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Top 3 reasons why you should run your Enterprise workloads on GKE

This deck covers top 3 reasons why Google Kubernetes engine is best suited to run containerized workloads. The reasons covered are Security, Observability and Maturity.

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Top 3 reasons why you should run your Enterprise workloads on GKE

  1. 1. Top 3 reasons why you should run your Enterprise workloads on GKE Sreenivas Makam Partner Engineer @Google Cloud
  2. 2. Agenda ● Why Containers, Docker and Kubernetes ● GKE Value-Add ● GKE differentiators for Enterprises - Security, Observability and Openness ● Demo
  3. 3. “Keeping our infrastructure perfectly homogenous is giving me nightmares” “It ran fine on MY machine” Problem: Deployments and Ops are Hard “We want to get the best utilization of our infrastructure” “Keeping our infrastructure perfectly homogenous is giving me nightmares” “It ran fine on MY machine” “My developers aren’t as productive as they should be. Deployments are slowing us down”
  4. 4. Bare Metal, VM and Container Virtual machine Kernel Dependencies Application Code Hardware + hypervisor Dedicated server Kernel Dependencies Application Code Hardware Container Kernel + Container Runtime Dependencies Application Code Hardware Deployment ~mins (sec) Portable Very Efficient Deployment ~months Not portable Low utilization Deployment ~days (mins) Hypervisor specific Low isolation, Tied to OS
  5. 5. Why Containers ● Self contained ● Portability ● Decoupling from machine ● Image immutability ● Faster development ● Faster deployment Virtual machine Container ImageMagick 6.4.90 Container ImageMagick 7.0.28 Payments application Rendering application Linux distribution Hardware
  6. 6. But they introduce a new set of challenges “Where should I run my containers?” “If we run our containers on VMs, I don’t want to manage anything” “How do I get my containers to talk to one another?” “How do we ensure our containers are running smoothly?” “We don’t want to be locked into one cloud provider”
  7. 7. Why Kubernetes ● Decoupling from infra ● Autoscaling ● Autohealing ● Automated rollout and rollbacks ● Abstractions that are cloud native and microservices friendly ● Extensible ● Open-source ● Integrates well with other Devops tools
  8. 8. Kubernetes cluster Worker node Master node Worker node Docker Kubelet Control Plane Docker Kubelet Deployment Pod Contain er Container Pod Contain er Container Node pool Deployment Pod Contain er Container Pod Contain er Container Pod Contain er Container Pod Contain er Container Deployment Pod Contain er Container Pod Contain er Container Pod Contain er Container Pod Contain er Container service calls Service A Service B kubectl cmd Kubernetes Architecture
  9. 9. Kubernetes control plane Kubernetes Control Plane API Server etcd Scheduler Controller Manager Kubernetes Master API Server etcd Scheduler Controller Manager Kubernetes Nodes Kubelet Container Runtime Kube-Proxy Container Network
  10. 10. Kubernetes Abstractions Pod Deployment Service Config & Secrets Volume Stateful set Jobs
  11. 11. Google Kubernetes Engine (GKE) gcloud cmd Kubernetes cluster Worker node Master node Worker node Runtime E.g.Docker Kubelet Control Plane Runtime E.g.Docker Kubelet Deployment Pod Containe r Container Pod Containe r Container Node pool Deployment Pod Containe r Container Pod Containe r Container Pod Containe r Container Pod Containe r Container Deployment Pod Containe r Container Pod Containe r Container Pod Containe r Container Pod Containe r Container service calls Service A Service B kubectl cmd GKE with Kubernetes
  12. 12. GKE Value Add ● Master management including master redundancy, upgrade, replication and backup ● Worker node lifecycle management ● IAM integration for security and authentication ● Get all benefits of Google compute engine including Networking and Storage ● Integration with other Google cloud services like load balancer, storage, big data, analytics ● Pod and cluster autoscale ● Integrated logging and monitoring with Stackdriver ● 99.5% SLA
  13. 13. Observability Security Openness GKE for Enterprises - Top 3 reasons
  14. 14. 14 GKE for Enterprises - Security
  15. 15. Container Security pillars Software supply chain Is my container image secure to build and deploy? Infrastructure security Is my infrastructure secure for developing containers? Container runtime security Is my container secure to run? Application security Platform security Are my applications secure? Is my (cloud provider’s) infrastructure secure? ● IAM, RBAC, Pod access policy ● Shared VPC ● Private cluster ● Network control policy ● Image scanning ● Binary authorization ● Container OS ● Node OS(CoS) ● Cloud security command center ● Tie-up - Aquasec, Capsule8, Stackrox, Sysdig, Twistlock
  16. 16. Confidential & Proprietary Google Kubernetes Engine patches you to the latest version, automatically. This keeps you up to date with security patches and with new features Google Kubernetes Engine provides common best practices with security by default. There will always be app-level hardening and tuning to do Google Kubernetes Engine provides the best of Google Cloud Platform security features, with integrations with IAM, Audit Logging, VPC, and more 1 2 3 Why GKE security?
