The document discusses the evolution of API gateways driven by changes in application architecture and technology. It describes how API gateways evolved from hardware load balancers to software load balancers to application delivery controllers to first-generation API management platforms as applications moved to the cloud and adopted microservices. Managing APIs and microservices at the edge with Kubernetes poses new challenges around scaling edge management and supporting diverse requirements. The document outlines three strategies for managing APIs at the edge with Kubernetes and concludes that choosing an API gateway intentionally is important when adopting cloud-native technologies and platforms.

1. The Past, Present, and Future of
Cloud Native API Gateways
Daniel Bryant
Head of DevRel @ Ambassador Labs

2. tl;dr
• API gateways have undergone a series of evolutions,
driven by architecture and technology
• Adopting microservices, Kubernetes, and cloud also changes the workflow
• Choose your Kubernetes API gateway (and platform) intentionally
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3. @danielbryantuk
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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 and technology

6. 6
~1995

7. Application Architecture in the ‘90s
7

8. Hardware Load Balancer
8
User Systems administrators
Purpose High availability / scalability
Key Features
Load balancing
(round robin, sticky sessions)
Health checks

9. 9
~2000

10. Similar application architecture (some SOA?)
10

11. 11
2002
2001

12. So
ft
ware Load Balancer
12
User
Systems administrators
(“pre DevOps”)
Purpose High availability / scalability
Key Features
Load balancing
Health checks
Observability

13. 13
~2005

14. 14

15. 15
Ecommerce
0
75
150
225
300
2000 2005 2010 2015 2019
Amazon Revenue,
Billions

16. 16

17. The Application Delivery Controller (ADC)
17

18. Application Delivery Controllers (ADCs)
18
User Systems administrators
Purpose
High availability and
application acceleration
Key Features
SSL o
ff
load, caching,
compression + load balancing

19. 19
~2010

20. The proliferation of APIs
20
2005: API launched 2008 2009

21. API Gateway (1st Gen)
21
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

22. 22
~2015

23. 23

24. Mini-services
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25. API Gateway (2nd Generation)
25

26. API Gateway (2nd Generation)
26
User
Systems administrators &
API developers
Purpose
Centralize cross-cutting app
concerns
Key Features
Authentication, rate limiting,
monitoring + routing

27. 27
Cloud-native
applications

28. Cloud-Native Microservices
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• Modularisation (“microservices”)
• Built, released, & operated by
independent application teams
• Scaled independently

29. App Architecture: A Spectrum of Services
• Di
ff
erent locations (K8s, VMs, FaaS)
• Di
ff
erent protocols (gRPC, HTTP, WebSockets, TCP)
• Di
ff
erent load balancing requirements
(sticky sessions, round robin)
• Di
ff
erent authentication requirements
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30. Cloud Gateway
30
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

31. Microservices lead to an even bigger change.
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32. 32
“You build it, you run it”
- Werner Vogels, CTO Amazon
i.e. you own what you code,
from idea to production

33. Workflow: Full Cycle Development
33
• App teams have full responsibility (and authority) for
delivering a service, and ultimately, value to users
• Increase agility by accelerating the feedback loop
• https://netflixtechblog.com/full-cycle-developers-at-netflix-a08c31f83249

34. 34
This is a change in workflow.

35. 35
Thesis:
The future evolution of the edge will be driven by
application architecture, technology, and workflow

36. 36
Two Biggest
Challenges with
k8s & the Edge

37. Challenge #1: Scaling Edge Management
37
Development
Team
Operations / Platform Team

38. Challenge #1: Scaling Edge Management

39. Challenge #2: Supporting Diverse Edge Requirements
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40. 40
Three Strategies

41. 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
41
https://www.getambassador.io/resources/strategies-managing-apis-edge-kubernetes/

42. #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
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43. #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
di
ff
erent components
• Challenging to expose the functionality to each
independent microservice teams
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44. #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
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45. #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 CRDs/annotations
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46. #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
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47. #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/responsibility shi
ft
• Platform team must learn about new proxy
technologies and edge components
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48. 48
Wrapping Up

49. In Conclusion
• Edge/API gateways have undergone a series of evolutions, driven by architecture and tech
• Hardware -> so
ft
ware
• Networking Layer 4 -> Layer 7
• Centralized management -> decentralised
• Adopting microservices/Kubernetes changes workflow
• Scale edge management
• Support multi-protocol and cross-functional requirements
• Choose your cloud API gateway intentionally (and also your platform components in general)
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50. Many thanks!
• Learn more:
• www.getambassador.io/kubernetes-learning-center/
• www.getambassador.io/resources/accelerating-
kubernetes-for-cloud-native-organizations/
• www.infoq.com/profile/Daniel-Bryant
• Find me in:
• Ambassador OSS Slack: d6e.co/slack
• Twitter @danielbryantuk
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