| Name | baler-operator JSON |
| Version |
0.0.1.dev0
JSON |
| download |
| home_page | None |
| Summary | A Kubernetes operator for managing NLP framework deplotments. |
| upload_time | 2024-04-16 15:46:46 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license |
Apache License
Version 2.0, January 2004
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| keywords |
baler
baler-operator
haystack
kubernetes
nlp
operator
|
| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
|
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No Travis.
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| coveralls test coverage |
No coveralls.
|
# baler-operator
[](https://github.com/gatecastle/baler-operator/actions/workflows/release-pipeline.yaml)
[](https://github.com/gatecastle/baler-operator/actions/workflows/linter-check.yaml)
[](https://github.com/gatecastle/baler-operator/actions/workflows/make-docs.yaml)
[](https://coveralls.io/github/gatecastle/baler-operator)
[](https://hub.docker.com/r/gatecastle/baler-operator)
[](https://hub.docker.com/r/gatecastle/baler-operator)
[](https://artifacthub.io/packages/search?repo=baler-operator)
<img src="docs/source/assets/baler_logo.png" alt="logo" width="248"/>
👋 **Welcome to Baler!** A Kubernetes-native, secure, enterprise-grade operator engineered to redefine the deployment and operational paradigms of NLP pipelines.
Our platform serves as a beacon for developers and operations teams alike, facilitating the seamless transition of NLP frameworks like [Haystack](https://haystack.deepset.ai/) from development to robust, production-grade environments.
Through the synergy of open source and community collaboration, Baler is poised to unlock unprecedented efficiency and scalability in NLP pipeline management.
### Important links:
- [Documentation](https://baler.gatecastle.com)
- [Quickstart](https://baler.gatecastle.com/en/latest/quickstart.html)
- [Deployment](https://baler.gatecastle.com/en/latest/deployment.html)
- [DockerHub](https://hub.docker.com/r/gatecastle/baler-operator)
## Mission 🌟
**Our objective is clear: to empower teams by providing a streamlined pathway for deploying NLP pipelines**, not only for development purposes but also for deployment within demanding production contexts.
Leveraging Kubernetes' dynamic ecosystem, Baler delivers a platform where innovation meets reliability, enabling projects to scale seamlessly from concept to production without compromising on security, performance, or scalability.
## Philosophy 📘
At the heart of Baler lies the principle of KISS—Keep It Simple, Stupid.
This philosophy, rooted in a design principle from the U.S. Navy in 1960, emphasizes simplicity as the foundation of effective, error-resistant systems.
In the complex landscape of NLP pipeline development and operation, we understand that complexity can be a significant obstacle. Baler embodies simplicity, making our platform accessible, intuitive, and straightforward for all users.
Beyond ease of use, we believe that simplicity is a key ally in bolstering the security and reliability of our platform. These attributes are crucial for the success of real-life production deployments. By minimizing complexity, Baler enhances security, reducing vulnerability risks, and boosts reliability, ensuring that NLP pipelines can robustly meet real-world demands.
Discover more about the KISS principle [here](https://en.wikipedia.org/wiki/KISS_principle).
### Harmonizing Development and Operations ⚙️
Crafting NLP pipelines poses its own set of challenges; scaling them in production is an entirely different challenge. Baler strives to harmonize these efforts, equipping both developers and operations personnel with the tools they need. Whether you're fine-tuning pipelines in development or deploying them at scale in production, Baler provides a unified, secure, and scalable platform tailored to your needs.
By integrating advanced NLP frameworks within a Kubernetes-native ecosystem, Baler ensures your projects transition smoothly from ideation to production, without losing sight of security, reliability, and performance.
Join us on this journey to pioneer the future of NLP deployment. Together, let's establish a new standard for deploying and managing NLP pipelines, making them more accessible, reliable, and secure than ever before.
## Documentation 📚
For detailed information on how to use Baler, please refer to our [documentation](https://baler.gatecastle.com).
