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Navera Engine

We’re in Soft Launch - Contact Co-Founder & CEO, Murad to get lifetime perks!

Plan FAQs

1. What cloud providers do you support?

We currently support Google Cloud Platform (GCP) only. AWS and Azure support are coming soon.

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2. What cloud services can I use in a pipeline?

You can choose from cloud-native data and AI services like Cloud Storage, Dataflow, BigQuery, Vertex AI, Cloud Functions, and more — depending on your tier.

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3. How are “services” counted in my plan?

Services are counted based on the number of cloud services you use per organization. These are shared across all your projects and team members.
For example, a pipeline with Cloud Storage → Dataflow → BigQuery counts as 3 services.

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4. What happens when I hit my service cap?

You can either remove unused services or upgrade your plan. On Pro and Business tiers, you can add more services for $19/month per 10 services.

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5. Can I modify my pipeline after deploying it?

Yes. You can change, redeploy, or version your pipeline at any time. Navera tracks changes and ensures reproducibility.

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6. Do I need to know Terraform or YAML to use Navera?

No. Navera handles all infrastructure-as-code for you. You define your pipeline — we generate and manage the Terraform and YAML behind the scenes.

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7. Does Navera deploy the actual infrastructure in my cloud account?

Yes. Navera uses your credentials to deploy infrastructure directly into your own cloud account — securely and with best practices.

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8. Is my infrastructure portable if I stop using Navera?

Yes. Navera generates Terraform-based infrastructure, so you can export configurations and continue managing them independently if needed.

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9. Can I collaborate with my team?

Team collaboration is available on the Business and Enterprise tiers. You can manage users, assign roles, and track shared usage.

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10. What’s the difference between an organization, a project, and a pipeline?

An organization is the top-level workspace that brings together your users, projects, and service usage under one account. It lets you manage billing, track usage, and control access across your entire team.
A project represents a single cohesive use case (e.g., data ingestion, AI training). Each project can include one or more pipelines — sequences of connected services like Dataflow → BigQuery → Vertex AI.
A pipeline is a sequence of connected cloud services within a project — such as Dataflow → BigQuery → Vertex AI — that execute a specific task or workflow.

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​11. What does “x pipelines/day · y hours each” mean in the Sandbox feature?

Each tier includes access to a sandbox environment — a safe space to run pipelines without connecting your own GCP account.
“x pipelines/day” is the number of test runs you can execute per day, and “y hours each” is the maximum runtime for each pipeline. For example, “2 pipelines/day · 1 hour each” means you can run 2 separate pipelines per day, each lasting up to 1 hour in the sandbox.

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