Learning
  • Software Engineering Golden Treasury
  • Trail Map
  • Caching
    • Alternatives to use before using cache
    • Caching Architecture
    • Cache Invalidation and Eviction
    • Cache Patterns
    • Cache
    • Consistency
    • Distributed Caching
    • Issues with caching
    • Types of caches
  • Career
    • algo types
    • Backend Knowledge
    • Burnout
    • consultancy
    • dev-level
    • Enterprise Developer
    • how-to-get-in-tech-from-other-job
    • how-to-get-into-junior-dev-position
    • induction
    • Interview
    • junior
    • mid
    • New Job
    • paths
    • Principle/staff Engineer
    • Requirements for job
    • Senior Dev capabilities
    • learning
      • automating-beginner
      • company1
        • analyst-progression
        • core-eng-progression
        • dev-progression
        • perf-eng-progression
        • soft-deliv-progression
    • mentoring
      • mentor-resources
    • recruitment
      • questions
      • Spotting posers
  • Computer Science
    • boolean-algebra
    • Compiler
    • Finite State Machine
    • Hashing
    • Algorithms
      • Breadth Firth Search
      • complexity
      • Depth First Search
      • efficiency
      • Sliding Window
      • sorting
    • data-structures
      • AVL Trees
      • data-structures
      • Linked List
    • machines
      • Intel Machine
      • Turing Machine
      • von neumann machine
      • Zeus Machine
  • devops
    • The 5 Ideals
    • microservice
    • Artifact repository
    • Bugs and Fixes
    • Build police
    • cloud-servers
    • Deployments
    • Environments
    • GitOps
    • handling-releases
    • infrastructure-as-code
    • System Migrations
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    • On Premises Hosting
    • Properties/configuration
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    • Release
    • Roll Outs
    • serverless
    • Serverless
    • Cloud Services
    • Versioning
    • AWS
      • deploy-docker-esc
      • cloud-practitiioner-essentials-notes
        • Module 1 - Intro to AWS
        • Module 2 Compute in the cloud
        • Module 3 Global Infrastructure and Reliability
        • Module 4 Networking
        • Module 5 Storage and Databases
        • Security
        • 7 Monitoring and Aanlytics
        • 8 Pricing and Support
        • 9 Migration and Innovation
      • developer-associate
        • AWS Elastic Beanstalk
    • build-tools
      • Managing dependecies
      • Apache ANT
      • Gradle
        • Custom Plugins
        • local-jars
      • Project Management - maven
        • Archtypes
        • Build Lifecycles
        • Customising build lifecycle
        • Dependencies
        • Directory layout
        • jar-files
        • one-to-one
        • Modules
        • Phases
        • Maven Plugins
        • POM
        • profiles
        • setup
        • Starting a maven project
        • wrapper
    • CI/CD
      • Continuous Delivery
      • zookeeper
      • Continuous Integration (CI)
      • github-actions
      • Pipeline
      • Teamcity
    • Cloud computing
      • Overview
      • Service Models
      • Cloud Services
    • containers
      • Best Practices
      • Docker
    • Infrastructure
      • IT Infrastructure Model
      • Non functional Attributes (Quality Attributes)
        • Infrastructure Availability
        • Performance
        • Secruity
    • monitoring
      • Alerting
      • Monitoring & Metrics
      • Metrics
      • Ready pages
      • Splunk
      • Status pages
      • notes-devops-talk
      • logging
        • logging
        • issues
        • Logging
        • Logging
    • Service mesh
      • Service Discovery
      • Istio
    • Terraform
    • container-management
      • Kubernetes
        • commands-glossary
        • OLTP
        • config-maps
        • Links
        • ingress
        • SDP
        • minikube
        • filter
        • indexes
        • sidecar
        • continuous-deployment
  • General Paradigms
    • CAP theorem
    • designing data-intensive applications summary
    • a-philosophy-of-software-design-notes
    • Aspect oriented Programming (AOP)
    • Best Practice
    • Cargo Cult
    • Clean Code
    • Coding reflections
    • Cognitive Complexity
    • Complexity
    • Conventions
    • Design discussions
    • Design
    • Error Handling Checklist
    • Exceptions
    • Feature Flags/toggle
    • Functional requirements
    • Last Responsible Moment
    • Lock In
    • Named Arguments
    • Naming
    • Performance Fallacy
    • Quality
    • Redesign of a system
    • Resuse vs Decoupling
    • Rules for software designs
    • Sad Paths
    • Scaling Webservices
    • Scientific Method
