Intro To Microservices
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Introduction to Microservices Vlad Korolev [email protected]
Microservices
2 / 50
Microservices
What are the micro services?
3 / 50
Microservices
What are the micro services? Where did they come from?
3 / 50
Microservices
What are the micro services? Where did they come from? Core principles
3 / 50
Microservices
What are the micro services? Where did they come from? Core principles Why should I bother?
3 / 50
Microservices
What are the micro services? Where did they come from? Core principles Why should I bother? Challenges and pitfalls
3 / 50
Microservices
What are the micro services? Where did they come from? Core principles Why should I bother? Challenges and pitfalls Good practices
3 / 50
Microservices
What are the micro services? Where did they come from? Core principles Why should I bother? Challenges and pitfalls Good practices Pro-tips
3 / 50
Microservices : what’s that?
4 / 50
Microservices : what’s that?
Post continuous delivery SOA
5 / 50
Microservices : what’s that?
Post continuous delivery SOA Small independently releasable services, that work together, modeled around a business domain.
5 / 50
Prehistoric technology
6 / 50
Prehistoric technology
SOA
7 / 50
Prehistoric technology
SOA Domain driven design
7 / 50
Prehistoric technology
SOA Domain driven design Continous delivery
7 / 50
Case study
8 / 50
Case study
9 / 50
Case study
Catalog Recommendations / Promotions Shopping Cart Search Orders RMA Customer Support
10 / 50
Application Composition : Monolith
11 / 50
Application Composition : Monolith
Works most of the time Somewhat scalable Manageable up to a point All or nothing updates Tight coupling
12 / 50
SOA
Break up application into set of independent services
13 / 50
SOA
Break up application into set of independent services Add extra layers Integration Layer (ESB) Service Layer
13 / 50
SOA
Break up application into set of independent services Add extra layers Integration Layer (ESB) Service Layer
Rename existing layers Frontend → Consumer Interface Layer Database → Operational System Middleware → Business Process Layer
13 / 50
Application Composition : SOA
14 / 50
Application Composition : SOA
Did well in some organizations Not so well in others Reasons for failure Conway’s Law Ignoring CAP theorem Ignoring Fallacies of distributed computing
15 / 50
Conway’s Law
16 / 50
Conway’s Law
organizations which design systems ... are constrained to produce designs which are copies of the communication structures of these organizations – M. Conway
17 / 50
Conway’s Law
organizations which design systems ... are constrained to produce designs which are copies of the communication structures of these organizations
18 / 50
Fallacies of distributed computing
19 / 50
Fallacies of distributed computing
The network is reliable Latency is zero Bandwidth is infinite The network is secure Topology doesn’t change There is one administrator Transport cost is zero The network is homogeneous
20 / 50
CAP Theorem
21 / 50
CAP Theorem
Consistency Availability Partitioning tolerance
22 / 50
Domain Driven Design
23 / 50
Domain Driven Design
Bounded contexts
24 / 50
Domain Driven Design
Bounded contexts Draw boundaries around business domains
24 / 50
Domain Driven Design
Bounded contexts Draw boundaries around business domains Do not partition system based on technology
24 / 50
Application Composition : Microservices
25 / 50
Application Composition : Microservices
26 / 50
Application Composition : Microservices
Modeled around business domain Autonomous Hide implementation detail Decentralized Isolate the failure Highly observable Culture of automation
27 / 50
Microservices : Good Parts
28 / 50
Microservices : Good Parts
Small and focused
29 / 50
Microservices : Good Parts
Small and focused Independent
29 / 50
Microservices : Good Parts
Small and focused Independent Loosely coupled
29 / 50
Microservices : Good Parts
Small and focused Independent Loosely coupled Allow try and pilot new tech
29 / 50
Microservices : Good Parts
Small and focused Independent Loosely coupled Allow try and pilot new tech Firm module boundaries
29 / 50
Microservices : Good Parts
Small and focused Independent Loosely coupled Allow try and pilot new tech Firm module boundaries Decentralized data
29 / 50
Why bother?
30 / 50
Why bother?
Latest Buzzword
31 / 50
Why bother?
Latest Buzzword All the cool kids are doing it
31 / 50
Why bother?
Latest Buzzword All the cool kids are doing it Probably, not good reasons
31 / 50
Why bother?
Faster dev cycles
32 / 50
Why bother?
Faster dev cycles Team autonomy
32 / 50
Why bother?
