Showing 6 open source projects for "python accounting source code"

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  • 1
    PaaSTA

    PaaSTA

    An open, distributed platform as a service

    PaaSTA is a highly-available, distributed system for building, deploying, and running services using containers and Kubernetes. PaaSTA has been running production services at Yelp since 2016. It was originally designed to run on top of Apache Mesos but has subsequently been updated to use Kubernetes. Over time the features and functionality that PaaSTA provides have increased but the principal design remains the same. PaaSTA aims to take a declarative description of the services that teams...
    Downloads: 2 This Week
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  • 2
    Opta

    Opta

    The next generation of Infrastructure-as-Code

    Opta is an infrastructure-as-code framework. Rather than working with a low-level cloud configuration, Opta enables you to work with high-level constructs. Opta high-level constructs produce Terraform configuration files. This helps you avoid lock-in to Opta. You can write custom Terraform code or even take the Opta-generated Terraform and go your own way. Opta is a new kind of Infrastructure-as-Code (IaC) framework that lets engineers work with high-level constructs instead of getting lost...
    Downloads: 0 This Week
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  • 3
    Nebula-Python-SDK

    Nebula-Python-SDK

    A python SDK for managing Nebula container orchestrator

    A python SDK for managing Nebula container orchestrator. First, get NebulaPythonSDK onto your machine, now use it in your code. Nebula container orchestrator aims to help devs and ops treat IoT devices just like distributed Dockerized apps. It aim is to act as Docker orchestrator for IoT devices as well as for distributed services such as CDN or edge computing that can span thousands (possibly even millions) of devices worldwide and it does it all while being open-source and completely free. ...
    Downloads: 0 This Week
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  • 4
    Nebula docs

    Nebula docs

    Documentation repo of nebula orchestration system

    Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are appliances\virtual...
    Downloads: 0 This Week
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  • Cloud data warehouse to power your data-driven innovation Icon
    Cloud data warehouse to power your data-driven innovation

    BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.

    BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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  • 5
    Nebula reporter

    Nebula reporter

    The optional reporter container which reads nebula reports from Kafka

    Nebula is an open source-distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking effect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe. Ever wandered how your going to push an update...
    Downloads: 0 This Week
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  • 6
    lmctfy

    lmctfy

    lmctfy is the open source version of Google’s container stack

    lmctfy is Google’s open-source container runtime that exposed Linux cgroups and namespaces through a higher-level API, predating the widespread adoption of modern container tools. It offered a daemon and client for creating, updating, and destroying resource-isolated “containers” with quotas on CPU, memory, and other subsystems. The project focused on operational safety—clean hierarchies, accounting, and predictable behavior under resource pressure—reflecting lessons from running containers at scale. ...
    Downloads: 0 This Week
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