    • stream-processing
    • Upstream and Downstream
    • Patterns
      • Client-SDK-Pattern
      • ORM
      • Api gateway
      • Business Rules Engine
      • cache
      • Composition Root
      • Dependency Injection Containers
      • Dependency Injections
      • Double Dispatch
      • Exception Handling
      • Gateway pattern
      • Humble Object
      • Inheritance for reuse
      • Null Object Pattern
      • Object Mother
      • Patterns
      • Collection pipeline pattern
      • Service Locator
      • Setter constructor
      • Static factory method
      • Step Builder Pattern
      • telescopic constructors
      • Toggles
      • API
        • Aims of API designs
        • Avoid Checked Exceptions
        • Avoid returning nulls
        • Be defensive with your data
        • convience-methods
        • Fluent Interfaces
        • Loan Pattern
        • prefer-enums-to-boolean-returns
        • return-meaningful-types
        • Small intefaces
        • Support Lambdas
        • Weakest type
      • Gang of Four
        • Builder
        • Factory Pattern
        • Strategy Pattern
        • Template
        • abstract Factory
        • Adapter
        • Bridge Pattern
        • Chain of responsibility
        • Command Pattern
        • Composite Design Pattern
        • Decorator Pattern
        • Facade Pattern
        • Flyweight pattern
        • Guard Clause
        • Interpreter
        • html
        • Mediator Pattern
        • Memento Pattern
        • Observer
        • Prototype
        • Proxy
        • Singleton
        • State Pattern
        • Visitor Pattern
    • Architecture
      • Entity Component System
      • Integration Operation Segregation Principle
      • Adaptable Architecture
      • Architecture
      • C4 Modelling
      • cell-based
      • Clean/Hexagonal Architecture
      • Codifying architecture
      • Correct By configuration
      • Cost Base Architecture
      • Data Oriented Design
      • deliberate
      • Domain oriented DOMA
      • Event Driven Architecture
      • Evolutionary Architecture
      • examples
      • Feature Architecture
      • Framework and Libraries
      • functional-core-imperative-shell
      • Layered Architecture
      • Micro services
      • monoliths-to-services
      • Multi tiered Architecture
      • Multi tenant application
      • Resilient Architecture
      • stage event driven architecture (SEDA)
      • links spring rest app
      • Tomato Architecture
      • Tooling
      • Types of architecture
      • checklist
        • Checklist for new project
        • Back end Architecture Checklist
        • Front end Architecture Checklist
        • Mobile Architecture Checklist
      • Cloud Patterns
        • Command and Query Responsibility Segregation (CQRS)
        • Event Sourcing & CQRS
        • Asynchronous Request and Reply
        • Circuit Breaker
        • Retry
        • Sidecar
        • Strangler pattern
      • Domain driven design
        • value & entity
      • Microservices
        • Alternatives to choosing microservices first when scaling
        • Consistency in distributed systems
        • 12 Factor applications
      • Modularity
        • Module monolith vs Microservices
        • Spring Moduilth
      • Architecture Patterns
        • Hexagonal architecture
        • Inverting dependencies
        • Layering & Dependency Inversion Principle
        • Mappings
        • Vertical Slice architecture
        • Web Client Server
        • domain
          • Business and Data Layers Separation
          • DTO
          • Domain Model Pattern
          • Domain Object
          • Transaction Script/ Use Case pattern
        • Enterprise Patterns
          • Concurrency
          • Distribution strategies
          • Domain layer patterns
          • Layering/organisation of code
          • Mapping to datasource
          • Session State
        • Usecases
          • Use case return types
      • Serverless
        • Knative
    • Design architecture aims
      • back of envelope
      • Design ideas
      • Design mistakes
      • high-volume-design
      • ISO Quality Attributes
      • Non functional requirements
      • “Designing for Performance” by Martin Thompson
      • High Performance
      • Qaulity Attributes
        • Availability
        • System Availability
        • Fault Tolerance
        • interoperability
        • Latency
        • Maintability
        • Modifiability
        • Performance
        • Readability
        • Reliability
        • Scalability vs performance
        • Scalability
        • Scaling
        • statelessness
        • Testability
        • Throughput
      • System Design
      • web-scalability-distributed-arch
