Memory Management
/ˈmɛməri ˈmænɪdʒmənt/
noun … “Organizing, allocating, and reclaiming memory.”
Memory Management is the process by which a computing system controls the allocation, usage, and reclamation of memory. It ensures that programs receive the memory they require while optimizing performance, preventing leaks, and avoiding conflicts. Effective memory management balances speed, space, and safety, and is implemented via operating system services, language runtimes, and hardware support.
Replication
/ˌrɛplɪˈkeɪʃən/
noun … “Copy data across nodes to ensure reliability.”
Replication is the process of creating and maintaining multiple copies of data across different nodes in a Distributed System. Its purpose is to enhance Availability, fault tolerance, and performance by allowing data to remain accessible even if some nodes fail. Replication is fundamental to distributed databases, file systems, and cloud storage platforms.
Consensus
/kənˈsɛnsəs/
noun … “Agreement among distributed nodes.”
Consensus is the process by which multiple nodes in a Distributed System agree on a single value or state despite failures, message delays, or node crashes. Consensus ensures that all non-faulty nodes make consistent decisions, which is crucial for maintaining data integrity, coordinating actions, and implementing replicated state machines. It underpins critical operations in databases, blockchain networks, and fault-tolerant services.
Global Interpreter Lock
/ˈɡloʊbəl ɪnˈtɜːrprɪtər lɒk/
noun … “A single-thread lock for memory safety in Python.”
Global Interpreter Lock, commonly abbreviated as GIL, is a mutex used in the CPython implementation of Python to ensure that only one thread executes Python bytecode at a time within a single process. The primary purpose of the GIL is to protect access to Python objects, preventing data corruption caused by concurrent modifications and simplifying memory management, especially in reference counting-based garbage collection.