivalent anytime soon, so we had to build an adapter.

Instead of building an application around the specific infrastructure underneath it, we built around a common interface and treated each provider as an interchangeable implementation behind it.

At Altara, we took a step back from the infinite churn and took a three-step approach to building out this architecture:

interface Sandbox {  create(config): SandboxId  run(sandboxId, command): Result  upload(sandboxId, files): void  download(sandboxId, path): File  destroy(sandboxId): void  capabilities(): CapabilitySet}

class E2BSandbox implements Sandbox {  create(config) {    return e2b.create({      cpu: config.cpu,      memory: config.memory    })  }  run(id, command) {    return e2b.sandbox(id).execute(command)  }  capabilities() {    return {      snapshots: true,      privateNetworking: false,      zeroDataRetention: true    }  }}

class LambdaSandbox implements Sandbox {  create(config) {    return aws.startMicroVM({      vcpu: config.cpu,      memoryMb: config.memory    })  }  run(id, command) {    return aws.invoke(id, command)  }  capabilities() {    return {      snapshots: false,      privateNetworking: true,      zeroDataRetention: true    }  }}

const sandbox = selectSandbox({  customer,  workload,  requiredCapabilities})const session = sandbox.create(config)sandbox.upload(session, files)const result = sandbox.run(  session,  "python analysis.py")sandbox.destroy(session)

It’s important to remember that interchangeable doesn’t mean identical. Infinite churn happens because providers expose different capabilities. The challenge is leveraging those vendor-specific strengths without breaking abstractions. By baking capability awareness into our interfaces, Altara can adapt to provider-specific offerings when they matter, while using the interface’s core contract for general operations. Think USB-C: the interface is standardized, but cables situationally support charging, data transfer, audio/video streaming, or security key authentication, each of which is advertised by the cable hardware.

const sandbox = router.select({  required: [    Capabilities.ZERO_DATA_RETENTION,    Capabilities.PRIVATE_NETWORKING  ],  optimizeFor: [    "cost",    "startup_latency"  ]})const session = sandbox.create(config)

Evolving Without Disruption

Decoupling our platform from any hardwired sandbox vendor allows us to select providers dynamically based on customer compliance rules, performance benchmarks, and cost efficiency. All of this happens without any adverse impact on the customer’s environment.

Having a consistent interface between Altara’s application layer and infrastructure layer has also enabled us to make rapid application improvements as well. With these abstraction boundaries in place, we rapidly shipped features such as a skills injection engine, a unified subagent execution harness, and interactive in-sandbox data visualization tools. A stable contract with the infrastructure layer enables us to prototype and iterate on features quickly and easily to constantly upgrade Altara’s capabilities.

Building for Change

Building in environments with infinite churn has taught us the value of strong abstractions beyond just cleaner code - when underlying systems are constantly shifting, these abstractions are defenders against accumulated technical debt, unnecessary complexity and vendor lock-in. Plug and play architecture helps companies at all stages constantly evaluate different approaches and technologies, something that is critical in an AI landscape where software generation is commoditized, but cost, security, and performance remain critical.

We’re taking our learnings from sandbox providers and applying it across the platform at Altara. Databases and storage, model providers, and even coding harnesses are currently all areas of high competition and churn, and Altara’s architecture lets us evaluate and adopt improvements without asking customers to migrate alongside us.

Building for change means creating systems that adapt as fast as the frontier moves and future-proofing our platform so our customers don’t have to. By turning infrastructure into swappable primitives, Altara ensures enterprise customers automatically inherit the highest-performing, most secure runtimes available – with zero migration friction.