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Тема доклада
Тема доклада
Тема доклада
KYIV 2019
Irina Scurtu
Forget about HTTP
.NET CONFERENCE #1 IN UKRAINE
Irina Scurtu
 Romania Based
 Software Architect @Endava
 Organizer of DotNetIasi user group
 I teach .Net
@irina_scurtu
Agenda
 Monoliths& Microservices
 HTTP calls – sync & async
 RPC
 Messaging
 Queues
 Message Brokers
 Actor Model
Easy life
The Monolith
MONOLITH
 Self-contained
 Single codebase
 Single deploy unit
 Easy life for developers
 Dependencies are in your code
 Single technology stack
MONOLITH
 All or nothing deploys
 Downtimes
 Long build times
 ~ 0 continuous delivery
 Hard to test
Scaling the MONOLITH
Scale up
2
1 5
3
monolith syndrome?
MICROSERVICE
 it’s that thing that is not a monolith
 With it’s own database
 Easy to deploy
 Standalone
 Easy to maintain
Is it?
MICROSERVICES?
 Introduces complexity
 Cascading effects in case of failure
 Need to monitor them closely
2
1 5
3
Independent
units
2
1 5
3
Dou you
know?
150 Amazoncalls
APIs to Build a Page
5 billions
/day
Netflix
 services about 5
billions API
calls/day
 97.7 % are internal
Sync Calls
HTTP
HTTP CALLS
API
Response
API
HTTP CALLS
API API
HTTP CALLS
NFRs
Availablity
Troughput
Reliability
Timeouts
Latency
Retries
Resilience
“It’s perfectly
fine to use sync
HTTP Calls”
 Timeouts
 Availability
 Going back to
coupling?
 You can loose
requests
 Retries?
async Calls
HTTP
“It’s perfectly fine to use async HTTP Calls”
You’ll have exactly the same issues as with sync
calls
Distribute load?!
You can serve more request
You can serve the requests faster
HTTP General Notes
 Sync by nature
 Make a TCP connection for each request
 No retry out of the box
 No delivery guarantees
 Location transparency
 Good for public facing APIs
 Familiar
 Easy to debug
Challenges
Service Discovery
Retry policies
Timeouts
Routing
Tracing
gRPC
gRPC
 No-code references
 Contract based
 Uses HTTP/2 => faster
 Efficient ProtoBuf serialization => smaller payload
 Available in many languages
 Code generation
syntax = "proto3";
option csharp_namespace = "MyFirstGrpc";
package Fibonacci;
// The service definition.
service Fibo {
rpc ComputeFibonacci(RequestedNumber) returns (FibonacciResult){}
}
//the request message format
message RequestedNumber {
int32 number = 1;
}
//the response message format
message FibonacciResult {
int32 result = 1;
}
syntax = "proto3";
option csharp_namespace = "MyFirstGrpc";
package Fibonacci;
// The service definition.
service Fibo {
rpc ComputeFibonacci(RequestedNumber) returns (FibonacciResult){}
}
//the request message format
message RequestedNumber {
int32 number = 1;
}
//the response message format
message FibonacciResult {
int32 result = 1;
}
syntax = "proto3";
option csharp_namespace = "MyFirstGrpc";
package Fibonacci;
// The service definition.
service Fibo {
rpc ComputeFibonacci(RequestedNumber) returns (FibonacciResult){}
}
//the request message format
message RequestedNumber {
int32 number = 1;
}
//the response message format
message FibonacciResult {
int32 result = 1;
}
syntax = "proto3";
option csharp_namespace = "MyFirstGrpc";
package Fibonacci;
// The service definition.
service Fibo {
rpc ComputeFibonacci(RequestedNumber) returns (FibonacciResult){}
}
//the request message format
message RequestedNumber {
int32 number = 1;
}
//the response message format
message FibonacciResult {
int32 result = 1;
}
syntax = "proto3";
option csharp_namespace = "MyFirstGrpc";
package Fibonacci;
// The service definition.
