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The Past, Present, and Future of
Cloud Native API Gateways
Daniel Bryant
tl;dr
• Edge gateways have undergone a series of evolutions, driven by architecture
• “Cloud native” (microservices/K8s) changes architecture and workflow
• Chose your cloud API gateway solution intentionally
2
@danielbryantuk
3
4
Edge: The boundary between your
data center and your user(s)
5
Thesis: The evolution of the edge has
been driven by application architecture
6
The past:
A trip down memory lane
7
~1995
Application Architecture in the ‘90s
8
Hardware Load Balancer
9
User Systems administrators
Purpose High availability / scalability
Key Features
Load balancing
(round robin, sticky sessions)
Health checks
10
~2000
Similar application architecture
11
12
20022001
Software Load Balancer
13
User
Systems administrators
(“pre DevOps”)
Purpose High availability / scalability
Key Features
Load balancing
Health checks
Observability
14
~2005
15
16
Ecommerce
0
75
150
225
300
2000 2005 2010 2015 2019
Amazon Revenue,
Billions
17
The Application Delivery Controller (ADC)
18
Application Delivery Controllers
19
User Systems administrators
Purpose
High availability and
application acceleration
Key Features
SSL offload, caching,
compression + load balancing
20
https://www.flickr.com/photos/pchow98/5518600886
21
~2010
The proliferation of APIs
22
2005: API launched 2008 2009
API Gateway (1st Gen)
23
User
Systems administrators &
API developers
Purpose
Expose business APIs to
broader ecosystem
(“API management”)
Key Features
L7 routing (e.g., throttling),
Publishing, Dev Portal,
Analytics, Monetization
24
~2015
25
Mini-services
26
API Gateway (2nd Generation)
27
API Gateway (2nd Generation)
28
User
Systems administrators &
API developers
Purpose
Centralize cross-cutting app
concerns
Key Features
Authentication, rate limiting,
monitoring + routing
29
Present day:
Cloud-native apps
Cloud-Native Microservices
30
• Modularisation (“microservices”)
• Built, released, & operated by
independent application teams
• Scaled independently
App Architecture: A Spectrum of Services
• Different locations (K8S, VMs, FaaS)
• Different protocols (gRPC, HTTP, WebSockets, TCP)
• Different load balancing requirements (sticky
sessions, round robin)
• Different authentication requirements
31
Cloud Gateway
32
Real-time Service
Discovery
Need ADC-like traffic management
capabilities: timeouts, retries, rate
limiting, load balancing, caching, …
Need API Gateway-type
management capabilities:
authentication, developer
portal, metrics, …
1
2
3
“Microservices” lead to an even bigger change.
33
34
Developers are on call.
Microservices: Full Cycle Development
35
• App teams have full responsibility (and authority) for
delivering a service
• Increases agility by accelerating the feedback loop.
• https://netflixtechblog.com/full-cycle-developers-at-netflix-a08c31f83249
36
This is a change in workflow.
37
Thesis: The evolution of the edge will be
driven by application architecture and the
application development workflow.
38
Two Biggest
Challenges
Challenge #1: Scaling Edge Management
39
Development
Team
Operations / Platform Team
Challenge #1: Scaling Edge Management
Challenge #2: Supporting Diverse Edge Requirements
41
42
Three Strategies
Three Strategies for the Edge with Kubernetes
#1: Deploy an Additional Kubernetes API Gateway
#2: Extend Existing API Gateway
#3: Deploy an in-Cluster Edge Stack
43
https://www.getambassador.io/resources/strategies-managing-apis-edge-kubernetes/
#1 Deploy an Additional Kubernetes API Gateway
• Simply deploy an additional “in-cluster” gateway
• Below the existing gateway
• Below the load balancer
• Management
• Development teams responsible
• OR existing ops team manages this
44
#1 Deploy an Additional Kubernetes API Gateway
• Pros
• There is minimal change to the core edge infrastructure.
• Incremental migration easily
• Cons
• Increased management overhead of working with
different components
• Challenging to expose the functionality to each
independent microservice teams
45
#2 Extend Existing API Gateway
• Implemented by modifying or augmenting the existing API
gateway solution
• Enable synchronization between the API endpoints and
location of k8s services
• Custom ingress controller for the existing API Gateway or
load balancer
46
#2 Extend Existing API Gateway
• Pros
• Reuse the existing tried and trusted API gateway
• Leverage existing integrations with on-premises
infrastructure and services
• Cons
• Workflows must change to preserve a single source of
truth for the API gateway configuration
• Limited amount of configuration parameters via
Kubernetes annotations
47
#3 Deploy an In-Cluster Edge Stack
• Deploy Kubernetes-native API gateway with
integrated supporting edge components
• Installed in each of the new Kubernetes clusters,
replacing existing edge
• Ops team own, and provide sane defaults
• Dev teams responsible for configuring the edge
stack as part of their normal workflow
48
#3 Deploy an In-Cluster Edge Stack
• Pros
• Edge management is simplified into a single stack
• Supports cloud native best practices: “single
source of truth”, GitOps etc
• Cons
• Potentially a large architectural shift
• Platform team must learn about new proxy
technologies and edge components
49
50
Wrapping Up
In Conclusion
• Edge/API gateways have undergone a series of evolutions, driven by architecture
• Hardware -> software
• Networking Layer 4 -> Layer 7
• Centralized management -> decentralised
• Adopting microservices/Kubernetes changes workflow. We need to:
• Scale edge management
• Support multi-protocol and cross-functional requirements
• Chose your solution intentionally
51
Many thanks!
