awesome-repositories.com
ब्लॉग
awesome-repositories.com

AI-संचालित खोज के साथ बेहतरीन ओपन-सोर्स रिपॉजिटरी खोजें।

एक्सप्लोर करेंक्यूरेटेड खोजेंओपन-सोर्स विकल्पसेल्फ-होस्टेड सॉफ्टवेयरब्लॉगसाइटमैप
प्रोजेक्टहमारे बारे मेंहम रैंकिंग कैसे करते हैंप्रेसMCP सर्वर
कानूनीगोपनीयताशर्तें
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

13 रिपॉजिटरी

Awesome GitHub RepositoriesCluster Node Management

Defines configuration settings for individual compute nodes within a distributed processing cluster.

Distinguishing note: Focuses on node-level resource and identity settings, distinct from high-level cluster orchestration.

Explore 13 awesome GitHub repositories matching data & databases · Cluster Node Management. Refine with filters or upvote what's useful.

Awesome Cluster Node Management GitHub Repositories

AI के साथ बेहतरीन रिपॉजिटरी खोजें।हम AI का उपयोग करके सबसे सटीक रिपॉजिटरी खोजेंगे।
  • pola-rs/polarspola-rs का अवतार

    pola-rs/polars

    38,855GitHub पर देखें↗

    Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters. The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e

    Defines cluster node settings including identifiers, license paths, and memory limits for cluster deployments.

    Rustarrowdataframedataframe-library
    GitHub पर देखें↗38,855
  • vitessio/vitessvitessio का अवतार

    vitessio/vitess

    20,788GitHub पर देखें↗

    Vitess is a database clustering system for horizontal scaling of MySQL. It functions as a middleware layer that abstracts complex sharding and physical topology, allowing applications to interact with a distributed database environment through a unified interface. By intercepting and routing SQL queries across multiple shards, it enables large-scale data management while maintaining the appearance of a single database instance. The platform distinguishes itself through its ability to perform online schema migrations and distributed transaction coordination without requiring application downti

    Wraps individual database instances with a sidecar process to handle health monitoring, query execution, and lifecycle state transitions.

    Gocncfdatabase-clusterkubernetes
    GitHub पर देखें↗20,788
  • qax-os/excelizeqax-os का अवतार

    qax-os/excelize

    20,682GitHub पर देखें↗

    Excelize is a library for reading and writing spreadsheet files in the Office Open XML format. It provides a comprehensive suite of tools for programmatically creating, modifying, and analyzing workbooks, worksheets, and cell data, ensuring compatibility across various office software suites through structured XML serialization. The library distinguishes itself with a built-in formula calculation engine that evaluates complex mathematical and logical expressions directly against workbook data. It also features a memory-mapped streaming architecture, which allows for the efficient processing o

    Defines configuration settings for managing nodes within a distributed processing cluster.

    Goagentaianalytics
    GitHub पर देखें↗20,682
  • redis/node-redisredis का अवतार

    redis/node-redis

    17,550GitHub पर देखें↗

    This project is a database driver for Node.js applications designed to interface with Redis. It provides structured access to data stores, enabling the execution of commands, management of data structures, and the implementation of atomic transaction processing. The client distinguishes itself through native support for the binary-safe serialization protocol and a promise-based command pipeline that groups operations to minimize latency. It includes a dedicated manager for distributed environments that handles node discovery and request routing, alongside an event-driven messaging system that

    Handles node discovery, request routing, and connection resilience across distributed cluster topologies.

    TypeScriptnode-redisnodejsredis
    GitHub पर देखें↗17,550
  • aws/aws-cdkaws का अवतार

    aws/aws-cdk

    12,817GitHub पर देखें↗

    The AWS Cloud Development Kit is an infrastructure-as-code framework that enables developers to define and provision cloud resources using familiar programming languages. By utilizing construct-based synthesis, it translates high-level, object-oriented code into declarative templates, allowing for the automated management of complex cloud environments through a centralized, code-driven control plane. The framework distinguishes itself through its ability to model infrastructure as a dependency-aware resource graph, ensuring that components are provisioned and updated in the correct order. It

    Allows granular configuration of cache node types, scaling modes, and availability zone placement.

    TypeScriptawscloud-infrastructurehacktoberfest
    GitHub पर देखें↗12,817
  • crazyguitar/pysheeetcrazyguitar का अवतार