        • scalable-and-distributed-web-architecture
    • README
      • Conflict-free Replicated Data Type
      • Fallacies
      • Load balancing
      • Rate Limiting
      • Transactions
    • Patterns of Enterprise Application Architecture
      • Repository Pattern
      • Rules Engines
      • scatter-gather
      • Specification Design Pattern
      • Table Driven Development
      • Workflow Design Patterns
        • Triggers
    • Principles
      • Do It Or Get Bitten In The End
      • Dont Repeat Yourself
      • Habitability
      • Keep it simple
      • Responsibility Driven Design
      • Ya Ain’t Gonna Need It
      • Conceptual Overhead
      • CUPID
      • Reuse existing interfaces
      • Facts and Fallacies
      • locality of behaviour
      • Separation of Concerns
      • Simplicity
      • SLAP principle
      • Step down rule
      • Unix Philosophy
      • Wrong abstractions
      • SOLID
        • 1. Single Responsibility Principle
        • 2. Open Close Principle
        • 3. Liskov Substitution Principle
        • 4. Interface Segregation Principle
        • 5. Dependency Inversion Principle
        • GRASP (General Responsibility Assignment Software Principles)
        • Solid for packages
          • jobs
          • CCP
          • CRP
          • REP
          • egress
          • gossip-protocol
        • STUPID
    • programming-types
      • Coding to Contract/Interface
      • Links
      • Declarative vs Imperative Programming Languages
      • defensive-programming
      • Design by contract
      • Domain Specific Languages (DSL)
      • Event Driven
      • file-transfers
      • Logical Programming
      • Mutability
      • Self Healing
      • Simplicity
      • Type Driven Design
      • Value objects
      • Aspect Oriented Programming
      • Concurrent and Parallel Programming
        • Actor Model
        • Asynchronous and Synchronous Programming
        • Batch processing
        • Concurrency Models
        • SAP
        • Multithreading
        • Non Blocking IO
        • Optimistic vs Pessimistic Concurrency
        • Thread per connection or request model
        • Actor
        • aysnchronous-tasks
          • Computational Graphs
          • Divide and conquer
          • Future
          • Thread Pool
        • barriers
          • Barriers
          • Race conditions
        • design
          • agglomeration
          • Communication
          • Mapping
          • Partitioning
        • Liveness
          • Abandoned Lock
          • Deadlocks
          • Livelock
          • Starvation
        • locks
          • Read write lock
          • Reentrant lock
          • Try Lock
        • Mutual Exclusion
          • Data Races
          • Mutual Exclusion AKA Locks
        • performance
          • Amdahl's Law
          • Latency, throughput & speed
          • Measure Speed up
        • synchronization
          • Condition variable
          • producer consumer pattern
          • Semaphore
        • Threads and processes
          • Concurrent and parallel programming
          • Daemon Thread
          • Execution Scheduling
          • sequential-parallel
          • Thread Lifecycle
          • threads-and-processes
      • Functional Programming
        • Currying
        • design-patterns-to-func
        • imperative-programming
        • First class functions
        • Functional Looping
        • Higher Order Functions
        • Immutability
        • Issues with functional Programming
        • Lambda calculus
        • Lazy & Eager
        • map
        • Monad
        • Railway Programming
        • Recursion
        • Reduce
        • referential-transparacy
        • Referential transparency
        • Supplier
      • oop-design
        • Issues with object oriented code
        • Aggregation
        • Anti Patterns
        • Association
        • class-and-objects
        • Composition
        • general-laws-of-programming
        • general-notes
        • Getters and Setters
        • Inside out programming
        • Inversion of control
        • oop-design
        • Other principles
        • Outside in programming
        • Readability
        • Why OO is bad
        • README
          • abstraction
          • encapsulation
          • inheritance
          • Polymorphism
        • clean-code
          • Code Smells
          • Comments
          • Naming
          • CLEAN design
            • code is assertive
            • Cohesion
            • Connascence
            • Coupling
            • Encapsulation
            • Loose Coupling
            • Nonredundant code
      • Reactive Programming
        • reactive-programming
    • Projects and Software types
