https://DevOpsCloud.io -- Cloud Monk Losang Jinpa, Ph.D., MCSE/MCT, GitOps DevOps Engineer

Golang Performance Glossary

“ (SysPrfBGrg 2021)

Goroutines are lightweight threads managed by the Go runtime. They allow Go programs to execute concurrent tasks efficiently without the overhead of traditional system threads. Managing large numbers of goroutines can improve performance, but it is important to avoid blocking operations that can cause goroutine leaks. https://en.wikipedia.org/wiki/Go_(programming_language)#Concurrency:_goroutines_and_channels

Channels are a core feature of Go that allow goroutines to communicate with each other safely. Channels provide synchronization mechanisms to pass data between goroutines without the need for explicit locking. Misuse of channels can lead to performance bottlenecks if not handled efficiently. https://en.wikipedia.org/wiki/Go_(programming_language)#Channels

Garbage Collection in Go automatically manages memory allocation and deallocation. While this simplifies memory management for developers, garbage collection pauses can affect the performance of applications, especially in programs with high memory usage or frequent object allocations. https://en.wikipedia.org/wiki/Go_(programming_language)#Garbage_collection

Heap Allocation in Go occurs when objects are created dynamically at runtime. Minimizing heap allocation can reduce the workload on the garbage collector, improving application performance. Performance-conscious developers often use stack allocation to avoid unnecessary heap usage. https://github.com/golang/go/wiki/Heap_Allocations

Escape Analysis is a technique used by the Go compiler to determine whether variables can be allocated on the stack or if they need to be allocated on the heap. Efficient escape analysis helps reduce heap allocation, which can improve performance by reducing garbage collection overhead. https://en.wikipedia.org/wiki/Escape_analysis

Mutex is a synchronization primitive used in Go to prevent multiple goroutines from accessing shared data concurrently. Although mutexes are useful for ensuring data consistency, overuse or contention for mutex locks can degrade performance, leading to bottlenecks. https://golang.org/pkg/sync/#Mutex

Context Switching refers to the process of switching between goroutines or system threads in a Go program. While goroutines minimize the cost of context switching compared to traditional threads, excessive switching between goroutines can still introduce performance overhead. https://en.wikipedia.org/wiki/Context_switch

Defer is a Go keyword used to schedule a function to be executed after the surrounding function completes. While convenient for cleaning up resources, excessive use of defer in performance-critical code paths can introduce overhead, as it incurs a small but non-trivial cost for each deferred function call. https://golang.org/doc/effective_go#defer

Profiling in Go is performed using tools like pprof to measure the performance characteristics of a program. Go provides built-in support for profiling CPU usage, memory allocation, and goroutine execution, enabling developers to identify bottlenecks and optimize performance. https://pkg.go.dev/net/http/pprof

Inlining is an optimization performed by the Go compiler, where small functions are embedded directly into their call sites to reduce the overhead of function calls. While inlining can improve performance, aggressive inlining can increase binary size and reduce code readability. https://en.wikipedia.org/wiki/Inline_expansion

Stack Allocation in Go refers to the process of allocating memory for variables on the stack rather than the heap. Stack-allocated variables are automatically deallocated when a function returns, which reduces the workload on the garbage collector and improves performance. https://en.wikipedia.org/wiki/Stack-based_memory_allocation

Race Conditions occur when multiple goroutines access shared resources concurrently without proper synchronization, leading to unpredictable results. Go provides the race detector tool to help developers identify and resolve race conditions, as they can severely impact both performance and correctness. https://golang.org/doc/articles/race_detector.html

Sync.Pool is a Go standard library feature that provides a pool of reusable objects to reduce the frequency of heap allocations. Using sync.Pool can improve performance in scenarios where objects are frequently allocated and discarded, helping to reduce garbage collection pressure. https://pkg.go.dev/sync#Pool

Deadlocks occur when two or more goroutines are stuck waiting for each other to release resources, preventing the program from making progress. Go's concurrency model, while powerful, can lead to deadlocks if mutexes or channels are not used carefully. https://en.wikipedia.org/wiki/Deadlock

