Which parts of the browser stack will your team operate?
Managed browser access removes one infrastructure responsibility. Your team may still own the code runner, state store, scheduler and artifacts. A self-hosted engine moves more of that responsibility back into your environment.
Moving a browser to another region while leaving the controller in place changes the network path of every action. The advertised browser creation time does not describe those repeated round trips.
Compare deployment ownership
Kernel: Kernel Apps move the automation process next to the browser. Alternatively, an external process can control a browser through the browser API. Choose based on execution locality and deployment ownership.
Lightpanda: Compare hosted Lightpanda access with operating the engine yourself. The engine's supported APIs and website compatibility remain relevant in either deployment.
Sources: kernel.sh [1] ↗lightpanda.io [2] ↗
Compare the execution model
Kernel: Deploy a TypeScript or Python App and expose Actions that callers invoke. Kernel co-locates code with the browser environments the app creates. An Action invocation is the execution unit rather than a bare CDP connection.
Lightpanda: The reviewed documentation establishes a browser engine and hosted access, not a deployed Python Function contract. A separate automation process must have its own deployment, triggers and monitoring design.
Sources: kernel.sh [1] ↗lightpanda.io [2] ↗
Compare operational limits
Kernel: Kernel documents concurrent browsers, browser creation rate and per-browser resources separately. Standby browsers can still consume concurrency. Pools change how browsers are acquired; they do not erase account limits.
Lightpanda: Use Lightpanda Cloud's limits and billing documentation for hosted capacity. Self-operated engine instances have a different capacity model and should not inherit cloud account assumptions.
Sources: kernel.sh [1] ↗lightpanda.io [2] ↗
How to evaluate this choice
Use the deployment that fits the work your team wants to own. Reusing an existing runner can be practical; a hosted Function can reduce operations; self-hosting can meet a specific infrastructure requirement at the cost of operating it.
- Draw the controller, browser, state store and scheduler as separate components.
- Check the available browser and execution regions independently.
- Identify which provider owns upgrades, capacity and recordings.
- Verify code and stored-state portability before changing providers.
- Include maintenance and on-call work in a self-hosting decision.
Requirements side by side
| Requirement | Kernel | Lightpanda |
|---|---|---|
| Browser control | Documented | Compatibility-dependent |
| Saved browser state | Documented | Not established |
| Code execution | TypeScript / Python Apps | External worker |
| Deployment choice | Check deployment offering | Engine available |
Sources: kernel.sh [1] ↗kernel.sh [2] ↗kernel.sh [3] ↗kernel.sh [4] ↗kernel.sh [5] ↗kernel.sh [6] ↗lightpanda.io [7] ↗
Which approach fits?
Choose Kernel when your code makes many browser calls and you want to deploy it beside the browser, or you need Kernel's managed sign-in flow.
Kernel tradeoff: Browser-local code changes the deployment model. Check app action behavior, account limits and persistent-state ownership before moving an external worker into it.
Choose Lightpanda when your workflow can use Lightpanda's supported browser APIs and you want to evaluate that engine on the pages you actually automate.
Lightpanda tradeoff: CDP connectivity does not establish complete Chromium compatibility. Validate rendering-dependent steps, downloads and browser features with the selected engine before a migration.
Sources: kernel.sh [1] ↗lightpanda.io [2] ↗
A useful acceptance check
Write a pass/fail result for the real task before running the evaluation. Record the account, configuration and code version next to that result. Repeat failures need an explanation, not an automatically different browser configuration.
When Notte belongs on this shortlist
Kernel's browser-local Apps make execution placement part of the decision. Compare the repeated action path with the proposed Notte controller or Function deployment before concluding that a lifecycle or hourly-rate difference decides the workflow.
Lightpanda introduces a browser-engine decision. Keep it on the shortlist when its supported actions fit the real pages you use; a successful CDP connection or text task does not establish visual or full-browser equivalence with the proposed Notte workflow.
Notte: Functions deploy Python code with a run() entry point. Invoke them over HTTP or with an SDK, inspect run history, and roll back code by redeploying an earlier version as the latest version.
Consider this third option when its documented mechanism addresses a requirement left open by the two providers above. A working configuration on either original provider can still be the better choice; compare the task and ownership cost before switching.
Sources: kernel.sh [1] ↗lightpanda.io [2] ↗docs.notte.cc [3] ↗