      • Applicatoin Development
      • Buying or creating software
      • Console Applications
      • Embedded Software development
      • Enterprise
      • Framework Development
      • Games
      • Library development
      • Rewriting
      • White Label Apps
    • State Machines
      • Spring State Machine
  • Other
    • 10x devs
    • Aim of software
    • Choosing Technologies
    • Coding faster
    • Component ownership
    • developer-pain-points
    • Developer Types
    • Effective Software design
    • Full Stack Developer
    • Good coder
    • Issues with Software Engineering and Engineers
    • Learning
    • Logic
    • Role
    • Software Actions
    • Software craftmanship
    • Software Designed
    • Software Engineering
    • Software
    • article-summaries
      • General notes
      • Summary of The Grug Brained Developer A layman's guide to thinking like the self-aware smol brained
      • improve-backend-engineer
      • Optimising Api
      • Simple and Easy
    • README
  • Hardware
    • Cpu memory
    • Storage
  • Integration
    • GRPC
    • API
    • Apis and communications between apps
    • asynchronous and synchronous communications
    • Batch Processing
    • Communications between apps
    • Delivery
    • Distributed Computing
    • Entry point
    • Event Source
    • SDP
    • egress
    • Graphql
    • Idempotency
    • Libraries
    • Long Polling
    • Multiplexing & Demultiplexing
    • Publish Subscribe
    • Push
    • Request & Response
    • REST
    • Remote Method Invocation
    • Remote Procedure Calls
    • Server Sent Events
    • Short Polling
    • Sidecars
    • SOAP
    • Stateless and Stateful
    • Streams
    • Third Party Integrations
    • wdsl
    • Web Services
    • Webhooks
    • repository
    • Kafka
      • Kafka Streams
    • message-queues
      • ActiveMQ
      • Dead Letter Queue
      • JMS
      • Messaging
  • Languages
    • C
    • Choosing A Language
    • cobol
    • Composite Data Types
    • creating
    • Date time
    • Numbers
    • Pass by value vs Pass by reference
    • Primitive Data Types
    • REST anti-patterns
    • Rust
    • Scripting
    • Static typing
    • string
    • Task Oriented Language
    • assembly
    • Getting started
      • Functional Concepts
    • cpp
    • Java
      • Code style
      • Garbage Collection
      • Intellij Debugging
      • Artifacts, Jars
      • Java internals
      • Java resources
      • Java versions
      • JShell
      • Libraries
      • opinionated-guide
      • Starting java
      • Java Tools
      • Why use java
      • Advanced Java
        • Annotations
        • API
        • Database and java
        • Debugging Performance
        • Files IO
        • Finalize
        • JDBC
        • jni
        • Libraries
        • Logging
        • SAP
        • Memory Management
        • Modules
        • OTher
        • Packaging Application
        • Pattern matching
        • performance
        • Properties
        • Reference
        • reflection
        • Scaling
        • Scheduling
        • secruity
        • Serilization
        • Time in Java
        • validation
        • Vector
        • Concurrency and Multithreaading
          • Akka
          • ExecutorCompletionService
          • Asynchronous Programming
          • Concurrency and Threads
          • CountDownLatch
          • Conccurrent Data Structures
          • Executor Service
          • Futures
          • reactive
          • Semaphore
          • structured concurrency
          • Threadlocal
          • Threads
          • Virtual Threads
          • Mutual Exclusion
            • Atomic
            • Synchronized
            • Thread safe class
            • Threads
        • debug
          • heap-dumps
          • thread-dumps
        • functional
          • Collectors
          • Exception Handling
          • Flatmap
          • Functional Programming
          • Generators
          • Immutability
          • issues
          • Optional
          • Parallel Streams
          • Reduce
        • networks
          • HTTP client
          • servlet-webcontainers
          • sockets
          • ssl-tls-https
      • Basics of java
        • compilation
        • computation
        • Conditonal/Flow control
        • Excuting code
        • Instructions
        • Looping/Iterating
        • memory-types-variables
        • methods
        • Printing to screen/debugging
        • Setup the system
        • Data structures
          • Arrays
          • Arayslist/list
          • Map
      • Effective Java notes
        • Creating and Destroying Objects
        • Methods Common to All Objects
        • best-practice-api
