Name: Kubernetes, Data Science, and Machine Learning
Start: 2018-05-23T15:45:00Z
End: 2018-05-23T15:45:39.000Z
Location: BrightTALK
Rating: 0

The Kublr Team delivers insights, tutorials, and best practices on how to leverage Kubernetes to enable your Dev and Ops teams to get the most out of the development and deployment of containerized applications. Built on top of upstream vanilla Kubernetes, Kublr allows developers to maintain the desired openness, portability, and pluggability of open source technology, while operations gains multi-factor enterprise security, backup, disaster recovery, and vendor support.

What's Kubernetes? A container orchestrator. Yes, but there is a lot more to it. Well implemented, Kubernetes can function as an infrastructure abstraction running across clouds and data centers, creating a single pool of resources. 

Allowing enterprises to untie themselves from infrastructure provider-specific technology stack and free development to use whichever tool fits their needs best, almost sounds like IT nirvana! 

During this webinar, Oleg, CTO at Kublr, will outline a view of Kubernetes as an infrastructure and cloud abstraction layer, as well as how to implement open source cloud-native technologies while meeting enterprise security and governance requirements: 

- Prerequisites for running Kubernetes in prod; 
- How to leverage fine-grained controls and separation of responsibilities to meet enterprise governance and security needs; 
- What’s needed for a general architecture of a centralized Kubernetes operations layer based on open source components such as Prometheus, Grafana, ELK Stack, Keycloak, etc.

Cloud abstraction, the overlooked power of Kubernetes

Self-healing does not equal self-healing. There are multiple layers to it, whether a self-healing infrastructure, cluster, pods, or Kubernetes. Kubernetes itself ensures self-healing pods. But how do you ensure your applications, whose reliability depends on every single layer, are truly reliable?

During this webinar, Oleg will discuss the different self-healing layers, what Kubernetes does and doesn't do (at least not by default), and what you should look out for to ensure true reliable applications. Hint: infrastructure provisioning plays a key role.

Designing reliable, self-healing cloud native Kubernetes applications

If you are wondering whether advanced scheduling in Kubernetes is achievable, the short answer is yes. There are some challenges, however. For instance, you'll need to accommodate every possible real-life scenario a Kubernetes user might encounter. Then, figure out how to leverage advanced scheduling techniques to shape and describe each scenario via simple rules and configurations.

During this webinar, Oleg, CTO at Kublr, will talk about advanced scheduling techniques in Kubernetes. These include resource and environment constraints, affinity and anti-affinity rules, taints and tolerations, custom schedulers and more. You’ll get a run-down of the potential pitfalls and considerations to keep in mind.

Advanced Scheduling in Kubernetes

In a microservices world, applications consist of dozens, hundreds, or even thousands of components. Manually deploying and verifying deployment quality in production is virtually impossible. Kubernetes, which natively supports rolling updates, enables blue-green application deployments with Spinnaker. However, the gradual rollout is a feature that doesn’t come out-of-the-box but can be achieved by adding Istio and Prometheus to the equation.
During this webinar, Slava Koltovich will discuss canary release implementations on Kubernetes with Spinnaker, Istio, and Prometheus. He’ll examine the role of each tool in the process and how they are all connected. During a demo, he will demonstrate a successful and failed canary release, and how these tools enable IT teams, to properly roll out changes to their customer base without any downtime.

Canary Releases on Kubernetes with Spinnaker, Istio, Prometheus

While developers see and realize the benefits of Kubernetes, how it improves efficiencies, saves time, and enables focus on the unique business requirements of each project; InfoSec, infrastructure, and software operations teams still face challenges when managing a new set of tools and technologies, and integrating them into an existing enterprise infrastructure. 

During this online meetup, Oleg  will discuss what’s needed for a general architecture of a centralized Kubernetes operations layer based on open source components such as Prometheus, Grafana, ELK Stack, Keycloak, etc., and how to set up reliable clusters and multi-master configuration without a load balancer. He’ll also describe how  these components should be combined into an operations-friendly enterprise Kubernetes management platform with centralized monitoring and log collection, identity and access management, backup and disaster recovery, and infrastructure management capabilities.  This presentation will show real-world open source projects use cases to implement an ops-friendly environment using Kublr centralized Kubernetes management as an example.

