SlideShare una empresa de Scribd logo
1 de 83
Descargar para leer sin conexión
Architecting for Scale
Microservices at Netflix-Uber-Spotify Scale
Pooyan	Jamshidi
Foundations	of	
Software	Engineering
Learning	Goals
• Understand	the	value	of	microservices for	building	complex	
applications	that	need	to	operate	at	higher	scale
• Identify	requirements	that	derive	companies	to	migrate	to	
microservices (contrast	of	requirements	between	companies)
• Understand	strategies	for	reliability of microservice architecture	
either	at	micro-level	using	design	patterns	or	at	a	larger	level
• Build	agile	team	structure	that	enable	large	scale	companies	to	move	
fast	(organizational	challenges)
• Understand	challenges	that	Netflix-Uber-Spotify	faced	in	realizing	
microservice based	applications
2
Disclaimer
• I	used	materials	from	
• Netflix	blog
• Spotify,	Uber	and	Netflix’s	architects	GOTO	talks
• And	some	other	sources	referenced	in	the	slides
• I’m	a	postdoc	in	Christian’s	group
• Software	Engineering	+	Machine	Learning
• I	worked	as	a	software	practitioners	for	7	years
• Pre-PhD
• 4	years	as	a	developer
• 3	years	as	an	architect
• Involved	in	migration	to	cloud	and	microservices
2 IEEE SOFTWARE | PUBLISHED BY THE IEEE COMPUTER SOCIETY 0740-7459/16/$33.00 © 2016 IEEE
Microservices
Architecture
Enables DevOps
Migration to a Cloud-Native
Architecture
Armin Balalaie and Abbas Heydarnoori, Sharif University of
Technology
Pooyan Jamshidi, Imperial College London
// This article reports on experiences and lessons learned
during incremental migration and architectural refactoring of
a commercial mobile back end as a service to microservices
architecture. It explains how the researchers adopted
DevOps and how this facilitated a smooth migration. //
A LOOK AT the searches related to
the term “microservices” on Google
Trends revealed that the top searches
are now technology driven. This im-
plies that the time of general search
terms such as “What is microser-
vices?” has now long passed. Not
only are software vendors (for ex-
ample, IBM and Microsoft) using
microservices and DevOps practices,
but also content providers (for exam-
ple, Netflix and the BBC) have ad-
opted and are using them.
In addition, Google Trends re-
veals that both DevOps and mi-
croservices are growing concepts,
with an equal rate of growth after
2014 (see Figure 1). Although Dev-
Ops can also be applied to mono-
lithic software systems, microservices
enable effective implementation of
DevOps by promoting the impor-
tance of small teams.1 (For more on
DevOps and Microservices, see the
related sidebar.)
A microservices architecture is a
cloud-native architecture that aims
to realize software systems as a
package of small services. Each ser-
vice is independently deployable on
a potentially different platform and
technological stack. It can run in
its own process while communicat-
ing through lightweight mechanisms
such as RESTful or RPC-based
APIs—for example, Finagle. (REST
stands for Representational State
Transfer.) In this setting, each ser-
vice is a business capability that can
utilize various programming lan-
guages and data stores and is devel-
oped by a small team.2
Migrating monolithic architec-
tures to microservices brings in
many benefits. In particular, it pro-
vides adaptability to technological
changes to avoid technology lock-in
and, more important, reduced time-
to-market and better development
team structuring around services.3
Here we explain our experiences
and lessons learned during incre-
mental migration of Backtory (www.
backtory.com), a commercial mo-
bile back end as a service (MBaaS),
to microservices in the context of
DevOps. Microservices help Back-
tory in various ways, especially in
shipping new features more fre-
quently and providing scalability for
the collective set of users from differ-
ent mobile-app developers.
Furthermore, we report on migra-
tion patterns we developed on the
basis of our observations in migra-
tion projects. Practitioners can use
these patterns to migrate monolithic
software systems to microservices. In
addition, system consultants can use
FOCUS: DEVOPS
What	is	the	most	interesting	aspect	that	
you	have	learned	from	the	Netflix	talk?
Tradeoff	in	software	architecture
• Everything	is	tradeoff
• Try	to	make	them	intentionally
Organ	Systems
Each	organ	has	a	purpose
Organs	form	systems
Systems	form	an	organism
ELB
and	so	is	taking	traffic
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
Largest	Internet	TV	network
86	million	members
~190	countries,	10s	of	languages
125m	hours	content	per	day
Microservices on	AWS
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
Netflix	DVD	Data	Center	- 2000
Linux	Host
Apache
Tomcat
Javaweb
STORE
Load	Balancer
BILLING
HTTP
JDBC
DB	Link
HTTP/S
Monolithic	code	base
Monolithic	database
Tightly	coupled	architecture
What	microservices are	not
What	microservices are	not
Enterprise Service Bus (ESB)
Privacy
Service (PS)
Service
Consumer
Service
Consumer
Service
Consumer
Service
Provider
Service
Provider
Service
Provider
Other
Services
Routing
Service Registry Transport
Replication
• Message Routing
• Message Monitoring
• Service Replication
• Language transforma
Edge
ELB
Zuul
NCCP
API
Middle	Tier	&	Platform
Product
• Bucket	testing
• Subscriber
• Recommendations
Platform
• Routing
• Configuration
• Crypto
Persistence
• Cache
• Database
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
Architectural	pattern	1:	API	Gateway	
12
Source:	Kasun Indrasiri,	Microservices in	Practice:	From	Architecture	to	Deployment
Architectural	pattern	2:	Inter-process	
Communication	in	a	Microservices Architecture	
13
Architectural	pattern	3:	Service	Discovery	in	a	
Microservices Architecture	
14
Architectural	pattern	4:	Event-Driven	Data	
Management	for	Microservices
15
There are two kinds of channels, point-to-point and publish-subscribe:
• A point-to-point channel delivers a message to exactly one of the consumers that are
reading from the channel. Services use point-to-point channels for the one-to-one
interaction styles described earlier
• A publish-subscribe channel delivers each message to all of the attached consumers.
Services use publish-subscribe channels for the one-to-many interaction styles
described above
Figure 3-4 shows how the taxi-hailing application might use publish-subscribe channels
Figure 3-4. Using publish-subscribe channels in a taxi-hailing application.
DISPATCHER
TRIP CREATED
DRIVER PROPOSED
TRIP
MANAGEMENT
PASSENGER
MANAGEMENT
DRIVER
MANAGEMENT
Chris	Richadson,	Microservices from	Design	to	Deployment
Architectural	pattern	5:	Decentralized	Data	
Management
Christian	Posta,	The	Hardest	Part	About	Microservices:	Your	Data
