Search Results for "logs"
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Showing 8 open source projects for "logs"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Ethereum ETL
Python scripts for ETL (extract, transform and load) jobs for Ethereum
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. Ethereum ETL lets you convert blockchain data into convenient formats like CSVs and relational databases. -
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Tactical RMM
A remote monitoring & management tool, built with Django, Vue and Go
...Remote command and script execution (batch, powershell and python scripts). Event log viewer. Services management. Windows patch management. Automated checks with email/SMS alerting (cpu, disk, memory, services, scripts, event logs). Automated task runner (run scripts on a schedule). Remote software installation via chocolatey. Software and hardware inventory. -
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LocalStack
Develop and test your cloud apps offline
LocalStack is a fully functional local AWS cloud stack that enables you to develop and test your cloud and serverless apps offline. It spins up an easy-to-use testing environment on your local machine that has the same APIs and works the same way as the real AWS cloud environment. It can spin up a number of different core Cloud APIs on your local machine, including API Gateway, Kinesis, DynamoDB, Firehose, Lambda and many others. LocalStack was built on some of today’s best-of-breed... -
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TensorFlow Model Garden
Models and examples built with TensorFlow
...We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models are suitable. A flexible and lightweight library that users can easily use or fork when writing customized training loop code in TensorFlow 2.x. It seamlessly integrates with tf.distribute and supports running on different device types (CPU, GPU, and TPU). -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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AWS Chalice
Python Serverless Microframework for AWS
...A single command builds your app, bundles dependencies, generates infrastructure templates, and deploys to your account with sensible defaults. The framework includes local development tools so you can iterate on HTTP routes and inspect logs before shipping to the cloud. It also manages per-stage configuration, environment variables, IAM permissions scaffolding, and packaging optimizations to keep cold starts small. While it’s intentionally lightweight, it supports common production needs like CORS, custom authorizers, binary responses, and fine-grained IAM so you can grow from prototype to production without rewriting your stack. -
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Model Search
Framework that implements AutoML algorithms
...It supports multiple tasks (such as vision or text) by letting you express reusable building blocks—layers, cells, and topologies—that the search can recombine. Training, evaluation, and promotion of candidates are orchestrated automatically, with strong emphasis on reproducibility and fair comparisons. The framework logs trials, metrics, and artifacts so you can analyze what the search learned and why certain designs dominate. It’s intended as a platform for method development as much as for model discovery. -
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StreamAlert
StreamAlert is a serverless, realtime data analysis framework
...Rules are written in Python; they can utilize any Python libraries or functions. Merge similar alerts and automatically promote new rules if they are not too noisy. Ingested logs and generated alerts can be retroactively searched for compliance and research. Serverless design is cheaper, easier to maintain, and scales to terabytes per day. Deployment is automated, simple, safe and repeatable for any AWS account. Secure by design, least-privilege execution, containerized analysis, and encrypted data storage. -
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Jeffy
Serverless Application Framework for Python AWS Lambda
...Logging - Jeffy provides easy to see JSON format logging. All events, responses and errors are captured and you can make configurations for any additional attributes you'd like to see on the logs. 2. Decorators - Jeffy has an extensive range of decorators/ event handlers for implementing common things for Lambda functions. 3. Tracing - Events are traceable within related functions and AWS services with generating and passing correlation_id.
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