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- The __consumer__ ingests the ZTF Kafka stream and republishes it as a Pub/Sub stream.
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- The __data storage__ (x2) and __processing__ (x1) components ingest the consumer's Pub/Sub stream and proceed with their function. These components store their output data to Cloud Storage and/or BigQuery, and publish it to a dedicated Pub/Sub topic/stream.
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In addition, there is a "__night conductor__" (running on a VM) that
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orchestrates the broker,
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starting up resources and jobs at night (and will shut them down in the morning, but that script isn't written yet).
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You can monitor the production broker at the [__ZTF Stream Monitoring Dashboard__](https://console.cloud.google.com/monitoring/dashboards/builder/d8b7db8b-c875-4b93-8b31-d9f427f0c761?project=ardent-cycling-243415&dashboardBuilderState=%257B%2522editModeEnabled%2522:false%257D&timeDomain=1w).
1. Setup and configure a new Google Cloud Platform (GCP) project.
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-[Instructions in our current docs](https://pitt-broker.readthedocs.io/en/latest/installation_setup/installation.html). We would need to follow pieces of the "Installation" and "Defining Environmental Variables" sections. Our project is already setup, so leaving out most of the details for now.
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2. Install GCP tools on your machine:
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-[Google Cloud SDK](https://cloud.google.com/sdk/docs/install): Follow the instructions at the link. (This installs `gcloud`, `gsutil` and `bq` command line tools). I use a minimum version of Google Cloud SDK 323.0.0.
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-[Cloud Client Libraries for Python](https://cloud.google.com/python/docs/reference): Each service requires a different library; the ones we need are (I hope) all listed in the `requirements.txt` in this directory. Install them with (e.g., ) `pip install -r requirements.txt`.
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3. Follow instructions in [broker/README.md](broker/README.md) to complete the setup.
@@ -9,3 +88,5 @@ Data from the Large Synoptic Survey Telescope ([LSST](https://www.lsst.org)) wil
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The 60-second alert stream will not be made available to the public (at least not in its entirety). Instead, LSST will rely on a small number of (~7) community developed *broker* systems to publically relay the information. This repo represents the construction of an LSST broker designed to run on the Google Cloud Platform ([GCP](https://cloud.google.com)) using alerts from the Zwicky Transient Facility ([ZTF](https://www.ztf.caltech.edu)) as a testing ground.
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Full online documentation is available online via [Read the Docs](https://pitt-broker.readthedocs.io/en/latest/index.html).
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