Rethink Running Node.js
Run your frontend, APIs, and AI agents at scale, all on your own infrastructure. No code changes. No migration.
Adopted by:
The Problem
Primitives that Empower your Existing Infrastructure
Scaling high-traffic Node apps in single-cpu pods can lead to severe performance degradation, and nearly all teams respond with expensive over-provisioning that does little to remediate the core problem.
Application Server For Node.js
Run your pixels, APIs, and agents in one runtime. 2-3x throughput on the same hardware. Zero migration.
Reduce your Node.js infrastructure by 50%
Reduce your Node.js infrastructure by 50%+ with Watt and node-caged.
Improve latency and failure rate during traffic spikes
Improve latency and failure rate during traffic spikes with Watt's self-healing threads.
Turbo-charge server-side rendering
Turbo-charge server-side rendering work by fully-saturating available CPUs.
Intelligent Command Center. Watt Control Plane
Observability and control across every Watt instance in your fleet.
Skew Protection
Immutable deployments per release. New sessions get the latest, in-flight ones drain, zero mismatched assets or APIs.
Distributed Caching
ICC orchestrates tag-based cache invalidation across every instance simultaneously. One Redis-compatible store, always in sync.
Watt
Everything your app needs, in one runtime.
Platformatic's Node.js application server. Run your existing frameworks across every core — threading, observability, and service-to-service calls handled by the runtime, not your glue code.
One runtime, many apps
Run frontend, API, and backend services as individually scalable threads under a single process.
Bring your stack
Keep the frameworks you already use. Watt runs them as they are; no rewrite, no proprietary framework to adopt.
Multithreading in one command
Worker threads run on every core, so you do not need cluster boilerplate, IPC, or an extra process manager.
Call services by name
Fetch any service by name. Watt handles discovery, no ports or env URLs, inter-thread calls skip the network stack.
Observability, on by default
Structured logs, metrics, and traces are provided out-of-the-box. Flame graphs included.
Caching, built in
Built-in HTTP caching for all your services, powered by a shared Redis-compatible store. No need to add another layer.
WATT
Use the whole machine, not one core
Watt runs every service across cores in one runtime, so the hardware you already pay for actually gets used.
Single-threaded. One core, one process
Two axes, one platform. Watt fills the pod — every core working in a single runtime. ICC counts the pods — the right number of replicas, scaled ahead of demand. Vertical efficiency times horizontal prediction.
Don't guess your capacity ceiling — model it.
A single Node event loop has a hard throughput ceiling, set by the synchronous work in each request. Plug in your own sync and async timings and see exactly where latency and queue depth take off.
View the Capacity Model →ICC - Intelligent Command Center
Everything it takes to run Node.js in production.
Watt is the runtime; ICC is how you run it at scale. Predictive scaling, skew protection, and cost control, operated from one command center across Kubernetes and ECS.
Predictive autoscaling
We plan for increased demand before it happens. Our capacity follows the forecast and recovers about 40% that most teams usually over-provision.
Skew protection
Each release uses immutable deployments. New sessions use the latest version, the sessions already in progress finish without issues. No mismatched.
Sandbox every workload
eBPF kernel policies limit syscalls, files, and network egress for each tenant. Policies are applied instantly, no restarts or any special runtime or microVM.
Signals, not guesswork
Scale and alert on what actually predicts saturation in Node.js; ELU and queue depth. Not a CPU number that reads fine while requests pile up.
Distributed caching
Share one cache across every instance, with ICC orchestrating invalidation across the whole fleet. When data changes, the stale entries clear everywhere at once.
Kubernetes and ECS
One command center, either orchestrator. ICC runs the same on Kubernetes and ECS, and outscales native options like HPA, KEDA, and ECS target tracking.
ICC — Predictive autoscaling
Scale before the spike, not after it
ICC reads demand trends and provisions ahead of the spike, so capacity tracks the forecast instead of chasing a metric that is already stale.
HPA reacts to CPU after spike has already hit. Cold starts and dropped requests during the ramp
ICC forecast demand and provisions ahead, with skew protection across rollouts.
Over-provisioning around the clock so the worst case never breaks the SLO.
Capacity tracks the forecast. Reclaim the headroom you were burning on idle.
Guess from CPU and memory, blind to what the runtime is actually doing.
Decide on real signals: event-loop utilization, queue depth, saturation.
Rewrites, sidecars, and YAML sprawl to wire it all together.
Run your services on Watt as they are — no code changes.