        • Classes and Interfaces
        • Enums and Annotations
        • Generics
      • framework
        • aop
        • bad
        • Dagger
        • Databases
        • Lombok
        • Mapstruct
        • netty
        • resliance4j
        • RxJava
        • Vert.x
        • Spring
          • Spring Data Repositories
          • actuator
          • cloud-native
          • H2 Db in Spring
          • Initializrs
          • JDBC Template
          • Java Persistence API (JPA)
          • kotlin
          • Pitfalls and advice
          • PRoxies
          • Reactive
          • spring security
          • spring-aop
          • Spring Boot
          • spring-jdbc
          • Spring MVC
          • Spring Testing
          • Testing
          • Transaction
          • patterns
            • Component Scan Patterns
            • Concurrency
            • Decorator Pattern in Spring
        • Micronaut
          • DI
        • Quarkus
          • database
          • Links
      • Intermediate level java
        • String Class
        • Assertions
        • Casting
        • Clonable
        • Command line arguments
        • Common Libraries/classes
        • Comparators
        • Where to store them?
        • Shallow and Deep Copy
        • Date and Time
        • Enums
        • Equals and Hashcode
        • Equals and hashcode
        • Exceptions
        • Final
        • Finally
        • Generics
        • incrementors
        • Null
        • packages and imports
        • Random numbers
        • Regex
        • Static
        • toString()
        • OOP
          • Accessors
          • Classes
          • Object Oriented Programming
          • Constructors
          • Fields/state
          • Inheritence
          • Interfaces
          • Methods/behaviour
          • Nested Classes
          • Objects
          • Static VS Instance
          • Whether to use a dependency or static method?
        • Other Collections
          • Other Collections
          • Arraylist vs Linkedlist
          • LinkedHashMap
          • Linked List
          • Priority queue
          • Sequenced Collections
          • Set
          • Shallow vs Deep Copy
          • Time Complexity of Collections
          • What Collection To use?
    • kotlin
      • Domain Specific Language
      • learning
      • Libraries
      • Personal Roadmap
      • Links
    • Nodejs
      • Performance
  • Management & Workflow
    • Agile
    • Take Breaks
    • # Communication
    • Engineering Daybook
    • Estimates
    • Feedback Loops
    • Little's law
    • Managing Others
    • poser.
    • Presentations
    • self-improvement
    • software-teams
    • Task List
    • trade-off
    • Types of devs
    • Type of work
    • Waterfall Methodology
    • coding-process
      • Bugs
      • Code Review
      • Code Reviews
      • Documentation
      • Done
      • Handover
      • Mob Programming
      • Navigate codebase
      • Pair Programming
      • Pull Requests
      • How to do a story
      • Story to code
      • Trunk based development
      • Xtreme Programming (XP)
      • debugging
        • 9 Rules of Thumb of Dubugging
        • Debugging
        • using-debugger
      • Legacy code
        • Legacy crisis
        • Working with legacy code
    • Managing work
      • Theory of constraints
      • Distributed Teams
      • estimations
      • Improving team's output
      • Kanban
      • Kick offs
      • Retrospectives
      • Scrum
      • Sign offs
      • Stand ups
      • Time bombs
      • Project management triangle
    • Notion
    • recruitment
      • In Person Test
      • Interviews
      • Unattended test
  • Networks
    • Content Delivery Network - CDN
    • DNS
    • cache control
    • Cookies and Sessions
    • Docker Networking
    • Duplex
    • Etags
    • HTTP Cache
    • HTTP - Hyper Text Transfer Protocol
    • HTTP/2
    • Http 3
    • Internet & Web
    • iptables
    • Keep alive
    • Leader Election
    • Load balancer
    • long-polling
    • Network Access Control
    • Network Address Translation (NAT)
    • Network Layers
    • Nginx
    • OSI network model
    • Persistent Connection
    • Polling
    • Proxy
    • Quic
    • reverse-proxy
    • servers
    • Server sent events (SSE)
    • SSH
    • Streaming
    • Timeouts
    • Url Encoding
    • Web sockets
    • WebRTC (Web Real-Time Communication)
    • Wireshark
    • tcp/ip
      • Congestion
      • IP - Internet Protocol
      • TCP - Transmission Control Protocol
  • Operating Systems
    • Cloud Computing
    • Distributed File Systems
    • Distributed Shared Memory
    • Input/Output Management
    • Inter-Process Communication
    • Threads and Concurrency
