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Top 23 Python Cloud Projects
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LocalStack
💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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SaltStack
Software to automate the management and configuration of any infrastructure or application at scale. Get access to the Salt software package repository here:
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awesome-aws
A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources. Featuring the Fiery Meter of AWSome.
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prowler
Prowler is an Open Source Security tool for AWS, Azure, GCP and Kubernetes to do security assessments, audits, incident response, compliance, continuous monitoring, hardening and forensics readiness. Includes CIS, NIST 800, NIST CSF, CISA, FedRAMP, PCI-DSS, GDPR, HIPAA, FFIEC, SOC2, GXP, Well-Architected Security, ENS and more
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server
The Triton Inference Server provides an optimized cloud and edge inferencing solution. (by triton-inference-server)
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dev-setup
macOS development environment setup: Easy-to-understand instructions with automated setup scripts for developer tools like Vim, Sublime Text, Bash, iTerm, Python data analysis, Spark, Hadoop MapReduce, AWS, Heroku, JavaScript web development, Android development, common data stores, and dev-based OS X defaults.
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cloud-custodian
Rules engine for cloud security, cost optimization, and governance, DSL in yaml for policies to query, filter, and take actions on resources
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apache-libcloud
Apache Libcloud is a Python library which hides differences between different cloud provider APIs and allows you to manage different cloud resources through a unified and easy to use API.
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cloudproxy
Hide your scrapers IP behind the cloud. Provision proxy servers across different cloud providers to improve your scraping success.
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nagios-plugins
450+ AWS, Hadoop, Cloud, Kafka, Docker, Elasticsearch, RabbitMQ, Redis, HBase, Solr, Cassandra, ZooKeeper, HDFS, Yarn, Hive, Presto, Drill, Impala, Consul, Spark, Jenkins, Travis CI, Git, MySQL, Linux, DNS, Whois, SSL Certs, Yum Security Updates, Kubernetes, Cloudera etc...
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Project mention: LocalStack – a functional local AWS cloud stack | news.ycombinator.com | 2024-04-05
The AWS CLI is a must-have tool if your team relies on Amazon Web Services. It lets you effortlessly interact with AWS services, orchestrate resource management, and automate tasks from the comfort of your terminal. Once you get used to the tool, you'll notice how convenient and quick it is to fit into your processes – especially compared to going through AWS's web-based user interface.
Project mention: Looking for a way to remote in to K's of raspberry pi's... | /r/sysadmin | 2023-12-10
Project mention: Superpower REST API DX with Serverless ⚡ and DevOps Best Practices on AWS (🐍 Python Version) | dev.to | 2024-04-30If you want to write serverless apps with Python without using Serverless Framework, you can ship them with Chalice.
1. Prowler: https://github.com/prowler-cloud/prowler Prowler provides security best practices assessments, audits, incident response readiness, and continuous monitoring for AWS environments.
Project mention: AWS Python SDK downloaded over 1.4B times a month | news.ycombinator.com | 2024-05-08Might also consider how many times it is downloaded and never used, because it is a dependency in another project. There are a number of projects using boto just for the S3 compatibility layer too
https://github.com/boto/boto3/network/dependents
While at it - I heartily recommend you to install aws-shell which boosts your aws cli productivity by providing graphical autocompletion, hints and shortcuts as shown in the image below. I only discovered it recently myself and it's definitely a game changer!
Prowler and ScoutSuite are a good start for cloud stuff.
Project mention: Cutting down AWS cost by $150k per year simply by shutting things off | news.ycombinator.com | 2024-01-22> The best optimization is simply shutting things off
This is the way.
A similar idea has been bouncing around in my mind for a while now. An ideal, turnkey system would do the following:
- Execute via Lambda (serverless).
- Support automated startup and shutdown of various AWS resources on a schedule influenced by specially formatted tags.
- Enable resources to be brought back up out of schedule when demand dictates.
- Operate as a TCP/HTTP proxy that can delay clients so that a given service can be started when it is dormant or, even better, the service isn't serverless but you want it to be. This can't work for everything, but perhaps enough things such that the need to run always on services is reduced.
Cloud Custodian [1] can purportedly do some of this, but I've been reluctant to learn yet another YAML-based DSL to use it.
So this is my "make things designed to be always-on serverless instead" project and the work AWS has done to make Java apps function on Lambda keeps me thinking about the potential to take things that 1) have a relatively long startup time and 2) are designed to be long running service loops, and find a way to force them into the serverless execution model.
[1] https://cloudcustodian.io/
Project mention: Show HN: Running LLMs in one line of Python without Docker | news.ycombinator.com | 2023-10-04Hello Hacker News! We're Yangqing, Xiang and JJ from lepton.ai. We are building a platform to run any AI models as easy as writing local code, and to get your favorite models in minutes. It's like container for AI, but without the hassle of actually building a docker image.
We built and contributed to some of the world's most popular AI software - PyTorch 1.0, ONNX, Caffe, etcd, Kubernetes, etc. We also managed hundreds of thousands of computers in our previous jobs. And we found that the AI software stack is usually unnecessarily complex - and we want to change that.
Imagine if you are a developer who sees a good model on github, or HuggingFace. To make it a production ready service, the current solution usually requires you to build a docker image. But think about it - I have a few python code and a few python dependencies. That sounds like a huge overhead, right?
lepton.ai is really a pythonic way to free you from such difficulties. You write a simple python scaffold around your PyTorch / TensorFlow code, and lepton launches it as a full-fledged service callable via python, javascript, or any language that understands OpenAPI. We use containers under the hood, but you don't need to worry about all the infrastructure nuts and bolts.
We have made the python library open-source at https://github.com/leptonai/leptonai/. With it, launching a common HuggingFace model is as simple as a one liner. For example, if you have a GPU, Stable Diffusion XL is as simple as:
```
Python Cloud related posts
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AWS Python SDK downloaded over 1.4B times a month
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9 Ways to an EKS Cluster - Way 2 - AWS CLI
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Show HN: Real-time image autocomplete in <100 lines of code with SDXL Lightning
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AWS Boto3: Clients vs Resources - DynamoDB
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When have you screwed up, bad?
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Azure CLI takes ~700MB of disk space
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Asynchronous Python lib to work with Amazon SQS
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A note from our sponsor - SaaSHub
www.saashub.com | 10 May 2024
Index
What are some of the best open-source Cloud projects in Python? This list will help you:
Project | Stars | |
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1 | LocalStack | 52,289 |
2 | aws-cli | 14,924 |
3 | SaltStack | 13,873 |
4 | awesome-aws | 12,174 |
5 | chalice | 10,312 |
6 | prowler | 9,611 |
7 | boto3 | 8,712 |
8 | docker-android | 8,249 |
9 | server | 7,384 |
10 | aws-shell | 7,127 |
11 | ScoutSuite | 6,191 |
12 | dev-setup | 6,032 |
13 | cloud-custodian | 5,229 |
14 | SAWS | 5,193 |
15 | azure-cli | 3,865 |
16 | leptonai | 2,461 |
17 | apache-libcloud | 2,011 |
18 | policy_sentry | 1,941 |
19 | mist-ce | 1,826 |
20 | nixops | 1,724 |
21 | sceptre | 1,454 |
22 | cloudproxy | 1,358 |
23 | nagios-plugins | 1,120 |
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