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Fun with Kubernetes
& Payara Micro 5
Before we Begin
• Intermediate knowledge of:
• Distributed Concepts & Clustering
• Container Technologies and Docker
• Questions at the end
Fabio Turizo
• IT Professional with over 9(y) of experience
• Oracle Certified Professional Java SE 8
• Oracle Certified Master Java EE 6
• Architecting with GKE Specialist
• Software Architecture Enthusiast
• Toptal Network FreelancerSenior Services Engineer
Payara Services Limited
• Payara Platform - Commercial Support
• OpenJDK Support via Azul Systems
Partnership
• Eclipse MicroProfile Founding Member
• EE4J Project Board Members
Payara Micro
• Small, Simple and Serious
• Cloud & Container Friendly
• Auto-scalable, elastic deployments
• Small-sized (<80 MB)
Domain Data Grid
• Large-scale grid structure
• Across a domain of Payara instances
• Across the nodes of a cluster topology
• Features:
• High Availability
• Scalability + Elasticity
Domain Data Grid
• Backed up by Hazelcast IMDG (Open Source)
• Cluster formed by auto-discovery via:
• Domain Information
• TCP IP
• DNS
• Multicast  default
• Kubernetes (5.184 +)
Containers (Docker)
• Standard Unit of Software
• Executable Packages with:
• Application Code
• Runtime Environment
• System Dependencies (Libraries)
• Portable, Lightweight and Secure
Kubernetes (k8s)
• Container Infrastructure Orchestration
• On-premises
• Cloud Native
• Originally implemented by Google
• Donated to Cloud Native Computing Foundation
• Standard Container Support via OCI
Kubernetes (k8s)
• Easy automation of
• Deployments
• Scaling
• Container Management
• Declarative & Imperative Configuration
• Stateless and Stateful Applications
k8s Concepts
• Clusters are controlled by objects
• Persistent State
• K8S Control Plane does the work!
• Fix with Remediation Actions
• Objects defined by specs
• YAML files
k8s - Architecture
k8s – Nodes
• Worker Machines (minions)
• Maybe VM or Bare Metal
• Hosts both a kubelet and kube-proxy
• Usually auto-managed by Cloud Provider
• Zone + Regional Scaling (!)
k8s – Pods
• Most basic execution unit
• Can hold multiple containers
• Unique IP address
• Shared storage volumes (!)
• Usually managed by Controllers
• Deployments, StatefulSets, DaemonSets, Jobs
k8s – Deployments
• Sets the desired of Pods
• Favor declarative stance
• ReplicaSet handles replication
• Maintain specific versions of Pods
• Rolling Updates (!)
k8s – Deployments
• Updates / Upgrades:
• New ReplicaSets are created
• Plan strategy for availability
• Multiple upgrade strategies:
• Blue/Green Deployments
• Canary Deployments
k8s – Services
• Expose applications running on Pods
• Help Pods find each other
• IP Address and DNS Support
• Types:
• ClusterIP
• NodePort
• LoadBalancer
• Ingress
k8s – Pod Scaling
• Manual scaling is easy!
• But autoscaling is much better!
• Horizontal Pod Auto-scaler
• Works on multiple controllers
• Supported for Rolling Updates
k8s – Horizontal Pod AutoScaler
• Both resource and controller
• Queries Pod resources
• CPU and Memory by default
• Custom Metrics are supported (!)
• Supported on MicroProfile Metrics as Well.
• Target Deployments (and other controllers)
Payara Micro – DDG + k8s
• Hazelcast Kubernetes Discovery Mode
• java -jar payara-micro.jar --autobindhttp --clustermode kubernetes
• Hazelcast Kubernetes Plugin
• https://github.com/hazelcast/hazelcast-kubernetes
• Can target specific namespaces and services
Payara Micro – DDG + k8s
• Hazelcast Plugin Modes:
• Kubernetes API (Default)
• DNS Lookup
• Kubernetes API requires Special Permissions
• Role Bindings Needed (Security API)
Demo Time !!
Code Repository at:
https://github.com/fturizo/K8SPayaraDemo
Q & A
Many thanks!
Not using Payara yet?