Work Stealing is a scheduling technique used by the Go runtime to balance the execution of goroutines across multiple CPU cores. It improves performance by ensuring that CPU cores remain busy, even when some goroutines finish their work earlier than others. https://en.wikipedia.org/wiki/Work_stealing

Batching refers to the practice of processing multiple operations together rather than individually to reduce overhead. In Go, batching can significantly improve performance when dealing with I/O operations, database queries, or network requests by reducing the frequency of context switches and I/O waits. https://en.wikipedia.org/wiki/Batch_processing

Escape Detection is part of Go's escape analysis that identifies variables that “escape” from the current function and must be allocated on the heap rather than the stack. Reducing the number of escaping variables can optimize performance by lowering heap allocation and garbage collection overhead. https://github.com/golang/go/wiki/EscapeAnalysis

Channel Buffering allows Go channels to store multiple values before a receiver retrieves them, reducing the need for synchronization between goroutines. Efficient use of buffered channels can improve concurrency performance by avoiding blocking when a sender or receiver is not immediately available. https://golang.org/doc/effective_go#channels

Go Scheduler is responsible for managing the execution of goroutines on system threads. The Go scheduler balances load across available CPU cores and minimizes the overhead of goroutine switching, ensuring optimal performance for concurrent applications. https://golang.org/doc/go1.1#sched

Atomic Operations in Go allow developers to perform operations on shared variables without the need for explicit locks. Atomic operations are faster than mutexes for simple operations, making them a preferred choice for lightweight concurrency scenarios where locking overhead would degrade performance. https://pkg.go.dev/sync/atomic

Memory Profiling in Go is a technique used to measure the memory usage of a program. Tools like pprof allow developers to track heap allocations, identify memory leaks, and optimize garbage collection performance, helping to reduce memory overhead in applications. https://pkg.go.dev/runtime/pprof

Channel Deadlocks occur when goroutines are indefinitely blocked waiting for data on a channel, but no other goroutine is sending or receiving data. These deadlocks can lead to performance issues and application crashes in Go programs, requiring careful design of channel communication to avoid them. https://golang.org/doc/effective_go#channels

Blocking Operations in Go refer to operations that halt the progress of a goroutine until a specific condition is met, such as waiting for I/O or channel communication. Excessive blocking operations can degrade concurrency and overall performance by preventing other tasks from running. https://golang.org/doc/go1.14#runtime

Heap Fragmentation in Go occurs when free memory is scattered in small, unusable blocks, making it difficult for the garbage collector to allocate new objects efficiently. Reducing heap fragmentation through efficient memory management improves performance by minimizing garbage collection pauses. https://en.wikipedia.org/wiki/Fragmentation_(computing)

Select Statement in Go is used to manage multiple channel operations concurrently. The select statement enables non-blocking channel communication and improves performance by allowing the program to respond to whichever channel operation is ready first. https://golang.org/doc/effective_go#select

Profiling Granularity refers to the level of detail captured during performance profiling. In Go, finer profiling granularity provides more precise data on function execution times, memory usage, and goroutine behavior, helping developers optimize performance-critical parts of their applications. https://pkg.go.dev/runtime/pprof

WaitGroup is a concurrency primitive in Go that waits for a collection of goroutines to finish executing. Using a WaitGroup ensures that the main program doesn’t exit prematurely, improving program stability and performance by allowing goroutines to complete their tasks. https://golang.org/pkg/sync/#WaitGroup

Lazy Initialization in Go refers to deferring the initialization of a resource or data structure until it is needed. This technique improves performance by avoiding unnecessary resource allocation and speeding up program startup, particularly in applications that may not require all initialized resources. https://en.wikipedia.org/wiki/Lazy_initialization

Memory Pooling in Go is a technique where frequently used objects are reused instead of constantly allocating and deallocating memory. This can significantly reduce the strain on the garbage collector and improve performance in applications with frequent allocations. https://golang.org/pkg/sync/#Pool

