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

Android in docker solution with noVNC supported and video recording

Open Source Platform for developing, scaling and deploying serious ML, AI, and data science systems

Prevent cloud misconfigurations and find vulnerabilities during build-time in infrastructure as code, container images and open source packages with Checkov by Bridgecrew.

Multi-Cloud Security Auditing Tool

Rules engine for cloud security, cost optimization, and governance, DSL in yaml for policies to query, filter, and take actions on resources

Python scripts for ETL (extract, transform and load) jobs for Ethereum blocks, transactions, ERC20 / ERC721 tokens, transfers, receipts, logs, contracts, internal transactions. Data is available in Google BigQuery https://goo.gl/oY5BCQ

[UNMAINTAINED] A goal, task & habit tracker + personal dashboard to focus on what matters

Fix Inventory helps you identify and remove the most critical risks in AWS, GCP, Azure and Kubernetes.

Cloud ML Engine repo. Please visit the new Vertex AI samples repo at https://github.com/GoogleCloudPlatform/vertex-ai-samples

dstack is a lightweight, open-source alternative to Kubernetes & Slurm, simplifying AI container orchestration with multi-cloud & on-prem support. It natively supports NVIDIA, AMD, & TPU.

LLMs for your CLI

Forseti Security

FinOps, MLOps and cloud cost optimization tool. Supports AWS, Azure, GCP, Alibaba Cloud and Kubernetes.

🔥 Blazing fast bulk data transfers between any cloud 🔥

Dispatch and distribute your ML training to "serverless" clusters in Python, like PyTorch for ML infra. Iterable, debuggable, multi-cloud/on-prem, identical across research and production.

The next generation of Infrastructure-as-Code. Work with high-level constructs instead of getting lost in low-level cloud configuration.

🌀 𝗧𝗵𝗲 𝗙𝘂𝗹𝗹 𝗦𝘁𝗮𝗰𝗸 𝟳-𝗦𝘁𝗲𝗽𝘀 𝗠𝗟𝗢𝗽𝘀 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 | 𝗟𝗲𝗮𝗿𝗻 𝗠𝗟𝗘 & 𝗠𝗟𝗢𝗽𝘀 for free by designing, building and deploying an end-to-end ML batch system ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 2.5 𝘩𝘰𝘶𝘳𝘴 𝘰𝘧 𝘳𝘦𝘢𝘥𝘪𝘯𝘨 & 𝘷𝘪𝘥𝘦𝘰 𝘮𝘢𝘵𝘦𝘳𝘪𝘢𝘭𝘴

SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture.

80+ DevOps & Data CLI Tools - AWS, GCP, GCF Python Cloud Functions, Log Anonymizer, Spark, Hadoop, HBase, Hive, Impala, Linux, Docker, Spark Data Converters & Validators (Avro/Parquet/JSON/CSV/INI/XML/YAML), Travis CI, AWS CloudFormation, Elasticsearch, Solr etc.