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Multi-Cluster Service-Mesh Patterns
Christian Posta
Field CTO – Solo.io
2 | Copyright © 2020
CHRISTIAN POSTA
Global Field CTO, Solo.io
@christianposta
christian@solo.io
https://blog.christianposta.com
https://slideshare.net/ceposta
3 | Copyright © 2020
As we move to services architectures,
on cloud-native deployment platforms,
we increase the complexity between
our services.
4 | Copyright © 2020
Service Mesh
5 | Copyright © 2020
Service proxy lives with application instance
6 | Copyright © 2020
Service proxy lives with application instance
7 | Copyright © 2020
Service mesh technologies provide the following:
• Service discovery / Load balancing
• Secure service-to-service communication
• Traffic control / shaping / shifting
• Policy / Intention based access control
• Traffic metric collection
• Service resilience
• API / programmable interface
8 | Copyright © 2020
More, smaller clusters
• High availability
• Compliance
• Isolation / Autonomy
• Scale
• Data locality, cost
• Public/DMZ/Private networks
9 | Copyright © 2020
Pattern: flat network across pods
Account
User
Products
Cluster 1 Cluster 2
History
10 | Copyright © 2020
Pattern: Different network, expose all services
Account
User
Products
Cluster 1 Cluster 2
History
11 | Copyright © 2020
Pattern: Different network, controlled gateway
Account
User
Products
Cluster 1 Cluster 2
History
User
12 | Copyright © 2020
Envoy is the magic behind service mesh
http://envoyproxy.io
13 | Copyright © 2020
Service Mesh
14 | Copyright © 2020
Envoy implements:
• zone aware, priority/locality load balancing
• circuit breaking, outlier detection
• timeouts, retries, retry budgets
• traffic shadowing
• request racing
• rate limiting
• RBAC, TLS origination/termination
• access logging, statistics collection
15 | Copyright © 2020
Envoy to do application networking heavy lifting
Account
work
load
work
load
work
load
mTLS
• Transparent client-side routing
decisions
• TLS orig/termination
• Circuit breaking
• Stats collection
16 | Copyright © 2020
Envoy as backbone for multi-cluster
communication federation
Account
User
Cluster 1 Cluster 2
Products
History
User
17 | Copyright © 2020
Other key Envoy proxying features
• Request hedging
• Retry Budgets
• Load balancing priorities
• Locality weighted load balancing
• Zone aware routing
• Degraded endpoints (fallback)
• Aggregated clusters
18 | Copyright © 202018 | Copyright © 2020
Multi-cluster examples
Service mesh examples using Envoy Proxy
19 | Copyright © 2020
Shared control plane, flat network
Account
User
Cluster 1 Cluster 2
Products
History
User
Istiod
20 | Copyright © 2020
Account
User
Cluster 1 Cluster 2
Products
History
User
Istiod
Shared control plane, separate networks
21 | Copyright © 2020
Account
User
Cluster 1 Cluster 2
Products
History
User
Istiod
Separate control planes, separate networks
Istiod
22 | Copyright © 2020
Increased operator burden
• Making each cluster aware of what services live where
• Unifying identity domains / limited trust networks
• Often need to write multiple configurations in multiple clusters just to
accomplish something simple (like traffic routing)
• Consistent security
• Defining failover semantics (locality, priority, etc)
• Isolating fault domains (trust, configuration, etc)
23 | Copyright © 2020
What to do about the added
burden for the operator?
https://github.com/solo-io/gloo-mesh
24 | Copyright © 2020
What to do about the added burden for the
operator?
https://github.com/solo-io/gloo-mesh
25 | Copyright © 2020 @christianposta
Cluster 1 Cluster 2
Istiod
work
load
Ingress
Gateway
Istiod
work
load
work
load
work
load
work
load
work
load
Gloo Mesh
Management
Ingress
Gateway
Management
Plane
26 | Copyright © 202026 | Copyright © 2020
Demo
Service Mesh Hub
27 | Copyright © 2020 @christianposta
THANK YOU FOR ATTENDING!
@christianposta
christian@solo.io
https://blog.christianposta.com
https://slideshare.net/ceposta
28 | Copyright © 2020
• https://solo.io
• https://slack.solo.io
• https://gloo.solo.io
• https://envoyproxy.io
• https://istio.io
• https://webassemblyhub.io
• https://servicemeshhub.io
• https://blog.christianposta.com

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Multi-cluster service mesh with GlooMesh