Inlining Threshold is the limit at which the Go compiler decides whether to inline a function based on its size and complexity. Controlling the inlining threshold improves performance by reducing function call overhead while balancing the binary size and complexity of the compiled program. https://en.wikipedia.org/wiki/Inline_expansion

Data Races occur in Go when multiple goroutines access shared memory concurrently, and at least one access is a write. Data races lead to unpredictable program behavior and can severely impact performance and correctness. Go’s race detector helps identify and eliminate data races during development. https://golang.org/doc/articles/race_detector.html

CPU Profiling is a performance analysis technique in Go that tracks the CPU usage of various functions and goroutines. Using pprof for CPU profiling helps developers identify functions with high CPU consumption, enabling targeted optimizations to improve application speed. https://golang.org/pkg/runtime/pprof/

Channel Synchronization in Go is a technique for coordinating the execution of multiple goroutines using channels. By using channel synchronization, developers can manage dependencies between goroutines efficiently, preventing race conditions and improving program stability. https://golang.org/doc/effective_go#channels

Garbage Collection Latency is the time taken by the Go garbage collector to free unused memory. While garbage collection reduces memory leaks, excessive latency can lead to noticeable pauses in application performance, particularly in latency-sensitive applications. https://golang.org/doc/go1.5#garbage_collection

Non-Blocking Channels are used in Go to prevent goroutines from waiting on channel operations. By using non-blocking channels, developers can improve application responsiveness and avoid performance bottlenecks in situations where channels are not immediately available. https://golang.org/doc/effective_go#channels

Load Shedding is a technique used in Go to handle high traffic by discarding low-priority or excess requests. Implementing load shedding helps maintain system responsiveness under heavy load, ensuring that critical operations are prioritized and reducing the risk of goroutine overload. https://en.wikipedia.org/wiki/Load_shedding_(computing)

Inlining Heuristics are guidelines used by the Go compiler to decide which functions to inline. Effective inlining heuristics improve performance by reducing function call overhead while balancing the compiled binary size and complexity. https://en.wikipedia.org/wiki/Inline_expansion

Memory Leak Detection is a crucial aspect of performance management in Go, ensuring that all allocated memory is freed after use. The Go runtime and pprof provide tools for identifying memory leaks, which can cause excessive garbage collection and impact system performance over time. https://golang.org/pkg/runtime/pprof/

Buffered Channel Capacity refers to the number of values a buffered channel can hold before blocking further sends. Choosing an appropriate buffered channel capacity improves performance by reducing blocking and synchronization costs between goroutines, especially in high-throughput scenarios. https://golang.org/doc/effective_go#channels

Fan-Out/Fan-In Pattern is a concurrency design pattern in Go used to parallelize tasks by creating multiple goroutines (fan-out) and then collecting their results (fan-in) through a single channel. This pattern enhances performance by distributing workload while maintaining organized result aggregation. https://blog.golang.org/pipelines

Heap Profiling in Go is a technique that tracks memory allocations on the heap over time. Using tools like pprof to perform heap profiling helps developers identify memory-intensive parts of their application, allowing them to optimize memory usage and reduce garbage collection overhead. https://golang.org/pkg/runtime/pprof/

Go Memory Model defines how goroutines interact with memory when using synchronization primitives like channels and mutexes. Understanding the Go memory model is crucial for writing concurrent programs that are free from race conditions and ensuring predictable performance. https://golang.org/ref/mem

Tight Loops in Go refer to loops that execute continuously without any form of blocking or yielding control, often consuming excessive CPU resources. Optimizing or breaking up tight loops can significantly improve performance, especially in goroutines that run alongside other tasks. https://en.wikipedia.org/wiki/Busy_waiting

Fan-Out Concurrency is a concurrency pattern where one goroutine spawns multiple worker goroutines to handle tasks in parallel. Properly managing fan-out concurrency improves performance by maximizing CPU utilization, but it requires careful control of goroutine lifetimes and resources to avoid goroutine leaks. https://golang.org/doc/effective_go#channels