service Fibo {
rpc ComputeFibonacci(RequestedNumber) returns (FibonacciResult){}
}
//the request message format
message RequestedNumber {
int32 number = 1;
}
//the response message format
message FibonacciResult {
int32 result = 1;
}
syntax = "proto3";
option csharp_namespace = "MyFirstGrpc";
package Fibonacci;
// The service definition.
service Fibo {
rpc ComputeFibonacci(RequestedNumber) returns (FibonacciResult){}
}
//the request message format
message RequestedNumber {
int32 number = 1;
}
//the response message format
message FibonacciResult {
int32 result = 1;
}
Trough a message
broker
RPC
RPC
 A kind of API call
Done through a message broker
 Ties systems together but preserves their
encapsulations
Makes an external system look ‘local’
No direct code dependencies
RPC
S H
Queues
Request
RPC
S
Queues
Response
Request
H
Gain vs Loss
You don’t lose the requests
You can add more handler instances
You can ‘apparently’ spread the load
You can process more requests
 Need to match the request
to the response
 Is still sync
Messaging Body
Header
Messaging
Gives you loosely coupled integration
Doesn’t require both systems to be up
Messages ca be transformed in transit - Enrichers
Messaging systems trade consistency for availability
You don’t lose messages
Involves a Producer and a consumer
Messaging
ASYNC Message Processing
S H
Queues
RequestRequest
Queue
S
Queues
Response
Request
RequestRequest
H
Queue
Response
Response
With a DB
S
Queues
Response
Request
RequestRequest
H
Storage
With a DB
s
Queues
Response
Request
RequestRequest
H
Storage
Gains
• Is a reaction to the problems
of distributed systems
• Process more requests
• Process request faster
• Don’t lose requests
 You move the potential
issues to another
subsystem (DB in our case)
 Eventual consistency
remains a problem
Loss
Solutions to eventual problems
 Connection is scarce
 Batch process the message
 Use a semaphore to process them in batches
WHY USE a messaging
system with MSA ?
Agility
Faster development
No integration process
You depend only on a response
Teams have ownership and full understanding of the codebase
You can switch technologies if needed
Scalability
Scale up
Scale out
Increased Throughput
38 267 vs 3500
ElasticityScale down to
reduce costs
A lot of ‘ilities’
Reliability
Flexibility
Distribution
Increased Throughput
Scalability
Elasticity
Performance
Agility
Fault Tolerance
Tools/Frameworks/Systems
What options do I have?
plenty
Many more
Data Types
Queues
Actor Model
Message Brokers
Queues
Useful for point to point communication
Messages are ordered and timestamped
Pull-mode
Actor model
Born from Reactive Programming
Actors are processes that encapsulate behavior
Actors are more than message consumers
Can delegate and create new actors
Can supervise children
At most once delivery
Reactive Manifesto
Message Driven
ResilientElastic
Responsive
Async message
Loose coupling
Location transparency
Scalable
React to workload
changes
Failures are self contained
Recovery
Isolation
Message Brokers
Message Brokers
One process sends a message to a named queue/topic
One or many consumers
Handles connections and disconnections
Dead-letter queue concept
Message Guarantees ( 3 types)
Different Protocols
Guarantees
RabbitMQ
Message Brokers
Lightweight
Queues are FIFO
Supports AMQP protocol
Easy to use, fast
At-least-once delivery
AMQP General Notes
 Async by nature
 Guaranteed message delivery
 At-least once, exactly once, at most once delivery
 No DNS resolve
 Programmatic routing
 Retries out-of-the box
 Ack, Nack out of the box
 Has the “channel” concept
AMQP General Notes
 Has the “channel”
concept
Topic Exchange
References
Distributed systems are
all about tradeoffs
Http is not
the only
option!
PLEASE DON’T FOLLOW
ME
@irina_scurtu
Q&A

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