The document provides an overview of applying microservice and serverless architecture principles, including the twelve-factor methodology for web services and applications. It covers key concepts such as componentization via services, adaptive routing, health checks, and API gateways, alongside practical examples and best practices. The content addresses the need for organizations to embrace these principles for improved scalability, modularity, and efficient deployment of applications.

1. #CLUS
Stève Sfartz, API Evangelist
DEVNET-1871
Microservices
and Serverless
architecture principles
applied

2. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS
/Cisco/DevNet/SteveSfartz
• API Evangelist @CiscoDevNet
• API Design,Architecture and Deployment
• WebexTeams & xAPI developer
• hosted @CiscoROI: Paris Innovation Center
• Node.js mainly, a bit of #golang
• Europe and all over the world
• github: //ObjectIsAdvantag
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“vision without
execution is
hallucination”
-- Thomas Edison
mailto: stsfartz@cisco.com
twitter: @SteveSfartz
2

3. Agenda
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS
• ApplyingTwelve Factors
• Scaling Monoliths
• MicroserviceArchitecture Design
Principles
• Componentization via Services
• Adaptative Routing
• Healthchecks
• API Gateways
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4

5. ApplyingTwelve Factors in
the Enterprise
- for developers: building Web
services and applications
- for ops engineers: who deploy or
manage such apps

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Twelve Factors
https://12factor.net/
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Twelve factors applied to Spark Bots
https://github.com/CiscoDevNet/botkit-template/blob/master/bot.js#L49
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8. Twelve factors applied to Spark Bots
« One code base to rule them all »
local dev env demo

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The ‘config file’ versus ‘env variables’ dilemna
• Where to put all not env specific info, nevertheless configurable
• Think defaults for PORTS, HTTP ROUTES, INSTANCE NAME
• Common practice to use a ‘.env’ file to load variables to ENV
• Ruby: https://github.com/bkeepers/dotenv
• Node: https://github.com/motdotla/dotenv
• ALWAYS read from ENV and assume env variables precedence
• over-ride defaults, the execution environment always has the last world
• env may be injected by CI/CD tools, your production platform
• environment managed by Puppet or Chef
• ‘heroku config’ CLI command, and console environment
• env field in a Kubernetes PodYAML configuration
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10. Twelve factors applied to Spark Bots
« One code base to rule them all »
Heroku & Glitch Demos

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Twelve Factor sum up
• Take time to iterate on your code’s launch code to read from the
environment:
• local dev machines, integration, demo, production platforms
• when appropriate, dig into each platform specifics
• Add ops teams feedback to your backlog
• Total launch time
• Maintenance mode
• Enrich logs
• Add healthchecks
• …
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12. Applying Microservices
Design Principles

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Monolithic versus Microservices
http://martinfowler.com/articles/microservices.html
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Scaling the Monolith
• Several instances behind a load balancer
• lack of modularity
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Load
Balancer
Client
Client
Client
- Complexity to route traffic
- Very large code base
- Change cycles tied together
- Limited scalability
+ Quickest path to scale
+ High availability

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Making the Monolith more modular
• Specialized instances of a single codebase
• Modular invocation
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Load
Balancer Real time
business logic
Client
Client
Client
Monolith
MonolithAuthentication
Monolith
Batches
Load
Balancer
+ ‘Renovation’ as an alternative to a rewrite
+ Generally does the trick
+ Tip: engage an iterative API-fication
15

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The End of Monoliths ?
http://www.stavros.io/posts/microservices-cargo-cult
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Microservices (2014)
Martin Fowler, James Lewis
• In short, the microservice architectural style is an approach to developing a
single application as a suite of small services, each running in its own
process and communicating with lightweight mechanisms, often an HTTP
resource API.
• These services are built around business capabilities and independently
deployable by fully automated deployment machinery.
• There is a bare minimum of centralized management of these services,
which may be written in different programming languages and use
different data storage technologies.
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Monolithic versus Microservices
http://martinfowler.com/articles/microservices.html
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Common Characteristics
http://martinfowler.com/articles/microservices.html
 Componentization via Services
 Organized around Business Capabilities
 Products not Projects
 Smart endpoints and dumb pipes
 Decentralized governance
 Decentralized data management
 Infrastructure automation
 Design for failure
 Evolutionary design
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Organized around Business Capabilities
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Any organization that
designs a system will
produce a design
whose structure is a
copy of the
organization's
communication
structure.
Melvyn Conway,
1967.
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Organized around Business Capabilities
• Microservices to solve Conway’s anti-pattern
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Cross-functional teams…. … organised around capabilities
21

