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Cloud Automation workshop roadshow: Kick-off

Dynatrace

With all the technology changes through the past three years, with the world moving to K8s, the rise of GitOps, everything as code, event-driven automation, and many new open standards in the cloud-native space, it was time to update our workshop. Last week we kicked it off with a three-hour virtual hands-on workshop.

Cloud 214
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Open Source at AWS re:Invent

Adrian Cockcroft

We’re excited to let you know that we have an Open Source track at re:Invent this year! Brendan Gregg tours BPF tracing, with open source tools & examples for EC2 instance analysis. Learn about what’s in it: [link] Some selected sessions: OPN201 Change is coming to robotics development: The shift to ROS 2 ??

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Open Source at AWS re:Invent

Adrian Cockcroft

We’re excited to let you know that we have an Open Source track at re:Invent this year! Brendan Gregg tours BPF tracing, with open source tools & examples for EC2 instance analysis. Learn about what’s in it: [link] Some selected sessions: OPN201 Change is coming to robotics development: The shift to ROS 2 ??

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Dynatrace’s automatic and intelligent observability co-flies with GKE Autopilot for managed Kubernetes – you can have it all!

Dynatrace

The Dynatrace Software Intelligence Platform delivers the deepest and broadest hybrid cloud observability, spanning applications, infrastructure, and user experience, as well as the latest open-source standards, including OpenTelemetry. Hands-on workshop: Dynatrace with Kubernetes. Need help getting started?

DevOps 229
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SpringOne Platform: Four great days of sharing new ways of innovating with Pivotal Platform

Dynatrace

Tanzu will allow organizations to build applications with velocity, run open source Kubernetes with consistency, and manage entire footprint with confidence. Automation was a hot topic at the event and Dynatrace had the opportunity to host a workshop “Building Autonomous Operations for Pivotal Platform with Keptn”.

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MXNet - Deep Learning Framework of Choice at AWS

All Things Distributed

A set of programming models has emerged to help developers define and train AI models with deep learning; along with open source frameworks that put deep learning in the hands of mere mortals. Some examples of popular deep learning frameworks that we support on AWS include Caffe, CNTK, MXNet, TensorFlow, Theano, and Torch.

AWS 167
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8 Top Test Automation Mistakes And Tips For QA Teams to Avoid Them

Testsigma

Complete test coverage should include scenarios on latency, speed, security, and usability. Before enacting your automation strategy, create a training document and have multiple meetings and workshops. The tool is chosen just because it’s open-source. Common Test Automation Mistakes QA Teams Tend To Make.

Testing 73