Search Results for "production management" - Page 2

Showing 6852 open source projects for "production management"

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  • 1
    K3s

    K3s

    Lightweight Kubernetes

    Lightweight Kubernetes. Production-ready, easy to install, half the memory, all in a binary less than 100 MB. K3s is a highly available, certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. K3s is packaged as a single <70MB binary that reduces the dependencies and steps needed to install, run and auto-update a production Kubernetes cluster. Both ARM64 and ARMv7 are supported with binaries...
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  • 2
    Dagster

    Dagster

    An orchestration platform for the development, production

    Dagster is an orchestration platform for the development, production, and observation of data assets. Dagster as a productivity platform: With Dagster, you can focus on running tasks, or you can identify the key assets you need to create using a declarative approach. Embrace CI/CD best practices from the get-go: build reusable components, spot data quality issues, and flag bugs early. Dagster as a robust orchestration engine: Put your pipelines into production with a robust multi-tenant...
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  • 3
    Kruise

    Kruise

    Automated management of large-scale applications on Kubernetes

    OpenKruise is an extended component suite for Kubernetes, which mainly focuses on automated management of large-scale applications, such as deployment, upgrade, ops, and availability protection. Most features provided by OpenKruise are built primarily based on CRD extensions. They can work in pure Kubernetes clusters without any other dependencies. Kubernetes itself has already provided some features for application deployment and management, such as some basic Workloads. However, it is far...
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  • 4
    Feathr

    Feathr

    A scalable, unified data and AI engineering platform for enterprise

    Feathr is a data and AI engineering platform that is widely used in production at LinkedIn for many years and was open sourced in 2022. It is currently a project under LF AI & Data Foundation. Define data and feature transformations based on raw data sources (batch and streaming) using Pythonic APIs. Register transformations by names and get transformed data(features) for various use cases including AI modeling, compliance, go-to-market and more. Share transformations and data(features) across...
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  • 5
    Great Expectations

    Great Expectations

    Always know what to expect from your data

    ... are a great start, but it takes more to get to production-ready data validation. Where are Expectations stored? How do they get updated? How do you securely connect to production data systems? How do you notify team members and triage when data validation fails? Great Expectations supports all of these use cases out of the box. Instead of building these components for yourself over weeks or months, you will be able to add production-ready validation to your pipeline in a day.
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  • 6
    Juju

    Juju

    Orchestration engine that enables the deployment, and integration

    Juju is an open source application orchestration engine that enables any application operation (deployment, integration, lifecycle management) on any infrastructure (Kubernetes or otherwise) at any scale (development or production) in the same easy way (typically, one line of code), through special operators called ‘charms’. A charm is an operator - business logic encapsulated in reusable software packages that automate every aspect of an application's life.
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  • 7
    Breeze

    Breeze

    Deploy a Production Ready Kubernetes Cluster with graphical interface

    Deploy a Production Ready Kubernetes Cluster with a graphical interface. Project Breeze is an open source trusted solution that allows you to create Kubernetes clusters on your internal, secure, cloud network with the graphical user interface. As a cloud-native installer project, Breeze is listed in CNCF Cloud Native Interactive Landscape. Breeze combines all resources you need such as kubernetes components images, ansible playbooks for the deployment of kubernetes clusters into a single docker...
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  • 8
    ContainerSSH

    ContainerSSH

    ContainerSSH: Launch containers on demand

    An SSH Server that Launches Containers in Kubernetes and Docker. Building a lab environment can be time-consuming. ContainerSSH solves this by providing dynamic SSH access with APIs, automatic cleanup on logout using ephemeral containers, and persistent volumes for storing data. Perfect for vendor and student labs. Provide production access to your developers, give them their usual tools while logging all changes. Authorize their access and create short-lived credentials for the database using...
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  • 9
    Eru

    Eru

    Eru, a simple, stateless, flexible, production-ready orchestrator

    Eru, a simple, stateless, flexible, production-ready orchestrator designed to easily integrate into existing workflows. Can run any virtualization things in long or short time. Eru can use multiple engines to run anything for the long or short term. This project is Eru Core. The Core use for resource allocation and managing resources' lifetime. After we implemented bootstrap in eru, now you can build and deploy eru with cli tool. Make sure you can clone code. After the fresh image was named...
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  • 10
    Conduit

    Conduit

    Conduit streams data between data stores. Kafka Connect replacement

    Conduit is a data streaming tool written in Go. It aims to provide the best user experience for building and running real-time data pipelines. Conduit comes with batteries included, it provides a UI, common connectors, processors and observability data out of the box. Sync data between your production systems using an extensible, event-first experience with minimal dependencies that fit within your existing workflow. Eliminate the multi-step process you go through today. Just download...
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  • 11
    Recommenders

    Recommenders

    Best practices on recommendation systems

    The Recommenders repository provides examples and best practices for building recommendation systems, provided as Jupyter notebooks. The module reco_utils contains functions to simplify common tasks used when developing and evaluating recommender systems. Several utilities are provided in reco_utils to support common tasks such as loading datasets in the format expected by different algorithms, evaluating model outputs, and splitting training/test data. Implementations of several...
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  • 12
    MLRun

    MLRun

    Machine Learning automation and tracking

    MLRun is an open MLOps framework for quickly building and managing continuous ML and generative AI applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications, significantly reducing engineering efforts, time to production, and computation resources. MLRun breaks the silos between data, ML, software, and DevOps/MLOps teams, enabling collaboration and fast continuous...
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  • 13
    ODD Platform

