App Modernization: The Focus For Production

App Modernization will have:

✅ Kubernetes
✅ Containerization
✅ Specified app services (Azure App Services, AWS ECS, etc.)
✅ And eventually WASM

At the forefront of the modernization.

We’ve seen a paradigm shift as Kubernetes becomes the default platform in the background. It’s just “expected” now.

And when a particular platform is expected, that means it has gained overall mass adoption, which is when things start becoming production ready.

With Application Modernization, these technologies and platforms will lead legacy systems into cloud-native.

In this session, you'll learn what app modernization looks like in production scenarios, how you can start, and what the key benefits are to every cloud-native scenario.

How To Ensure You’re Ready for Kubernetes in Production

What does Kubernetes truly look like for production workloads?

Is it third-party tools and services? Managed clusters in the cloud? The actual Kubernetes project itself?

The usage of Kubernetes and the tools getting built around it causes a massive amount of confusion for engineers attempting to adopt Kubernetes in their production environments, so they need a method they can follow to ensure success.

In this session, the Day Zero, Day One, and Day Two method will be broken down that'll work in ANY production-level Kubernetes environment.

Day Zero is all about planning and architecture.
Day One is all about deployments.
Day Two is the management of clusters and deployments.

Join Michael Levan, Consultant, Trainer, and Content Creator for a hands-on session for how you can succeed with your Kubernetes production deployment.

AI and ML On Kubernetes For The Absolute Beginner

AI has been a popular topic, but there haven't been a lot of true engineering explanations behind it all.

For example, what systems can it run on, and more importantly, how can it run efficiently?

What's the engineering behind AI, GenAI, ML, and LLM's that make it all "tick"?

In this session, you will learn from an engineering perspective how AI and ML work under the hood on Kubernetes.

You'll learn about:
- Kubeflow
- How to train Models on Kubeflow
- Why Kubernetes is the perfect AI/ML platform
- How organizations save money by training models on AI/ML
- Installation steups

and perhaps most importantly, how it all ties into Kubernetes.

The combination of AI and Kubernetes isn't just a fad anymore, it's a topic that can be truly embraced by all engineers.

Join Michael Levan, Consultant, Trainer, and Content Creator on how you can truly understand how the most popular stack is truly working.

The Hybrid Kubernetes Platform Engineering Model

Platform Engineering is a term that's being thrown around the tech world as a new and popular method of implementing abstraction.

But how does it work on Kubernetes in a production scenario?

It comes down to a few topics:
- Kubernetes Operators
- Cluster API
- KubeVirt
- IDP's
- Crossplane

Operators allow you to extend the capability of Kubernetes. Cluster API gives you the ability to manage and build Kubernetes clusters WITH Kubernetes. KubeVirt makes it possible to manage VM's on Kubernetes. Crossplane extends the management of various resources outside of Kubernetes. To tie it all together, Internal Developer Platforms (IDP) gives an abstraction layer on top of complex tooling.

By tying all of the above together, you have a production-ready Kubernetes Platform Engineering environment.

Join Michael Levan, Consultant, Trainer, and Content Creator for a hands-on, engineering-focused, practitioner-led session on how to think about Platform Engineering on Kubernetes.

Platform Engineering is a term that's being thrown around the tech world as a new and popular method of implementing abstraction.

But how does it work on Kubernetes in a production scenario?

It comes down to a few topics:
- Kubernetes Operators
- Cluster API
- KubeVirt
- IDP's
- Crossplane

Operators allow you to extend the capability of Kubernetes. Cluster API gives you the ability to manage and build Kubernetes clusters WITH Kubernetes. KubeVirt makes it possible to manage VM's on Kubernetes. Crossplane extends the management of various resources outside of Kubernetes. To tie it all together, Internal Developer Platforms (IDP) gives an abstraction layer on top of complex tooling.

By tying all of the above together, you have a production-ready Kubernetes Platform Engineering environment.

