Software Engineer interview Prep. Master list

by Deepak Dhakal 2. July 2021 00:46

System Design Interview Prep Master Doc

Compiled by - Pooja Biswas

pooja biswas | LinkedIn

All system design youtube channels

20. https://www.youtube.com/c/OktaDev/videos

Important Books :

Amazon.com: System Design Interview – An Insider's Guide eBook: Xu, Alex: Kindle Store
Amazon.com: Operating Systems: Three Easy Pieces eBook: Arpaci-Dusseau, Remzi, Arpaci-Dusseau, Andrea: Kindle Store
Web Scalability for Startup Engineers: Ejsmont, Artur: 9780071843652: Amazon.com: Books
Understanding Distributed Systems: What every developer should know about large distributed applications: Vitillo, Roberto: 9781838430207: Amazon.com: Books
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems: Kleppmann, Martin: 9781449373320: Amazon.com: Books
Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale: 9781491936160: Computer Science Books @ Amazon.com
Buy Distributed Algorithms – An Intuitive Approach 2e (The MIT Press) Book Online at Low Prices in India | Distributed Algorithms – An Intuitive Approach 2e (The MIT Press) Reviews & Ratings - Amazon.in
Elasticsearch: The Definitive Guide: A Distributed Real-Time Search and Analytics Engine eBook: Gormley, Clinton, Tong, Zachary: Amazon.in: Kindle Store
Buy Cassandra – The Definitive Guide, 3e: Distributed Data at Web Scale Book Online at Low Prices in India | Cassandra – The Definitive Guide, 3e: Distributed Data at Web Scale Reviews & Ratings - Amazon.in

Imp keywords

Write ahead logging
SSL passthrough / termination on load balancers
Clock vectors
Hinted handoff
Bloom filters
Gossip protocols
Merkle trees
Two phase commit
Two phase locking
Consistent hashing
Data replication
Total order broadcast
Isolation levels (read uncomitted, read comitted, repeatable read, serializable)
Quad trees (GeoHashin)
Inverse indexing - Google search/any search indexing
Gaming ranking - rank players based on score and faster.
Word search in trie - auto suggestions system design
Sort 5gb data in 1gb memory - merge sort
Paxos algo
Merkle Tree
Backpressure
Circuit breaker
Raft
Service discovery
Saga
Hyperloglog

Important algorithms

https://github.com/resumejob/system-design-algorithms

Frugal Streaming
Geohash / S2 Geometry
Leaky bucket / Token bucket
Loosy Counting
Operational transformation
Quadtree / Rtree
Ray casting
Reverse index
Rsync algorithm
Trie algorithm

Consistent Hashing
Count-Min Sketch
Bloom Filters
HyperLogLog
Skip Lists
LRU
B tree
Hierarchical Timing Wheels https://blog.acolyer.org/2015/11/23/hashed-and-hierarchical-timing-wheels/
Merkle trees
Fenwick Tree - http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=2FDD6F53D3DC3BB91FA42E7277B6765B?doi=10.1.1.14.8917&rep=rep1&type=pdf
AMS (Alon Matias Szegedy) algorithm

