Search Results for "learning"
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Showing 9 open source projects for "learning"
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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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8 Monitoring Tools in One APM. Install in 5 Minutes.AppSignal works out of the box for Ruby, Elixir, Node.js, Python, and more. 30-day free trial, no credit card required.
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DevOps
Contains learning resources related to DevOps tools and tech
I created this repository to keep my learning, notes, and code in one place for various tools in DevOps. Now, it's helping thousands of learners, practitioners, and professionals every day in their DevOps journey. -
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Volcano
A Cloud Native Batch System (Project under CNCF)
Volcano is a batch system built on Kubernetes. It provides a suite of mechanisms that are commonly required by many classes of batch & elastic workload including machine learning/deep learning, bioinformatics/genomics, and other "big data" applications. These types of applications typically run on generalized domain frameworks like TensorFlow, Spark, Ray, PyTorch, MPI, etc, which Volcano integrates with. Volcano builds upon a decade and a half of experience running a wide variety of high-performance workloads at scale using several systems and platforms, combined with best-of-breed ideas and practices from the open-source community. ... -
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JAX Toolbox
Public CI, Docker images for popular JAX libraries
JAX Toolbox is a development toolkit designed to streamline and optimize the use of JAX for machine learning and high-performance computing on NVIDIA GPUs. It provides prebuilt Docker images, continuous integration pipelines, and optimized example implementations that help developers quickly set up and run JAX workloads without complex configuration. The project supports popular JAX-based frameworks and models, including architectures used for large-scale pretraining such as GPT and LLaMA variants. ... -
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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 Canary Rollouts to your ML deployments. ... -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Kubernetes Handbook
Cloud native application architecture practice handbook
Cloud native is a behavioral method and design concept. In its essence, all behaviors or methods that can improve resource utilization and application delivery efficiency on the cloud are cloud-native. The history of cloud computing is a history of cloud native. Kubernetes opened the prelude to cloud native 1.0. The emergence of service mesh Istio led to microservices in the post-Kubernetes era. The rise of serverless has enabled cloud native to advance from the infrastructure layer to the... -
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TKEStack
Native Kubernetes container management platform
...Provides an intuitive UI interface to support visualization and YAML import and other resource creation and editing methods, enabling users to run containers without learning all Kubernetes concepts up-front. An abstract project-level resource container that supports multiple namespace management and deployment applications across multiple clusters. Unified authorization management, not only at the cluster management level but even at the Kubernetes resource level. Integration with your existing authentication mechanisms, including LDAP, OIDC, front proxy, and public OAuth providers such as GitHub. -
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SuperEdge
An edge-native container management system for edge computing
...It makes non-intrusive enhancements to Kubernetes and is fully compatible with all Kubernetes APIs and resources. Kubernetes users can leverage SuperEdge easily for edge environments with minimal learning. When the network connection between the edge and the cloud is unstable, or the edge node is offline, the node can still work independently. But at this time, edge node can't do anything associated with writing operation, such as create/delete/update. -
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Open Application Model
Open Application Model (OAM)
Open Application Model (OAM) is a set of standard yet higher-level abstractions for modeling cloud-native applications on top of today's hybrid and multi-cloud environments. Focused on application rather than container or orchestrator, Open Application Model brings modular, extensible, and portable design for defining application deployment with higher level API. This is the key to enabling simple, consistent yet robust application delivery across hybrid environments including Kubernetes,... -
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pico
A Git-driven task runner built to facilitate GitOps and Infrastructure
...The modern browser is very much like an operating system, both in terms of complexity and code size. Only massive corporations can build and maintain it. Further, the web breeds platforms that exploit your reward and learning centers in order to increase "engagement." We have no issue with the commercialization of the web -- that's how useful services exist. However, we are more aligned with products and services that promote human communication and collaboration in its purest forms. Many of our services don't require a password, but still offer many familiar features like content management. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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