A Blueprint for Enterprise-grade Centralized Kubernetes Management

Self-healing does not equal self-healing. There are multiple layers
to it, whether a self-healing infrastructure, cluster, pods, or Kubernetes. Kubernetes itself ensures self-healing pods. But how do you ensure your applications, whose reliability depends on every single layer, are truly reliable?

During this webinar, Oleg will discuss the different self-healing layers, what Kubernetes does and doesn't do (at least not by default), and what you should look out for to ensure true reliable applications. Hint: infrastructure provisioning plays a key role.

How Self-Healing Nodes and Infrastructure Management Impact Reliability

Realizing Cloud-Native Day Two in Restrictive Environments

While developers see and realize the benefits of Kubernetes, how it improves efficiencies, saves time, and enables focus on the unique business requirements of each project; InfoSec, infrastructure, and software operations teams still face challenges when managing a new set of tools and technologies, and integrating them into existing enterprise infrastructure. This is especially true for environments where security and governance requirements are so strict as to come into conflict with the cloud-native reference architectures.

During his presentation, Oleg will outline a plan that leverages Kubernetes as an infrastructure abstraction (hint: there is a lot more to it than just container orchestration!). Such an approach allows enterprises to untie themselves from infrastructure provider-specific technology stack and free development to use whichever tool fits their use case best. But how do you implement open source cloud-native technologies while meeting enterprise security and governance requirements? He’ll summarize common prerequisites for running Kubernetes in production, and how to leverage fine-grained controls and separation of responsibilities to meet enterprise governance and security needs; what’s needed for a general architecture of a centralized Kubernetes operations layer based on open source components such as Prometheus, Grafana, ELK Stack, Keycloak, etc.

Kubernetes as Infrastructure Abstraction

Meeting the Needs of Enterprise Governance and Security 

Installing Kubernetes is easy. Ensuring it complies with your organization’s enterprise governance and security requirements isn’t. 

Oleg will outline a plan to use the technology while meeting enterprise security requirements. In this technically-focused talk, he’ll summarize common prerequisites for running Kubernetes in production, and how to leverage fine-grained controls and separation of responsibilities to meet enterprise governance and security needs. 

The presentation will include basic requirements for audit, security, authentication, authorization, integration with existing identity broker, logging, and monitoring. Additionally, the audience will learn whether cloud-hosted Kubernetes cover these requirements, how to integrate a compliant Kubernetes installation with their existing cloud infrastructure and how to handle cross-team communication (network/compute/storage/security).  

Since on-premise Kubernetes deployments have their challenges, Oleg will cover the limitations of a bare-metal installation, interactions with vSphere’s API, achieving HA, reliability and disaster recovery, as well as handling OS upgrades, security patches, and Kubernetes upgrades. He will close with a quick outlook of what’s next, including infrastructure as a code, immutable infrastructure, and GitOps.

Kubernetes in Highly Restrictive Environments

In a microservices world, applications consist of dozens, hundreds, or even thousands of components. Manually deploying and verifying deployment quality in production is virtually impossible. Kubernetes, which natively supports rolling updates, enables blue-green application deployments with Spinnaker. However, gradual rollouts is a feature that doesn't come out-of-the-box but can be achieved by adding Istio and Prometheus to the equation.

During this online meetup, Slava and Oleg will discuss canary release implementations on Kubernetes with Spinnaker, Istio, and Prometheus. They'll examine the role of each tool in the process and how they are all connected. During a demo, they will demonstrate a successful and a failed canary release, and how these tools enable IT teams to properly roll out changes to their customer base without any downtime.

Canary Releases on Kubernetes with Spinnaker, Istio, and Prometheus

While developers see and realize the benefits of Kubernetes, how it improves efficiencies, saves time, and enables focus on the unique business requirements of each project; InfoSec, infrastructure, and software operations teams still face challenges when managing a new set of tools and technologies, and integrating them into an existing enterprise infrastructure.   