Architectural	pattern	6:	Choosing	a	
Microservices Deployment	Strategy	
17
Architectural	pattern	7:	Security
18
Source:	Kasun Indrasiri,	Microservices in	Practice:	From	Architecture	to	Deployment
What	architectural	patterns	you	can	
identify	within	these	architectures?
Edge
ELB
Zuul
NCCP
API
Middle	Tier	&	Platform
Product
• Bucket	testing
• Subscriber
• Recommendations
Platform
• Routing
• Configuration
• Crypto
Persistence
• Cache
• Database
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
Microservices at	Uber
21
Microservices
at	Spotify
22
Why	reliability	matters	in	
microservices world?
Linux	Host
Linux	Host
Linux	Host
Linux	Host
Intra-service	Requests
Linux	Host
Apache Tomcat
Linux	Host
Apache Tomcat
Network	latency,	congestion,	failure
Logical	or	scaling	failure
Service	A Service	B
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
Crossing	the	Chasm
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
Cascading	Failure
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
Vaccination
Device Service	B	
Service	C
Internet EdgeZuul
Service	A	
ELB
FITSynthetic	transactions
Override	by	device	or	account
%	of	live	traffic	up	to	100%
Fault	Injection	Testing	(FIT)
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
Device Service	B	
Service	C
Internet EdgeZuul
Service	A	
ELB
FIT
Fault	Injection	Testing	(FIT)
Enforced	throughout	the	call	path
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
ELB
API
API	
Gateway
App	1
App	2
App	4
App	5
App	6
App	3
App	7
App	8
99.99
99.99
99.99
99.99
99.99
99.99
99.99
99.99
Proxy
99.99 99.99
Combinatorial	Math
99.9910 =	99.9
Critical	Microservices
Persistence
In	the	presence	of	a	network	partition,	you	must	choose	
between	consistency	and	availability
CAP	Theorem
DB
DB
DB
Network	B
Network	C
Network	D
Service
Network	A
X
Zone	A
Zone	B
Zone	C
Zone	B
Zone	C
Clien
t
Zone	A
Local	Quorum
(Typical)
100ms
Eventual	Consistency
Infrastructure
December	24th,	2012
US-East-1
Canada
No	place	to	go
US
Latin	America
US-East-1US-West-2 EU-West-1
Regional	failover
x x
Regional fail-over
Ruslan Meshenberg,	Microservices at	Netflix	Scale:	Principles,	Tradeoffs	&	Lessons	Learned
Regional	failover
Regional fail-over
Ruslan Meshenberg,	Microservices at	Netflix	Scale:	Principles,	Tradeoffs	&	Lessons	Learned
What	is	a	stateless	service?
What	is	a	stateless	service?
• Not	a	cache	or	a	database
• Frequently	accessed	metadata
• No	instance	affinity
• Loss	a	node	is	a	non-event
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
Minimum	size
Desired	capacity
Maximum	size
Scale	out	as	needed
S3AMI	retrieved	on	demand
Compute	efficiency
Node	failure
Traffic	spikes
Performance	bugs
Auto	Scaling	Groups
Cluster	A Cluster	D
Edge	Cluster
Cluster	B
Cluster	C
Surviving Instance Failure
Source:	Josh	Evans,	Mastering	Chaos	- A	Netflix	Guide	to	Microservices
What	is	a	stateful service?
What	is	a	stateless	service?
• Databases	and	caches
• Custom	apps	which	hold	data
• Loss	of	a	node	is	a	notable	event
Dedicated	Shards	– An	Antipattern
Squid	1 Squid	2 Squid	3
Client	Application
Subscriber	Client	Library
Cache	Client Service	Client
S S S S.	.	.
DB DB DB DB.	.	.
Squid	n
HA	Proxy
Set	1 Set	2 Set	3 Set	n
X
Redundancy	is	fundamental
Zone	A Zone	B Zone	C
.	.	..	.	..	.	.
EVCache Writes
Client	Application
Client	Library
EVCache	Client
Client	Application
Client	Library
EVCache	Client
Client	Application
Client	Library
EVCache	Client
.	.	.
Zone	A Zone	B Zone	C
Client	Application
Client	Library
EVCache	Client
.	.	..	.	..	.	.
EVCache Reads
Client	Application
Client	Library
EVCache	Client
Client	Application
Client	Library
EVCache	Client
.	.	.
Why	automation,	in	all	software	
dev/ops	stages,	is	important?
Autonomic	Nervous
System
You	don’t	have	to	think	about	
digestion	or	breathing
Priorities
Our Priorities
1. Innovation
3. Efficiency
2. Reliability
Ruslan Meshenberg,	Microservices at	Netflix	Scale:	Principles,	Tradeoffs	&	Lessons	Learned
Innovation:	tight	coupling	doesn’t	work
Monolithic	vs	Microservice-based	
Applications
59
Lee	Atchison,	Architecting	for	Scale:	High	Availability	for	Your	Growing	Applications
End	to	end	ownership
60
End-end ownership + velocity
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Architect
Design
Develop
ReviewTest
Deploy
Run
Support
Ruslan Meshenberg,	Microservices at	Netflix	Scale:	Principles,	Tradeoffs	&	Lessons	Learned
Kevin	Goldsmith,	Microservices @	Spotify
Server
Core Library
Platform Platform Platform Platform
Infrastructure
Kevin	Goldsmith,	Microservices @	Spotify
Challenges
Synchronization
Client UX implementation
Core Library Implementation
depends on
depends on
depends onServer Implementation
Infrastructure Implementation
Kevin	Goldsmith,	Microservices @	Spotify
Kevin	Goldsmith,	Microservices @	Spotify
Full-stack autonomous
teams
Requires you to structure your
application in loosely coupled parts
Architecture	evolution	of	Spotify
67
Kevin	Goldsmith,	Microservices @	Spotify
Architecture	evolution	of	Spotify
68
69
70
71
LoadBallancer
72
Microservices:	Yay!
• Easier	to	Scale
• Easier	to	test
• Easier	to	deploy
• Easier	to	monitor	
• They	can	versioned	independently
Microservices:	Boo!
• Monitoring	lots	of	services
• Documentations	
• Increased	latency
75
What does this look like at Spotify?
‣ 810activeservices
‣ ~10Systemspersquad
‣ ~1.7Systemsperpersonwithaccessto
productionservers
‣ ~1.15Systemspermemberof
Technology
Microservices
at	Spotify
76
As of April 2016:
Uber Cities Worldwide: 400+
Countries: 70
Employees: 6,000+
Uber
Matt	Ranney,	What	I	Wish	I	Had	Known	Before	Scaling	Uber	to	1000	Services
Microservices at	Uber
79
Matt	Ranney,	What	I	Wish	I	Had	Known	Before	Scaling	Uber	to	1000	Services
pre-history PHP (outsourced)
Dispatch Node.JS, moving Go
Core Services Python, moving to Go
Maps Python and Java
Data Python and Java
Metrics Go
Matt	Ranney,	What	I	Wish	I	Had	Known	Before	Scaling	Uber	to	1000	Services
LANGUAGES
Hard to share code
Hard to move between teams
WIWIK: Fragments the culture
Matt	Ranney,	What	I	Wish	I	Had	Known	Before	Scaling	Uber	to	1000	Services
Matt	Ranney,	What	I	Wish	I	Had	Known	Before	Scaling	Uber	to	1000	Services
Matt	Ranney,	What	I	Wish	I	Had	Known	Before	Scaling	Uber	to	1000	Services
Summary
• Microservices may	be	a	right	solution	for	building	complex	
applications	that	need	to	operate	at	higher	scale
• Tradeoffs	that	companies	made	to	migrate	to	microservices (contrast	
of	requirements	between	companies)
• Making	reliable	microservice architecture	requires	strategies	to	deal	
with	failure	either	at	micro-level	or	at	a	larger	level
• Microservices architecture	help	to	build	agile	team	structure	that	
enable	large	scale	companies	to	move	fast	(organizational	challenges)

