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

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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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Edge: The boundary between your
data center and your user(s)

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Thesis:
The evolution of the edge has been driven by
application architecture and technology

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~1995

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Application Architecture in the ‘90s
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Hardware Load Balancer
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User Systems administrators
Purpose High availability / scalability
Key Features
Load balancing
(round robin, sticky sessions)
Health checks

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~2000

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Similar application architecture (some SOA?)
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2002
2001

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

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~2005

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

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

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~2010

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The proliferation of APIs
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2005: API launched 2008 2009

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API Gateway (1st Gen)
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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

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~2015

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

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Cloud-native
applications

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

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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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Cloud Gateway
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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

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

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Workflow: Full Cycle Development
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• 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

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This is a change in workflow.

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

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Two Biggest
Challenges with
k8s & the Edge

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

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Challenge #1: Scaling Edge Management

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Challenge #2: Supporting Diverse Edge Requirements
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Three Strategies

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

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#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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#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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#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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#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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#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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#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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Wrapping Up

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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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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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