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Showing 10 open source projects for "cpu-g"
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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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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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ChaosBlade
An easy to use and powerful chaos engineering experiment toolkit
ChaosBlade is an Alibaba open source experimental injection tool that follows the principles of chaos engineering and chaos experimental models to help enterprises improve the fault tolerance of distributed systems and ensure business continuity during the process of enterprises going to cloud or moving to cloud-native systems. Chaosblade is an internal open-source project of MonkeyKing. It is based on Alibaba's nearly ten years of failure testing and drill practice and combines the best... -
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Pumba
Chaos testing, network emulation, stress testing tool for containers
Pumba is a chaos testing command line tool for Docker containers. Pumba disturbs your containers by crashing containerized applications, emulating network failures and stress-testing container resources (cpu, memory, fs, io, and others). -
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Aria2 AriaNg Docker
The Docker image for Aria2 + AriaNg + File Browser + Rclone
One Docker image for file downloading, managing, sharing, as well as video playing and evening cloud storage synchronization. Furthermore, it's pretty small and ARM CPU compatible which means you can also run it on Raspberry Pi. Last but not least, Auto HTTPS can't be more easy. -
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Robusta KRR
Prometheus-based Kubernetes Resource Recommendations
Robusta KRR (Kubernetes Resource Recommender) is a CLI tool for optimizing resource allocation in Kubernetes clusters. It gathers pod usage data from Prometheus and recommends requests and limits for CPU and memory. This reduces costs and improves performance. -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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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... -
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OpenCost
Cost monitoring for Kubernetes workloads and cloud costs
OpenCost is a vendor-neutral open-source project for measuring and allocating cloud infrastructure and container costs in real-time. Built by Kubernetes experts and supported by Kubernetes practitioners, OpenCost shines a light into the black box of Kubernetes spending. Flexible, customizable cost allocation and cloud resource monitoring for accurate showback, chargeback, and ongoing reporting. Dynamic asset pricing, through integrations with AWS, Azure, and GCP billing APIs as well as... -
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Pixie
Instant Kubernetes-Native Application Observability
...Pixie uses eBPF to automatically collect telemetry data such as full-body requests, resource and network metrics, application profiles, and more. Pixie collects, stores and queries all telemetry data locally in the cluster. Pixie uses less than 5% of cluster CPU and in most cases less than 2%. PxL, Pixie’s flexible Pythonic query language, can be used across Pixie’s UI, CLI, and client APIs. -
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Loggie
A lightweight, cloud-native data transfer agent and aggregator
...With sufficient resources for the Agent specification, modify the number of files collected, the concurrency of the sending client (configure Filebeat worker and Loggie parallelism), and observe their respective CPU, memory, and pod network card transmission rates. -
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barco
Linux containers from scratch in C
barco is a project I worked on to learn more about Linux containers and the Linux kernel, based on other guides on the internet. Linux containers are made up by a set of Linux kernel features. namespaces: are used to group kernel objects into different sets that can be accessed by specific process trees. There are different types of namespaces, for example,the PID namespace is used to isolate the process tree, while the network namespace is used to isolate the network stack. -
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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. Although it has since been archived in favor of the broader ecosystem, the code remains a reference for how to map kernel primitives to service-oriented container management. ...
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