#other #application_architecture #architect #architecture #architecture_guidelines #enterprise_architecture #howto #roadmap #self_learning #skills #software #software_engineering

https://github.com/justinamiller/SoftwareArchitect

#other #ai #data_science #devops #engineering #federated_learning #machine_learning #ml #mlops #software_engineering

https://github.com/visenger/awesome-mlops

#other #architecture #cto #management #software_engineering #startups

https://github.com/kuchin/awesome-cto

#other #awesome #books #goodreads #software_engineering #awesome_list #software_architecture #software_design

https://github.com/mhadidg/software-architecture-books

#javascript #book #metaprogramming #programming #software_engineering

https://github.com/HowProgrammingWorks/Book

#other #aws #cloud_computing #coding_interviews #computer_science #interview_questions #software_architecture #software_development #software_engineering #system_design #system_design_interview

This resource, "System Design 101," is designed to help you understand complex systems using simple terms and visuals. Here’s the key benefit It explains various system design concepts, such as communication protocols (REST, GraphQL, gRPC), CI/CD pipelines, architecture patterns (MVC, MVP, MVVM), database systems, caching strategies, microservice architecture, payment systems, DevOps tools (Kubernetes, Docker), and security mechanisms (HTTPS, OAuth 2.0) in an easy-to-understand manner.
- **Practical Examples** The resource uses diagrams and images to make complex technical topics more accessible and easier to comprehend.

Overall, this resource helps you prepare for system design interviews or simply understand how systems work, making it a valuable tool for developers and engineers.

https://github.com/ByteByteGoHq/system-design-101

#other #algorithm #algorithms #coding_interview #coding_interviews #computer_science #data_structures #interview #interview_prep #interview_preparation #programming_interviews #software_engineering #study_plan

This study plan is designed to help you prepare for technical interviews at large software companies like Amazon, Facebook, Google, and Microsoft. Here’s the key information and benefits The plan covers a wide range of computer science topics, ensuring you are well-prepared for various types of technical interviews.
- **Practical Application** The plan advises on how to focus your study time effectively, avoiding unnecessary details and emphasizing retention techniques like flashcards.
- **Career Advancement**: By following this plan, you can gain the skills and confidence needed to secure a job as a software engineer at top tech companies.

Overall, this study plan is a structured approach to learning and practicing computer science fundamentals, making it easier to prepare for and succeed in technical interviews.

https://github.com/jwasham/coding-interview-university

#other #ai #data_science #devops #engineering #federated_learning #machine_learning #ml #mlops #software_engineering

This resource is a comprehensive guide to Machine Learning Operations (MLOps), providing a wide range of tools, articles, courses, and communities to help you manage and deploy machine learning models effectively.

**Key Benefits** Access to numerous books, articles, courses, and talks on MLOps, machine learning, and data science.
- **Community Support** Detailed guides on workflow management, feature stores, model deployment, testing, monitoring, and maintenance.
- **Infrastructure Tools** Resources on model governance, ethics, and responsible AI practices.

Using these resources, you can improve your skills in designing, training, and running machine learning models efficiently, ensuring they are reliable, scalable, and maintainable in production environments.

https://github.com/visenger/awesome-mlops

#other #architecture #awesome #awesome_list #cto #decision_making #engineering_management #hiring #interviewing #leadership #management #principles #roadmap #software_engineering #startups

This resource is a comprehensive list of guides, articles, and tools specifically designed for Chief Technology Officers (CTOs) and VP R&D, especially in startups and hyper-growth companies. It covers a wide range of topics such as the CTO role, hiring, people management, career growth, project management, handbooks, development processes, architecture, technologies, data management, startups, due diligence, finance, product management, marketing, and recommended books.

The benefit to the user is access to a curated and opinionated collection of resources that can help them navigate various aspects of their role effectively. Whether you need advice on hiring engineers, managing teams, planning projects, or understanding technical architectures, this list provides valuable insights and practical tips from industry experts. It serves as a one-stop shop for professional development and problem-solving in the tech leadership space.

https://github.com/kuchin/awesome-cto

#python #agents #ai #software_engineering

RA.Aid is a tool that helps you develop software on your own. It can research, plan, and implement complex tasks for you. This means it breaks down big jobs into smaller steps and does them one by one. RA.Aid also uses the internet to find information and best practices, making sure your code is up-to-date and efficient. Using RA.Aid saves time and effort because it automates many parts of coding, allowing you to focus on more important things[1][3].

https://github.com/ai-christianson/RA.Aid

#csharp #architecture #aspnetcore #clean_architecture #cqrs #ddd #dotnet #dotnetcore #event_driven_architecture #event_sourcing #kubernetes #masstransit #messaging #microservice #microservices #oauth2 #opentelemetry #software_architecture #software_design #software_engineering #vertical_slice_architecture

Migrating from a monolithic architecture to a cloud-native microservices architecture offers several benefits. It improves scalability, allowing different parts of the application to grow independently. This approach also enhances reliability by isolating faults, so if one service fails, others continue to work. Additionally, microservices enable faster deployment and updates, as each service can be developed and deployed separately. This flexibility allows teams to use the best technology for each service, making development more efficient and agile[2][3][5].

https://github.com/meysamhadeli/monolith-to-cloud-architecture