The Gib Five - Modern IT Architecture

BASEL BERN BRUGG DÜSSELDORF FRANKFURT A.M. FREIBURG I.BR. GENF
HAMBURG KOPENHAGEN LAUSANNE MÜNCHEN STUTTGART WIEN ZÜRICH
The Big Five
IT Architektur Today
Anatole Tresch, Principal Consultant AD-ZH
anatole.tresch@trivadis.com
Twitter: @atsticks

Agenda
1. Introduction
2. The Big "Five"
Microservices and Container
Cloud and DevOps
Big Data
IoT
Artifial Intelligence
3. And in practice?

The good old times…
Schwarzwaldgipfel3 22.03.2018
• Requirements
• Specification
• Implementation
• Operations
• Maintenance
-> Clear targets
-> Long term and relatively stable

…and as of today?
• New, complex requirements
• Increased flexibility
• Functional
• Time wise
• Multi device support
• Truely distributed systems
• Exploding Complexity and maintenance efforts
• 24x7 world-wide operations

The «Big Five»

Microservices
• Unix-Philosophy: „Do One Thing and Do It Well“
• Bounded Context
• APIs encapsulate implementation details
• Isolation
• Decentralized and horizontally scalable
• Failure tolerance

Advantages of Microservices
• Independent teams -> Scaling the development process, enable agility
• Easy to adapt or replace
• Stable architecture
• Long term productivity in development
• Independent scalable
• Emracing with failures of other services rendering the system as a whole stable
• Continuous Delivery
• Managed and flexible Technology stack

Disadvantages of Microservices
• Exposed Complexity
• Network-Latencies, Load balancing or network failures
• Increased failure probability for the system as a whole
• Complex software distribution and rollback
• High efforts for migrating legacy systems towards MS
• Logging and Monitoring
• Different Time zones
• CAP-Theorem (Availability vs. Consistency)
• Multiple programming languages and software stacks

Container
• OS-Virtualization
• Process-Isolation, shared kernel
• Virtual Runtime environment (no additional OS)
• Layered file systems
• Container registries

Advantages of Containers
• Portability
• Efficient ressource consumption (CPU, RAM, FS)
• Restartability, simple recovery
• Simply resettable
• Full runtime isolation incl. dependencies

Disadvantages of Containers
• Kernel isolation is complex
• Update of multiple containers in case of issues/upgrades
• Many configuration options may lead to errors (eg privileged containers)
• Quality of container registries

Cloud
• Services providing IT-Infrastructure eg
Storage, CPU or
application software
• Network access without local installation
• IaaS
• PaaS
• SaaS
• FaaS

Cloud Characterics
• On-demand Self-Service
• Broad network access
• Resource Pooling
• Fast elasticity
• Controlled and measured resource consumption
• Variety of cost models

Cloud Delivery Models
• Public Cloud
• Private Cloud
• Hybrid Cloud
• Community Cloud
• Virtual Private Cloud
• Multi Cloud

DevOps
• Improving the development and
delivery processes for software
• Incentives and tools for more effective
and efficient collaboration of
Dev, Ops and
Quality Control

DevOps in Practice
• Automation of processes with CI- and CD-Tools as „Deployment Pipeline“:
• Code – Development and review, version control and merging/branching
• Build – Continuous-Integration-Tools, Build Status
• Test – Static code analysis and dynamic tests
• Package – Packing into a binary formatted deliverable
• Release – Change Management, Promoting and publishing of releases
• Configure – Configuration / System Management tools
• Monitoring – Application performance, Customer feedback
• Common Tools: Docker, Jenkins, Ansible, Puppet

BigData
• Amount of data, which is
• too big,
• too complex,
• too volatile or
• too unstructured
So it cannot be handled with traditional
methods of data processing.

BigData – «Big»
• Volume
Amount, volume
• Velocity
Speed at which data is generated or transferred
• Variety
Different data types and -sources

BigData – «Data»
• Improvements of bussiness processes in all areas, especially in
• Technology evolution and information technology
• Marketing
• Distribution and service optimization
• Trend research and detection
• Prognosis

IoT
• Internet of Things
• Vision of a global infrastructure
of information societies
• Linking of physical and virtual things
based on information and communication
technology
• Applicable to all areas

IoT

Artificial Intelligence
• Automating intelligent behaviour and
machine learning
• What is „intelligent behaviour“ ?
• Key drivers of the digital revolution
• Artificial model of human comparable decision logic
• Often only «fake» intelligence:
• Simulation of „intelligent behaviour“ with simple algorithms

Impact
• Automatisierung intelligenten Verhaltens und
Maschinenlernen
• „Intelligenz“ ?
• Wegweisende Antriebskräfte der Digitalen Revolution
• Nachbildung menschenähnlicher Entscheidungsstrukturen
• Oftmals «nachgeahmte» Intelligenz:
• Simulation „intelligentes Verhalten“ mit einfachen
Algorithmen
And in Practice?