Deferred Functions in Go are used to clean up resources after a function call. Although defer is a useful construct for resource management, overusing deferred functions in performance-critical paths can add overhead, as each deferred call introduces a small cost at runtime. https://golang.org/doc/effective_go#defer

Pipelining is a concurrency pattern in Go where the output of one goroutine becomes the input of another through channels. This pattern improves system throughput by allowing stages of computation to proceed in parallel, but it requires careful handling of channel synchronization to avoid bottlenecks. https://blog.golang.org/pipelines

Garbage Collection Overhead in Go refers to the performance cost associated with the automatic management of memory by the garbage collector. Reducing memory allocations or using sync.Pool can minimize garbage collection overhead and improve the performance of memory-intensive applications. https://golang.org/doc/go1.5#garbage_collection

Preemption in Go allows the scheduler to interrupt long-running goroutines to give other goroutines a chance to execute. While preemption improves fairness in task scheduling, it can introduce small performance costs due to the interruption and context switching overhead. https://golang.org/doc/go1.14#runtime

Runtime Package in Go provides functions that interact directly with the Go runtime system, such as controlling garbage collection, goroutines, and memory statistics. Using the runtime package efficiently allows developers to fine-tune application performance based on runtime conditions. https://golang.org/pkg/runtime/

Timer Heap is a data structure used in the Go runtime to manage scheduled tasks and timeouts. Efficient management of the timer heap ensures that time-based operations, such as delayed function execution or timeouts in goroutines, occur with minimal performance overhead. https://golang.org/pkg/time/#Timer

Go Scheduler Latency refers to the delay in scheduling a goroutine for execution. While the Go scheduler efficiently manages thousands of goroutines, under heavy load, scheduler latency can increase, causing delays in task execution and affecting performance, especially in real-time applications. https://golang.org/doc/go1.1#sched

Atomic Value in Go provides low-level synchronization without using mutexes. The sync/atomic package allows operations like reading and writing shared variables atomically, improving performance in situations where fine-grained locking would introduce too much overhead. https://golang.org/pkg/sync/atomic/

Timer Drift occurs when scheduled tasks in Go do not execute at the precise time due to goroutine scheduling delays or other system load. While small amounts of timer drift are usually acceptable, significant drift can affect the performance of time-sensitive applications. https://golang.org/pkg/time/

Memory Zeroing is the process where Go sets memory to zero when it is allocated to prevent programs from reading uninitialized data. While essential for safety, excessive memory zeroing can degrade performance in memory-heavy applications, especially when large blocks of memory are allocated frequently. https://en.wikipedia.org/wiki/Zero_initiation

Map Performance in Go depends on the use case, as maps are hash tables that offer average O(1) time complexity for lookups and inserts. However, poor key distribution or frequent resizing can cause performance degradation, particularly when used in high-concurrency environments. https://golang.org/doc/effective_go#maps

Work Pool in Go is a design pattern where a pool of goroutines is used to process tasks concurrently. By limiting the number of goroutines to match the number of available CPU cores, work pools can maximize resource utilization and prevent excessive context switching. https://golang.org/doc/effective_go#concurrency

Backpressure in Go refers to a situation where producers of data generate it faster than consumers can process it. Managing backpressure using buffered channels or goroutine rate limiting can help maintain performance in high-throughput applications. https://blog.golang.org/pipelines

Memory Alignment affects performance in Go as misaligned data structures require more CPU cycles to access. Ensuring proper memory alignment when defining data structures can improve memory access speeds, especially in performance-critical applications. https://en.wikipedia.org/wiki/Data_structure_alignment

Spurious Wakeup refers to the phenomenon where a goroutine is woken up by the scheduler without a corresponding event or condition. While rare in Go, handling spurious wakeups carefully ensures that goroutines don’t waste CPU time processing unnecessary wakeups. https://en.wikipedia.org/wiki/Spurious_wakeup

