Ballerinas & Zebras in Kubernetes [ONLINE ONLY]

Welcome to our March session of "Kubernetes for Developers"-- Online Edition.

Weblink: https://adobe.bluejeans.com/767341876/6978

Phone Dial-In:
Dial one of the following numbers, enter the participant PIN followed by # to confirm:
+1 (415) 466-7000 (US)
PIN: 2190337 #
Secondary:
+1 (760) 699-0393 (US)
PIN: 4110158083 #

Joining from outside the US?
https://www.bluejeans.com/numbers/primetime-attendees/event?id=csqfucyh

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Agenda:

6:30pm -- Lakmal Warusawithana, Ballerina.io
~7:00pm -- Larry Lancaster, Zebrium
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Autonomous Incident Detection in Kubernetes deployments
Larry Lancaster - Founder and CTO @ Zebrium

Kubernetes makes it easy to deploy, manage and scale large distributed apps. But what happens when something goes wrong with an app? And how do you even know? Traditional monitoring and log management tools require skilled operators for setup and alert management. And hunting for root cause across vast Kubernetes logs can be extremely challenging. Fortunately, machine learning can be used to greatly reduce effort involved with incident identification and resolution.

Please join us for a technology discussion and demo of a technique that uses unsupervised machine learning to autonomously detect critical incidents together with root cause indication.
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Ballerina - Code to Cloud
Lakmal Warusawithana - Sr Director - Developer Relations, WSO2

Earlier, developers simply wrote their program, built it and ran it. Today, developers need to also think of the various ways of running it whether it be as a binary on a machine (virtual most likely), by packaging it into a container, by making that container a part of a bigger deployment (K8s) or by deploying it into a serverless environment or a service mesh. However, these deployment options are not part of the programming experience for a developer. The developer has to write code in a certain way to work well in a given execution environment, and removing this from the programming problem isn’t good.

Ballerina is an open-source programming language that specializes in moving from code to cloud while providing a unique developer experience. Its compiler can be extended to read annotations defined in the source code and generate artifacts to deploy your code into different clouds. These artifacts can be Dockerfiles, Docker images, Kubernetes YAML files or serverless functions. This session will demonstrate how you can move from code to cloud by using the built-in Kubernetes annotation support in Ballerina.

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Bios:

Larry Lancaster is the founder and CTO of Zebrium. He started Zebrium with the vision that machine learning could be used to automatically detect software incidents by structuring and learning patterns in logs and metrics. Before Zebrium, Larry was Chief Data Scientist at Nimble Storage, founding that company's data science team and architecting/implementing their petascale platform for automation and analytics. He also started NetApp's Engineering Informatics Group as Senior Engineer, invented Glassbeam's ETL-focused SPL technology as CTO/Co-Founder, and received a leadership award from the International Congress on Neural Networks as a graduate student.

Lakmal Warusawithana is the Senior Director - Developer Relations of WSO2. Lakmal has a long history of working in open source, cloud, and DevOps technologies and has been Vice President of Apache Stratos PaaS Project. Lakmal is an architect for containerization and deployment orchestration of Ballerina, an open-source programming language for network distributed application. Lakmal has also presented at numerous events, including ApacheCon, CloudOpen, QCon, JaxLondon, Cloud Expo, Cloudstack Collaboration Conference, WSO2Con, KubeCon, ContainerCamp, DeveloperWeek, API Summit, and many tech meetups.