Cloud design patterns

https://docs.microsoft.com/en-us/azure/architecture/patterns/index-patterns

Cloud arch pattern

Ambassador	Create helper services that send network requests on behalf of a consumer service or application.	Design and Implementation, Operational Excellence
Anti-Corruption Layer	Implement a façade or adapter layer between a modern application and a legacy system.	Design and Implementation, Operational Excellence
Asynchronous Request-Reply	Decouple backend processing from a frontend host, where backend processing needs to be asynchronous, but the frontend still needs a clear response.	Messaging
Backends for Frontends	Create separate backend services to be consumed by specific frontend applications or interfaces.	Design and Implementation
Bulkhead	Isolate elements of an application into pools so that if one fails, the others will continue to function.	Reliability
Cache-Aside	Load data on demand into a cache from a data store	Data Management, Performance Efficiency
Choreography	Let each service decide when and how a business operation is processed, instead of depending on a central orchestrator.	Messaging, Performance Efficiency
Circuit Breaker	Handle faults that might take a variable amount of time to fix when connecting to a remote service or resource.	Reliability
Claim Check	Split a large message into a claim check and a payload to avoid overwhelming a message bus.	Messaging
Compensating Transaction	Undo the work performed by a series of steps, which together define an eventually consistent operation.	Reliability
Competing Consumers	Enable multiple concurrent consumers to process messages received on the same messaging channel.	Messaging
Compute Resource Consolidation	Consolidate multiple tasks or operations into a single computational unit	Design and Implementation
CQRS	Segregate operations that read data from operations that update data by using separate interfaces.	Data Management, Design and Implementation, Performance Efficiency
Deployment Stamps	Deploy multiple independent copies of application components, including data stores.	Reliability, Performance Efficiency
Event Sourcing	Use an append-only store to record the full series of events that describe actions taken on data in a domain.	Data Management, Performance Efficiency
External Configuration Store	Move configuration information out of the application deployment package to a centralized location.	Design and Implementation, Operational Excellence
Federated Identity	Delegate authentication to an external identity provider.	Security
Gatekeeper	Protect applications and services by using a dedicated host instance that acts as a broker between clients and the application or service, validates and sanitizes requests, and passes requests and data between them.	Security
Gateway Aggregation	Use a gateway to aggregate multiple individual requests into a single request.	Design and Implementation, Operational Excellence
Gateway Offloading	Offload shared or specialized service functionality to a gateway proxy.	Design and Implementation, Operational Excellence
Gateway Routing	Route requests to multiple services using a single endpoint.	Design and Implementation, Operational Excellence
Geodes	Deploy backend services into a set of geographical nodes, each of which can service any client request in any region.	Reliability, Operational Excellence
Health Endpoint Monitoring	Implement functional checks in an application that external tools can access through exposed endpoints at regular intervals.	Reliability, Operational Excellence
Index Table	Create indexes over the fields in data stores that are frequently referenced by queries.	Data Management, Performance Efficiency
Leader Election	Coordinate the actions performed by a collection of collaborating task instances in a distributed application by electing one instance as the leader that assumes responsibility for managing the other instances.	Design and Implementation, Reliability
Materialized View	Generate prepopulated views over the data in one or more data stores when the data isn't ideally formatted for required query operations.	Data Management, Operational Excellence
Pipes and Filters	Break down a task that performs complex processing into a series of separate elements that can be reused.	Design and Implementation, Messaging
Priority Queue	Prioritize requests sent to services so that requests with a higher priority are received and processed more quickly than those with a lower priority.	Messaging, Performance Efficiency
Publisher/Subscriber	Enable an application to announce events to multiple interested consumers asynchronously, without coupling the senders to the receivers.	Messaging
Queue-Based Load Leveling	Use a queue that acts as a buffer between a task and a service that it invokes in order to smooth intermittent heavy loads.	Reliability, Messaging, Resiliency, Performance Efficiency
Retry	Enable an application to handle anticipated, temporary failures when it tries to connect to a service or network resource by transparently retrying an operation that's previously failed.	Reliability
Scheduler Agent Supervisor	Coordinate a set of actions across a distributed set of services and other remote resources.	Messaging, Reliability
Sequential Convoy	Process a set of related messages in a defined order, without blocking processing of other groups of messages.	Messaging
Sharding	Divide a data store into a set of horizontal partitions or shards.	Data Management, Performance Efficiency
Sidecar	Deploy components of an application into a separate process or container to provide isolation and encapsulation.	Design and Implementation, Operational Excellence
Static Content Hosting	Deploy static content to a cloud-based storage service that can deliver them directly to the client.	Design and Implementation, Data Management, Performance Efficiency
Strangler Fig	Incrementally migrate a legacy system by gradually replacing specific pieces of functionality with new applications and services.	Design and Implementation, Operational Excellence
Throttling	Control the consumption of resources used by an instance of an application, an individual tenant, or an entire service.	Reliability, Performance Efficiency
Valet Key	Use a token or key that provides clients with restricted direct access to a specific resource or service.	Data Management, Security