Trace Tool in Go provides detailed information about the execution of goroutines, syscalls, and GC events. Using the trace tool, developers can gain insights into bottlenecks and optimize performance by identifying long goroutine stalls or frequent garbage collection pauses. https://golang.org/pkg/runtime/trace/

Go Benchmarking is the process of measuring the performance of Go code using the built-in testing/benchmark package. Benchmarking helps identify slow functions or operations by providing metrics like execution time and memory allocations, allowing developers to optimize performance-critical code. https://pkg.go.dev/testing#hdr-Benchmarks

Channel Select Latency refers to the time it takes for the select statement in Go to choose an available communication channel. Poorly designed select blocks or high contention for channels can increase channel select latency, negatively affecting concurrent program performance. https://golang.org/doc/effective_go#select

Heap Size Tuning is the process of adjusting the size of the memory heap in Go to optimize garbage collection performance. By managing heap growth and limiting its size, developers can reduce garbage collection frequency and avoid large pauses, improving application responsiveness. https://golang.org/doc/go1.5#garbage_collection

Concurrency Granularity refers to the level at which tasks are divided into smaller units of work for concurrent execution in Go. Striking the right balance in concurrency granularity helps optimize goroutine performance by avoiding the overhead of too many small tasks or too few large ones. https://en.wikipedia.org/wiki/Granularity_(parallel_computing)

GC Tuning in Go is the process of adjusting the garbage collector's behavior to optimize performance, especially for memory-intensive applications. GC tuning can include adjusting GOGC, Go’s garbage collection tuning variable, to control how often the collector runs and how much memory is used. https://golang.org/doc/go1.5#garbage_collection

Runtime Latency in Go refers to delays introduced by the Go runtime itself, including garbage collection, scheduler overhead, and goroutine switching. Reducing runtime latency is key to improving the responsiveness and throughput of Go applications, especially in high-concurrency environments. https://golang.org/doc/go1.14#runtime

Channel Contention occurs when multiple goroutines try to access the same channel simultaneously, leading to delays. Reducing channel contention by using buffered channels or distributing tasks across multiple channels can improve concurrency and overall system performance. https://golang.org/doc/effective_go#channels

Garbage Collection Pauses are the times when the Go garbage collector stops the application to reclaim memory. Minimizing GC pauses through careful memory management and reducing object allocation frequency is crucial for maintaining high performance in latency-sensitive applications. https://golang.org/doc/go1.5#garbage_collection

Memory Footprint refers to the amount of memory used by a Go program during its execution. Keeping the memory footprint low by optimizing data structures and reducing object allocation helps minimize garbage collection pressure and improve overall application performance. https://en.wikipedia.org/wiki/Memory_footprint

Syscall Overhead in Go refers to the cost associated with making system calls from user-space code. Excessive syscalls can degrade performance by introducing context switches between user mode and kernel mode, so reducing syscall frequency improves overall system efficiency. https://golang.org/pkg/syscall/

Pprof Tool is a Go performance profiling tool that collects data on CPU usage, memory allocation, and goroutine activity. By analyzing the profiles generated by pprof, developers can pinpoint bottlenecks in their code and optimize for better performance. https://pkg.go.dev/net/http/pprof

Defer Overhead refers to the performance cost associated with using the defer keyword in Go. While defer simplifies resource management, it introduces a small overhead for each deferred function, which can accumulate in performance-critical paths. https://golang.org/doc/effective_go#defer

GOMAXPROCS is an environment variable in Go that controls the number of operating system threads allocated for running goroutines. Tuning GOMAXPROCS appropriately for multi-core systems improves CPU utilization and can significantly enhance parallel performance. https://golang.org/pkg/runtime/#GOMAXPROCS

Scheduler Fairness refers to how evenly the Go scheduler distributes CPU time among running goroutines. Poor scheduler fairness can lead to some goroutines being starved of CPU resources, impacting overall program efficiency and performance. https://golang.org/doc/go1.1#sched

Lazy Initialization in Go refers to delaying the creation of an object or resource until it is first needed. This technique improves startup performance by reducing unnecessary allocations and defers the cost of initialization to when it is truly required. https://en.wikipedia.org/wiki/Lazy_initialization