Más contenido relacionado

La actualidad más candente

Sizing Your MongoDB Cluster
Sizing Your MongoDB ClusterSizing Your MongoDB Cluster
Sizing Your MongoDB ClusterMongoDB
 
Apache Iceberg - A Table Format for Hige Analytic Datasets
Apache Iceberg - A Table Format for Hige Analytic DatasetsApache Iceberg - A Table Format for Hige Analytic Datasets
Apache Iceberg - A Table Format for Hige Analytic DatasetsAlluxio, Inc.
 
Apache Kafka® Use Cases for Financial Services
Apache Kafka® Use Cases for Financial ServicesApache Kafka® Use Cases for Financial Services
Apache Kafka® Use Cases for Financial Servicesconfluent
 
Running Apache Spark on Kubernetes: Best Practices and Pitfalls
Running Apache Spark on Kubernetes: Best Practices and PitfallsRunning Apache Spark on Kubernetes: Best Practices and Pitfalls
Running Apache Spark on Kubernetes: Best Practices and PitfallsDatabricks
 
Delta from a Data Engineer's Perspective
Delta from a Data Engineer's PerspectiveDelta from a Data Engineer's Perspective
Delta from a Data Engineer's PerspectiveDatabricks
 
Migrating Airflow-based Apache Spark Jobs to Kubernetes – the Native Way
Migrating Airflow-based Apache Spark Jobs to Kubernetes – the Native WayMigrating Airflow-based Apache Spark Jobs to Kubernetes – the Native Way
Migrating Airflow-based Apache Spark Jobs to Kubernetes – the Native WayDatabricks
 
Concord: Simple & Flexible Stream Processing on Apache Mesos: Data By The Bay...
Concord: Simple & Flexible Stream Processing on Apache Mesos: Data By The Bay...Concord: Simple & Flexible Stream Processing on Apache Mesos: Data By The Bay...
Concord: Simple & Flexible Stream Processing on Apache Mesos: Data By The Bay...Concord
 
Kappa vs Lambda Architectures and Technology Comparison
Kappa vs Lambda Architectures and Technology ComparisonKappa vs Lambda Architectures and Technology Comparison
Kappa vs Lambda Architectures and Technology ComparisonKai Wähner
 
The Top Five Mistakes Made When Writing Streaming Applications with Mark Grov...
The Top Five Mistakes Made When Writing Streaming Applications with Mark Grov...The Top Five Mistakes Made When Writing Streaming Applications with Mark Grov...
The Top Five Mistakes Made When Writing Streaming Applications with Mark Grov...Databricks
 
Building Pinterest Real-Time Ads Platform Using Kafka Streams
Building Pinterest Real-Time Ads Platform Using Kafka Streams Building Pinterest Real-Time Ads Platform Using Kafka Streams
Building Pinterest Real-Time Ads Platform Using Kafka Streams confluent
 
Microservices Docker Kubernetes Istio Kanban DevOps SRE
Microservices Docker Kubernetes Istio Kanban DevOps SREMicroservices Docker Kubernetes Istio Kanban DevOps SRE
Microservices Docker Kubernetes Istio Kanban DevOps SREAraf Karsh Hamid
 
Microservices Part 3 Service Mesh and Kafka
Microservices Part 3 Service Mesh and KafkaMicroservices Part 3 Service Mesh and Kafka
Microservices Part 3 Service Mesh and KafkaAraf Karsh Hamid
 
Amazon Redshift: Performance Tuning and Optimization
Amazon Redshift: Performance Tuning and OptimizationAmazon Redshift: Performance Tuning and Optimization
Amazon Redshift: Performance Tuning and OptimizationAmazon Web Services
 
