Julien Bisconti - Google Developer Expert for Google Cloud

devops

In this talk, we will outline what is a service mesh. A service mesh is a inter communication infrastructure that allows the traffic to be routed by configuring proxy running as a side car to each services. It’s a network for services, not for bytes.

Starting to do chaos engineering can seem like a daunting task if one has never practice that before. In this talk, we will outline what is a service mesh and how does it help us to do chaos engineering. A service mesh is a inter communication infrastructure that allows the traffic to be routed by configuring proxy running as a side car to each services.

Starting to do chaos engineering can seem like a daunting task if one has never practice that before. In this talk, we will outline what is a service mesh and how does it help us to do chaos engineering. A service mesh is a inter communication infrastructure that allows the traffic to be routed by configuring proxy running as a side car to each services. It’s a network for services, not for bytes.

Starting to do chaos engineering can seem like a daunting task if one has never practice that before. In this talk, we will outline what is a service mesh and how does it help us to do chaos engineering. A service mesh is a inter communication infrastructure that allows the traffic to be routed by configuring proxy running as a side car to each services.

This presentation outlines the tradeoffs and tooling of having all the code base in one place (monorepo) or many places (multirepo). It goes as far as to question the existence of a local dev environment.

Starting to do chaos engineering can seem like a daunting task if one has never practice that before. In this talk, we will outline what is a service mesh and how does it help us to do chaos engineering. A service mesh is a inter communication infrastructure that allows the traffic to be routed by configuring proxy running as a side car to each services.

Developers are taught to write code but what about deploying code ? Using a serverless architecture, testing, building, deploying and monitoring are activities that happens in a cloud native environment. Coding is still done locally. What can we do to enable developers in the cloud?

Developers are taught to write code but what about deploying code ? Using a serverless architecture, testing, building, deploying and monitoring are activities that happens in a cloud native environment. Coding is still done locally. What can we do to enable developers in the cloud?

Sub title: Automating Chaos Engineering with a Service Mesh and the Chaos Toolkit.

In this talk, Julien and Sylvain will take you on the journey of performing Chaos Engineering exploration and automation of a simple set of services backed by Istio, a service mesh provider.

The two main workflows of machine learning are, first, train the model, then deploy the model. The time it takes to go from a Jupyter notebook to a deployed model in production can be months.The tooling around the training workflow is getting better but deploying is still cumbersome.That is why Kubeflow was created.The KubeFlow project is dedicated to making deployments of machine learning workflows on Kubernetes simple, portable and scalable. In this presentation, we are going to see why such a project exists and the challenges Machine Learning Operations (MLOps) brings to the table.
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