Books and Papers

Books I have, read or want to read, computer science and stuff.

Books

Distributed Systems

1. Distributed Systems; Andrew S. Tanenbaum

2. Designing Data-Intensive Applications; Kleppman

3. Designing Event-Driven Systems; Stopford

4. Kafka: The Definitive Guide; Neha Narkhede, Gwen Shapira, Todd Palino

5. Making Sense of Stream Processing; Kleppmann

6. I Heart Logs; Kreps

7. Microservices AntiPatterns and Pitfalls, Richards

8. Software Architecture Patterns, Richards

Operating Systems, Networks & SRE

1. Modern Operating Systems; Andrew S. Tanenbaum

2. Computer Networks; Andrew S. Tanenbaum

3. The Site Reliability Engineering: How Google Runs Production Systems; Murphy, Beyer, Jones, Petoff

4. The Site Reliability Workbook; Murphy, Beyer, Jones, Petoff

5. Linux System Programming; Love

6. Linux Kernel Development; Love

7. The Linux Programmer's Toolbox; Fusco

8. Systems Performance: Enterprise and the Cloud; Gregg

9. UNIX and Linux System Administration Handbook; Evi Nemeth, Garth Snyder, Trent R. Hein, Ben Whaley, Dan Mackin

Databases

1. Database Internals. A Deep Dive into How Distributed Data Systems Work; Alex Petrov
2. Database Design for Mere Mortals: A Hands-On Guide to Relational Database Design;

   Michael J. Hernandez
3. High Performance MySQL: Optimization, Backups, and Replication; Baron Schwartz
4. The Art of PostgreSQL; Dimitri Fontaine

Performance Engineering

1. Every Computer Performance Book: How to Avoid and Solve Performance Problems 
on The Computers You Work With; Bob Wescott
2. The Practical Performance Analyst; Neil Gunther
3. Systems Performance: Enterprise and the Cloud; Gregg
4. BPF Performance Tools; Gregg
5. Performance Solutions: A Practical Guide to Creating Responsive, Scalable Software; Connie U. Smith, Lloyd G. Williams
6. The Art of Capacity Planning: Scaling Web Resources; John Allspaw

7. Java Performance - The Definitive Guide; Scott Oaks
8. Optimizing Java: Practical Techniques for Improving JVM Application Performance; Benjamin J Evans , James Gough, Chris Newland
9. High Performance Browser Networking: What every web developer should know about networking and web performance; Ilya Grigorik
10. High-Performance Java Persistence; Vlad Mihalcea
11. Go-Perf Book, Thoughts on Go performance optimization, Damian Gryski
12. The Garbage Collection Handbook: The Art of Automatic Memory Management;

    Richard Jones, Antony Hosking, Eliot Moss

Programming languages

1. Core Java, Volume I and II; Horstmann

2. Thinking in Java; Eckel

3. OCA/OCP Java SE 7 Programmer I & II Study Guide; Sierra & Bates

4. Effective Java; Bloch

5. Java Concurrency in Practice; Goetz

6. Spring Boot in Action; Walls

7. Java EE 7 Development with WildFly; Ćmil, Matłoka, Marchioni

8. Java Performance - The Definitive Guide - Scott Oaks

9. The C Programming Language; Kernighan, Ritchie

10. The C++ Programming Language; Stroustrup

11. Effective Modern C++; Meyers

12. The Go Programming Language; Donovan and Kernighan

13. Learning Python: Powerful Object-Oriented Programming; Lutz

14. Scala for the Impatient; Horstmann

15. Functional Programming in Scala; Chiusano, Bjarnason

16. Scala in Depth, Suereth

17. Javascript: The Good Parts, Crockford

18. Seven Languages in Seven Weeks, Tate

19. The Rust Programming Language Paperback; Steve Klabnik

Design Patterns

1. Design Patterns; Gang of Four

2. Head First, Design Patterns; Sierra, Robson, Bates & Freeman

Algorithms & Maths

1. Algorithms Unlocked, Cormen

2. Introduction to Algorithms, Cormen

3. Algorithms, 4th Edition by Robert Sedgewick and Kevin Wayne

4. A Programmer's Introduction to Mathematics, Kun

Craftsmanship

1. Clean Code; Martin

2. Working Effectively with Legacy Code; Martin

3. The Pragmatic Programmer; Hunt

4. Test Driven Development: By Example, Hunt

5. The Software Craftsman: Professionalism, Pragmatism, Pride; Mancuso

Domain Driven-Design

1. Domain Driven-Design, Evans

2. Implementing Domain-Driven Design, Vernon

Devops

1. The Goal 1 & 2, Goldratt

2. The Phoenix Project, Kim

3. The DevOPS Handbook, Kim

Papers and articles

1. https://paperswelove.org/
2. What Every Programmer Should Know About Memory https://www.akkadia.org/drepper/cpumemory.pdf
3. First "Software Engineering" Nato Conference White Paper http://homepages.cs.ncl.ac.uk/brian.randell/NATO/nato1968.PDF
4. https://aws.amazon.com/whitepapers/architecting-for-the-aws-cloud-best-practices/
5. On the Impact of Memory Allocation on High-Performance Query Processing https://arxiv.org/abs/1905.01135
6. I/O Is Faster Than the CPU – Let’s Partition Resources and Eliminate (Most) OS Abstractions https://penberg.org/parakernel-hotos19.pdf
7. The benefits and costs of writing a POSIX kernel in a high-level language https://www.usenix.org/system/files/osdi18-cutler.pdf
8. Learn where some of the network sysctl variables fit into the Linux/Kernel network flow https://github.com/leandromoreira/linux-network-performance-parameters
9. Distributed consensus revised https://blog.acolyer.org/2019/05/07/distributed-consensus-revised-part-i/
10. Monitoring and Tuning the Linux Networking Stack: Sending Data https://blog.packagecloud.io/eng/2017/02/06/monitoring-tuning-linux-networking-stack-sending-data/
11. The Definitive Guide to Linux System Calls https://blog.packagecloud.io/eng/2016/04/05/the-definitive-guide-to-linux-system-calls/
12. https://blog.packagecloud.io/tag/linux/
13. Simple Testing Can Prevent Most Critical Failures: An Analysis of Production Failures in Distributed Data-Intensive Systems https://www.usenix.org/system/files/conference/osdi14/osdi14-paper-yuan.pdf
14. https://github.com/trimstray/technical-whitepapers

Various

1. Data and Reality: A Timeless Perspective on Perceiving and Managing Information in Our Imprecise World; by William Kent , Steve Hoberman