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...confluent
 
Redis + Apache Spark = Swiss Army Knife Meets Kitchen Sink
Redis + Apache Spark = Swiss Army Knife Meets Kitchen SinkRedis + Apache Spark = Swiss Army Knife Meets Kitchen Sink
Redis + Apache Spark = Swiss Army Knife Meets Kitchen SinkDatabricks
 
Kafka 101 and Developer Best Practices
Kafka 101 and Developer Best PracticesKafka 101 and Developer Best Practices
Kafka 101 and Developer Best Practicesconfluent
 

La actualidad más candente (20)

Sizing Your MongoDB Cluster
Sizing Your MongoDB ClusterSizing Your MongoDB Cluster
Sizing Your MongoDB Cluster
 
Apache Iceberg - A Table Format for Hige Analytic Datasets
Apache Iceberg - A Table Format for Hige Analytic DatasetsApache Iceberg - A Table Format for Hige Analytic Datasets
Apache Iceberg - A Table Format for Hige Analytic Datasets
 
kafka
kafkakafka
kafka
 
Apache Kafka® Use Cases for Financial Services
Apache Kafka® Use Cases for Financial ServicesApache Kafka® Use Cases for Financial Services
Apache Kafka® Use Cases for Financial Services
 
Running Apache Spark on Kubernetes: Best Practices and Pitfalls
Running Apache Spark on Kubernetes: Best Practices and PitfallsRunning Apache Spark on Kubernetes: Best Practices and Pitfalls
Running Apache Spark on Kubernetes: Best Practices and Pitfalls
 
AWS_Meetup_BLR_July_22_Social.pdf
AWS_Meetup_BLR_July_22_Social.pdfAWS_Meetup_BLR_July_22_Social.pdf
AWS_Meetup_BLR_July_22_Social.pdf
 
The delta architecture
The delta architectureThe delta architecture
The delta architecture
 
Delta from a Data Engineer's Perspective
Delta from a Data Engineer's PerspectiveDelta from a Data Engineer's Perspective
Delta from a Data Engineer's Perspective
 
Migrating Airflow-based Apache Spark Jobs to Kubernetes – the Native Way
Migrating Airflow-based Apache Spark Jobs to Kubernetes – the Native WayMigrating Airflow-based Apache Spark Jobs to Kubernetes – the Native Way
Migrating Airflow-based Apache Spark Jobs to Kubernetes – the Native Way
 
Concord: Simple & Flexible Stream Processing on Apache Mesos: Data By The Bay...
Concord: Simple & Flexible Stream Processing on Apache Mesos: Data By The Bay...Concord: Simple & Flexible Stream Processing on Apache Mesos: Data By The Bay...
Concord: Simple & Flexible Stream Processing on Apache Mesos: Data By The Bay...
 
Kappa vs Lambda Architectures and Technology Comparison
Kappa vs Lambda Architectures and Technology ComparisonKappa vs Lambda Architectures and Technology Comparison
Kappa vs Lambda Architectures and Technology Comparison
 
The Top Five Mistakes Made When Writing Streaming Applications with Mark Grov...
The Top Five Mistakes Made When Writing Streaming Applications with Mark Grov...The Top Five Mistakes Made When Writing Streaming Applications with Mark Grov...
The Top Five Mistakes Made When Writing Streaming Applications with Mark Grov...
 
Building Pinterest Real-Time Ads Platform Using Kafka Streams
Building Pinterest Real-Time Ads Platform Using Kafka Streams Building Pinterest Real-Time Ads Platform Using Kafka Streams
Building Pinterest Real-Time Ads Platform Using Kafka Streams
 
Microservices Docker Kubernetes Istio Kanban DevOps SRE
Microservices Docker Kubernetes Istio Kanban DevOps SREMicroservices Docker Kubernetes Istio Kanban DevOps SRE
Microservices Docker Kubernetes Istio Kanban DevOps SRE
 
Microservices Part 3 Service Mesh and Kafka
Microservices Part 3 Service Mesh and KafkaMicroservices Part 3 Service Mesh and Kafka
Microservices Part 3 Service Mesh and Kafka
 
Amazon Redshift: Performance Tuning and Optimization
Amazon Redshift: Performance Tuning and OptimizationAmazon Redshift: Performance Tuning and Optimization
Amazon Redshift: Performance Tuning and Optimization
 
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...
Performance Tuning RocksDB for Kafka Streams' State Stores (Dhruba Borthakur,...
 
Apache Kafka
Apache KafkaApache Kafka
Apache Kafka
 
Redis + Apache Spark = Swiss Army Knife Meets Kitchen Sink
Redis + Apache Spark = Swiss Army Knife Meets Kitchen SinkRedis + Apache Spark = Swiss Army Knife Meets Kitchen Sink
Redis + Apache Spark = Swiss Army Knife Meets Kitchen Sink
 
Kafka 101 and Developer Best Practices
Kafka 101 and Developer Best PracticesKafka 101 and Developer Best Practices
Kafka 101 and Developer Best Practices
 

Similar a Architecting for Scale

Microservice Pattern Launguage
Microservice Pattern LaunguageMicroservice Pattern Launguage
Microservice Pattern LaunguageInho Kang
 
Business and IT agility through DevOps and microservice architecture powered ...
Business and IT agility through DevOps and microservice architecture powered ...Business and IT agility through DevOps and microservice architecture powered ...
Business and IT agility through DevOps and microservice architecture powered ...Lucas Jellema
 
The Reality of Managing Microservices in Your CD Pipeline
The Reality of Managing Microservices in Your CD PipelineThe Reality of Managing Microservices in Your CD Pipeline
The Reality of Managing Microservices in Your CD PipelineDevOps.com
 
Application Centric Microservices from Redhat Summit 2015
Application Centric Microservices from Redhat Summit 2015Application Centric Microservices from Redhat Summit 2015
Application Centric Microservices from Redhat Summit 2015Ken Owens
 
Microservices Architecture, Monolith Migration Patterns
Microservices Architecture, Monolith Migration PatternsMicroservices Architecture, Monolith Migration Patterns
Microservices Architecture, Monolith Migration PatternsAraf Karsh Hamid
 
Automating Applications with Habitat - Sydney Cloud Native Meetup
Automating Applications with Habitat - Sydney Cloud Native MeetupAutomating Applications with Habitat - Sydney Cloud Native Meetup
Automating Applications with Habitat - Sydney Cloud Native MeetupMatt Ray
 
Do You Need A Service Mesh?
Do You Need A Service Mesh?Do You Need A Service Mesh?
Do You Need A Service Mesh?NGINX, Inc.
 