Data Management patterns

06/23/2017

Data management is the key element of cloud applications, and influences most of the quality attributes. Data is typically hosted in different locations and across multiple servers for reasons such as performance, scalability or availability, and this can present a range of challenges. For example, data consistency must be maintained, and data will typically need to be synchronized across different locations.

Additionally data should be protected at rest, in transit, and via authorized access mechanisms to maintain security assurances of confidentiality, integrity, and availability. Refer to the Azure Security Benchmark Data Protection Control for more information.

Pattern	Summary
Cache-Aside	Load data on demand into a cache from a data store
CQRS	Segregate operations that read data from operations that update data by using separate interfaces.
Event Sourcing	Use an append-only store to record the full series of events that describe actions taken on data in a domain.
Index Table	Create indexes over the fields in data stores that are frequently referenced by queries.
Materialized View	Generate prepopulated views over the data in one or more data stores when the data isn't ideally formatted for required query operations.
Sharding	Divide a data store into a set of horizontal partitions or shards.
Static Content Hosting	Deploy static content to a cloud-based storage service that can deliver them directly to the client.
Valet Key	Use a token or key that provides clients with restricted direct access to a specific resource or service.

DATA MANAGEMENT PATTERNS

Design and Implementation patterns

06/23/2017
2 minutes to read

Good design encompasses factors such as consistency and coherence in component design and deployment, maintainability to simplify administration and development, and reusability to allow components and subsystems to be used in other applications and in other scenarios. Decisions made during the design and implementation phase have a huge impact on the quality and the total cost of ownership of cloud hosted applications and services.

Pattern	Summary
Ambassador	Create helper services that send network requests on behalf of a consumer service or application.
Anti-Corruption Layer	Implement a façade or adapter layer between a modern application and a legacy system.
Backends for Frontends	Create separate backend services to be consumed by specific frontend applications or interfaces.
CQRS	Segregate operations that read data from operations that update data by using separate interfaces.
Compute Resource Consolidation	Consolidate multiple tasks or operations into a single computational unit
External Configuration Store	Move configuration information out of the application deployment package to a centralized location.
Gateway Aggregation	Use a gateway to aggregate multiple individual requests into a single request.
Gateway Offloading	Offload shared or specialized service functionality to a gateway proxy.
Gateway Routing	Route requests to multiple services using a single endpoint.
Leader Election	Coordinate the actions performed by a collection of collaborating task instances in a distributed application by electing one instance as the leader that assumes responsibility for managing the other instances.
Pipes and Filters	Break down a task that performs complex processing into a series of separate elements that can be reused.
Sidecar	Deploy components of an application into a separate process or container to provide isolation and encapsulation.
Static Content Hosting	Deploy static content to a cloud-based storage service that can deliver them directly to the client.
Strangler Fig	Incrementally migrate a legacy system by gradually replacing specific pieces of functionality with new applications and services.

DESIGN AND IMPLEMENTATION PATTERNS

Messaging patterns

The distributed nature of cloud applications requires a messaging infrastructure that connects the components and services, ideally in a loosely coupled manner in order to maximize scalability. Asynchronous messaging is widely used, and provides many benefits, but also brings challenges such as the ordering of messages, poison message management, idempotency, and more.

Deepak Dhakal..Not that personal

Software Engineer interview Prep. Master list

System Design Interview Prep Master Doc

All system design youtube channels

Imp keywords

Important algorithms

Cloud design patterns

LEETCODE all system design problems

Software Engineer interview Prep. Master list

System Design Interview Prep Master Doc

All system design youtube channels

Imp keywords

Important algorithms

Cloud design patterns

LEETCODE all system design problems

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