Search Results for "half"

...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. Until June 2021, Volcano has been widely used around the world at a variety of industries such as Internet/Cloud/Finance/ Manufacturing/Medical. ...

Lightweight Kubernetes. Production-ready, easy to install, half the memory, all in a binary less than 100 MB. K3s is a highly available, certified Kubernetes distribution designed for production workloads in unattended, resource-constrained, remote locations or inside IoT appliances. K3s is packaged as a single <70MB binary that reduces the dependencies and steps needed to install, run and auto-update a production Kubernetes cluster.

...Dragonboat handles all technical difficulties associated with Raft to allow users to just focus on their application domains. It is also very easy to use, our step-by-step examples can help new users to master it in half an hour. Easy to use pure-Go APIs for building Raft based applications. Feature complete and scalable multi-group Raft implementation. Disk based and memory based state machine support. Fully pipelined and TLS mutual authentication support.

...For passive testing, the flow of the Trojan agreement is completely consistent with the characteristics and behavior of the HTTPS flow. HTTPS traffic accounts for more than half of current Internet traffic, and the traffic is confidential after TLS's handshake is successful. There is almost no feasible way to distinguish Trojan protocol traffic from it.

kube-batch is a batch scheduler for Kubernetes, providing mechanisms for applications which would like to run batch jobs leveraging Kubernetes. It builds upon a decade and a half of experience on running batch workloads at scale using several systems, combined with best-of-breed ideas and practices from the open source community.

...Or maybe you've written a monitoring framework which is capable of gathering a bunch of metrics, then evaluating a few expressions to see if any metrics should be alerted upon, but the conditions for alerting are different for each monitor. A lot of people wind up writing their own half-baked style of evaluation language that fits their needs but isn't complete. Or they wind up baking the expression into the actual executable, even if they know it's subject to change. These strategies may work, but they take time to implement, time for users to learn, and induce technical debt as requirements change.