## Getting Started 🚀
Read the [Getting Started](https://baler.gatecastle.com/en/latest/quickstart.html) guide to learn how to deploy Baler on your local machine for experimentation.
## Deployment 🚢
Read the [Deployment](https://baler.gatecastle.com/en/latest/deployment.html) guide to learn how to deploy pipelines to any Kubernetes cluster using Baler.
## Contributing 👥
Please read [CONTRIBUTING.md](https://github.com/gatecastle/baler-operator/blob/main/CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us.
## Versioning 🏷️
We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://github.com/gatecastle/baler-operator/tags).
## Authors ✍️
* **Greg Nagy** - *Initial work* - [justcallmegreg](https://github.com/justcallmegreg)
See also the list of [contributors](https://github.com/gatecastle/baler-operator/graphs/contributors) who participated in this project.
## License 📄
This project is licensed under the Apache License, Version 2.0 - see the [LICENSE.md](https://github.com/gatecastle/baler-operator/blob/main/LICENSE.md) file for details.
[](https://app.fossa.com/projects/git%2Bgithub.com%2Fgatecastle%2Fbaler-operator?ref=badge_large&issueType=license)
Raw data
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"keywords": "baler, baler-operator, haystack, kubernetes, nlp, operator",
"author": null,
"author_email": "Greg Nagy <greg@gatecastle.com>",
"download_url": "https://files.pythonhosted.org/packages/f3/fe/b4cea052ec9fe6448b4312a8984b1ce94f49bf77984a2b99dcc28e89c4c2/baler_operator-0.0.1.dev0.tar.gz",
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"description": "# baler-operator\n\n\n\n[](https://github.com/gatecastle/baler-operator/actions/workflows/release-pipeline.yaml)\n[](https://github.com/gatecastle/baler-operator/actions/workflows/linter-check.yaml)\n[](https://github.com/gatecastle/baler-operator/actions/workflows/make-docs.yaml)\n[](https://coveralls.io/github/gatecastle/baler-operator)\n\n\n[](https://hub.docker.com/r/gatecastle/baler-operator)\n[](https://hub.docker.com/r/gatecastle/baler-operator)\n\n[](https://artifacthub.io/packages/search?repo=baler-operator)\n\n<img src=\"docs/source/assets/baler_logo.png\" alt=\"logo\" width=\"248\"/>\n\n\ud83d\udc4b **Welcome to Baler!** A Kubernetes-native, secure, enterprise-grade operator engineered to redefine the deployment and operational paradigms of NLP pipelines.\n\nOur platform serves as a beacon for developers and operations teams alike, facilitating the seamless transition of NLP frameworks like [Haystack](https://haystack.deepset.ai/) from development to robust, production-grade environments.\n\nThrough the synergy of open source and community collaboration, Baler is poised to unlock unprecedented efficiency and scalability in NLP pipeline management.\n\n### Important links:\n\n- [Documentation](https://baler.gatecastle.com)\n- [Quickstart](https://baler.gatecastle.com/en/latest/quickstart.html)\n- [Deployment](https://baler.gatecastle.com/en/latest/deployment.html)\n- [DockerHub](https://hub.docker.com/r/gatecastle/baler-operator)\n\n\n## Mission \ud83c\udf1f\n\n**Our objective is clear: to empower teams by providing a streamlined pathway for deploying NLP pipelines**, not only for development purposes but also for deployment within demanding production contexts. \n\nLeveraging Kubernetes' dynamic ecosystem, Baler delivers a platform where innovation meets reliability, enabling projects to scale seamlessly from concept to production without compromising on security, performance, or scalability.\n\n## Philosophy \ud83d\udcd8\n\nAt the heart of Baler lies the principle of KISS\u2014Keep It Simple, Stupid. \n\nThis philosophy, rooted in a design principle from the U.S. Navy in 1960, emphasizes simplicity as the foundation of effective, error-resistant systems. \n\nIn the complex landscape of NLP pipeline development and operation, we understand that complexity can be a significant obstacle. Baler embodies simplicity, making our platform accessible, intuitive, and straightforward for all users.\n\nBeyond ease of use, we believe that simplicity is a key ally in bolstering the security and reliability of our platform. These attributes are crucial for the success of real-life production deployments. By minimizing complexity, Baler enhances security, reducing vulnerability risks, and boosts reliability, ensuring that NLP pipelines can robustly meet real-world demands.