    • Virtualization
    • Searching using CLI
    • Bash and scripting
    • Booting of linux
    • makefile
    • Memory Management
    • Processes and Process Management
    • Scheduling
    • Scripting
    • Links
    • Ubuntu
    • Unix File System
    • User groups
    • Linux
  • Other Topics
    • Finite state machine
    • Floating point
    • Googling
    • Setup
    • Unicode
    • Machine Learning
      • Artificial Intelligence
      • Jupyter Notebook
    • Blockchain
    • Front End
      • Single Page App
      • cqrs
      • css
      • Debounce
      • Dom, Virtual Dom
      • ADP
      • htmx
      • Island Architecture
      • Why use?
      • Java and front end tech
      • mermaidjs
      • Next JS
      • javascript
        • Debounce
        • design
        • Event loop
        • testing
        • Typescript
        • react
          • Design
          • learning
          • performance
          • React JS
          • testing
      • performance
      • Static website
    • jobs
      • Tooling
      • bash text editor - vim
      • VS code
      • scaling
        • AI Assistant
        • Debugging
        • General features and tips and tricks
        • IDE - Intellij
        • Plugins
        • Spring usage
  • persistance
    • ACID - Atomicity, Consistency, Isolation, Durability
    • BASE - Basic Availability, Soft state, Eventual Consistency
    • Buffer
    • Connection pooling
    • service
    • Database Migrations - flywaydb
    • Databases
    • Eventual Consistency
    • GraphQL
    • IDs
    • indexing
    • MongoDB
    • Normalisation
    • ORacle sql
    • Partitioning
    • patterns
    • PL SQL
    • Replication and Sharding
    • Repository pattern
    • Sharding
    • Snapshot
    • Strong Consistency
    • links
    • Files
      • Areas to think of
    • hibernate
      • ORM-hibernate
    • Indexes
      • Elastisearch
    • relationships
      • many-to-many
      • SDP
      • serverless
      • x-to-x-relationships
    • sql
      • Group by
      • indexes
      • Joins
      • Common mistakes
      • operators
      • performance
    • types
      • maven-commands-on-intellij
      • in-memory-database-h2
      • Key value database/store
      • Mongo DB
      • NoSQL Databases
      • Relational Database
      • Relational Vs Document Databases
  • Security
    • OAuth
    • API Keys
    • Certificates and JKS
    • Cluster Secruity
    • Communication Between Two Applications via TLS
    • Cookies & Sessions
    • CORS - Cross-Origin Resource Sharing
    • csrf
    • Encryption and Decryption
    • Endpoint Protection
    • JWT
    • language-specific
    • OpenID
    • OWASP
    • Secrets
    • Secruity
    • Servlet authentication and Authorization
    • vault
  • Testing, Maintainablity & Debugging
    • Service-virtualization and api mocking
    • a-test-bk
    • Build Monitor
    • Builds
    • Code coverage
    • consumer-driven contract testing
    • Fixity
    • Living Documentation
    • Mocks, Stubs & Doubles
    • patterns
    • Quality Engineering
    • Reading and working with legacy code
    • Reading
    • remote-debug-intellij
    • simulator
    • Technical Debt
    • Technical Waste
    • Test cases
    • Test Data Builders
    • Test Pyramids
    • Test Types
    • Testing Good Practice
    • Testing
    • What to prime
    • What to test
    • Debugging
      • Debugging in kubernetes or Docker
    • fixing
      • How to Deal with I/O Expense
      • How to Manage Memory
      • How to Optimize Loops
      • How to Fix Performance Problems
    • Legacy Code
      • Learning
      • Legacy code
      • techniques
    • libraries
      • assertj
      • Data Faker
      • Junit
      • mockito
      • Test Containers
      • Wiremock
      • Yatspec
    • Refactoring
      • Code Smells
      • refactoring-types
      • Refactoring
      • Technical Debt
      • pyramid-of-refactoring
        • Pyramid of Refactoring
    • Test first strategies
      • Acceptance Testing Driven Developement (ATDD)
      • Behaviour Driven Development/Design - BDD
      • Inside out
      • Outside in
      • Test driven development (TDD)
    • testing
      • Acceptance tests
      • How Much Testing is Enough?
      • Approval Testing
      • Bad Testing
      • End to end tests
      • Honeycomb
      • Testing Microservices
      • Mutation testing
      • Property based testing
      • Smoke Testing
      • social-unit-tests
      • solitary-unit-tests
      • Static Analysis Test
      • Unit testing
  • Version Control - Git
    • Branch by Abstraction
    • feature-branching
    • Git patches
    • Trunk Based Development
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Types