Download Payara Micro from:
https://payara.fish/downloads
Need Support?
https://payara.fish/support

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Fun with Kubernetes and Payara Micro 5

  • 1. Fun with Kubernetes & Payara Micro 5
  • 2. Before we Begin • Intermediate knowledge of: • Distributed Concepts & Clustering • Container Technologies and Docker • Questions at the end
  • 3. Fabio Turizo • IT Professional with over 9(y) of experience • Oracle Certified Professional Java SE 8 • Oracle Certified Master Java EE 6 • Architecting with GKE Specialist • Software Architecture Enthusiast • Toptal Network FreelancerSenior Services Engineer
  • 4. Payara Services Limited • Payara Platform - Commercial Support • OpenJDK Support via Azul Systems Partnership • Eclipse MicroProfile Founding Member • EE4J Project Board Members
  • 5. Payara Micro • Small, Simple and Serious • Cloud & Container Friendly • Auto-scalable, elastic deployments • Small-sized (<80 MB)
  • 6. Domain Data Grid • Large-scale grid structure • Across a domain of Payara instances • Across the nodes of a cluster topology • Features: • High Availability • Scalability + Elasticity
  • 7. Domain Data Grid • Backed up by Hazelcast IMDG (Open Source) • Cluster formed by auto-discovery via: • Domain Information • TCP IP • DNS • Multicast  default • Kubernetes (5.184 +)
  • 8. Containers (Docker) • Standard Unit of Software • Executable Packages with: • Application Code • Runtime Environment • System Dependencies (Libraries) • Portable, Lightweight and Secure
  • 9. Kubernetes (k8s) • Container Infrastructure Orchestration • On-premises • Cloud Native • Originally implemented by Google • Donated to Cloud Native Computing Foundation • Standard Container Support via OCI
  • 10. Kubernetes (k8s) • Easy automation of • Deployments • Scaling • Container Management • Declarative & Imperative Configuration • Stateless and Stateful Applications
  • 11. k8s Concepts • Clusters are controlled by objects • Persistent State • K8S Control Plane does the work! • Fix with Remediation Actions • Objects defined by specs • YAML files
  • 13. k8s – Nodes • Worker Machines (minions) • Maybe VM or Bare Metal • Hosts both a kubelet and kube-proxy • Usually auto-managed by Cloud Provider • Zone + Regional Scaling (!)
  • 14. k8s – Pods • Most basic execution unit • Can hold multiple containers • Unique IP address • Shared storage volumes (!) • Usually managed by Controllers • Deployments, StatefulSets, DaemonSets, Jobs
  • 15. k8s – Deployments • Sets the desired of Pods • Favor declarative stance • ReplicaSet handles replication • Maintain specific versions of Pods • Rolling Updates (!)
  • 16. k8s – Deployments • Updates / Upgrades: • New ReplicaSets are created • Plan strategy for availability • Multiple upgrade strategies: • Blue/Green Deployments • Canary Deployments
  • 17. k8s – Services • Expose applications running on Pods • Help Pods find each other • IP Address and DNS Support • Types: • ClusterIP • NodePort • LoadBalancer • Ingress
  • 18. k8s – Pod Scaling • Manual scaling is easy! • But autoscaling is much better! • Horizontal Pod Auto-scaler • Works on multiple controllers • Supported for Rolling Updates
  • 19. k8s – Horizontal Pod AutoScaler • Both resource and controller • Queries Pod resources • CPU and Memory by default • Custom Metrics are supported (!) • Supported on MicroProfile Metrics as Well. • Target Deployments (and other controllers)
  • 20. Payara Micro – DDG + k8s • Hazelcast Kubernetes Discovery Mode • java -jar payara-micro.jar --autobindhttp --clustermode kubernetes • Hazelcast Kubernetes Plugin • https://github.com/hazelcast/hazelcast-kubernetes • Can target specific namespaces and services
  • 21. Payara Micro – DDG + k8s • Hazelcast Plugin Modes: • Kubernetes API (Default) • DNS Lookup • Kubernetes API requires Special Permissions • Role Bindings Needed (Security API)
  • 22. Demo Time !! Code Repository at: https://github.com/fturizo/K8SPayaraDemo
  • 23. Q & A
  • 24. Many thanks! Not using Payara yet? Download Payara Micro from: https://payara.fish/downloads Need Support? https://payara.fish/support