\n\nDiscover more about the KISS principle [here](https://en.wikipedia.org/wiki/KISS_principle).\n\n### Harmonizing Development and Operations \u2699\ufe0f\n\nCrafting NLP pipelines poses its own set of challenges; scaling them in production is an entirely different challenge. Baler strives to harmonize these efforts, equipping both developers and operations personnel with the tools they need. Whether you're fine-tuning pipelines in development or deploying them at scale in production, Baler provides a unified, secure, and scalable platform tailored to your needs.\n\nBy integrating advanced NLP frameworks within a Kubernetes-native ecosystem, Baler ensures your projects transition smoothly from ideation to production, without losing sight of security, reliability, and performance.\n\nJoin us on this journey to pioneer the future of NLP deployment. Together, let's establish a new standard for deploying and managing NLP pipelines, making them more accessible, reliable, and secure than ever before.\n\n## Documentation \ud83d\udcda\n\nFor detailed information on how to use Baler, please refer to our [documentation](https://baler.gatecastle.com).\n\n## Getting Started \ud83d\ude80\n\nRead the [Getting Started](https://baler.gatecastle.com/en/latest/quickstart.html) guide to learn how to deploy Baler on your local machine for experimentation.\n\n## Deployment \ud83d\udea2\n\nRead the [Deployment](https://baler.gatecastle.com/en/latest/deployment.html) guide to learn how to deploy pipelines to any Kubernetes cluster using Baler.\n\n## Contributing \ud83d\udc65\n\nPlease read [CONTRIBUTING.md](https://github.com/gatecastle/baler-operator/blob/main/CONTRIBUTING.md) for details on our code of conduct, and the process for submitting pull requests to us.\n\n## Versioning \ud83c\udff7\ufe0f\n\nWe use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://github.com/gatecastle/baler-operator/tags).\n\n## Authors \u270d\ufe0f\n\n* **Greg Nagy** - *Initial work* - [justcallmegreg](https://github.com/justcallmegreg)\n\nSee also the list of [contributors](https://github.com/gatecastle/baler-operator/graphs/contributors) who participated in this project.\n\n## License \ud83d\udcc4\n\nThis project is licensed under the Apache License, Version 2.0 - see the [LICENSE.md](https://github.com/gatecastle/baler-operator/blob/main/LICENSE.md) file for details.\n\n[](https://app.fossa.com/projects/git%2Bgithub.com%2Fgatecastle%2Fbaler-operator?ref=badge_large&issueType=license)\n",
"bugtrack_url": null,
"license": "\n Apache License\n Version 2.0, January 2004\n http://www.apache.org/licenses/\n \n TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\n \n 1. Definitions.\n \n \"License\" shall mean the terms and conditions for use, reproduction,\n and distribution as defined by Sections 1 through 9 of this document.\n \n \"Licensor\" shall mean the copyright owner or entity authorized by\n the copyright owner that is granting the License.\n \n \"Legal Entity\" shall mean the union of the acting entity and all\n other entities that control, are controlled by, or are under common\n control with that entity. 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For the purposes\n of this License, Derivative Works shall not include works that remain\n separable from, or merely link (or bind by name) to the interfaces of,\n the Work and Derivative Works thereof.\n \n \"Contribution\" shall mean any work of authorship, including\n the original version of the Work and any modifications or additions\n to that Work or Derivative Works thereof, that is intentionally\n submitted to Licensor for inclusion in the Work by the copyright owner\n or by an individual or Legal Entity authorized to submit on behalf of\n the copyright owner. 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If You\n institute patent litigation against any entity (including a\n cross-claim or counterclaim in a lawsuit) alleging that the Work\n or a Contribution incorporated within the Work constitutes direct\n or contributory patent infringement, then any patent licenses\n granted to You under this License for that Work shall terminate\n as of the date such litigation is filed.