Search Results for "machine"

...You can run a single cAdvisor to monitor the whole machine.

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. ...

...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 to collect logs, and send them to a Kafka topic without using client compression, with the Kafka topic partition configured as 3. 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.

The Azure Container Service Engine (acs-engine) generates ARM (Azure Resource Manager) templates for Docker enabled clusters on Microsoft Azure with your choice of DC/OS, Kubernetes, OpenShift, Swarm Mode, or Swarm orchestrators. The input to the tool is a cluster definition. The cluster definition (or apimodel) is very similar to (in many cases the same as) the ARM template syntax used to deploy a Microsoft Azure Container Service cluster.

novm is an experimental, minimalist virtual machine monitor that explores running Linux guests with a streamlined user-space control plane. Its goal is fast, scriptable VM lifecycle management—boot, snapshot, pause, resume—without the heft of a full cloud stack. The design favors small, understandable code paths around KVM and tap networking so developers can reason about isolation and performance trade-offs.