Slides - Intro to Akka.Cluster

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This document provides an introduction to Akka.Cluster, including defining what a cluster is, the benefits of clustering, how to enable clustering in an application, and examples of using clusters. It describes how clusters are formed and maintain themselves, including initial node discovery, leader election, and ring formation. Location transparency is discussed, where the physical location of actors does not impact functionality.

Technologie

@petabridge Petabridge.com
Intro to Akka.Cluster
Andrew Skotzko
Co-Founder, Petabridge
@askotzko

@petabridge Petabridge.com
Introduction to Clustering
• What is a cluster?
• What does clustering give me?
• How do I enable clustering?
• How do I actually use clustering?

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What is a cluster?

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Network View of a Cluster

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Akka.Cluster brings clustering
to Akka.NET

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Benefits of Clustering
• Elastic
• Recover from failure
• Easy microservices
And the best part…

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No Code Changes!

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Akka.Cluster HOCON

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NOTE: All nodes in an
Akka.NET Cluster must have
the same ActorSystem name.

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When do we use clustering?

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Clustering Examples

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How do clusters form?

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Initial State

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Seed Node: Initial, well-known
nodes contacted by nodes
attempting to join the cluster

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Lighthouse - Dedicated Seed
Node for Akka.NET
• Never needs to be
upgraded*
• Configurable
• Low resource
consumption

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Joining the Cluster

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Leader Election

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Ring Formation

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How do I enable clustering?

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How to Enable Akka.Cluster

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Simple Cluster Sample

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What makes this all possible?

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Location Transparency

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Location of Actor in Cluster
Doesn't Matter

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How do I actually use
clustering?

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Running Multiple Akka.NET
Apps in a Cluster
(Microservices)

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Cluster Roles

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Roles - WebCrawler Sample

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Demo!*
*fingers crossed

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See WebCrawler for yourself

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Subscribe for more tutorials!
Click here to master Akka.Cluster, with
Petabridge’s Advanced Clustering
Training.
Thank you!

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Tracing the root cause of a performance issue requires a lot of patience, experience, and focus. It’s so hard that we sometimes attempt to guess by trying out tentative fixes, but that usually results in frustration, messy code, and a considerable waste of time and money. This talk explains how to correctly zoom in on a performance bottleneck using three levels of profiling: distributed tracing, metrics, and method profiling. After we learn to read the JVM profiler output as a flame graph, we explore a series of bottlenecks typical for backend systems, like connection/thread pool starvation, invisible aspects, blocking code, hot CPU methods, lock contention, and Virtual Thread pinning, and we learn to trace them even if they occur in library code you are not familiar with. Attend this talk and prepare for the performance issues that will eventually hit any successful system. About authorWith two decades of experience, Victor is a Java Champion working as a trainer for top companies in Europe. Five thousands developers in 120 companies attended his workshops, so he gets to debate every week the challenges that various projects struggle with. In return, Victor summarizes key points from these workshops in conference talks and online meetups for the European Software Crafters, the world’s largest developer community around architecture, refactoring, and testing. Discover how Victor can help you on victorrentea.ro : company training catalog, consultancy and YouTube playlists.

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The Good, the Bad and the Governed - Why is governance a dirty word? David O'Neill, Chief Operating Officer - APIContext Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/

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