    crazyguitar/pysheeet

    8,150GitHub पर देखें↗

    pysheeet एक तकनीकी संदर्भ लाइब्रेरी है जो उन्नत Python डेवलपमेंट, सिस्टम एकीकरण और उच्च-प्रदर्शन कंप्यूटिंग के लिए कोड स्निपेट्स और कार्यान्वयन पैटर्न का एक क्यूरेटेड संग्रह प्रदान करती है। यह निम्न-स्तरीय नेटवर्क प्रोग्रामिंग, नेटिव C एक्सटेंशन, और एसिंक्रोनस और समवर्ती प्रोग्रामिंग को लागू करने के लिए एक व्यापक गाइड के रूप में कार्य करती है। यह प्रोजेक्ट वितरित GPU इन्फरेंस और उच्च-प्रदर्शन सर्विंग के लिए टूल्स सहित लार्ज लैंग्वेज मॉडल्स के विकास और डिप्लॉयमेंट के लिए विशेष फ्रेमवर्क प्रदान करती है। इसमें GPU रिसोर्स एलोकेशन और मल्टी-नोड वर्कलोड मैनेजमेंट को कवर करते हुए उच्च-प्रदर्शन कंप्यूटिंग क्लस्टर ऑर्केस्ट्रेशन के लिए विस्तृत पैटर्न भी शामिल हैं। यह लाइब्रेरी सुरक्षित नेटवर्क संचार और क्रिप्टोग्राफी, ऑब्जेक्ट-रिलेशनल मैपिंग और डेटाबेस मैनेजमेंट, और जटिल डेटा स्ट्रक्चर्स और एल्गोरिदम के कार्यान्वयन सहित क्षमताओं की एक विस्तृत श्रृंखला को कवर करती है। यह मेमोरी मैनेजमेंट, फॉरेन-फंक्शन इंटरफ़ेस के माध्यम से नेटिव इंटरऑपरेबिलिटी, और सिस्टम-स्तरीय OS एकीकरण के लिए यूटिलिटीज़ भी प्रदान करती है।

    Provides implementation patterns for coordinating distributed workloads and resource allocation across multi-node GPU clusters.

    Python
    GitHub पर देखें↗8,150
  • olivere/elasticolivere का अवतार

    olivere/elastic

    7,450GitHub पर देखें↗

    This project is a Go client library and API wrapper for interacting with Elasticsearch clusters. It serves as a programmatic interface for managing documents, indices, and cluster health, allowing Go applications to perform search and indexing operations via the REST API. The library functions as a distributed search orchestrator, providing specialized tools for high-throughput data ingestion and cluster administration. It features a buffered bulk processor with exponential backoff retries for optimizing write performance and supports automated index lifecycle transitions and historical data

    Monitors data distribution across nodes by retrieving shard allocation data from the cluster.

    Go
    GitHub पर देखें↗7,450
  • kubernetes-sigs/metrics-serverkubernetes-sigs का अवतार

    kubernetes-sigs/metrics-server

    6,651GitHub पर देखें↗

    Metrics Server is a lightweight, single-purpose daemon that collects CPU and memory usage data from every node and pod in a Kubernetes cluster and exposes those metrics through a standard Kubernetes API endpoint. It registers as an aggregated extension API server behind the Kubernetes apiserver, making resource utilization data available to the Horizontal Pod Autoscaler and Vertical Pod Autoscaler for automatic replica count and resource request adjustments. The project distinguishes itself by operating as a focused, in-cluster resource metrics collector that polls kubelet summary endpoints a

    Polls kubelet summary endpoints on each node to gather CPU and memory usage for pods and nodes.

    Gok8s-sig-instrumentation
    GitHub पर देखें↗6,651
  • redis/lettuceredis का अवतार

    redis/lettuce

    5,756GitHub पर देखें↗

    Lettuce is a Redis client library for Java that provides synchronous, asynchronous, and reactive programming models for interacting with Redis databases. It supports standalone, cluster, sentinel, pub/sub, and search operations through a single thread-safe connection model that handles command execution without blocking the calling thread. The library distinguishes itself through its reactive streams integration with Project Reactor, enabling non-blocking, backpressure-aware data processing with Mono and Flux types. It offers cluster slot routing that transparently handles MOVED and ASK redir

    Dispatches commands to a subset of cluster nodes and collects results asynchronously.

    Javaasynchronousaws-elasticacheazure-redis-cache
    GitHub पर देखें↗5,756
  • gpustack/gpustackgpustack का अवतार

    gpustack/gpustack

    5,173GitHub पर देखें↗

    gpustack is a GPU cluster management platform and LLM inference orchestrator. It functions as a centralized system for pooling and orchestrating graphics processing units across local servers and cloud environments, serving as a heterogeneous compute manager for diverse hardware and software configurations. The system provides a secure AI model deployment gateway that serves models as scalable services using key-based authentication. It includes a GPU resource scheduler that balances workloads across accelerators and coordinates multiple inference engines to map specific AI models to compatib

    Provides a centralized management plane for orchestrating distributed workloads and resource allocation across multi-node GPU clusters.

    Python
    GitHub पर देखें↗5,173
  • yahoo/tensorflowonsparkyahoo का अवतार

    yahoo/TensorFlowOnSpark

    3,850GitHub पर देखें↗

    TensorFlowOnSpark is a distributed framework for running TensorFlow machine learning workloads and model training across Apache Spark clusters. It functions as a cluster computing orchestrator that manages worker processes and resource allocation to scale deep learning tasks across multiple computing nodes. The platform enables distributed deep learning training and large-scale model inference, allowing users to execute tasks across a cluster of servers to handle datasets that exceed the memory of a single machine. It integrates deep learning workloads with Spark data processing to create end

    Coordinates distributed workloads and resource allocation across Spark clusters for machine learning pipelines.

