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* [Architecture Overview](developers/architecture.md)
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* [Architecture Overview](developers/architecture.md)
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* [Ocean Node](developers/ocean-node/README.md)
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* [Ocean Node](developers/ocean-node/README.md)
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* [Node Architecture](developers/ocean-node/node-architecture.md)
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* [Node Architecture](developers/ocean-node/node-architecture.md)
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* [Compute-to-data (C2D)](developers/compute-to-data-c2d.md)
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* [Page 1](developers/page-1.md)
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* [Page 1](developers/page-1.md)
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* [Contracts](developers/contracts/README.md)
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* [Contracts](developers/contracts/README.md)
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* [Data NFTs](developers/contracts/data-nfts.md)
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* [Data NFTs](developers/contracts/data-nfts.md)
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developers/compute-to-data-c2d.md
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developers/compute-to-data-c2d.md
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# Compute-to-data (C2D)
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C2Dv2 continues the concept of bringing algorithms to the data, allowing both public and private datasets to be used with algorithms. While previous versions relied on external components (Provider -> Operator Service running in Kubernetes -> multiple Operator-Engines each running in their own Kubernetes namespace), C2Dv2 is embedded entirely within the ocean-node.
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It has a modular approach, allowing multiple compute engines to be connected to the same ocean-node engine. These compute engines can be internal (Docker or Kubernetes if ocean-node runs in a Kubernetes environment) or external (in the future, integration with projects like Bachalau, iExec, etc., is possible).
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### Additional Features
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* Allow multiple C2D engines to connect to the same ocean-node
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* Support multiple jobs (stages) in a workflow
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* Jobs can be dependent or independent of previous stages, allowing for parallel or serial job execution
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### Workflows
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A workflow defines one or more jobs to be executed. Each job may have dependencies on a previous job.
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```json
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[
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{
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"index": number,
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"jobId": "generated by orchestrator",
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"runAfter": "if defined, wait for specific jobId to finish",
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"input": [
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{
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"index": number,
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"did": "optional",
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"serviceId": "optional",
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"files": "filesObject, optional"
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}
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],
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"algorithm": {
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"did": "optional",
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"serviceId": "optional",
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"files": "filesObject, optional",
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"rawcode": "optional",
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"container": {
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"entrypoint": "string",
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"image": "string",
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"tag": "string"
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}
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}
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}
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]
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```
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### Orchestration Layer
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Formerly known as the "operator-service," this layer handles interactions between the ocean-node core layer and different execution environments.
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In summary, it should:
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* Expose a list of compute environments for all engines
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* Expose a list of running jobs and limits (e.g., max concurrent jobs)
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* Take on new jobs (created by the startJob core handler)
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* Determine which module to use (Docker, Kubernetes, Bachalau, etc.)
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* Insert workflow into the database
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* Signal the engine handler to take over job execution
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* Read workflow status when the C2D getStatus core is called
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* Serve job results when the C2D getJobResult is called
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Due to technical constraints, both internal modules (Docker and Kubernetes) will use Docker images for data provisioning (previously pod-configuration) and results publishing (previously pod-publishing). The orchestration layer will also expose two new core commands:
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* `c2dJobStatusUpdate` (called by both pod-configuration and pod-publishing to update job status)
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* `c2dJobPublishResult` (called by pod-publishing when results need to be uploaded)
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When any pod-\*\* calls one of these endpoints, we must verify the signature and respond accordingly.
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### Payment Flow in Orchestration
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This will be based on an escrow contract. The orchestrator will:
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* Compute the sum of maxDuration from all jobs in the workflow
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* Calculate the required fee (depending on the previous step, token, environment, etc.)
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* Lock the amount in the escrow contract
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* Wait until all jobs are finished (successfully or not)
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* Calculate the actual duration spent
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* Compute proof
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* Withdraw payment & provide proof, releasing the difference back to the customer
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### C2D Engines
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A C2D Engine is a piece of code that handles C2D jobs running on a specific orchestration implementation. This document focuses on internal compute engines: Docker-based (host with Docker environment installed) and Kubernetes-based (if ocean-node runs inside a Kubernetes cluster).
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An engine that uses external services (like Bachalau) follows the same logic but will likely interact with remote APIs.
