In this talk we will be talking about an open-source way to fully automated K8s clusters that can host workloads that can survive any failure, using pure DNS as the underlying tool for switching the communication among available Kubernetes clusters. No single vendor lock-in. Workloads can be deployed in AWS, Azure, GCP, on-prem. The only common denominators are Kubernetes and Cluster-API.
These days k8s namespaces don't provide enough isolation for our cloud native experiments. It's much easier to give a user the whole cluster to play with. Let them to break it; repeat. However, this assumes the cluster creation and deletion is an easy thing to do. Also there should be a nice API for that, not just some 5 years old web. Have you ever heard about clusterctl? If not, then come to this talk to learn how easy it is to start using it. If yes, then come to this talk to learn how hard it is to use it in production. Cluster API (CAPI) is a unique standardization effort among multiple cloud providers such as GCP, AWS, Azure but can also work with on-prem solutions such as OpenStack, KVM or vSphere. It allows you to dedicate one cluster in your infra as a control plane for creating the workload clusters. If you are into self-replicating robots, you are going to love this API!
k8gb is DNS based global service load balancer that can interconnect multiple Kubernetes clusters into one resilient system. Join this talk to learn how it can handle a failover scenario when pods in one cluster go down and second cluster in different location saves the situation.
k8gb is an open-source Kubernetes operator that is deployed in each participating cluster. It is comprised of CoreDNS, ExternalDNS and the k8gb controller itself. Using ExternalDNS it can create a zone delegation on a common cloud DNS server like Route53 or Infoblox so that the embedded CoreDNS servers work as an authoritative DNS. K8gb controller makes sure these CoreDNS servers are updated accordingly based on the readiness probes of the application.
In this sense this solution is unique, because it is using Kubernetes native tools with customisable probes and battle tested DNS protocol instead of HTTP pings or other similar approaches where single point of failure might be a problem. In k8gb architecture all k8s clusters are equal and there is no SPoF except the common edge DNS server.
If you have ever developed an operator pattern for Kubernetes, you have probably had to tweak your service account and assign it to a role. Setting up the RBAC correctly is not that hard, but it's not fun and it distracts you from the real problem the operator is about to solve. This often leads to assigning the cluster admin to the operator and neglecting the security altogether.
Log2rbac is a tool (yet another operator) that aims to solve this issue. It assists you with setting up your RBAC roles that are tailored for your application's needs. Come to see this talk and learn more.
In this talk Jiri Kremser and Mike McCune will show a library for implementing the operator pattern for Kubernetes in JVM languages. The library has been used to develop an operator for deploying and managing Apache Spark clusters in Kubernetes. The talk will also feature a live-coding demo in which you will see how easy it is to create a new operator from scratch on your own.
Have you ever wondered how to implement your own operator pattern for you service X in Kubernetes? You can learn this in this session and see an example of open-source project that does spawn Apache Spark clusters on Kubernetes and OpenShift following the pattern. You will leave this talk with a better understanding of how spark-on-k8s native scheduling mechanism can be leveraged and how you can wrap your own service into operator pattern not only in Go lang but also in Java. The pod with spark operator and optionally the spark clusters expose the metrics for Prometheus so it makes it easy for monitoring and alerting.
I will show the Blockchain analysis in Jupyter interactive notebook using the external Spark cluster running in Kubernetes, everything dockerized.
The talk will briefly describe how Blockchain transactions work, but most of the time would be the demo. In the demo I will show how we can run various queries on the publicly available Blockchain data, graph algorithms such as PageRank for identifying significant BTC addresses and more.
Intended audience: intermediate, analysts, Bitcoin/Altcoin enthusiasts
Let's go together through the cloud native landscape and explore all the goodies that may help you to develop scalable and reliable distributed systems. Hopefully, you will leave this talk with basic understanding of Kubernetes and motivated to use it in production.