    ODD Platform

    First open-source data discovery and observability platform

    Unlock the power of big data with OpenDataDiscovery Platform. Experience seamless end-to-end insights, powered by unprecedented observability and trust - from ingestion to production - while building your ideal tech stack! Democratize data and accelerate insights. Find data that fits your use case and discover hints left by your peers to leverage existing knowledge. Explore tags, ownership details, links to other sources and other information to shorten and simplify data discovery phase. Forget...
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  • 14
    memphis

    memphis

    Next-Generation Event Processing Platform

    .... Increase observability, integrations with 3rd-party monitoring tools, real-time notifications, stream lineage, and therefore troubleshooting time reduction. Enable rapid development and ultra-short time-to-production.
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  • 15
    iRODS

    iRODS

    Open Source Data Management Software

    The Integrated Rule-Oriented Data System (iRODS) is open-source data management software used by research, commercial, and governmental organizations worldwide. iRODS is released as a production-level distribution aimed at deployment in mission-critical environments. It virtualizes data storage resources, so users can take control of their data, regardless of where and on what device the data is stored. The development infrastructure supports exhaustive testing on supported platforms; plugin...
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  • 16
    NVIDIA Merlin

    NVIDIA Merlin

    Library providing end-to-end GPU-accelerated recommender systems

    ... on the NVIDIA developer website. Transform data (ETL) for preprocessing and engineering features. Accelerate your existing training pipelines in TensorFlow, PyTorch, or FastAI by leveraging optimized, custom-built data loaders. Scale large deep learning recommender models by distributing large embedding tables that exceed available GPU and CPU memory. Deploy data transformations and trained models to production with only a few lines of code.
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  • 17
    Eventmie

    Eventmie

    Run your own Events business with Eventmie

    Create a dedicated platform for Event Planning with Laravel for Free. Eventmie is an Event planning and management Laravel package. With Eventmie, launch a dedicated platform for Event planning on your domain. Streamline the event planning process through automation. Eventmie is secure, scalable, and production-ready. Just install it into a brand new Laravel application or an existing one and start selling events for free. Streamline the event planning process through automation. Eventmie...
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  • 18
    dynaconf

    dynaconf

    Configuration Management for Python

    Inspired by the 12-factor application guide. Settings management (default values, validation, parsing, templating). Protection of sensitive information (passwords/tokens). Multiple file formats toml|yaml|json|ini|py and also customizable loaders. Full support for environment variables to override existing settings (dotenv support included). Optional layered system for multi environments [default, development, testing, production] (also called multi profiles). Built-in support for Hashicorp...
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  • 19
    Weights and Biases

    Weights and Biases

    Tool for visualizing and tracking your machine learning experiments

    Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Quickly identify model regressions. Use W&B to visualize results in real time, all in a central dashboard. Focus on the interesting ML. Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. Reproduce any model, with saved code...
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  • 20
    HyperDX

    HyperDX

    An open source observability platform unifying session replays & logs

    HyperDX helps engineers figure out why production is broken faster by centralizing and correlating logs, metrics, traces, exceptions and session replays in one place. An open-source and developer-friendly alternative to Datadog and New Relic. The HyperDX stack ingests, stores, and searches/graphs your telemetry data. After standing up the Docker Compose stack, you'll want to instrument your app to send data over to HyperDX.
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  • 21
    Authorizer

    Authorizer

    Your data, your control. Fully open source, authentication, etc.

    ...+ databases including Postgres, MySQL, SQLite, SQLServer, YugaByte, MariaDB, PlanetScale, CassandraDB, ScyllaDB, MongoDB, ArangoDB). This guide helps you practice using Authorizer to evaluate it before you use it in a production environment. It includes instructions for installing the Authorizer server in local or standalone mode.
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  • 22
    KServe

    KServe

    Standardized Serverless ML Inference Platform on Kubernetes

    KServe provides a Kubernetes Custom Resource Definition for serving machine learning (ML) models on arbitrary frameworks. It aims to solve production model serving use cases by providing performant, high abstraction interfaces for common ML frameworks like Tensorflow, XGBoost, ScikitLearn, PyTorch, and ONNX. It encapsulates the complexity of autoscaling, networking, health checking, and server configuration to bring cutting edge serving features like GPU Autoscaling, Scale to Zero, and Canary...
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  • 23
    Node.js Backend Architecture

    Node.js Backend Architecture

    Node.js Backend Architecture Typescript

    This project is designed for a production-ready environment. It can handle the scale and complexity of a very demanding application. This project is being used by companies like MindOrks, AfterAcademy, and CuriousJr. Apps/Websites having 10+ million userbase.
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  • 24
    SOFAJRaft

    SOFAJRaft

    A production-grade java implementation of RAFT consensus algorithm

    SOFAJRaft is a production-level, high-performance Java implementation based on the RAFT consistency algorithm that supports MULTI-RAFT-GROUP for high-load, low-latency scenarios. With SOFAJRaft you can focus on your business area. SOFAJRaft handles all RAFT-related technical challenges. SOFAJRaft is very user-friendly, which provides several examples, making it easy to understand and use.
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  • 25
    Loggie

    Loggie

    A lightweight, cloud-native data transfer agent and aggregator

    Loggie is a lightweight, high-performance, cloud-native agent and aggregator based on Golang. Loggie includes LogConfig/ClusterLogConfig/Interceptor/Sink CRDs, allowing for the creation of data collection, transfer, processing, and sending pipelines through simple YAML file creation. Supports deployment as an independent intermediate machine, which can receive aggregated data sent by Loggie Agent and can also be used to consume and process various data sources. Configure Filebeat and Loggie...
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