Designing Microservices
Designing MicroservicesDesigning Microservices
Designing MicroservicesDavid Chou
 
CNCF Introduction - Feb 2018
CNCF Introduction - Feb 2018CNCF Introduction - Feb 2018
CNCF Introduction - Feb 2018Krishna-Kumar
 
The elegant way of implementing microservices with istio
The elegant way of implementing microservices with istioThe elegant way of implementing microservices with istio
The elegant way of implementing microservices with istioInho Kang
 
12월 16일 Meetup [Deep Dive] Microservice 트래픽 관리를 위한 Istio 알아보기 | 강인호 컨설턴트, 오라클
12월 16일 Meetup [Deep Dive] Microservice 트래픽 관리를 위한 Istio 알아보기 | 강인호 컨설턴트, 오라클12월 16일 Meetup [Deep Dive] Microservice 트래픽 관리를 위한 Istio 알아보기 | 강인호 컨설턴트, 오라클
12월 16일 Meetup [Deep Dive] Microservice 트래픽 관리를 위한 Istio 알아보기 | 강인호 컨설턴트, 오라클Oracle Korea
 
Microservices and docker
Microservices and dockerMicroservices and docker
Microservices and dockerAlex Ivy
 
Microservice architecture
Microservice architectureMicroservice architecture
Microservice architectureTouraj Ebrahimi
 
Containing your microservice sprawl
Containing your microservice sprawlContaining your microservice sprawl
Containing your microservice sprawlLibbySchulze
 
DevOps and Microservice
DevOps and MicroserviceDevOps and Microservice
DevOps and MicroserviceInho Kang
 
Reference architectures shows a microservices deployed to Kubernetes
Reference architectures shows a microservices deployed to KubernetesReference architectures shows a microservices deployed to Kubernetes
Reference architectures shows a microservices deployed to KubernetesRakesh Gujjarlapudi
 
A Guide on What Are Microservices: Pros, Cons, Use Cases, and More
A Guide on What Are Microservices: Pros, Cons, Use Cases, and MoreA Guide on What Are Microservices: Pros, Cons, Use Cases, and More
A Guide on What Are Microservices: Pros, Cons, Use Cases, and MoreSimform
 
Do I Need A Service Mesh.pptx
Do I Need A Service Mesh.pptxDo I Need A Service Mesh.pptx
Do I Need A Service Mesh.pptxPINGXIONG3
 

Similar a Architecting for Scale (20)

Microservice Pattern Launguage
Microservice Pattern LaunguageMicroservice Pattern Launguage
Microservice Pattern Launguage
 
Business and IT agility through DevOps and microservice architecture powered ...
Business and IT agility through DevOps and microservice architecture powered ...Business and IT agility through DevOps and microservice architecture powered ...
Business and IT agility through DevOps and microservice architecture powered ...
 
The Reality of Managing Microservices in Your CD Pipeline
The Reality of Managing Microservices in Your CD PipelineThe Reality of Managing Microservices in Your CD Pipeline
The Reality of Managing Microservices in Your CD Pipeline
 
Application Centric Microservices from Redhat Summit 2015
Application Centric Microservices from Redhat Summit 2015Application Centric Microservices from Redhat Summit 2015
Application Centric Microservices from Redhat Summit 2015
 
Microservices Architecture, Monolith Migration Patterns
Microservices Architecture, Monolith Migration PatternsMicroservices Architecture, Monolith Migration Patterns
Microservices Architecture, Monolith Migration Patterns
 
Automating Applications with Habitat - Sydney Cloud Native Meetup
Automating Applications with Habitat - Sydney Cloud Native MeetupAutomating Applications with Habitat - Sydney Cloud Native Meetup
Automating Applications with Habitat - Sydney Cloud Native Meetup
 
Do You Need A Service Mesh?
Do You Need A Service Mesh?Do You Need A Service Mesh?
Do You Need A Service Mesh?
 
Designing Microservices
Designing MicroservicesDesigning Microservices
Designing Microservices
 
CNCF Introduction - Feb 2018
CNCF Introduction - Feb 2018CNCF Introduction - Feb 2018
CNCF Introduction - Feb 2018
 
The elegant way of implementing microservices with istio
The elegant way of implementing microservices with istioThe elegant way of implementing microservices with istio
The elegant way of implementing microservices with istio
 
12월 16일 Meetup [Deep Dive] Microservice 트래픽 관리를 위한 Istio 알아보기 | 강인호 컨설턴트, 오라클
12월 16일 Meetup [Deep Dive] Microservice 트래픽 관리를 위한 Istio 알아보기 | 강인호 컨설턴트, 오라클12월 16일 Meetup [Deep Dive] Microservice 트래픽 관리를 위한 Istio 알아보기 | 강인호 컨설턴트, 오라클
12월 16일 Meetup [Deep Dive] Microservice 트래픽 관리를 위한 Istio 알아보기 | 강인호 컨설턴트, 오라클
 
Microservices and docker
Microservices and dockerMicroservices and docker
Microservices and docker
 
Microservice architecture
Microservice architectureMicroservice architecture
Microservice architecture
 
Containing your microservice sprawl
Containing your microservice sprawlContaining your microservice sprawl
Containing your microservice sprawl
 
DevOps and Microservice
DevOps and MicroserviceDevOps and Microservice
DevOps and Microservice
 
Why Microservice
Why Microservice Why Microservice
Why Microservice
 
Reference architectures shows a microservices deployed to Kubernetes
Reference architectures shows a microservices deployed to KubernetesReference architectures shows a microservices deployed to Kubernetes
Reference architectures shows a microservices deployed to Kubernetes
 
