Microsegmentation for containers and microservices: best practices

There is a reason why traditional network-based segmentation solutions will not work in cloud-native environments, and that’s because they are not built for it! A Kubernetes-native approach is required to isolate containerized workloads within a deployment. Kubernetes is an open system with dynamic infrastructure; microsegmentation is the only way to isolate and protect workloads from threats that can move laterally.

During this webinar, we’ll dive into:

• What microsegmentation is and how it can limit the blast radius of a threat
• Understand the unified and dynamic segmentation model for Containers, VMs, and Bare Metal
• How to create security policies as code for consistent enforcement at workload level

After a 30-minute talk there’ll be a 15-minute Q&A, for which we encourage you to submit questions in advance.
A webinar recording and related materials will be shared with all attendees after the event.

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Speakers:

Jen Luther Thomas, Technical Marketing Engineer at Tigera
Jen Luther Thomas is a Technical Marketing Engineer at Tigera. She has 10 years of experience in the geospatial industry and in more recent years was responsible for customer success of cloud and container deployments of enterprise ETL software. At Tigera, she is a subject matter expert for Calico security solutions and is responsible for producing technical content to support colleagues and users.

Dhiraj Sehgal, Director, Product Marketing at Tigera
Dhiraj Sehgal is Director of Product, Technical, and Partner Marketing at Tigera. His expertise lies in effectively communicating cloud-native and SaaS technology to customers, and he is knowledgeable on a wide range of topics including security, networking, storage, the data layer, compute, virtualization, and data management platforms. Dhiraj has worked in product and technical marketing, product management, customer success and engineering, and he holds four patents on data center technologies (storage, networking, and server).