  • On prem

  • IaaS - Infrastructure as a Service

    • examples: DigitalOcean, Linode, Rackspace, Amazon Web Services (AWS), Cisco Metapod, Microsoft Azure, Google Compute Engine (GCE)

    • made of highly scalable and automated compute resources

    • is fully self-service for accessing and monitoring computers, networking, storage, and other services

    • allows businesses to purchase resources on-demand and as-needed instead of having to buy hardware outright

    • Delivery

      • delivers cloud computing infrastructure, including servers, network, operating systems, and storage, through virtualization technology

      • are typically provided to the organization through a dashboard or an API, giving IaaS clients complete control over the entire infrastructure. IaaS provides the same technologies and capabilities as a traditional data center without having to physically maintain or manage all of it

      • clients can still access their servers and storage directly, but it is all outsourced through a “virtual data center” in the cloud

      • clients are responsible for managing aspects such as applications, runtime, OSes, middleware, and data.

      • providers of the IaaS manage the servers, hard drives, networking, virtualization, and storage. Some providers even offer more services beyond the virtualization layer, such as databases or message queuing

    • Advantages

      • The most flexible cloud computing model

      • Easy to automate deployment of storage, networking, servers, and processing power

      • Hardware purchases can be based on consumption

      • Clients retain complete control of their infrastructure

      • Resources can be purchased as-needed

      • Highly scalable

    • Characteristics

      • Resources are available as a service

      • Cost varies depending on consumption

      • Services are highly scalable

      • Multiple users on a single piece of hardware

      • Organization retain complete control of the infrastructure

      • Dynamic and flexible

    • When to Use

      • Startups and small companies may prefer IaaS to avoid spending time and money on purchasing and creating hardware and software.

      • Larger companies may prefer to retain complete control over their applications and infrastructure, but they want to purchase only what they actually consume or need.

      • Companies experiencing rapid growth like the scalability of IaaS, and they can change out specific hardware and software easily as their needs evolve.

      • IaaS offers plenty of flexibility and scalability.

    • Limitations & Concerns

      • Security

        • While the customer is in control of the apps, data, middleware, and the OS platform, security threats can still be sourced from the host or other virtual machines (VMs).

        • Insider threat or system vulnerabilities may expose data communication between the host infrastructure and VMs to unauthorized entities.

      • Legacy systems operating in the cloud

        • While customers can run legacy apps in the cloud, the infrastructure may not be designed to deliver specific controls to secure the legacy apps.

        • Minor enhancement to legacy apps may be required before migrating them to the cloud, possibly leading to new security issues unless adequately tested for security and performance in the IaaS systems

      • Internal resources and training

        • Additional resources and training may be required for the workforce to learn how to effectively manage the infrastructure.

        • Customers will be responsible for data security, backup, and business continuity.

        • Due to inadequate control into the infrastructure however, monitoring and management of the resources may be difficult without adequate training and resources available inhouse

      • Multi-tenant security

        • Since the hardware resources are dynamically allocated across users as made available, the vendor is required to ensure that other customers cannot access data deposited to storage assets by previous customers

        • Similarly, customers must rely on the vendor to ensure that VMs are adequately isolated within the multitenant cloud architecture.

  • PaaS - Platform as a Service

    • examples: AWS Elastic Beanstalk, Windows Azure, Heroku, Force.com, Google App Engine, Apache Stratos, OpenShift

    • Cloud platform services

    • provide cloud components to certain software while being used mainly for applications

    • delivers a framework for developers that they can build upon and use to create customized applications

    • All servers, storage, and networking can be managed by the enterprise or a third-party provider while the developers can maintain management of the applications

    • Delivery

      • is similar to SaaS, except instead of delivering the software over the internet, PaaS provides a platform for software creation

      • delivered via the web, giving developers the freedom to concentrate on building the software without having to worry about operating systems, software updates, storage, or infrastructure.

      • allows businesses to design and create applications that are built into the PaaS with special software components

        • These applications, sometimes called middleware, are scalable and highly available as they take on certain cloud characteristics.

    • Advantages

      • Simple, cost-effective development and deployment of apps

      • Scalable

      • Highly available

      • Developers can customize apps without the headache of maintaining the software

      • Significant reduction in the amount of coding needed

      • Automation of business policy

      • Easy migration to the hybrid model

    • Characteristics

      • Builds on virtualization technology, so resources can easily be scaled up or down as your business changes

      • Provides a variety of services to assist with the development, testing, and deployment of apps

      • Accessible to numerous users via the same development application

      • Integrates web services and databases

    • When to Use

      • can streamline workflows when multiple developers are working on the same development project

      • If other vendors must be included, PaaS can provide great speed and flexibility to the entire process

      • if you need to create customized applications

      • can greatly reduce costs and it can simplify some challenges that come up if you are rapidly developing or deploying an app.

    • Limitations & Concerns

    • Data security

      • Organizations can run their own apps and services using PaaS solutions, but the data residing in third-party, vendor-controlled cloud servers poses security risks and concerns

      • Your security options may be limited as customers may not be able to deploy services with specific hosting policies

    • Integrations

      • he complexity of connecting the data stored within an onsite data center or off-premise cloud is increased, which may affect which apps and services can be adopted with the PaaS offering.

      • Particularly when not every component of a legacy IT system is built for the cloud, integration with existing services and infrastructure may be a challenge.

    • Vendor lock-in

      • Business and technical requirements that drive decisions for a specific PaaS solution may not apply in the future.

      • If the vendor has not provisioned convenient migration policies, switching to alternative PaaS options may not be possible without affecting the business

    • Customization of legacy systems

      • PaaS may not be a plug-and-play solution for existing legacy apps and services.