Faster dev cycles Team autonomy Smoother scaling
32 / 50
Challenges
Complex runtime
33 / 50
Challenges
Complex runtime Distributed deployment
33 / 50
Challenges
Complex runtime Distributed deployment Extensive communication
33 / 50
Challenges
Complex runtime Distributed deployment Extensive communication Handling failures
33 / 50
Good practices Humane registries
34 / 50
Good practices Humane registries Team composition
34 / 50
Good practices Humane registries Team composition Isolate failures
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
Standardize communications
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
Standardize communications REST or Message Queues
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
Standardize communications REST or Message Queues
Robust Service Discovery
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
Standardize communications REST or Message Queues
Robust Service Discovery Consider something like Consul / Zookeeper / ETCd
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
Standardize communications REST or Message Queues
Robust Service Discovery Consider something like Consul / Zookeeper / ETCd Monitor everything
34 / 50
Deployments
Avoid huge build jobs
35 / 50
Deployments
Avoid huge build jobs One service per host
35 / 50
Deployments
Avoid huge build jobs One service per host Host is either physical host, VM or container
35 / 50
Deployments
Avoid huge build jobs One service per host Host is either physical host, VM or container
Test
35 / 50
Deployments
Avoid huge build jobs One service per host Host is either physical host, VM or container
Test Contract Tests
35 / 50
Deployments
Avoid huge build jobs One service per host Host is either physical host, VM or container
Test Contract Tests Consumer driven development
35 / 50
Potential pitfalls
Incorrect partitioning
36 / 50
Potential pitfalls
Incorrect partitioning Distributed point of failure
36 / 50
Potential pitfalls
Incorrect partitioning Distributed point of failure Misunderstanding your network
36 / 50
Refactoring to Microservices
Strangler pattern
37 / 50
Refactoring to Microservices
Strangler pattern Use static analysis tool to find natural boundaries
37 / 50
Refactoring to Microservices
Strangler pattern Use static analysis tool to find natural boundaries Shadow systems
37 / 50
Personal Experiences
38 / 50
Monitor Everything
Exception catchers
39 / 50
Monitor Everything
Exception catchers Centralized log collections
39 / 50
Monitor Everything
Exception catchers Centralized log collections
39 / 50
Monitor Everything
Exception catchers Centralized log collections Synthetic transactions
39 / 50
Understand your networking
Microservices increase network chatter
40 / 50
Understand your networking
Microservices increase network chatter More failures with UDP based protocols (DNS, discovery)
40 / 50
Understand your networking
Microservices increase network chatter More failures with UDP based protocols (DNS, discovery) More hiccups with TCP based protocols
40 / 50
Understand your networking
Microservices increase network chatter More failures with UDP based protocols (DNS, discovery) More hiccups with TCP based protocols Run out of sockets Decrease TCP timeouts, seconds instead of minutes
40 / 50
Understand your networking
Microservices increase network chatter More failures with UDP based protocols (DNS, discovery) More hiccups with TCP based protocols Run out of sockets Decrease TCP timeouts, seconds instead of minutes
Batch the transactions. But can’t have batching service
40 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments Pre-build AMis, Containers
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments Pre-build AMis, Containers Test coverage
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments Pre-build AMis, Containers Test coverage Consumer Driven Tests
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments Pre-build AMis, Containers Test coverage Consumer Driven Tests Avoid integration tests written by service devs
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments Pre-build AMis, Containers Test coverage Consumer Driven Tests Avoid integration tests written by service devs https://github.com/realestate-com-au/pact
41 / 50
Consider using client side load balancing
Service side load balancers create point of failure
42 / 50
Consider using client side load balancing
Service side load balancers create point of failure Hard to deploy and manage HW load balancers
42 / 50
Consider using client side load balancing
Service side load balancers create point of failure Hard to deploy and manage HW load balancers Problem of running out of sockets
42 / 50
Consider using client side load balancing
Service side load balancers create point of failure Hard to deploy and manage HW load balancers Problem of running out of sockets Netflix Ribbon Library https://github.com/Netflix/ribbon/wiki/Working-with-loadbalancers
42 / 50
Never make MapReduce pipeline talk to service outside of your cluster
43 / 50
Never make MapReduce pipeline talk to service outside of your cluster
44 / 50
Further resources
45 / 50
Further resources
46 / 50
Further resources
47 / 50
Further resources
Toughtworks Youtube channel
48 / 50
???
49 / 50
Thank you
50 / 50
Microservices
2 / 50
Microservices
What are the micro services?