Join Michael Levan, Consultant, Trainer, and Content Creator for a hands-on, engineering-focused, practitioner-led session on how to think about Platform Engineering on Kubernetes.

Cost and Resource Optimization In Kubernetes

Have you ever worked in an environment where servers were just sitting around underutilized? What about in an environment where you requested resources and they weren’t available? These questions lead to not only resource optimization, but understanding cost and how to bring it down.

This session is all about how you can optimize resources for Kubernetes clusters utilizing various tools and platforms.

In the cloud, resources (compute, storage, etc.) are either constantly overprovisioned or underprovisioned. Organizations are either spending way too much money monthly in the cloud for resources that aren’t needed or “scaling up” strategies aren’t in place, which ends in production environments not performing the way engineers are expecting.

How can you plan for resource and cost optimization in the cloud?

Kubernetes Secret Management The Right Way With Vault

Kubernetes Secrets by default aren't secure. In fact, some Kubernetes documentation itself even recommends to take a look at a third party utility. In short (but you'll learn more about it in this session), it's because secrets are stored in plain-text by default.

Looking through different secret solutions for Kubernetes, one always pops up in production environments - Vault.

In this session, you'll learn:
- How to incorporate Vault in a live Kubernetes environment.
- Deploy Vault as a Kubernetes Deployment.
- see the code in real-time for proper Vault/Kubernetes configurations.
- Learn how you can utilize secrets to secure any configuration data that you don't want in plain text (passwords, API keys, etc.)

Production-Ready Platform Engineering: From Conception To Build To FAIL

How much hype is there around Platform Engineering? A lot.

Overall, the idea of Platform Engineering isn’t new, but what's new is the path it's taking.

Because of that, we need a production-ready approach to get Platform Engineering right without creating more tech debt.

In this session, you’ll learn from theory to hands-on how to create a proper platform. It will contain:

1. The underlying platform (Kubernetes)
2. Platform capabilities (various open-source tools from monitoring and observability to GitOps and more)
3. Platform interaction/interface (how engineers using the platform that Platform Engineers create for them interact with it)

First, we'll talk about the various details that all engineers will need to know to create and configure a proper, production-ready Kubernetes cluster that works with Platform Engineering.

Next, we'll dive into the capabilities that will exist on the Kubernetes cluster in the Platform Engineering environment. These capabilities can be anything from GitOps to monitoring to cost and resource optimization. It all depends on what the engineers need (the engineers using the platform)

Lastly, you'll learn how an end-user (the engineer using a Platform Engineering environment) can interact with it. Is it an IDP? A CLI? Another automated solution?

You’ll see everything from Kubernetes to Crossplane to Backstage and everything in between. You’ll also learn how to think about Platform Engineering as a whole when it comes to using Kubernetes as your underlying platform.

The Top k8s Security Concern By 55%: Misconfigurations. How can you mitigate?

Security is a tricky thing. Despite what we've seen from Hugh Jackman hacking into systems with 50 CRT monitors (who else has watched Sword?... I'm getting old), it really comes down to two things:

- Application Security
- Network Security

And in each of those categories, the absolute largest method of bad actors getting into applications and systems is misconfigurations... and unfortunately, it's incredibly easy to misconfigure a Kubernetes environment.

In this session, you'll learn about a few of the mitigation steps you can take for every Kubernetes environment which include:

- The 4C's of Kubernetes Security
- SecurityContexts
- Pod Security Standards
- Policy Enforcement
- Network Policies

and a few other goodies.

Remember - security is about mitigating as much as possible, but you'll never be able to stop everything.

KubeVirt: In With The Old And In With The New (VMs For All)

"Out with the old and in with the new" is usually how we see technology, but what about if we were bringing in the "old" with the "new"?

KubeVirt takes the idea of Virtual Machines and puts a cloud-native spin on it.

Any Systems Engineer, Sysadmin, DevOps Engineer, or whoever else was/is managing the virtualization environment can take a new approach with the old best practices of creating and managing virtual machines.