      • Instead, several customizations and configuration changes may be necessary for legacy systems to work with the PaaS service.

      • The resulting customization can result in a complex IT system that may limit the value of the PaaS investment altogether

    • Runtime issues

      • In addition to limitations associated with specific apps and services, PaaS solutions may not be optimized for the language and frameworks of your choice

      • Specific framework versions may not be available or perform optimally with the PaaS service

      • Customers may not be able to develop custom dependencies with the platform

    • Operational limitation

      • Customized cloud operations with management automation workflows may not apply to PaaS solutions, as the platform tends to limit operational capabilities for end users.

      • Although this is intended to reduce the operational burden on end users, the loss of operational control may affect how PaaS solutions are managed, provisioned, and operated

  • SaaS - Software as a Service

    • examples: Google Workspace, Dropbox, Salesforce, Cisco WebEx, Concur, GoToMeeting

    • cloud application services

    • utilizes the internet to deliver applications, which are managed by a third-party vendor, to its users.

    • A majority of SaaS applications run directly through your web browser, which means they do not require any downloads or installations on the client side.

    • Delivery

      • eliminates the need to have IT staff download and install applications on each individual computer

      • vendors manage all potential technical issues, such as data, middleware, servers, and storage, resulting in streamlined maintenance and support for the business.

    • Advantages

      • reducing the time and money spent on tedious tasks such as installing, managing, and upgrading software. Thus more time spent on delivering features

    • Characteristics

      • Managed from a central location

      • Hosted on a remote server

      • Accessible over the internet

      • Users not responsible for hardware or software updates

    • When to Use

      • Startups or small companies that need to launch ecommerce quickly and don’t have time for server issues or software

      • Short-term projects that require quick, easy, and affordable collaboration

      • Applications that aren’t needed too often, such as tax software

      • Applications that need both web and mobile access

    • Limitations & Concerns

      • Interoperability

        • Integration with existing apps and services can be a major concern if the SaaS app is not designed to follow open standards for integration

          • organizations may need to design their own integration systems or reduce dependencies with SaaS services, which may not always be possible/feasible

      • Vendor lock-in

        • Vendors may make it easy to join a service and difficult to get out of it.

        • the data may not be portable–technically or cost-effectively–across SaaS apps from other vendors without incurring significant cost or inhouse engineering rework

        • Not every vendor follows standard APIs, protocols, and tools, yet the features could be necessary for certain business tasks.

      • Lack of integration support

        • Many organizations require deep integrations with on-premise apps, data, and services

        • The SaaS vendor may offer limited support in this regard, forcing organizations to invest internal resources in designing and managing integrations

        • The complexity of integrations can further limit how the SaaS app or other dependent services can be used.

      • Data security

        • Large volumes of data may have to be exchanged to the backend data centers of SaaS apps in order to perform the necessary software functionality

        • ransferring sensitive business information to public-cloud based SaaS service may result in compromised security and compliance in addition to significant cost for migrating large data workloads

      • Customization

        • Since a one-size-fits-all solution does not exist, users may be limited to specific functionality, performance, and integrations as offered by the vendor

        • In contrast, on-premise solutions that come with several software development kits (SDKs) offer a high degree of customization options.

      • Lack of control

        • involves handing control over to the third-party service provider. These controls are not limited to the software–in terms of the version, updates, or appearance–but also the data and governance

        • Customers may therefore need to redefine their data security and governance models to fit the features and functionality of the SaaS service

      • Feature limitations

        • Since SaaS apps often come in a standardized form, the choice of features may be a compromising tradeoff against security, cost, performance, or other organizational policie

        • vendor lock-in, cost, or security concerns may mean it’s not viable to switch vendors or services to serve new feature requirements in the future.

      • Performance and downtime

        • Because the vendor controls and manages the SaaS service, your customers now depend on vendors to maintain the service’s security and performance.

        • Planned and unplanned maintenance, cyber-attacks, or network issues may impact the performance of the SaaS app despite adequate service level agreement (SLA) protections in place.

Differences

Last updated 3 years ago

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Type
On Prem
IaaS
PaaS
SaaS

Application

y

y

y

n

Data

y

y

y

n

Runtime

y

y

n

n

Middleware

y

y

n

n

O/S

y

y

n

n

Virtualisation

y

n

n

n

Servers

y

n

n

n

Storage

y

n

n

n

Networking

y

n

n

n

  1. devops

Cloud Services

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  • Differences