3 / 50
Microservices
What are the micro services? Where did they come from?
3 / 50
Microservices
What are the micro services? Where did they come from? Core principles
3 / 50
Microservices
What are the micro services? Where did they come from? Core principles Why should I bother?
3 / 50
Microservices
What are the micro services? Where did they come from? Core principles Why should I bother? Challenges and pitfalls
3 / 50
Microservices
What are the micro services? Where did they come from? Core principles Why should I bother? Challenges and pitfalls Good practices
3 / 50
Microservices
What are the micro services? Where did they come from? Core principles Why should I bother? Challenges and pitfalls Good practices Pro-tips
3 / 50
Microservices : what’s that?
4 / 50
Microservices : what’s that?
Post continuous delivery SOA
5 / 50
Microservices : what’s that?
Post continuous delivery SOA Small independently releasable services, that work together, modeled around a business domain.
5 / 50
Prehistoric technology
6 / 50
Prehistoric technology
SOA
7 / 50
Prehistoric technology
SOA Domain driven design
7 / 50
Prehistoric technology
SOA Domain driven design Continous delivery
7 / 50
Case study
8 / 50
Case study
9 / 50
Case study
Catalog Recommendations / Promotions Shopping Cart Search Orders RMA Customer Support
10 / 50
Application Composition : Monolith
11 / 50
Application Composition : Monolith
Works most of the time Somewhat scalable Manageable up to a point All or nothing updates Tight coupling
12 / 50
SOA
Break up application into set of independent services
13 / 50
SOA
Break up application into set of independent services Add extra layers Integration Layer (ESB) Service Layer
13 / 50
SOA
Break up application into set of independent services Add extra layers Integration Layer (ESB) Service Layer
Rename existing layers Frontend → Consumer Interface Layer Database → Operational System Middleware → Business Process Layer
13 / 50
Application Composition : SOA
14 / 50
Application Composition : SOA
Did well in some organizations Not so well in others Reasons for failure Conway’s Law Ignoring CAP theorem Ignoring Fallacies of distributed computing
15 / 50
Conway’s Law
16 / 50
Conway’s Law
organizations which design systems ... are constrained to produce designs which are copies of the communication structures of these organizations – M. Conway
17 / 50
Conway’s Law
organizations which design systems ... are constrained to produce designs which are copies of the communication structures of these organizations
18 / 50
Fallacies of distributed computing
19 / 50
Fallacies of distributed computing
The network is reliable Latency is zero Bandwidth is infinite The network is secure Topology doesn’t change There is one administrator Transport cost is zero The network is homogeneous
20 / 50
CAP Theorem
21 / 50
CAP Theorem
Consistency Availability Partitioning tolerance
22 / 50
Domain Driven Design
23 / 50
Domain Driven Design
Bounded contexts
24 / 50
Domain Driven Design
Bounded contexts Draw boundaries around business domains
24 / 50
Domain Driven Design
Bounded contexts Draw boundaries around business domains Do not partition system based on technology
24 / 50
Application Composition : Microservices
25 / 50
Application Composition : Microservices
26 / 50
Application Composition : Microservices
Modeled around business domain Autonomous Hide implementation detail Decentralized Isolate the failure Highly observable Culture of automation
27 / 50
Microservices : Good Parts
28 / 50
Microservices : Good Parts
Small and focused
29 / 50
Microservices : Good Parts
Small and focused Independent
29 / 50
Microservices : Good Parts
Small and focused Independent Loosely coupled
29 / 50
Microservices : Good Parts
Small and focused Independent Loosely coupled Allow try and pilot new tech
29 / 50
Microservices : Good Parts
Small and focused Independent Loosely coupled Allow try and pilot new tech Firm module boundaries
29 / 50
Microservices : Good Parts
Small and focused Independent Loosely coupled Allow try and pilot new tech Firm module boundaries Decentralized data
29 / 50
Why bother?
30 / 50
Why bother?
Latest Buzzword
31 / 50
Why bother?
Latest Buzzword All the cool kids are doing it
31 / 50
Why bother?
Latest Buzzword All the cool kids are doing it Probably, not good reasons
31 / 50
Why bother?
Faster dev cycles
32 / 50
Why bother?
Faster dev cycles Team autonomy
32 / 50
Why bother?
