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Merge pull request #253 from quixio/dev
Docs Release 2024-02-002
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docs/create/create-environment.md

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There are three broker options:
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1. Quix broker
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2. Managed Kafka
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2. Managed Kafka (using a broker provider)
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3. Self-hosted
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Each of these is described briefly in the following sections.
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1. [Confluent Cloud](https://www.confluent.io/confluent-cloud/){target=_blank}
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2. [Redpanda](https://redpanda.com/){target=_blank}
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3. [Aiven](https://aiven.io/kafka){target=_blank}
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4. [Upstash](https://upstash.com/){target=_blank}
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Select your managed broker option, and then follow the detailed setup guide provided to connect Quix to the broker.
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You also have the option to test your connection with the Kafka server before continuing.
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### Broker setup guides
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As well as the guides built into Quix Cloud to help set up your broker, there are also some setup guides in the [Integrations documentation](../integrations/brokers/overview.md).
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## Data and streaming services
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The last step in creating an environment is to choose your data and streaming services option.

docs/get-started/welcome.md

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---
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title: Quix Developer Documentation
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description: Welcome to the Quix Developer documentation. This documentation includes guides, tutorials, and API references for using Quix Cloud, Quix Streams, and Quix Bring Your Own Cluster (BYOC).
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---
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# Quix developer docs
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<p style="font-size: 1rem;">Quix is a complete platform for building, deploying, and monitoring stream processing pipelines.</p>

docs/get-started/what-is-quix.md

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description: Quix is a complete solution for building, deploying, and monitoring stream processing pipelines with Python, Docker, Kafka, and Git.
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# What is Quix?
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# Quix: Python stream processing made simple
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Quix is a complete platform for building, deploying, and monitoring streaming data pipelines. It enables software developers, data scientists, and data engineers who use Python to focus on app development and extracting value from real-time data pipelines, rather than dealing with the underlying infrastructure.
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[Sign up for free](https://portal.platform.quix.io/self-sign-up){target=_blank}.
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## Quix in brief
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## Python stream processing in brief
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Briefly, here's how you would build a stream processing pipeline with Quix:
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Briefly, here's how you would build a Python stream processing pipeline with Quix:
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1. Configure data sources and destinations (see [connectors](#connectors)).
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2. Write your stream processing application in Python using [Quix Streams](../quix-streams/quix-streams-intro.md), an open source stream processing library.
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