Web Application Architectures

MVC: Model-View-Controller

• Model
• Does all the computational work
• It contains data and performs computation on it
• View (the user interface)
• Show the results from model or controller

• Controller (of states sequences)
• Handles events/requests affecting model or view
• User inputs/requests go to the controller
• Available commands are determined by controller (based on model)
• Tells the model what to do
• Examples: MS Excel

MVC Interactions?!

MVVM Design Pattern

• What is the role of the controller in MVC?
• Basically updates V by changes in M and vice versa
• Instead of coding the C, make it automated
• Automatically update M by changes in V
• Automatically update V by changes in M
• Two-way binding

• The Model-View-ViewModel pattern
• The view model is a value converter
• Responsible for exposing (converting) the data objects from the model in such a way that objects are easily managed and presented.

Transactions?

• Where did you hear it?
• ACID Properties
• Atomicity
• Consistency
• Isolation
• Durability

Atomicity

• Transactions are often composed of multiple statements
• Atomicity guarantees that each transaction is treated as a single "unit", which either succeeds completely, or fails completely
• if any of the statements constituting a transaction fails to complete, the entire transaction fails and the system is left unchanged.

Consistency

• Consistency ensures that a transaction can only bring the system from one valid state to another

Isolation

• Transactions are often executed concurrently
• Isolation ensures that concurrent execution of transactions leaves the system in the same state that would have been obtained if the transactions were executed sequentially.

Durability

• Durability guarantees that once a transaction has been committed, it will remain committed even in the case of a system failure (e.g., power outage or crash).

A Real Story 🔥

• There was a micro-service architectured IoT Platform - 2018
• Users can create project and each project must be created on API gateway, X and Y services
• Requests are handled by API gateway and then it call X and Y services to create a new project
• Sometimes X service failed to create project and sometimes Y service isn't available to handle the request
• In each of these cases system goes into unrecoverable state

CAP Theorem

Impossible for a distributed data store to simultaneously provide more than two out of the following three guarantees:

• Consistency: Every read receives the most recent write or an error
• Availability: Every request receives a (non-error) response, without the guarantee that it contains the most recent write
• Partition tolerance: The system continues to operate despite an arbitrary number of messages being dropped (or delayed) by the network between nodes

Mongo DB (CP)

• MongoDB is a NoSQL database that stores data in one or more Primary nodes in the form of JSON files.
• The replica set nodes in the system send a heartbeat (ping) to every other node to keep track if other replicas or primary nodes are alive or dead.

• If a Primary node becomes inaccessible, then one of the secondary nodes needs to become the primary node.
• Till a new primary is elected from amongst the secondary nodes, the system remains unavailable to the user to make any new write query.
• Therefore, the MongoDB system behaves as a Consistent system and compromises on Availability during a partition.

Cassandra (AP)

• Cassandra is a peer-to-peer system. It consists of multiple nodes in the system. And each node can accept a read or write request from the user.
• Cassandra maintains multiple replicas of data in separate nodes
• A situation can occur where a partition occurs and the replica does not get an updated copy of the data.
• In such a situation the replica nodes will still be available to the user but the data will be inconsistent.
• All updates will reach all the replicas eventually. But in the meantime, it allows divergent versions of the same data to exist temporarily. Until we update them to the consistent state.

Asynchronous Messages

• More flexible
• By announcing events, you make it easy to extend the system to handle new requirements, because services no longer need to have knowledge of their downstream consumers.
• Asynchronous messaging typically requires a communication broker
• An independent system component that receives events and distributes them to event consumers.

Solutions

• EMQ (MQTT) in erlang
• VerneMQ (MQTT) in erlang
• RabbitMQ (AMQP) in erlang
• NATS (NATS) in golang
• ...

Quality of Service

• Fire and Forget
• at-least-once Delivery
• exactly-once Delivery
• ...

Performance Criteria

• Number of Concurrent Connections
• Messages per Second
• Connections per Second