In this session, we will go over:
1. Installation requirements for KubeVirt
2. Getting KubeVirt installed and configured
3. Going over the various KubeVirt components and terminology
4. Deploying both Linux and Windows in a VM via KubeVirt

Security Engineering: On-Prem and Cloud For Production

Security from a blue team perspective was always thought about in two ways:
1. Networks/systems
2. Software

A security engineer was either really good at securing software, really good at security networks and systems, or if they were lucky, both.

Now we're seeing an uptick in overall cloud security, which introduces topics like CDR, but more importantly, introduces a new attack surface.

Security Engineers now need to focus on both systems/networks and software.

In this session, we'll dive into:
1. Security Fundamentals and Best Practices
2. On-Premise Security Engineering vs Cloud Security
3. Implementing Cloud Security best practices
4. Notable tools needed to secure cloud environments (both paid and open-source)

A Standard To Secure All Of Your Clouds

Cloud Detection and Response is a combo of:
1. Network Detection and Response
2. Intrusion Detection and Prevention

With it's own spin to it.

CDR takes NDR and IDS and combines it with a heavy emphasis on authentication/authorization (RBAC), software/binary security, and API-driven security.

Essentially, you'll need to be thinking about security from the second a binary is built via CICD to where it's deployed (Kubernetes? VMs? Serverless?), and not to mention multi-cloud and hybrid-cloud scenarios.

This talk will go over the typical cloud-based threats and how to mitigate them across all clouds at the same time.

AppSec For All The Things

Whether you're securing:
1. Applications in the cloud.
2. Web Apps.
3. Containers.
4. On-prem/virtual apps

It's all part of your SDLC process, and securing the entire SDLC process regardless of where the apps run is what AppSec is all about.

In this session, we will dive into everything an engineer needs to know about AppSec. We will start with pentesting (ethically) demo applications that provide real-world results, show how to defend against the pentests, and see the differentiators between pentesting and defending apps in the cloud and on-prem.

GPUs On Kubernetes: How To Navigate The Graphical Landscape

With a larger need to run Data Models (LLMs/SLM/Standard Models) for AI workloads, GPU capabilities are necessary. The problem is that GPUs are expensive. If you look at the huge AI factories, they're spending billions of dollars on GPUs alone.

Just as Kubernetes helps engineers share resources across ephemeral stacks (Pods/Containers), it can also help engineers share GPU resources across Pods to not only keep cost and resource optimization low but to ensure the utmost performance, reliability, and scalability.

In this session, you'll learn why you want to run GPUs on Kubernetes and, from a hands-on perspective, how to deploy a cluster with GPU support. You'll also see how to connect Pods to Nvidia GPUs.

Wasm: The Next Iteration Of Developing Software

The founder of Docker said "If Wasm existed in 2008, Docker wouldn't exist". With that being said, it's safe to say that Wasm is the next iteration of application stacks.

In this session, everyone will learn about:
- Why Wasm exists
- The key differences between server-side Wasm and browser-based Wasm
- Cross-architecture complexities met with Wasm
- How you can use multiple languages for one binary
- How Wasm works with Docker and Kubernetes

And you'll learn it all both from a theory and hands-on perspective. This session will explain the "why" and then show the "how" by implementing it in real-time (viewers can follow along if they'd like).

Wasm On Kubernetes: Theory And Implementation

There was a time where discussions were occurring on Wasm being the next thing and "taking down" Kubernetes.

Then, everyone quickly realized that Wasm is a runtime, and because of that, it needs a place to run.

There are a ton of places where Wasm can run - locally, in serverless functions, on a VM, and even in Docker.

One of the best places for Wasm to run is with the world's largest orchestrator, Kubernetes.

In this session, you'll learn about:
1. How Wasm and Kubernetes work together.
2. How to create a Wasm binary via a container image.
3. How to run the Wasm binary in Kubernetes.
4. What runtime availability a k8s cluster needs to ensure that Wasm runs properly.