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An engine is responsible for:
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* Storing workflows and each job status (so on restart, we can resume or continue running flows)
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* Queueing new jobs
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#### Docker Engine
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This module requires Docker service installed at the host level. It leverages the Docker API to:
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* Create job volumes (with quotas)
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* Start the provisioning container (pod-configuration)
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* Monitor its status
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* Create YAML for algorithms with hardware constraints (CPU, RAM)
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* Pass devices for GPU environments
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* Start the algorithm container
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* Monitor algorithm health & timeout constraints
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* Stop the algorithm if the quota is exceeded
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* Start the publishing container
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* Delete job volumes
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```
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title C2Dv2 message flow for docker module
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User -> Ocean-node: start c2d job
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Ocean-node -> Orchestration-class: start c2d job
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Orchestration-class -> Orchestration-class: determinte module and insert workflow, random private key in db
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Orchestration-class -> Docker-engine: queue job
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Docker-engine -> Docker_host_api: create job volume
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Docker-engine -> Docker-engine: create yaml for pod-configuration, set private key
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Docker-engine -> Docker_host_api: start pod-configuration
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Pod_configuration -> Pod_configuration: starts ocean-node as pod-config
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Pod_configuration -> Ocean-node: call c2dJobProvision
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Ocean-node -> Pod_configuration: return workflow
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Pod_configuration -> Pod_configuration : download inputs & algo
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Pod_configuration -> Ocean-node: call c2dJobStatusUpdate
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Ocean-node -> Docker-engine: download success, start algo
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Docker-engine -> Docker-engine: create yaml for algo
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Docker-engine -> Docker_host_api: start algo container
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Docker-engine -> Docker-engine: monitor algo container, stop if timeout
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Docker-engine -> Docker-engine: create yaml for pod-publishing, set private key
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Docker-engine -> Docker_host_api: start pod-publishing
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Docker_host_api -> Pod-Publishing: start as docker container
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Pod-Publishing -> Pod-Publishing : prepare output
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Pod-Publishing -> Ocean-node: call c2dJobPublishResult
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Pod-Publishing -> Ocean-node: call c2dJobStatusUpdate
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```
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<figure><img src="../.gitbook/assets/image.png" alt=""><figcaption><p>C2Dv2 flow diagram</p></figcaption></figure>
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#### Kubernetes Engine
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This module requires access to Kubernetes credentials (or autodetects them if ocean-node already runs in a Kubernetes cluster). It leverages the Kubernetes API to:
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* Create job volumes (with quotas)
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* Start the provisioning container (pod-configuration)
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* Monitor its status
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* Create YAML for algorithms with hardware constraints (CPU, RAM)
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* Pass devices for GPU environments
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* Start the algorithm container
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* Monitor algorithm health & timeout constraints
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* Stop the algorithm if the quota is exceeded
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* Start the publishing container
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* Delete job volumes
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#### POD-\* Common Description
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For efficient communication between ocean-node and the two containers, the easiest way is to use p2p/http API. Thus, all pod-\* instances will run an ocean-node instance (each will have a job-generated random key) and connect to the main ocean-node instance. The main ocean-node instance's peerNodeId or HTTP API endpoint will be inserted in the YAML. Each pod-\* will use a private key, also exposed in the YAML.
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Each YAML of pod-\* will contain the following environment variables:
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* nodePeerId
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* nodeHttpApi
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* privateKey
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#### Pod-configuration
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Previously, pod-configuration was a standalone repository built as a Docker image. In this implementation, it will be ocean-node with a different entrypoint (entry\_configuration.js).
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Implementation:
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* Call ocean-node/c2dJobProvision and get the workflow's input section
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* Download all assets
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* Call the ocean-node/c2dJobStatusUpdate core command to update status (provision finished or errors)
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#### Pod-publishing
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Previously, pod-publishing was a standalone repository built as a Docker image. In this implementation, it will be ocean-node with a different entrypoint (entry\_publishing.js).
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Implementation:
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* Read the output folder
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* If multiple files or folders are detected, create a zip with all those files/folders
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* Call the ocean-node/c2dJobPublishResult core command and let ocean-node handle storage
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* Call the ocean-node/c2dJobStatusUpdate core command to update the job as done
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---
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---
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description: Monetise your data while preserving privacy
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description: Compute to data version 2 (C2dv2)
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---
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---
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# Compute to data
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# Compute to data
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@ -29,14 +29,14 @@ We suggest reading these guides to get an understanding of how compute-to-data w
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### User Guides
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### User Guides
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* [How to write compute to data algorithms](broken-reference)
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* [How to write compute to data algorithms](broken-reference/)
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* [How to publish a compute-to-data algorithm](broken-reference)
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* [How to publish a compute-to-data algorithm](broken-reference/)
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* [How to publish a dataset for compute to data](broken-reference)
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* [How to publish a dataset for compute to data](broken-reference/)
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### Developer Guides
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### Developer Guides
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* [How to use compute to data with ocean.js](../ocean.js/cod-asset.md)
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* [How to use compute to data with ocean.js](../ocean.js/cod-asset.md)
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* [How to use compute to data with ocean.py](../../data-scientists/ocean.py/)
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* [How to use compute to data with ocean.py](../../data-scientists/ocean.py)
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### Infrastructure Deployment Guides
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### Infrastructure Deployment Guides
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* Components layer (Indexer, Provider)
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* Components layer (Indexer, Provider)
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* Modules layer
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* Modules layer
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<figure><img src="../../.gitbook/assets/image.png" alt=""><figcaption><p>Ocean Node Infrastructure diagram</p></figcaption></figure>
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<figure><img src="../../.gitbook/assets/image (1).png" alt=""><figcaption><p>Ocean Node Infrastructure diagram</p></figcaption></figure>
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### Features
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### Features
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