22. Lessons learnt building the event chatbot

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Componentization via Services
 Services as components rather than libraries
 Services avoid tight coupling by using explicit remote call mechanisms.
 Services are independently deployable and scalable
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Componentization via Services
https://creations.devnetcloud.com/detail?cid=1e4a9f92-deea-11e7-9d2f-aed03b187700
Events API
Bot Admin
Public
catalog
https://devnet-events-api.herokuapp.com/
CiscoDevNet
@sparkbot.io Postman JSON
Voice
Responder
Tropo
24

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Smart endpoints and dumb pipes
 Be as decoupled and as cohesive as possible
 own domain logic,
 act more as filters in the classical Unix sense
 using simple RESTish protocols and lightweight messaging
 Smarts live in the services, not in-between the endpoints
 No central tool / bus that includes sophisticated routing, transformations, process,
business rules
 Pre-requisite : turn the chatty in-process communication of the monolith
into coarser-grained network messaging
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Componentization via Services
Design Best Practices
 ThinkAPI first = 1 microservice
 Treat each API consumer as a new independent channel = multiple
consumers
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deployment
delivery
versioning
contracts
scaling/autoscaling
service discovery
load balancing
routing / adaptive routing
health checking
configuration
circuit breaking
TTL/deadlining
latency tracing
service causal tracing
distributed logging
metrics exposure, collection
26

27. Adaptive Routing

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When ONE backend becomes latent
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29. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS DEVNET-1871
At 50+ req/s, all request threads can block in seconds
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NetFlix Hystrix
• Latency and FaultTolerance library
• designed to isolate points of access to remote systems, services and 3rd party
libraries,
• stop cascading failure and enable resilience where failure is inevitable.
• real time monitoring via Dashboard
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Hystrix Dashboard
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Healthchecks
• Passive healthcheck
• Monitoring of your app responses (ie, checks status codes)
• Active healthcheck
• Basically GET / returns a 200 OK
• Provide extra JSON meaning full data
• Used for monitoring, diagnose but also traffic optimization
• Platform dependent: Nginx active healthckech, Amazon LB healthcheck
configuration, Kubernetes liveness probes, Envy
• Types of failure: use 50x error codes
• Tip: include Maintenance, Recovery states info
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33. Demo: Botkit template healthcheck

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Healthchecks Best Practices
• Always provide an healthcheck
• You cannot assume how your service will be deployed
• Make it configurable
• On / off toggle, secured via credentials
• Include maintenance, recovery states
• Provide extra JSON meaningful data
• Start small with 200, think big via adapters to address various platforms
• Nginx active healthcheck, Amazon LB healthcheck configuration, Kubernetes
liveness probes, Envoy healthcheck
• FAIL FAST (12-factor)
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Resources
• Amazon healthcheck configuration
• https://docs.aws.amazon.com/elasticloadbalancing/latest/classic/elb-
healthchecks.html
• Nginx active healthecks
• https://www.nginx.com/resources/admin-guide/http-health-check/#hc_active
• Kubernetess liveness probes
• https://kubernetes.io/docs/tasks/configure-pod-container/configure-liveness-
readiness-probes
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36. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS
Common Characteristics
http://martinfowler.com/articles/microservices.html
• Componentization via Services
• Organized around Business Capabilities
• Products not Projects
• Smart endpoints and dumb pipes
• Decentralized governance
• Decentralized data management
• Infrastructure automation
• Design for failure
• Evolutionary design
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37. ‘Sidecar’ pattern

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SideCar pattern
• Complement an existing service with extra capabilities via a distinct service
rather than in-process
• Ex: SSL endpoint, outgress routing, traffic priorization
• Typically reverse proxy or smart routing
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CaddyWeb Server
• Production-ready
• Secure by default: HTTPS by default, hardenedTLS stack
• Written in go, self-contained
• Single executable with no dependency
• https://caddyserver.com/download
• Multi-platform, container friendly
• Plugin-architecture
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WebexTeams Widgets
HTTPS required for Audio/Video calls
40DEVNET-1871
Caddyfile
https://github.com/CiscoDevNet/widget-samples