Faster dev cycles Team autonomy Smoother scaling
32 / 50
Challenges
Complex runtime
33 / 50
Challenges
Complex runtime Distributed deployment
33 / 50
Challenges
Complex runtime Distributed deployment Extensive communication
33 / 50
Challenges
Complex runtime Distributed deployment Extensive communication Handling failures
33 / 50
Good practices Humane registries
34 / 50
Good practices Humane registries Team composition
34 / 50
Good practices Humane registries Team composition Isolate failures
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
Standardize communications
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
Standardize communications REST or Message Queues
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
Standardize communications REST or Message Queues
Robust Service Discovery
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
Standardize communications REST or Message Queues
Robust Service Discovery Consider something like Consul / Zookeeper / ETCd
34 / 50
Good practices Humane registries Team composition Isolate failures Fail fast Bulkheading
Standardize communications REST or Message Queues
Robust Service Discovery Consider something like Consul / Zookeeper / ETCd Monitor everything
34 / 50
Deployments
Avoid huge build jobs
35 / 50
Deployments
Avoid huge build jobs One service per host
35 / 50
Deployments
Avoid huge build jobs One service per host Host is either physical host, VM or container
35 / 50
Deployments
Avoid huge build jobs One service per host Host is either physical host, VM or container
Test
35 / 50
Deployments
Avoid huge build jobs One service per host Host is either physical host, VM or container
Test Contract Tests
35 / 50
Deployments
Avoid huge build jobs One service per host Host is either physical host, VM or container
Test Contract Tests Consumer driven development
35 / 50
Potential pitfalls
Incorrect partitioning
36 / 50
Potential pitfalls
Incorrect partitioning Distributed point of failure
36 / 50
Potential pitfalls
Incorrect partitioning Distributed point of failure Misunderstanding your network
36 / 50
Refactoring to Microservices
Strangler pattern
37 / 50
Refactoring to Microservices
Strangler pattern Use static analysis tool to find natural boundaries
37 / 50
Refactoring to Microservices
Strangler pattern Use static analysis tool to find natural boundaries Shadow systems
37 / 50
Personal Experiences
38 / 50
Monitor Everything
Exception catchers
39 / 50
Monitor Everything
Exception catchers Centralized log collections
39 / 50
Monitor Everything
Exception catchers Centralized log collections
39 / 50
Monitor Everything
Exception catchers Centralized log collections Synthetic transactions
39 / 50
Understand your networking
Microservices increase network chatter
40 / 50
Understand your networking
Microservices increase network chatter More failures with UDP based protocols (DNS, discovery)
40 / 50
Understand your networking
Microservices increase network chatter More failures with UDP based protocols (DNS, discovery) More hiccups with TCP based protocols
40 / 50
Understand your networking
Microservices increase network chatter More failures with UDP based protocols (DNS, discovery) More hiccups with TCP based protocols Run out of sockets Decrease TCP timeouts, seconds instead of minutes
40 / 50
Understand your networking
Microservices increase network chatter More failures with UDP based protocols (DNS, discovery) More hiccups with TCP based protocols Run out of sockets Decrease TCP timeouts, seconds instead of minutes
Batch the transactions. But can’t have batching service
40 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments Pre-build AMis, Containers
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments Pre-build AMis, Containers Test coverage
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments Pre-build AMis, Containers Test coverage Consumer Driven Tests
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments Pre-build AMis, Containers Test coverage Consumer Driven Tests Avoid integration tests written by service devs
41 / 50
Robust CI/CD pipeline
1 Service = 1 Repo = 1 Build Job = 1 Artifact Instantaneous deployments Pre-build AMis, Containers Test coverage Consumer Driven Tests Avoid integration tests written by service devs https://github.com/realestate-com-au/pact
41 / 50
Consider using client side load balancing
Service side load balancers create point of failure
42 / 50
Consider using client side load balancing
Service side load balancers create point of failure Hard to deploy and manage HW load balancers
42 / 50
Consider using client side load balancing
Service side load balancers create point of failure Hard to deploy and manage HW load balancers Problem of running out of sockets
42 / 50
Consider using client side load balancing
Service side load balancers create point of failure Hard to deploy and manage HW load balancers Problem of running out of sockets Netflix Ribbon Library https://github.com/Netflix/ribbon/wiki/Working-with-loadbalancers
42 / 50
Never make MapReduce pipeline talk to service outside of your cluster
43 / 50
Never make MapReduce pipeline talk to service outside of your cluster
44 / 50
Further resources
45 / 50
Further resources
46 / 50
Further resources
47 / 50
Further resources
Toughtworks Youtube channel
48 / 50
???
49 / 50
Thank you
50 / 50
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