This document discusses key aspects of cloud native applications and platforms. It notes there is consensus around cloud native traits like containers, microservices, platform independence, and automation. Cloud Foundry is presented as a platform that can deploy and manage cloud native applications by providing automated scaling, routing, service integration, and other capabilities through declarative configuration. The platform handles tasks like detecting application frameworks, linking to services, self-service deployment, routing, versioning, upgrades, scaling, and more through simple commands. This allows developers to focus on their code while the platform manages the complex runtime environment.
5. There is a rough consensus on many Cloud Native traits.
Containers as an atomic unit, for example. Micro-services
as the means of both construction and communication.
Platform independence. Multiple language support.
Automation as a feature of everything from build to
deployment. High uptime. Ephemeral infrastructure (cattle
not pets). And so on.
Stephen O’Grady, Redmonk
http://redmonk.com/sogrady/2015/07/24/cloud-native-implications/
6. There is a rough consensus on many Cloud Native traits.
Containers as an atomic unit, for example. Micro-services
as the means of both construction and communication.
Platform independence. Multiple language support.
Automation as a feature of everything from build to
deployment. High uptime. Ephemeral infrastructure (cattle
not pets). And so on.
Stephen O’Grady, Redmonk
http://redmonk.com/sogrady/2015/07/24/cloud-native-implications/
7. There is a rough consensus on many Cloud Native traits.
Containers as an atomic unit, for example. Micro-services
as the means of both construction and communication.
Platform independence. Multiple language support.
Automation as a feature of everything from build to
deployment. High uptime. Ephemeral infrastructure (cattle
not pets). And so on.
Stephen O’Grady, Redmonk
http://redmonk.com/sogrady/2015/07/24/cloud-native-implications/
8. There is a rough consensus on many Cloud Native traits.
Containers as an atomic unit, for example. Micro-services
as the means of both construction and communication.
Platform independence. Multiple language support.
Automation as a feature of everything from build to
deployment. High uptime. Ephemeral infrastructure (cattle
not pets). And so on.
Stephen O’Grady, Redmonk
http://redmonk.com/sogrady/2015/07/24/cloud-native-implications/
9. There is a rough consensus on many Cloud Native traits.
Containers as an atomic unit, for example. Micro-services
as the means of both construction and communication.
Platform independence. Multiple language support.
Automation as a feature of everything from build to
deployment. High uptime. Ephemeral infrastructure (cattle
not pets). And so on.
Stephen O’Grady, Redmonk
http://redmonk.com/sogrady/2015/07/24/cloud-native-implications/
10. There is a rough consensus on many Cloud Native traits.
Containers as an atomic unit, for example. Micro-services
as the means of both construction and communication.
Platform independence. Multiple language support.
Automation as a feature of everything from build to
deployment. High uptime. Ephemeral infrastructure (cattle
not pets). And so on.
Stephen O’Grady, Redmonk
http://redmonk.com/sogrady/2015/07/24/cloud-native-implications/
11. There is a rough consensus on many Cloud Native traits.
Containers as an atomic unit, for example. Micro-services
as the means of both construction and communication.
Platform independence. Multiple language support.
Automation as a feature of everything from build to
deployment. High uptime. Ephemeral infrastructure (cattle
not pets). And so on.
Stephen O’Grady, Redmonk
http://redmonk.com/sogrady/2015/07/24/cloud-native-implications/
12. The Cloud Native Advantage:
Simple Patterns
Highly Automated
Scaled with Ease
14. Fast – Focus on Takt Time
Definition: the desired time between units of production output, synchronized
to customer demand
http://www.strategosinc.com/takt_time.htm
16. Safe – Runtime Characteristics Matter
• Visibility – Measure all the things. Translate data into knowledge. (see:
OODA loop)
• Fault Isolation – Smaller applications, released independently, isolate the
scope of a fault condition.
• Fault Tolerance – Failures happen (see: Circuit Breaker Pattern / Design
for Failure)
• Autonomic Recovery – Humans have better things to do at night
17. Scale – Prepare (as best you can) to Succeed
• Demand elastic infrastructure
• Separate concerns - Isolated ephemeral services, Solve persistence
independently
• Accept that the scalability of a system can be a series of plateaus
18.
19. “Any organization that designs
a system (defined broadly) will
produce a design whose
structure is a copy of the
organization's communication
structure.
Melvyn Conway, 1967
20. Microservices are great, but they require:
rapid provisioning
basic monitoring
rapid application deployment
devops culture
Martin Fowler
21.
22. • Use declarative formats for setup automation, to minimize time and
cost for new developers joining the project;
• Have a clean contract with the underlying OS, offering maximum
portability between execution environments;
• Are suitable for deployment on modern cloud platforms, obviating
the need for servers and systems administration;
• Minimize divergence between development and production,
enabling continuous deployment for maximum agility;
• And can scale up without significant changes to tooling,
architecture, or development practices.
24. • Role based access to resources: the right
people should be able to do things and the
wrong people shouldn’t
• Run specified bits on demand: take code, put
it together with all the rest of the things it
needs and and get it running
• Coordinate cross service configurations: in a
service oriented world, services need to be
configured to connect with each other
• Route public requests to running bits: the
next big thing needs access to the internet
• Read and write persistent data: data has to
live somewhere
• Add and remove resources: scaling is a great
problem to have, but still
• Isolate resources and failures without
isolation and decoupling, that is one big
distributed single point of failure
• Measure performance/health: can’t manage
what you don’t measure
• Detect and determine failure: sometimes,
things get real… but how do you know
• Recover failures: someone is going to have
to clean this mess
• Work tomorrow: when everything you’ve
thought to be true has been shown not to
27. Unit of Value
IaaS == Virtual Machine
• Opaque to the system
• Orchestration is post-hoc
• System changes are imperative
(“launch” stuff)
App Platform == Application
• Containers are transparent
• Lifecycle is fully managed
• System changes are
declarative (manifest.yml)
28. Unit of Value
IaaS == Virtual Machine
• Opaque to the system
• Orchestration is post-hoc
• System changes are imperative
(“launch” stuff)
App Platform == Application Time
to release a feature or App
• Containers are transparent
• Lifecycle is fully managed
• System changes are
declarative (manifest.yml)
38. = + +
Contents Processes
?
?
Isolation Rules
PID
User
Network
cgroups cflinuxfs2
What is a “Container”?
39. Let’s talk about Buildpacks / Staging
• Ruby code that detects language,
frameworks, whatnot…
• Compiles the code into executable
binaries (*)
/bin/detect < Am I supposed to run?
/bin/compile < Build the thing
/bin/release < Pass along potential metadata
cflinuxfs2
44. That was all about 12 factor
apps…
What about services?
45. CF and Services
- Development infrastructure components
(DBs, Cache, Queue, etc…)
- Loopback to other CF hosted apps
- Reaching out to your “legacy”
- External providers