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Resources
• Caddy
• https://caddyserver.com/
• Cisco SparkWidget Samples
• https://github.com/CiscoDevNet/widget-samples
• SparkAffinity: scalingWebhooks
• https://github.com/ObjectIsAdvantag/spark-webhook-affinity
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42. Programmable
API Gateways

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Decentralized Centralized
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Kong
• OpensourceAPI Gateway
• Consists in Nginx plugins written in LUA, leverages OpenResty
• Cluster configuration: persists data to Cassandra or PostgreSQL
• The API Gateway can be deployed on bare-metal, cloud or on-premises,
docker/container friendly
• Microservices management building block
• NEW: Kubernetes Ingress Controller for Kong
• https://konghq.com/blog/kubernetes-ingress-controller-for-kong/
https://getkong.org
44DEVNET-1871

45. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS DEVNET-2896

46. Kong demo
https://github.com/ObjectIsAdvantag/kong-101/tree/master/docker

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Kong: launching with docker
PostGreSQL backend
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docker network create kong-net
docker run -d --name kong-database
--network=kong-net
-p 5432:5432
-e "POSTGRES_USER=kong“
-e "POSTGRES_DB=kong“
postgres:9.6
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48. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS
Kong: launching with docker
PostGreSQL backend
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docker run --rm
--network=kong-net
-e "KONG_DATABASE=postgres"
-e "KONG_PG_HOST=kong-database"
kong:latest kong migrations up
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49. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS
Kong: launching with docker
Reverse proxy
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docker run -d --name kong --network=kong-net
-e "KONG_DATABASE=postgres" -e "KONG_PG_HOST=kong-database"
-e "KONG_PROXY_ACCESS_LOG=/dev/stdout"
-e "KONG_ADMIN_ACCESS_LOG=/dev/stdout"
-e "KONG_PROXY_ERROR_LOG=/dev/stderr"
-e "KONG_ADMIN_ERROR_LOG=/dev/stderr"
-e "KONG_ADMIN_LISTEN=0.0.0.0:8001, 0.0.0.0:8444 ssl"
-p 8000:8000 -p 8443:8443 -p 8001:8001 -p 8444:8444
kong:latest
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50. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS
Kong: launching with docker
• Proxy at port :8000
• Administration at :8001
• Exposes :8443 and :8444 for SSL support
• Healthcheck at admin root :8001/ and :8444/
Reverse proxy
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51. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS
Kong: Registering HTTP Endpoint
Via admin API
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curl http://localhost:8001/services/
--data 'name=minispark'
--data 'url=https://mini-spark.herokuapp.com/'
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Kong: Rate Limitation
https://getkong.org/plugins/rate-limiting
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curl http://localhost:8001/services/{{_service}}/plugins
--data "name=rate-limiting"
--data "config.second=1"
--data "config.minute=5"
--data "config.limit_by=ip"
--data "config.policy=local"
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53. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS
API Gateways use cases
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54. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS
Resources
• Kong
• https://getkong.org
• Tyk
• https://tyk.io
• Envoy
• https://www.envoyproxy.io
• Ambassador
• https://www.getambassador.io
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55. Wrapup

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Applying Microservices Principles
• Make your code easy to run and scale
• Embrace environment variables and configuration best practices
• Docker-ready, Kubernetes-ready
• Leverage the infrastructure, don’t ignore it !!!
• Get familiar with Load Balancers, Reverse Proxies, API Gateways
• Practice regularly: local tests, demo environments
• Expose healthchecks
as an Application Developer
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57. © 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public#CLUS
Furthers considerations
Lessons learnt from Microservices journeys
• Solid communications
• Fault tolerant pipes
• Gateways and Service discovery
• Committed teams
• Devops culture
• Code/Test/Deploy/Support, 24/7
• Automation, automation, automation
• Ownership
• Organisation aligned with the overall strategy
• Operational insights (monitoring, logging infrastructure, real time analysis)
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59. Q&A

60. Thank you
#CLUS

61. #CLUS