• Learn more:
• https://www.getambassador.io/learn/building-kubernetes-platform/
• https://www.getambassador.io/podcasts/
• https://blog.getambassador.io/
• Find me in:
• Datawire OSS Slack: http://d6e.co/slack
• Twitter @danielbryantuk
52

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SoftwareCircus 2020 "The Past, Present, and Future of Cloud Native API Gateways"

  • 1. The Past, Present, and Future of Cloud Native API Gateways Daniel Bryant
  • 2. tl;dr • Edge gateways have undergone a series of evolutions, driven by architecture • “Cloud native” (microservices/K8s) changes architecture and workflow • Chose your cloud API gateway solution intentionally 2
  • 4. 4 Edge: The boundary between your data center and your user(s)
  • 5. 5 Thesis: The evolution of the edge has been driven by application architecture
  • 6. 6 The past: A trip down memory lane
  • 9. Hardware Load Balancer 9 User Systems administrators Purpose High availability / scalability Key Features Load balancing (round robin, sticky sessions) Health checks
  • 13. Software Load Balancer 13 User Systems administrators (“pre DevOps”) Purpose High availability / scalability Key Features Load balancing Health checks Observability
  • 15. 15
  • 16. 16 Ecommerce 0 75 150 225 300 2000 2005 2010 2015 2019 Amazon Revenue, Billions
  • 17. 17
  • 18. The Application Delivery Controller (ADC) 18
  • 19. Application Delivery Controllers 19 User Systems administrators Purpose High availability and application acceleration Key Features SSL offload, caching, compression + load balancing
  • 22. The proliferation of APIs 22 2005: API launched 2008 2009
  • 23. API Gateway (1st Gen) 23 User Systems administrators & API developers Purpose Expose business APIs to broader ecosystem (“API management”) Key Features L7 routing (e.g., throttling), Publishing, Dev Portal, Analytics, Monetization
  • 25. 25
  • 27. API Gateway (2nd Generation) 27
  • 28. API Gateway (2nd Generation) 28 User Systems administrators & API developers Purpose Centralize cross-cutting app concerns Key Features Authentication, rate limiting, monitoring + routing
  • 30. Cloud-Native Microservices 30 • Modularisation (“microservices”) • Built, released, & operated by independent application teams • Scaled independently
  • 31. App Architecture: A Spectrum of Services • Different locations (K8S, VMs, FaaS) • Different protocols (gRPC, HTTP, WebSockets, TCP) • Different load balancing requirements (sticky sessions, round robin) • Different authentication requirements 31
  • 32. Cloud Gateway 32 Real-time Service Discovery Need ADC-like traffic management capabilities: timeouts, retries, rate limiting, load balancing, caching, … Need API Gateway-type management capabilities: authentication, developer portal, metrics, … 1 2 3
  • 33. “Microservices” lead to an even bigger change. 33
  • 35. Microservices: Full Cycle Development 35 • App teams have full responsibility (and authority) for delivering a service • Increases agility by accelerating the feedback loop. • https://netflixtechblog.com/full-cycle-developers-at-netflix-a08c31f83249
  • 36. 36 This is a change in workflow.
  • 37. 37 Thesis: The evolution of the edge will be driven by application architecture and the application development workflow.
  • 39. Challenge #1: Scaling Edge Management 39 Development Team Operations / Platform Team
  • 40. Challenge #1: Scaling Edge Management
  • 41. Challenge #2: Supporting Diverse Edge Requirements 41
  • 43. Three Strategies for the Edge with Kubernetes #1: Deploy an Additional Kubernetes API Gateway #2: Extend Existing API Gateway #3: Deploy an in-Cluster Edge Stack 43 https://www.getambassador.io/resources/strategies-managing-apis-edge-kubernetes/
  • 44. #1 Deploy an Additional Kubernetes API Gateway • Simply deploy an additional “in-cluster” gateway • Below the existing gateway • Below the load balancer • Management • Development teams responsible • OR existing ops team manages this 44
  • 45. #1 Deploy an Additional Kubernetes API Gateway • Pros • There is minimal change to the core edge infrastructure. • Incremental migration easily • Cons • Increased management overhead of working with different components • Challenging to expose the functionality to each independent microservice teams 45
  • 46. #2 Extend Existing API Gateway • Implemented by modifying or augmenting the existing API gateway solution • Enable synchronization between the API endpoints and location of k8s services • Custom ingress controller for the existing API Gateway or load balancer 46
  • 47. #2 Extend Existing API Gateway • Pros • Reuse the existing tried and trusted API gateway • Leverage existing integrations with on-premises infrastructure and services • Cons • Workflows must change to preserve a single source of truth for the API gateway configuration • Limited amount of configuration parameters via Kubernetes annotations 47
  • 48. #3 Deploy an In-Cluster Edge Stack • Deploy Kubernetes-native API gateway with integrated supporting edge components • Installed in each of the new Kubernetes clusters, replacing existing edge • Ops team own, and provide sane defaults • Dev teams responsible for configuring the edge stack as part of their normal workflow 48
  • 49. #3 Deploy an In-Cluster Edge Stack • Pros • Edge management is simplified into a single stack • Supports cloud native best practices: “single source of truth”, GitOps etc • Cons • Potentially a large architectural shift • Platform team must learn about new proxy technologies and edge components 49
  • 51. In Conclusion • Edge/API gateways have undergone a series of evolutions, driven by architecture • Hardware -> software • Networking Layer 4 -> Layer 7 • Centralized management -> decentralised • Adopting microservices/Kubernetes changes workflow. We need to: • Scale edge management • Support multi-protocol and cross-functional requirements • Chose your solution intentionally 51
  • 52. Many thanks! • Learn more: • https://www.getambassador.io/learn/building-kubernetes-platform/ • https://www.getambassador.io/podcasts/ • https://blog.getambassador.io/ • Find me in: • Datawire OSS Slack: http://d6e.co/slack • Twitter @danielbryantuk 52