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76 lines
4.0 KiB
Markdown
76 lines
4.0 KiB
Markdown
---
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title: Compute-to-Data
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description: Architecture overview
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---
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# Architecture
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### Architecture Overview
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Here's the sequence diagram for starting a new compute job.
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The Consumer calls the Provider with `start(did, algorithm, additionalDIDs)`. It returns job id `XXXX`. The Provider oversees the rest of the work. At any point, the Consumer can query the Provider for the job status via `getJobDetails(XXXX)`.
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Here's how Provider works. First, it ensures that the Consumer has sent the appropriate datatokens to get access. Then, it calls asks the Operator-Service (a microservice) to start the job, which passes on the request to Operator-Engine (the actual compute system). Operator-Engine runs Kubernetes compute jobs etc as needed. Operator-Engine reports when to Operator-Service when the job has finished.
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Here's the actors/components:
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- Consumers - The end users who need to use some computing services offered by the same Publisher as the data Publisher.
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- Operator-Service - Micro-service that is handling the compute requests.
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- Operator-Engine - The computing systems where the compute will be executed.
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- Kubernetes - a K8 cluster
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Before the flow can begin, these pre-conditions must be met:
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- The Asset DDO has a `compute` service.
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- The Asset DDO compute service must permit algorithms to run on it.
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- The Asset DDO must specify an Ocean Provider endpoint exposed by the Publisher.
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### Access Control using Ocean Provider
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As with [the `access` service](../../core-concepts/architecture.md#data-nfts-datatokens-and-access-control-tools), the `compute` service requires the **Ocean Provider** as a component handled by Publishers. Ocean Provider is in charge of interacting with users and managing the basics of a Publisher's infrastructure to integrate this infrastructure into Ocean Protocol. The direct interaction with the infrastructure where the data resides happens through this component only.
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Ocean Provider includes the credentials to interact with the infrastructure (initially in cloud providers, but it could be on-premise).
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### Compute-to-Data Environment
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#### Operator Service
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The **Operator Service** is a micro-service in charge of managing the workflow executing requests.
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The main responsibilities are:
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- Expose an HTTP API allowing for the execution of data access and compute endpoints.
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- Interact with the infrastructure (cloud/on-premise) using the Publisher's credentials.
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- Start/stop/execute computing instances with the algorithms provided by users.
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- Retrieve the logs generated during executions.
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Typically the Operator Service is integrated from Ocean Provider, but can be called independently of it.
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The Operator Service is in charge of establishing the communication with the K8s cluster, allowing it to:
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- Register new compute jobs
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- List the current compute jobs
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- Get a detailed result for a given job
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- Stop a running job
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The Operator Service doesn't provide any storage capability, all the state is stored directly in the K8s cluster.
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#### Operator Engine
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The **Operator Engine** is in charge of orchestrating the compute infrastructure using Kubernetes as backend where each compute job runs in an isolated [Kubernetes Pod](https://kubernetes.io/docs/concepts/workloads/pods/). Typically the Operator Engine retrieves the workflows created by the Operator Service in Kubernetes, and manage the infrastructure necessary to complete the execution of the compute workflows.
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The Operator Engine is in charge of retrieving all the workflows registered in a K8s cluster, allowing to:
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- Orchestrate the flow of the execution
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- Start the configuration pod in charge of download the workflow dependencies (datasets and algorithms)
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- Start the pod including the algorithm to execute
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- Start the publishing pod that publish the new assets created in the Ocean Protocol network.
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- The Operator Engine doesn't provide any storage capability, all the state is stored directly in the K8s cluster.
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#### Pod: Configuration
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#### Pod: Publishing
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