A Guide on What Are Microservices: Pros, Cons, Use Cases, and More
A Guide on What Are Microservices: Pros, Cons, Use Cases, and MoreA Guide on What Are Microservices: Pros, Cons, Use Cases, and More
A Guide on What Are Microservices: Pros, Cons, Use Cases, and More
 
Do I Need A Service Mesh.pptx
Do I Need A Service Mesh.pptxDo I Need A Service Mesh.pptx
Do I Need A Service Mesh.pptx
 
Whitepaper : Microservices In or Out
Whitepaper : Microservices   In or OutWhitepaper : Microservices   In or Out
Whitepaper : Microservices In or Out
 

Más de Pooyan Jamshidi

Learning LWF Chain Graphs: A Markov Blanket Discovery Approach
Learning LWF Chain Graphs: A Markov Blanket Discovery ApproachLearning LWF Chain Graphs: A Markov Blanket Discovery Approach
Learning LWF Chain Graphs: A Markov Blanket Discovery ApproachPooyan Jamshidi
 
A Framework for Robust Control of Uncertainty in Self-Adaptive Software Conn...
 A Framework for Robust Control of Uncertainty in Self-Adaptive Software Conn... A Framework for Robust Control of Uncertainty in Self-Adaptive Software Conn...
A Framework for Robust Control of Uncertainty in Self-Adaptive Software Conn...Pooyan Jamshidi
 
Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Aut...
Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Aut...Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Aut...
Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Aut...Pooyan Jamshidi
 
Ensembles of Many Diverse Weak Defenses can be Strong: Defending Deep Neural ...
Ensembles of Many Diverse Weak Defenses can be Strong: Defending Deep Neural ...Ensembles of Many Diverse Weak Defenses can be Strong: Defending Deep Neural ...
Ensembles of Many Diverse Weak Defenses can be Strong: Defending Deep Neural ...Pooyan Jamshidi
 
Transfer Learning for Performance Analysis of Machine Learning Systems
Transfer Learning for Performance Analysis of Machine Learning SystemsTransfer Learning for Performance Analysis of Machine Learning Systems
Transfer Learning for Performance Analysis of Machine Learning SystemsPooyan Jamshidi
 
Transfer Learning for Performance Analysis of Configurable Systems: A Causal ...
Transfer Learning for Performance Analysis of Configurable Systems:A Causal ...Transfer Learning for Performance Analysis of Configurable Systems:A Causal ...
Transfer Learning for Performance Analysis of Configurable Systems: A Causal ...Pooyan Jamshidi
 
Machine Learning meets DevOps
Machine Learning meets DevOpsMachine Learning meets DevOps
Machine Learning meets DevOpsPooyan Jamshidi
 
Integrated Model Discovery and Self-Adaptation of Robots
Integrated Model Discovery and Self-Adaptation of RobotsIntegrated Model Discovery and Self-Adaptation of Robots
Integrated Model Discovery and Self-Adaptation of RobotsPooyan Jamshidi
 
Transfer Learning for Performance Analysis of Highly-Configurable Software
Transfer Learning for Performance Analysis of Highly-Configurable SoftwareTransfer Learning for Performance Analysis of Highly-Configurable Software
Transfer Learning for Performance Analysis of Highly-Configurable SoftwarePooyan Jamshidi
 
Architectural Tradeoff in Learning-Based Software
Architectural Tradeoff in Learning-Based SoftwareArchitectural Tradeoff in Learning-Based Software
Architectural Tradeoff in Learning-Based SoftwarePooyan Jamshidi
 
Production-Ready Machine Learning for the Software Architect
Production-Ready Machine Learning for the Software ArchitectProduction-Ready Machine Learning for the Software Architect
Production-Ready Machine Learning for the Software ArchitectPooyan Jamshidi
 
Transfer Learning for Software Performance Analysis: An Exploratory Analysis
Transfer Learning for Software Performance Analysis: An Exploratory AnalysisTransfer Learning for Software Performance Analysis: An Exploratory Analysis
Transfer Learning for Software Performance Analysis: An Exploratory AnalysisPooyan Jamshidi
 
Learning Software Performance Models for Dynamic and Uncertain Environments
Learning Software Performance Models for Dynamic and Uncertain EnvironmentsLearning Software Performance Models for Dynamic and Uncertain Environments
Learning Software Performance Models for Dynamic and Uncertain EnvironmentsPooyan Jamshidi
 
Sensitivity Analysis for Building Adaptive Robotic Software
Sensitivity Analysis for Building Adaptive Robotic SoftwareSensitivity Analysis for Building Adaptive Robotic Software
Sensitivity Analysis for Building Adaptive Robotic SoftwarePooyan Jamshidi
 
Transfer Learning for Improving Model Predictions in Highly Configurable Soft...
Transfer Learning for Improving Model Predictions in Highly Configurable Soft...Transfer Learning for Improving Model Predictions in Highly Configurable Soft...
Transfer Learning for Improving Model Predictions in Highly Configurable Soft...Pooyan Jamshidi
 
Transfer Learning for Improving Model Predictions in Robotic Systems
Transfer Learning for Improving Model Predictions  in Robotic SystemsTransfer Learning for Improving Model Predictions  in Robotic Systems
Transfer Learning for Improving Model Predictions in Robotic SystemsPooyan Jamshidi
 
Machine Learning meets DevOps
Machine Learning meets DevOpsMachine Learning meets DevOps
Machine Learning meets DevOpsPooyan Jamshidi
 
An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing S...
An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing S...An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing S...
An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing S...Pooyan Jamshidi
 
Configuration Optimization Tool
Configuration Optimization ToolConfiguration Optimization Tool
Configuration Optimization ToolPooyan Jamshidi
 

Más de Pooyan Jamshidi (20)

Learning LWF Chain Graphs: A Markov Blanket Discovery Approach
Learning LWF Chain Graphs: A Markov Blanket Discovery ApproachLearning LWF Chain Graphs: A Markov Blanket Discovery Approach
Learning LWF Chain Graphs: A Markov Blanket Discovery Approach
 
A Framework for Robust Control of Uncertainty in Self-Adaptive Software Conn...
 A Framework for Robust Control of Uncertainty in Self-Adaptive Software Conn... A Framework for Robust Control of Uncertainty in Self-Adaptive Software Conn...
A Framework for Robust Control of Uncertainty in Self-Adaptive Software Conn...
 
Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Aut...
Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Aut...Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Aut...
Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Aut...
 
Ensembles of Many Diverse Weak Defenses can be Strong: Defending Deep Neural ...
Ensembles of Many Diverse Weak Defenses can be Strong: Defending Deep Neural ...Ensembles of Many Diverse Weak Defenses can be Strong: Defending Deep Neural ...
Ensembles of Many Diverse Weak Defenses can be Strong: Defending Deep Neural ...
 
Transfer Learning for Performance Analysis of Machine Learning Systems
Transfer Learning for Performance Analysis of Machine Learning SystemsTransfer Learning for Performance Analysis of Machine Learning Systems
Transfer Learning for Performance Analysis of Machine Learning Systems
 
Transfer Learning for Performance Analysis of Configurable Systems: A Causal ...
Transfer Learning for Performance Analysis of Configurable Systems:A Causal ...Transfer Learning for Performance Analysis of Configurable Systems:A Causal ...
Transfer Learning for Performance Analysis of Configurable Systems: A Causal ...
 
Machine Learning meets DevOps
Machine Learning meets DevOpsMachine Learning meets DevOps
Machine Learning meets DevOps
 
Learning to Sample
Learning to SampleLearning to Sample
Learning to Sample
 
Integrated Model Discovery and Self-Adaptation of Robots
Integrated Model Discovery and Self-Adaptation of RobotsIntegrated Model Discovery and Self-Adaptation of Robots
Integrated Model Discovery and Self-Adaptation of Robots
 
Transfer Learning for Performance Analysis of Highly-Configurable Software
Transfer Learning for Performance Analysis of Highly-Configurable SoftwareTransfer Learning for Performance Analysis of Highly-Configurable Software
Transfer Learning for Performance Analysis of Highly-Configurable Software
 
Architectural Tradeoff in Learning-Based Software
Architectural Tradeoff in Learning-Based SoftwareArchitectural Tradeoff in Learning-Based Software
Architectural Tradeoff in Learning-Based Software
 
Production-Ready Machine Learning for the Software Architect
Production-Ready Machine Learning for the Software ArchitectProduction-Ready Machine Learning for the Software Architect
Production-Ready Machine Learning for the Software Architect
 
Transfer Learning for Software Performance Analysis: An Exploratory Analysis
Transfer Learning for Software Performance Analysis: An Exploratory AnalysisTransfer Learning for Software Performance Analysis: An Exploratory Analysis
Transfer Learning for Software Performance Analysis: An Exploratory Analysis
 
Learning Software Performance Models for Dynamic and Uncertain Environments
Learning Software Performance Models for Dynamic and Uncertain EnvironmentsLearning Software Performance Models for Dynamic and Uncertain Environments
Learning Software Performance Models for Dynamic and Uncertain Environments
 
Sensitivity Analysis for Building Adaptive Robotic Software
Sensitivity Analysis for Building Adaptive Robotic SoftwareSensitivity Analysis for Building Adaptive Robotic Software
Sensitivity Analysis for Building Adaptive Robotic Software
 
Transfer Learning for Improving Model Predictions in Highly Configurable Soft...
Transfer Learning for Improving Model Predictions in Highly Configurable Soft...Transfer Learning for Improving Model Predictions in Highly Configurable Soft...
Transfer Learning for Improving Model Predictions in Highly Configurable Soft...
 
Transfer Learning for Improving Model Predictions in Robotic Systems
Transfer Learning for Improving Model Predictions  in Robotic SystemsTransfer Learning for Improving Model Predictions  in Robotic Systems
Transfer Learning for Improving Model Predictions in Robotic Systems
 
Machine Learning meets DevOps
Machine Learning meets DevOpsMachine Learning meets DevOps
Machine Learning meets DevOps
 
An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing S...
An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing S...An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing S...
An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing S...
 
Configuration Optimization Tool
Configuration Optimization ToolConfiguration Optimization Tool
Configuration Optimization Tool
 

Último

%in Bahrain+277-882-255-28 abortion pills for sale in Bahrain
%in Bahrain+277-882-255-28 abortion pills for sale in Bahrain%in Bahrain+277-882-255-28 abortion pills for sale in Bahrain
%in Bahrain+277-882-255-28 abortion pills for sale in Bahrainmasabamasaba
 
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Steffen Staab
 
%in kaalfontein+277-882-255-28 abortion pills for sale in kaalfontein
%in kaalfontein+277-882-255-28 abortion pills for sale in kaalfontein%in kaalfontein+277-882-255-28 abortion pills for sale in kaalfontein
%in kaalfontein+277-882-255-28 abortion pills for sale in kaalfonteinmasabamasaba
 
%+27788225528 love spells in new york Psychic Readings, Attraction spells,Bri...
%+27788225528 love spells in new york Psychic Readings, Attraction spells,Bri...%+27788225528 love spells in new york Psychic Readings, Attraction spells,Bri...
%+27788225528 love spells in new york Psychic Readings, Attraction spells,Bri...masabamasaba
 
OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...
OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...
OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...Shane Coughlan
 
%in Stilfontein+277-882-255-28 abortion pills for sale in Stilfontein
%in Stilfontein+277-882-255-28 abortion pills for sale in Stilfontein%in Stilfontein+277-882-255-28 abortion pills for sale in Stilfontein
%in Stilfontein+277-882-255-28 abortion pills for sale in Stilfonteinmasabamasaba
 
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...harshavardhanraghave
 
%+27788225528 love spells in Vancouver Psychic Readings, Attraction spells,Br...
%+27788225528 love spells in Vancouver Psychic Readings, Attraction spells,Br...%+27788225528 love spells in Vancouver Psychic Readings, Attraction spells,Br...
%+27788225528 love spells in Vancouver Psychic Readings, Attraction spells,Br...masabamasaba
 
Unlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language ModelsUnlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language Modelsaagamshah0812
 