  17. 17. Kubernetes Engine: Use RBAC and IAM RBAC is enabled by default for GKE 1.8+ clusters Use IAM to manage users and permissions at the project-level, including API access, service accounts, and quotas. Use RBAC at the cluster and namespace level to set permissions. Infra sec
  18. 18. Kubernetes: RBAC Example RBAC is enabled by default for Kubernetes 1.8+ clusters e.g., give the ‘blue team’ user ‘cluster admin’ rights in the ‘blue’ namespace $ cat blue-binding.yaml kind: RoleBinding apiVersion: rbac.authorization.k8s.io/v1 metadata: name: blue-dev-binding namespace: blue subjects: - kind: User name: blue-team-dev@kube-pw.iam.gsa.com roleRef: kind: ClusterRole name: admin apiGroup: rbac.authorization.k8s.io Infra sec
  19. 19. Kubernetes: PodSecurityPolicy apiVersion: extensions/v1beta1 kind: PodSecurityPolicy metadata: name: restricted spec: privileged: false # Don't allow privileged pods! allowPrivilegeEscalation: false # Don’t allow privilege escalation runAsUser: # Require the container to run without root privileges rule: ‘MustRunAsNonRoot’ supplementalGroups: # Forbid adding to the root group rule: ‘MustRunAs’ ranges: - min: 1 max: 65535 Infra sec
  20. 20. Network control policy kind: NetworkPolicy apiVersion: networking.k8s.io/v1 metadata: name: hello-allow-from-product spec: policyTypes: - Ingress podSelector: matchLabels: app: reviews ingress: - from: - podSelector: matchLabels: app: productpage Product Reviews Details Ratings Infra sec
  21. 21. Private Clusters Trusted Virtual Private Cloud (VPC) Kubernetes Engine Cluster Node Node Node Google Kubernetes Engine Kubernetes Master Trusted On-prem Host HostVPN Untrusted Internet Infra sec
  22. 22. Shared VPC Sharing of common resources More granular billing Isolation of data and support for multi-tenant workloads Security and separation of roles Infra sec
  23. 23. Shared VPC Organization Apps project Kubernetes Engine clusters Apps team Shared VPC network subnet-1 subnet-2 Network admin Host Project DB project Kubernetes Engine clusters DB team Infra project Kubernetes Engine clusters Infra team Private IP connectivity Infra sec
  24. 24. GKE: Minimal OS Container-optimized OS (COS) based on Chromium OS, and maintained by Google ● Built from source: Since COS is based on Chromium OS, Google maintains all components and is able to rebuild from source if a new vulnerability is discovered and needs to be patched ● Smaller attack surface: Container-Optimized OS is purpose-built to run containers, has a smaller footprint, reducing your instance's potential attack surface ● Locked-down by default: Firewall restricts all TCP/UDP except SSH on port 22, and prevents kernel modules. Root file system is mounted read-only ● Automatic Updates: COS instances automatically download weekly updates in the background; only a reboot is necessary to use the latest updates. Google provides patches and maintenance https://cloud.google.com/container-optimized-os/ Image sec
  25. 25. GCR: Vulnerability Scanning (Alpha) ● Scans all images in your private Google Container Registry for known Common Vulnerabilities and Exposures (CVEs) ● Examines images and packages ● Works for: Debian, Ubuntu and Alpine images ● Images are scanned when: ○ An image is added to the registry ○ There is an update to the vulnerability database https://cloud.google.com/container-registry/docs/vulnerability-scanning Image sec
  26. 26. To use, ● Enable the Container Analysis API ● Enable Vulnerability Scanning GCR: Vulnerability Scanning (Alpha) https://cloud.google.com/container-registry/docs/vulnerability-scanning Image sec
  27. 27. 27 Launch container Requirements met?YES Requirements Grafeas Binary Authorization policyNO Block launch Attestations Code Signed by: * Builder * Analysis tool Must be built by myphotos.com Binary authorization (Alpha) Image sec
