Prometheus, onto being ubiquitous

Prometheus, now a graduated CNCF project, is the de facto leader in the monitoring and metrics space. With the 2.0 launch nearly a year behind us, we are now focused on making Prometheus boring. i.e, more stable, more usable and even MOAR user friendly!

This talk will cover the new developments and the future roadmap of the project which includes among other things better remote integrations, backfilling API, security improvements and OpenMetrics.

Vorkenntnisse

Attendees should ideally be familiar with Prometheus and its underlying concepts to gain full advantage of the talk. That being said, anyone with a working understanding of monitoring will benefit from this talk.

Lernziele

* A short intro into the Prometheus eco-system.
* The state of Prometheus development and future direction.
* Will help you gain confidence in Prometheus, if you're on the edge now.

 

Agenda

ab 8.30 Uhr Registrierung und Begrüßungskaffee

9.30 Uhr Beginn

Intro

Machine Learning

  • Was ist Machine Learning?
  • Der typische ML Workflow
  • Was sind neuronale Netze?
  • Jupyter Lab mit Python
  • Eine Einführung in TensorFlow
  • Keras als High-Level API für TensorFlow

Praxisteil: Deep Learning Modelle mit Keras

  • Datengeneratoren
  • Datasets explorativ analysieren
  • Hold-Out vs. Cross Validation

11.00 - 11.15 Uhr: Kaffeepause

Praxisteil: Deep Learning Modelle mit Keras

  • Feed-Forward Netzarchitektur
  • Convolutional Neural Networks als Deep Learning Ansatz
  • Evaluation und Visualisierung des Modells

12.30 - 13.30 Uhr: Mittagspause

Pipelines mit Luigi

  • Anforderungen an produktive Modelle
  • Übersicht über Luigi und dessen Module
  • Bau eines Beispiel-Workflows

Praxisteil: Den Keras-Workflow mit Luigi implementieren

  • Anforderungen an produktive Modelle
  • Übersicht über Luigi und dessen Module
  • Bau eines Beispiel-Workflows

15.30 - 15.45 Uhr: Kaffeepause

Praxisteil: TensorFlow-Serving

  • Übersicht über TensorFlow-Serving
  • Ladestrategien konfigurieren
  • Deployment des Modells

ca. 17.00 Uhr: Ende

 

Referent

 

Goutham Veeramachaneni Goutham Veeramachaneni is Software Engineer from India who loves OpenSource and all things observability. He has been contributing to the Prometheus monitoring system for nearly 2 years now, and is a maintainer with a focus on the storage engine. He now works for GrafanaLabs, building Cortex, an open-source, distributed multi-tenant version of Prometheus. While not coding, you'll either find him on his couch or on a bike.

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