2. 2
Major Projects
• Open Solaris
• Scale out x86
• Cloud Foundry Since start 2010
• Spring, Boot generation
CF 2011 Core Team
Bio
Today
• Product leader at Pivotal
• 50/50 time split between
Customers and product
development
5. 55
Near-free
computing costs
Mobile devices
and connectivity
Ubiquity of
embedded sensors
Global scale
of operations
KEY TRENDS
The cost and ubiquity of computing
enables cloud native software
companies to reshape the world
8. 8
Is Cloud Native Enterprise Happening?
• Friday, London: Global Banking giant, building new digital
banking application for 27 country roll out
• Monday, Frankfurt: Stock Exchange looking to rebuild
whole stack cloud native
• Tuesday, Munich: Insurance giant 5 new agile projects
apps on platform
• Wednesday, Thursday: Co-Launch of Bosch’s industrial
cloud for connected services …
15. 15
Focus On First Principles
• Everything run as a service before it’s shipped as software
• Zero human intervention in individual machines through
lifecycle; immutable platform infrastructure
• Service automation’s goal is to ship holistic cloud services not
ad-hoc automation simplicity
• Multi-cloud primitives vs. AWS only features etc
• Industry standard Linux containers for speed; Virtual
machines when needed for advanced data/state management
17. 17
Multi-cloud Cloud Orchestration
and automation
• Builds of each supported cloud
• Configuration dialects != service delivery differentiation
• Run everything as a service on multiple clouds before
shipping as software
• Automation exists to deliver cloud native services not for
ad-hoc human intervention
18. 18
OSS API driven cloud integration drives
broad industry collaboration
Azure CPI donation
VMware on team 2 engineers on CPI
Openstack CPI helped by Pivotal, SAP, IBM
Google green light to contribute to CPI
22. 22
First Principles
• Velocity and autonomy of delivery for large teams in enterprise
environments
• Enterprise safety/security with startup cycle time (simple
repeatable deploys)
• Optimized for Cloud Native applications
• “Velocity on the JVM is the Killer App”
24. 24
Accelerating Velocity of Iterations
Ford Connected Car Microservices on Concourse
• Continuous delivery key to
iterative development
process
• Cloud Foundry is the first
platform built assuming CD
as the prime directive
• Deploy without risk of
failure, fully instrumented,
and optimized to support
rapid change
25. 25
Innovation Speed in Java WINS
“Velocity on
the JVM is the
Killer App”
Andy Glover (Netflix Cloud Ops)
@ SpringOne2GX 2014 Keynote –
Early Spring Boot adopters
Youtube Link to Video
26. 26
• Dynamic language productivity with maturity
of enterprise Java
• Cloud Native: Direct support for
Microservices, NetflixOSS++
• Fully automated app server configuration
and deployment
• Production ready Ops metrics out of the
box, with a switch
Spring Boot
27. 27
THEN NOW
• Java was verbose, complex
• Manual, SOAP based SOA
• App server sprawl, manual
• Complex Ops, Admin, Manage
• Low productivity for
Development and ops
• Dynamic language productivity
• Dynamic, REST microservices
• Autoconfig & embed app server
• Prod Ops features with a switch
• High productivity shared
• DevOps responsibility
39. 39
Steel Toe is an open-source project to make the Spring Cloud
server components consumable from .NET applications with an
idiomatic .NET experience
• Config Server + Auto-refresh
• Service Registration/Discovery (Eureka)
• Circuit Breaker (Hystrix)
What is Steel Toe?
40. 40
• .NET Core on Linux
– Currently in RC1 (via the ASP.NET 5 buildpack)
– This is the target framework for the project
• .NET Core on Windows 2012r2
– On a Diego Cell
– This also seems to work
Supported Frameworks
42. 42
Netflix Atlas: Primary Telemetry Platform
• Who is building Atlas for the cloud
native enterprise?
• Canary deployment metrics
integration
• Advanced metrics + Lifecycle
automation = ?
43. 43
PCF Metrix BETA
• Fast feedback loop that helps app
devs better understand the health
and performance of their apps
• Live stream and 24 hours of data
• Works without an embedded agent
• Metrics include:
– HTTP requests and errors
– Avg. response latency
– CPU, memory and disk
– App events like start, stop, scale,
update, and crash
44. 44
Operational Visibility: Distributed Tracing
• Latency visibility into a request’s end-to-end call graph
• Quickly identify a problematic service in a distributed system
• Zipkin is a open source distributed tracing system. It helps gather timing data
needed to troubleshoot latency problems in microservice architectures.
• Pivotal is investing in Zipkin to solve distributed tracing use cases
– Apache 2.0 License
– Created by Twitter in 2012.
– In 2015, OpenZipkin became the primary fork
Zipkin Tracing
47. • PCF Developers can redirect application traffic to a desired request
path in order to use logging, authentication or rate limiting systems
that exist outside of PCF
• PCF’s Service API will introduce a new field: route_service_url
• Developers will create a routing service instance and bind it to a
route (not an app)
– Service Instance can be created by a Service Broker or can
be a user-provided service instance
• Router is configured with and forwards requests to the URL
contained in the route_service_url field
• The route service is expected to forward the request back to the
route
• Knowing the request has already been forwarded to the route
service, the Router forwards to the associated applications
Route Services
client
load
balancer
CF router
CF app
route
service
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3
4
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55. 55
• Software product that is always ready to ship
• Always current visibility into product and requirements status
• 100% focus on development, no effort wasted below the value line
• Ongoing assessment of priorities and resource allocation to
optimize for highest impact
Listens to data in a Stream
Decoupled from the primary Stream’s lifecycle
• Cloud Foundry is built using concourse
• Helps us get commits from 40+ teams rolling into production hosted env as fast as possible with safety validated by tests
• Pipelines are the main focus, no longer is it about a single build, but how that build fits into a flexible pipeline of activities
• Concourse built from ground up using containers for execution isolation—your tests are repeatable without pollution, and the way a container runs a test on a workstation is the same as a test in the cloud CI
• Concourse configuration itself is meant to be stored in SCM and easily reproducible, no more jenkins falling over and multiple hours needed to rebuild CI
• Net result, faster feedback loops from code written to running in production