  • 1. Multi-Cluster Service-Mesh Patterns Christian Posta Field CTO – Solo.io
  • 2. 2 | Copyright © 2020 CHRISTIAN POSTA Global Field CTO, Solo.io @christianposta christian@solo.io https://blog.christianposta.com https://slideshare.net/ceposta
  • 3. 3 | Copyright © 2020 As we move to services architectures, on cloud-native deployment platforms, we increase the complexity between our services.
  • 4. 4 | Copyright © 2020 Service Mesh
  • 5. 5 | Copyright © 2020 Service proxy lives with application instance
  • 6. 6 | Copyright © 2020 Service proxy lives with application instance
  • 7. 7 | Copyright © 2020 Service mesh technologies provide the following: • Service discovery / Load balancing • Secure service-to-service communication • Traffic control / shaping / shifting • Policy / Intention based access control • Traffic metric collection • Service resilience • API / programmable interface
  • 8. 8 | Copyright © 2020 More, smaller clusters • High availability • Compliance • Isolation / Autonomy • Scale • Data locality, cost • Public/DMZ/Private networks
  • 9. 9 | Copyright © 2020 Pattern: flat network across pods Account User Products Cluster 1 Cluster 2 History
  • 10. 10 | Copyright © 2020 Pattern: Different network, expose all services Account User Products Cluster 1 Cluster 2 History
  • 11. 11 | Copyright © 2020 Pattern: Different network, controlled gateway Account User Products Cluster 1 Cluster 2 History User
  • 12. 12 | Copyright © 2020 Envoy is the magic behind service mesh http://envoyproxy.io
  • 13. 13 | Copyright © 2020 Service Mesh
  • 14. 14 | Copyright © 2020 Envoy implements: • zone aware, priority/locality load balancing • circuit breaking, outlier detection • timeouts, retries, retry budgets • traffic shadowing • request racing • rate limiting • RBAC, TLS origination/termination • access logging, statistics collection
  • 15. 15 | Copyright © 2020 Envoy to do application networking heavy lifting Account work load work load work load mTLS • Transparent client-side routing decisions • TLS orig/termination • Circuit breaking • Stats collection
  • 16. 16 | Copyright © 2020 Envoy as backbone for multi-cluster communication federation Account User Cluster 1 Cluster 2 Products History User
  • 17. 17 | Copyright © 2020 Other key Envoy proxying features • Request hedging • Retry Budgets • Load balancing priorities • Locality weighted load balancing • Zone aware routing • Degraded endpoints (fallback) • Aggregated clusters
  • 18. 18 | Copyright © 202018 | Copyright © 2020 Multi-cluster examples Service mesh examples using Envoy Proxy
  • 19. 19 | Copyright © 2020 Shared control plane, flat network Account User Cluster 1 Cluster 2 Products History User Istiod
  • 20. 20 | Copyright © 2020 Account User Cluster 1 Cluster 2 Products History User Istiod Shared control plane, separate networks
  • 21. 21 | Copyright © 2020 Account User Cluster 1 Cluster 2 Products History User Istiod Separate control planes, separate networks Istiod
  • 22. 22 | Copyright © 2020 Increased operator burden • Making each cluster aware of what services live where • Unifying identity domains / limited trust networks • Often need to write multiple configurations in multiple clusters just to accomplish something simple (like traffic routing) • Consistent security • Defining failover semantics (locality, priority, etc) • Isolating fault domains (trust, configuration, etc)
  • 23. 23 | Copyright © 2020 What to do about the added burden for the operator? https://github.com/solo-io/gloo-mesh
  • 24. 24 | Copyright © 2020 What to do about the added burden for the operator? https://github.com/solo-io/gloo-mesh
  • 25. 25 | Copyright © 2020 @christianposta Cluster 1 Cluster 2 Istiod work load Ingress Gateway Istiod work load work load work load work load work load Gloo Mesh Management Ingress Gateway Management Plane
  • 26. 26 | Copyright © 202026 | Copyright © 2020 Demo Service Mesh Hub
  • 27. 27 | Copyright © 2020 @christianposta THANK YOU FOR ATTENDING! @christianposta christian@solo.io https://blog.christianposta.com https://slideshare.net/ceposta
  • 28. 28 | Copyright © 2020 • https://solo.io • https://slack.solo.io • https://gloo.solo.io • https://envoyproxy.io • https://istio.io • https://webassemblyhub.io • https://servicemeshhub.io • https://blog.christianposta.com

Editor's Notes

  1. How does Solo help do this? Help pick right tech when it’s warranted (Envoy) Hedge when market still volatile (SMH) Simplify adoption Enterprise focus (security, heterogeneous) Solve the problem everywhere regardless of technology, infrastructure, footprint On prem/public cloud/hybrid Any service mesh technology VMs, containers, et. al
  2. Need a way to automate handling of explosive numbers of workloads (microservices) Placement of workloads AKA deployments Autoscale, health check, start/stop, rebalance, scale up/down Building applications for Kubernetes (or any cloud native platform) is fundamentally different Why Kubernetes won: * community Right level of API Extensible Declarative configuration model Foundation of DevOps and Automation model Adopting microservices to go fast!
  3. Need a way to automate handling of explosive numbers of workloads (microservices) Placement of workloads AKA deployments Autoscale, health check, start/stop, rebalance, scale up/down Building applications for Kubernetes (or any cloud native platform) is fundamentally different Why Kubernetes won: * community Right level of API Extensible Declarative configuration model Foundation of DevOps and Automation model Adopting microservices to go fast!
  4. Need a way to automate handling of explosive numbers of workloads (microservices) Placement of workloads AKA deployments Autoscale, health check, start/stop, rebalance, scale up/down Building applications for Kubernetes (or any cloud native platform) is fundamentally different Why Kubernetes won: * community Right level of API Extensible Declarative configuration model Foundation of DevOps and Automation model Adopting microservices to go fast!
  5. Need a way to automate handling of explosive numbers of workloads (microservices) Placement of workloads AKA deployments Autoscale, health check, start/stop, rebalance, scale up/down Building applications for Kubernetes (or any cloud native platform) is fundamentally different Why Kubernetes won: * community Right level of API Extensible Declarative configuration model Foundation of DevOps and Automation model Adopting microservices to go fast!