  28. 28. Container security Runtime security Sandboxing Verification with vTPM Isolate a workload at the pod level using hypervisor-like technology Bind information to a node and verify integrity of a workload using TPMs Runtime detection agent Monitor, detect, and react to common container attacks Runtime sec
  29. 29. Runtime security partners in Cloud SCC Cloud Security Command Center 5 partner integrations Runtime sec
  30. 30. 30 0GKE for Enterprises - Observability
  31. 31. Microservices Kubernetes makes it easy to break monolithic applications into independently scalable microservices More pieces to monitor and operate Stackdriver - Rethinking monitoring with Kubernetes Abstracted Infrastructure Kubernetes offers a lot of flexibility, with many constructs that support and make building your app easier Increased observability across your entire Kubernetes environment becomes necessary Highly Dynamic Environment Your environment scales and adapts as needed, changing as it reschedules and restarts components Keep track of your applications, which may be constantly moving
  32. 32. Multi-cluster monitoring with support for Kubernetes Engine on GCP and Kubernetes on-prem in a single place Hybrid, multi-cluster Kubernetes monitoring
  33. 33. 33 Stackdriver logging ● Review, monitor and alert on audit logs centrally ● “jamie@myphotos.com deployed a new frontend version @ time T” ● Runtime metrics gathered and exported ● “Photo book creation latency in the last 10 minutes was 1.3s” K8s Application logs audit logs Stackdriver monitoring Prometheus GKE: Monitoring & logging
  34. 34. VPC Flow Logs for Kubernetes Engine BigQuery Cloud Pubsub Stackdriver Logging Captures all flows in VPC Integration with a host of partners Optimize network usage and egress Network Forensics & Security Analysis Real-time Security Analysis
  35. 35. Kubernetes Load Balancing - Suboptimal Two levels of load balancing Inaccurate cloud-level health checks Multiple network hops
  36. 36. GKE Load balancing with Network Endpoint Group Containers are “just another endpoint” Accurate cloud-level health checks and load balancing No extra network hops; direct connection from load balancer to container
  37. 37. Region: US West Kubernetes Engine Alice California Google Edge myapp.com Chao Singapore Google Edge myapp.com Region: Asia East Kubernetes Engine Bob London Google Edge myapp.com Region: Europe West Kubernetes Engine kind: Ingress Google Global HTTP(S) Load Balancing Multi-region clusters
  38. 38. 38 GKE for Enterprises - Open & Mature
  39. 39. Each week, Google launches more than four billion containers across its data centers around the world. These containers house the full range of applications Google runs, including user-facing applications such as Search, Gmail, and YouTube. Kubernetes was directly inspired by Google’s cluster manager, internally known as Borg. Borg allows Google to direct hundreds of thousands of software tasks across vast clusters of machines numbering in the tens of thousands — supporting seven businesses with over one billion users each. Borg and Kubernetes are the culmination of Google’s experience deploying resilient applications at scale. Containers at Google
  40. 40. GA for 3 years
  41. 41. Marquee customers Kubernetes Engine (GKE) marquee customers
  42. 42. ...and many more
  43. 43. Cloud services platform(Hybrid cloud solution)
  44. 44. GKE Extended into your Datacenter Google Cloud Platform Serverless add-on for GKE Google Kubernetes Engine Istio add-on for GKE Service Marketplace Stackdriver + Prometheus Serverless add-on for GKE Google Kubernetes Engine On-Prem Istio add-on for GKE Service Marketplace Stackdriver + Prometheus Your Datacenter Single-pane-of-glass UI Policy Syncing Aggregated Logging CI/CD Service Discovery Multi-cluster Ingress
  45. 45. DEMO TIME!
  46. 46. Book review App
  47. 47. References ● Container Security - Blog series ● GKE NEXT18 sessions