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Are you spending more time and money than you need to on your Kubernetes platform? It’s a real challenge to adopt cloud-native best practises to build a secure, reliable, performance and efficient environment.

We’ve partnered with Magalix to demonstrate how using machine learning algorithms and GitOps can improve the performance, utilization, and cost of your Kubernetes environment.

Join this webinar to learn:
  • What capacity management is, and why you should introduce it early in your cloud-native journey
  • Cloud native best practices, metrics, and KPIs for optimizing Kubernetes and application capacity
  • How to set-up, diagnose and implement container and cluster recommendations
  • Configuration management with GitOps, and the benefits for using the Weave Kubernetes Platform

 


Tiffany Wang, Customer Reliability Engineer, Weaveworks

Tiffany has several years of experience as a full stack software engineer at companies in the education, healthcare, and automotive industries. She has successfully worked with distributed teams and built automated CI/CD pipelines deploying to major cloud providers using Kubernetes that empower engineers to not only write application code but also understand and maintain deployments and reliability.

A champion of GitOps and infrastructure as code, she is excited to design and implement solutions to reduce time to deployment, increase reliability and reproducibility, and ultimately, improve product delivery.


Ahmed Badran, CTO, Magalix

Ahmed has over 15 years of experience developing software at large scale and managing high-performing teams. He joined Amazon full-time in 2005 and worked on the AWS Platform team during the early years as AWS saw exponential growth in customers, services, and infrastructure. After two years at The Walt Disney Company, where he worked on the Advertisement System supporting ESPEN, ABC, and Disney Online; he joined a 10-person video management startup that was recently acquired by Limelight Networks, a leader in global content delivery.

Most recently, for the last 5.5 years Ahmed has been with Blue Origin as a Principal Software Engineer leading the design and implementation for their internal data ingestion and management system responsible for all telemetry data from Blue’s Launch vehicles, engine test stands, and hardware-in-the-loop simulation runs.
Before Joining Magalix last October as the CTO, he was bootstrapping Blue’s machine learning efforts under a newly established Advanced Technology group. He was responsible for drafting the company technology roadmap and 5-year plans in this area in collaboration with all stakeholders across all of Blue’s business units.

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