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The brainiest courses
for IT brainiacs.

Level Up your Kubernetes Scaling with KEDA

Course description

Whether it is a normal workday or Black Friday, service-oriented applications must be able to handle varying loads. This is the only way to ensure that users are provided with a good experience and that costs are kept to a minimum.

Kubernetes offers a way to vary the number of application instances running based on CPU or RAM utilization with the Horizontal Pod Autoscaler. However, modern applications often depend on a variety of components and should be able to respond to external events. These may include new messages in a queue or metrics in Azure Monitor.

As an application developer or operation manager, what do I need to consider to ensure that my application can respond to these events? How can I configure Kubernetes for “scale to 0” to run my application only when needed?

Using Azure Kubernetes Service and KEDA (Kubernetes Event-driven Autoscaling), this training will show practical examples of how to create and configure autoscalers to respond to external events and scale applications in Kubernetes accordingly.

Topics:

  • Introduction to KEDA – Kubernetes Event Driven Autoscaling
  • Practical examples using KEDA for scaling, such as scaling based on Azure Service Bus Queues or Azure DevOps Agents
  • Practice time for participants to implement KEDA scalers into their own application
  • Scale to 0 to optimize the resource usage of the Kubernetes cluster

Goals:

  • Participants will learn about the advantages of KEDA and what possibilities it brings to your software projects
  • This course provides enough knowledge to enable participants to install KEDA in their own Kubernetes cluster as well as how to use the built-in autoscalers
  • Attendees of this course will learn how to scale their applications using KEDA and what pitfalls to avoid when using KEDA in a production environment

Target audience

  • Software Engineers
  • Software Architects
  • Systems Engineer
  • IT Operations
  • DevOps Engineers

Prerequisites

  • Basic knowledge of Kubernetes is recommended for this course.

Course details

Duration: 1 day
Location: Online
Trainer:

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