    Python
    GitHub पर देखें↗3,850
  • thehive-project/thehiveTheHive-Project का अवतार

    TheHive-Project/TheHive

    3,891GitHub पर देखें↗

    TheHive is a security incident response platform and multi-tenant case management system. It functions as a Security Orchestration, Automation, and Response (SOAR) tool and a threat intelligence platform designed to coordinate security investigations by managing alerts, cases, and observables. The platform is distinguished by its multi-tenant architecture, which isolates data across different organizations while supporting selective cross-tenant sharing. It features a SOAR automation engine capable of executing sandboxed JavaScript logic to automate workflows and trigger response actions thro

    Manages individual database nodes, including decommissioning healthy nodes and removing crashed ones.

    Scalaanalyzerapicortex
    GitHub पर देखें↗3,891
  • lablup/backend.ailablup का अवतार

    lablup/backend.ai

    615GitHub पर देखें↗

    यह प्रोजेक्ट एक डिस्ट्रीब्यूटेड कंप्यूटिंग प्लेटफ़ॉर्म है जिसे विषम हार्डवेयर क्लस्टर्स में कंटेनरीकृत वर्कलोड को ऑर्केस्ट्रेट करने के लिए डिज़ाइन किया गया है। यह एक सेंट्रलाइज्ड कंट्रोल प्लेन के रूप में कार्य करता है जो संसाधन आवंटन, शेड्यूलिंग और निष्पादन वातावरण को मैनेज करता है, जिससे संगठन कई यूज़र्स और प्रोजेक्ट्स के बीच हाई-परफॉर्मेंस कंप्यूटिंग इंफ्रास्ट्रक्चर को सुरक्षित रूप से साझा कर सकते हैं। यह प्लेटफ़ॉर्म उन्नत हार्डवेयर वर्चुअलाइजेशन और मल्टी-टेनेंट मैनेजमेंट क्षमताओं के कारण अलग है। यह फिजिकल ग्राफिक्स प्रोसेसिंग यूनिट्स (GPUs) को आंशिक स्लाइस में विभाजित करने का समर्थन करता है, जिससे कई समवर्ती यूज़र्स सख्त अलगाव के साथ समर्पित हार्डवेयर संसाधनों तक पहुंच प्राप्त कर सकते हैं। इसके अतिरिक्त, यह सिस्टम इन अलग-थलग कंटेनरों के लिए सुरक्षित, एन्क्रिप्टेड रिमोट एक्सेस प्रदान करता है और सख्त डेटा संप्रभुता आवश्यकताओं को पूरा करने के लिए एयर-गैप्ड एनवायरनमेंट में पूर्ण ऑपरेशनल कार्यक्षमता बनाए रखता है। अपने कोर ऑर्केस्ट्रेशन के अलावा, इस प्लेटफ़ॉर्म में एक प्लगइन-आधारित आर्किटेक्चर शामिल है जो विविध AI एक्सेलेरेटर्स और स्टोरेज बैकएंड्स को एब्स्ट्रैक्ट करता है, जिससे ऑन-प्रेमिस और क्लाउड-आधारित इंफ्रास्ट्रक्चर में निरंतर वर्कफ़्लो सुनिश्चित होता है। इसमें क्लस्टर हेल्थ की निगरानी, संसाधन कोटा लागू करने और वर्चुअलाइज्ड स्टोरेज को मैनेज करने के लिए एकीकृत टूल्स शामिल हैं, जो जटिल कंप्यूटिंग कार्यों को स्केल और ऑप्टिमाइज़ करने के लिए एक एकीकृत इंटरफेस प्रदान करते हैं।

    Coordinates distributed containerized workloads and resource allocation across heterogeneous hardware clusters.

    Pythonapibackendaicloud-computing
    GitHub पर देखें↗615
  1. Home
  2. Data & Databases
  3. Cluster Node Management

सब-टैग एक्सप्लोर करें

  • Cluster OrchestratorsTools for coordinating distributed workloads and resource allocation across multi-node GPU clusters. **Distinct from Cluster Node Management:** Distinct from Cluster Node Management: focuses on high-level workload orchestration and scheduling rather than node-level configuration.
  • Kubelet Metric PollersPolls kubelet summary endpoints on each node to gather CPU and memory usage for pods and nodes. **Distinct from Cluster Node Management:** Distinct from Cluster Node Management: focuses on polling kubelet endpoints for resource metrics, not general node lifecycle management.
  • Shard Allocation MonitoringMonitoring and retrieving the distribution of data shards across different nodes in a cluster. **Distinct from Cluster Node Management:** Focuses on the inspection of shard distribution rather than the static configuration of node resources.
  • Targeted Command DispatchDispatching commands to a dynamic or static subset of cluster nodes and collecting results asynchronously. **Distinct from Cluster Node Management:** Distinct from Cluster Node Management: focuses on executing commands on selected nodes, not on managing node lifecycle or configuration.