Software Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsSoftware Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsArshad QA
 
introduction-to-automotive Andoid os-csimmonds-ndctechtown-2021.pdf
introduction-to-automotive Andoid os-csimmonds-ndctechtown-2021.pdfintroduction-to-automotive Andoid os-csimmonds-ndctechtown-2021.pdf
introduction-to-automotive Andoid os-csimmonds-ndctechtown-2021.pdfVishalKumarJha10
 
%+27788225528 love spells in Boston Psychic Readings, Attraction spells,Bring...
%+27788225528 love spells in Boston Psychic Readings, Attraction spells,Bring...%+27788225528 love spells in Boston Psychic Readings, Attraction spells,Bring...
%+27788225528 love spells in Boston Psychic Readings, Attraction spells,Bring...masabamasaba
 
Announcing Codolex 2.0 from GDK Software
Announcing Codolex 2.0 from GDK SoftwareAnnouncing Codolex 2.0 from GDK Software
Announcing Codolex 2.0 from GDK SoftwareJim McKeeth
 
Right Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsRight Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsJhone kinadey
 
Exploring the Best Video Editing App.pdf
Exploring the Best Video Editing App.pdfExploring the Best Video Editing App.pdf
Exploring the Best Video Editing App.pdfproinshot.com
 
%in Hazyview+277-882-255-28 abortion pills for sale in Hazyview
%in Hazyview+277-882-255-28 abortion pills for sale in Hazyview%in Hazyview+277-882-255-28 abortion pills for sale in Hazyview
%in Hazyview+277-882-255-28 abortion pills for sale in Hazyviewmasabamasaba
 
%in kempton park+277-882-255-28 abortion pills for sale in kempton park
%in kempton park+277-882-255-28 abortion pills for sale in kempton park %in kempton park+277-882-255-28 abortion pills for sale in kempton park
%in kempton park+277-882-255-28 abortion pills for sale in kempton park masabamasaba
 
The title is not connected to what is inside
The title is not connected to what is insideThe title is not connected to what is inside
The title is not connected to what is insideshinachiaurasa2
 
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfThe Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfkalichargn70th171
 

Último (20)

%in Bahrain+277-882-255-28 abortion pills for sale in Bahrain
%in Bahrain+277-882-255-28 abortion pills for sale in Bahrain%in Bahrain+277-882-255-28 abortion pills for sale in Bahrain
%in Bahrain+277-882-255-28 abortion pills for sale in Bahrain
 
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
 
%in kaalfontein+277-882-255-28 abortion pills for sale in kaalfontein
%in kaalfontein+277-882-255-28 abortion pills for sale in kaalfontein%in kaalfontein+277-882-255-28 abortion pills for sale in kaalfontein
%in kaalfontein+277-882-255-28 abortion pills for sale in kaalfontein
 
%+27788225528 love spells in new york Psychic Readings, Attraction spells,Bri...
%+27788225528 love spells in new york Psychic Readings, Attraction spells,Bri...%+27788225528 love spells in new york Psychic Readings, Attraction spells,Bri...
%+27788225528 love spells in new york Psychic Readings, Attraction spells,Bri...
 
OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...
OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...
OpenChain - The Ramifications of ISO/IEC 5230 and ISO/IEC 18974 for Legal Pro...
 
%in Stilfontein+277-882-255-28 abortion pills for sale in Stilfontein
%in Stilfontein+277-882-255-28 abortion pills for sale in Stilfontein%in Stilfontein+277-882-255-28 abortion pills for sale in Stilfontein
%in Stilfontein+277-882-255-28 abortion pills for sale in Stilfontein
 
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
 
%+27788225528 love spells in Vancouver Psychic Readings, Attraction spells,Br...
%+27788225528 love spells in Vancouver Psychic Readings, Attraction spells,Br...%+27788225528 love spells in Vancouver Psychic Readings, Attraction spells,Br...
%+27788225528 love spells in Vancouver Psychic Readings, Attraction spells,Br...
 
Unlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language ModelsUnlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language Models
 
Microsoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdfMicrosoft AI Transformation Partner Playbook.pdf
Microsoft AI Transformation Partner Playbook.pdf
 
Software Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsSoftware Quality Assurance Interview Questions
Software Quality Assurance Interview Questions
 
introduction-to-automotive Andoid os-csimmonds-ndctechtown-2021.pdf
introduction-to-automotive Andoid os-csimmonds-ndctechtown-2021.pdfintroduction-to-automotive Andoid os-csimmonds-ndctechtown-2021.pdf
introduction-to-automotive Andoid os-csimmonds-ndctechtown-2021.pdf
 
%+27788225528 love spells in Boston Psychic Readings, Attraction spells,Bring...
%+27788225528 love spells in Boston Psychic Readings, Attraction spells,Bring...%+27788225528 love spells in Boston Psychic Readings, Attraction spells,Bring...
%+27788225528 love spells in Boston Psychic Readings, Attraction spells,Bring...
 
Announcing Codolex 2.0 from GDK Software
Announcing Codolex 2.0 from GDK SoftwareAnnouncing Codolex 2.0 from GDK Software
Announcing Codolex 2.0 from GDK Software
 
Right Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsRight Money Management App For Your Financial Goals
Right Money Management App For Your Financial Goals
 
Exploring the Best Video Editing App.pdf
Exploring the Best Video Editing App.pdfExploring the Best Video Editing App.pdf
Exploring the Best Video Editing App.pdf
 
%in Hazyview+277-882-255-28 abortion pills for sale in Hazyview
%in Hazyview+277-882-255-28 abortion pills for sale in Hazyview%in Hazyview+277-882-255-28 abortion pills for sale in Hazyview
%in Hazyview+277-882-255-28 abortion pills for sale in Hazyview
 
%in kempton park+277-882-255-28 abortion pills for sale in kempton park
%in kempton park+277-882-255-28 abortion pills for sale in kempton park %in kempton park+277-882-255-28 abortion pills for sale in kempton park
%in kempton park+277-882-255-28 abortion pills for sale in kempton park
 
The title is not connected to what is inside
The title is not connected to what is insideThe title is not connected to what is inside
The title is not connected to what is inside
 
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfThe Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
 

Architecting for Scale