During this online meetup, Oleg will discuss what’s needed for a general architecture of a centralized Kubernetes operations layer based on open source components such as Prometheus, Grafana, ELK Stack, Keycloak, etc., and how to set up reliable clusters and multi-master configuration without a load balancer. He’ll also describe how these components should be combined into an operations-friendly enterprise Kubernetes management platform with centralized monitoring and log collection, identity and access management, backup and disaster recovery, and infrastructure management capabilities.  This presentation will show real-world open source projects use cases to implement an ops-friendly environment.

Centralizing Kubernetes and Container Operations

Digital transformation may be in danger of becoming an overused buzzword. Yet, real business needs are driving this trend and IT leaders feel the pressure to transform their businesses every day. Whether it is the need for speed, agility, or rethinking business processes as a whole – these challenges are here to stay.  
 
Remember that bookseller? The one that decided not to be a bookseller but a computing powerhouse and is now shaking up the entire retail industry? Companies such as Amazon, Airbnb or Uber, are pushing traditional enterprises to rethink their modus operandi. 
 
Whether you seek to transform your business model or improve your operations and customer interactions, Digital Transformation Initiatives have several common elements:
•Experimentation and speed
•Realignment and partnering between IT and the business
•Use of cloud technologies
•Modern application architectures
 
Containers and Kubernetes are part of the technology ecosystem enabling Digital Transformation. In this online meetup, we’ll discuss how container technologies facilitate organizational alignment in IT around DevOps, cloud-native technologies, microservices, and APIs, as well as hybrid and multi-cloud architectures.

Enabling Digital Transformation with Container Technologies

Kubernetes ensures your deployed applications are always available to users. But how do you deploy applications in Kubernetes without user/service interruptions? Should you write your own scripts using low-level Kubernetes objects, package everything in Helm, or use specific CI/CD tools? There isn’t a clear-cut answer; it always depends.

In this online meetup, Slava Koltovich, CEO of Kublr, will discuss various application deployment options and demonstrate how tools like Spinnaker, Istio, and Jenkins can be used to implement blue-green or canary deployments to ensure zero-downtime application rollout.

Application Deployments with Kubernetes

Is advanced scheduling in Kubernetes achievable? Yes, however, how do you properly accommodate every real-life scenario that a Kubernetes user might encounter? How do you leverage advanced scheduling techniques to shape and describe each scenario in easy-to-use rules and configurations?

Oleg Chunikhin answers those questions and demonstrate techniques for implementing advanced scheduling. For example, using spot instances and cost-effective resources on AWS, coupled with the ability to deliver a minimum set of functionalities that cover the majority of needs – without configuration complexity. You’ll get a run-down of the pitfalls and things to keep in mind for this route.

SPEAKER: Oleg Chunikhin, CTO at Kublr, has been working in the field of software architecture and development for nearly 20 years. He joined Kublr in 2017, as he specializes in DevOps technologies including Kubernetes, Docker, and Puppet. Oleg has successfully defined Kublr’s technology strategy and innovative standards, tools, technologies, and processes.

Implement Advanced Scheduling Techniques in Kubernetes

Containers and Kubernetes allow for code portability across on-premise VMs, bare metal or multiple cloud provider environments. Yet, despite this portability promise, developers may include configuration and application definitions that constrain or even eliminate application portability. In this online meetup Oleg Chunikhin, CTO at Kublr, describes best practices for “configuration as code” in a Kubernetes environment. He demonstrates how a properly constructed containerized app can be deployed to both Amazon and Azure using the Kublr platform, and how Kubernetes objects, such as persistent volumes, ingress rules and services, can be used to abstract from the infrastructure.

Dev How You Want. Run Where You Want: Application Portability with Kubernetes

Enabling support for data processing, data analytics, and machine learning workloads in Kubernetes has been one of the goals of the open source community. During this meetup we’ll discuss the growing use of Kubernetes for data science and machine learning workloads. We’ll examine how new Kubernetes extensibility features such as custom resources and custom controllers are used for applications and frameworks integration. Apache Spark 2.3.’s native support is the latest indication of this growing trend. We’ll demo a few examples of data science workloads running on Kubernetes clusters setup by our Kublr platform.

Kubernetes, Data Science, and Machine Learning

Kubernetes

Data Analytics

Apache Spark

Machine Learning

Data Processing

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Kubernetes, Data Science, and Machine Learning

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