Modern Architecture in Practice
• Multiple Solution Options
• Distribution and separation creates new concerns
• Combination of *old* and *new*
• Challenging traditional concepts
• Cloud Native Know How is rare

Know How Example – Web-Shop for …
• Webshop
• 1 Database
• 1 Business Tier (REST API)
• 1 Frontend
// Add a product
POST /cart/product/123
// View basket
GET /cart
// View products
GET /products
// Place Order
POST /order (with product data)

Know How Example – Web-Shop
• Let’s split up in «Microservices»
• Products API
• Order API
• Cart API
// Place Order
POST /order (with product data)
// View products
GET /products
// Add a product
POST /cart/product/123
// View basket
GET /cart
Service
Service
Service

• The «Product» Microservice
• REST Service
• Messaging Service
• Datastore Service
• Monitoring Service
// View products
GET /products

• Final draft Microservice Architecture
-> Wow! We have already 12 microservices!
Products Orders Cart
REST Service REST Service REST Service
Messagebus Messagebus Messagebus
Datastore Datastore Datastore
Monitoring Monitoring Monitoring

What’s the problem?

Sometimes things break…

...sometimes things break as many...

...or they get lost somehow...

...sometimes you even not know...

...and our new toys do not really help...

We need a resilient architecture!
So how we must built our systems to get all the
advantages we have seen but to ensure stable
operations?

Resilient Architecture
Schwarzwaldgipfel
Resilience = Capability of self-healing
MTTF
Availability =
MTTF + MTTR
Resilient Approach:
Minimize MTTR
42 22.03.2018

Service
Service
Input
Service
Service
Managed state
Service Isolation
Isolation
1. Decoupled communications
(Events)

Supervision
Going Resilient…45 19.10.16
Service
Input Output
Service
InputOutput
Queue
Error
Error
Handler
Monitoring
Errors
Super
visor

Characteristics of Resilient Systems
• Asynchronous communication
• Idempotente, self-contained events
• Location transparency
• Isolation & recursive restartability
• Complete Input and Output Validation
• Managed Error Handling and Monitoring
• Supervision
• Minimal shared state, redundancy

Resilient Platforms
• Cloud (resilience delegated to cloud provider)
• Orchestration (zB Mesos, Kubernetes, Openshift)
• Software-Containers
In most cases on-premise operations is not recommened.
Mind Cloud-Vendor-Lock-in.

Resilient Software Design
• Bounded Queues
• Fan out & quickest reply
• Circuit Breakers and Fail Fast
• Timeouts
• Throttling, Semaphores
• Failover
• Degradation of service level

DevOps
• DevOps ensure the required flexibilität and agility
• Without DevOps the archicture and systems will stay inflexible
• DevOps Plattforms can be set in production within hours
• Establish collaborative working and accounting mechanisms
• Use PoCs and Pilot projects

Managing Data
• Storage is cheap
• Store data easy accessible and ready for analysis
• Support on-the-fly queries
• Use advantages of no-sql
• Use event driven mechanisms, zB Event-Sourcing nutzen
• Scale in the cloud (Storage and CPU)

Artificial Intelligece
• Still in ist early days
• All services available in the cloud
• Huge impact on many today‘s manual processes to be expected

Summary

…well, basically «only» microservices…
We just wanted a modern architecture…
…ok. Perhaps also some BigData ând IoT,
Cause it’s so cool...
DevOps belongs to the Charta of Human Rights
for developers ;-)
We simply ignore any Legacy-Systems…

A modern Cloud Architecture
1. Scalable
2. Microservices and Container Based
3. Elastic amd Load Balanced
4. Decoupled by APIs
5. With DevOps and Continuous Deployment in Place
6. With a resilient and Failure Tolerant Design
7. Connected
8. Collecting Data
9. Monitored

DANKE
• Fallacies of Distributed Computing:
https://de.wikipedia.org/wiki/Fallacies_of_Distributed_Computing
• 21 DevOps und Docker Reference Architectures:
https://devops.com/21-devops-docker-reference-architectures/
• Cloud Native Computing Foundation:
https://www.cncf.io/
• Docker: http://docker.com
• Openshift: http://openshift.org
Anatole Tresch
Principal Consultant AD-ZH
anatole.tresch@trivadis.com
Twitter: @atsticks

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