\n \n 4. Redistribution. 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The contents\n of the NOTICE file are for informational purposes only and\n do not modify the License. You may add Your own attribution\n notices within Derivative Works that You distribute, alongside\n or as an addendum to the NOTICE text from the Work, provided\n that such additional attribution notices cannot be construed\n as modifying the License.\n \n You may add Your own copyright statement to Your modifications and\n may provide additional or different license terms and conditions\n for use, reproduction, or distribution of Your modifications, or\n for any such Derivative Works as a whole, provided Your use,\n reproduction, and distribution of the Work otherwise complies with\n the conditions stated in this License.\n \n 5. Submission of Contributions. Unless You explicitly state otherwise,\n any Contribution intentionally submitted for inclusion in the Work\n by You to the Licensor shall be under the terms and conditions of\n this License, without any additional terms or conditions.\n Notwithstanding the above, nothing herein shall supersede or modify\n the terms of any separate license agreement you may have executed\n with Licensor regarding such Contributions.\n \n 6. Trademarks. This License does not grant permission to use the trade\n names, trademarks, service marks, or product names of the Licensor,\n except as required for reasonable and customary use in describing the\n origin of the Work and reproducing the content of the NOTICE file.\n \n 7. Disclaimer of Warranty. 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In no event and under no legal theory,\n whether in tort (including negligence), contract, or otherwise,\n unless required by applicable law (such as deliberate and grossly\n negligent acts) or agreed to in writing, shall any Contributor be\n liable to You for damages, including any direct, indirect, special,\n incidental, or consequential damages of any character arising as a\n result of this License or out of the use or inability to use the\n Work (including but not limited to damages for loss of goodwill,\n work stoppage, computer failure or malfunction, or any and all\n other commercial damages or losses), even if such Contributor\n has been advised of the possibility of such damages.\n \n 9. Accepting Warranty or Additional Liability. While redistributing\n the Work or Derivative Works thereof, You may choose to offer,\n and charge a fee for, acceptance of support, warranty, indemnity,\n or other liability obligations and/or rights consistent with this\n License. However, in accepting such obligations, You may act only\n on Your own behalf and on Your sole responsibility, not on behalf\n of any other Contributor, and only if You agree to indemnify,\n defend, and hold each Contributor harmless for any liability\n incurred by, or claims asserted against, such Contributor by reason\n of your accepting any such warranty or additional liability.\n \n END OF TERMS AND CONDITIONS\n \n APPENDIX: How to apply the Apache License to your work.\n \n To apply the Apache License to your work, attach the following\n boilerplate notice, with the fields enclosed by brackets \"[]\"\n replaced with your own identifying information. (Don't include\n the brackets!) The text should be enclosed in the appropriate\n comment syntax for the file format. We also recommend that a\n file or class name and description of purpose be included on the\n same \"printed page\" as the copyright notice for easier\n identification within third-party archives.\n \n Copyright [yyyy] [name of copyright owner]\n \n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a copy of the License at\n \n http://www.apache.org/licenses/LICENSE-2.0\n \n Unless required by applicable law or agreed to in writing, software\n distributed under the License is distributed on an \"AS IS\" BASIS,\n WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n See the License for the specific language governing permissions and\n limitations under the License.",
"summary": "A Kubernetes operator for managing NLP framework deplotments.",
"version": "0.0.1.dev0",
"project_urls": null,
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