Channel Fan-Out is a concurrency pattern in Go where a single goroutine distributes work to multiple worker goroutines via a channel. Efficient use of fan-out helps scale work across multiple CPU cores, improving throughput for parallelizable workloads. https://blog.golang.org/pipelines

Sync.Cond is a synchronization primitive in Go that allows one or more goroutines to wait until a condition is met. It is particularly useful for signaling between goroutines and coordinating concurrent tasks, but improper use can introduce deadlocks or excessive waiting. https://golang.org/pkg/sync/#Cond

False Sharing in Go occurs when multiple goroutines modify different variables that reside in the same cache line, causing unnecessary invalidation of the CPU cache. False sharing can degrade performance by increasing memory access latency in concurrent programs. https://en.wikipedia.org/wiki/False_sharing

Garbage Collection Mark Phase is the part of the Go garbage collection process where live objects are identified. The time spent in the mark phase can affect application performance, especially in programs with a large number of heap-allocated objects. https://en.wikipedia.org/wiki/Tracing_garbage_collection

Go Escape Analysis determines whether variables in a function can be allocated on the stack or must be moved to the heap. Efficient escape analysis helps minimize heap allocation, reducing the load on the garbage collector and improving performance. https://en.wikipedia.org/wiki/Escape_analysis

Go Race Detector is a tool that identifies race conditions in Go programs during execution. By using the race detector during development, developers can detect and resolve concurrency issues early, improving program correctness and avoiding performance problems caused by data races. https://golang.org/doc/articles/race_detector.html

Heap Fragmentation occurs when memory is allocated and freed in a way that leaves small, unusable gaps in the heap, leading to inefficient memory usage. In Go, managing memory allocations carefully can reduce heap fragmentation, improving performance and lowering garbage collection overhead. https://en.wikipedia.org/wiki/Fragmentation_(computing)

Channel Blocking in Go happens when a sender or receiver waits for the other side to be ready on an unbuffered channel. Reducing unnecessary channel blocking improves concurrency by allowing goroutines to make progress without waiting, thus enhancing performance in high-load applications. https://golang.org/doc/effective_go#channels

Panic and Recover is a mechanism in Go for handling unexpected runtime errors. Although panic and recover simplify error handling, overuse can degrade performance due to the overhead of creating stack traces and managing control flow interruptions. https://golang.org/doc/effective_go#panic

Spinning Goroutines occur when a goroutine repeatedly checks a condition without blocking or yielding control, wasting CPU cycles. In high-concurrency programs, avoiding spinning goroutines improves efficiency by freeing up CPU resources for other tasks. https://en.wikipedia.org/wiki/Busy_waiting

Write Barriers are mechanisms used during the garbage collection process in Go to track changes to memory. While write barriers help maintain memory safety, they introduce slight overhead in programs with frequent writes to heap-allocated objects, affecting performance. https://en.wikipedia.org/wiki/Write_barrier

Memory Churn in Go refers to the rapid allocation and deallocation of objects, leading to increased garbage collection activity. Reducing memory churn by reusing objects or using sync.Pool can improve performance by lowering the frequency of garbage collection cycles. https://en.wikipedia.org/wiki/Garbage_collection_(computer_science)

Thread Parking is a mechanism where goroutines are suspended (parked) when they are waiting for resources or synchronization events. While parking threads helps conserve CPU resources, excessive parking and resuming of goroutines can introduce scheduling delays, impacting performance. https://golang.org/doc/go1.1#sched

Channel Deadlock happens when all goroutines are waiting for each other to send or receive on channels, resulting in a system-wide freeze. Careful design of channel communication patterns can prevent channel deadlocks and ensure smooth, concurrent operation of the program. https://golang.org/doc/effective_go#channels

Preemptive Scheduling in Go allows the runtime to interrupt long-running goroutines to ensure fair CPU time distribution among all goroutines. This improves system responsiveness but may introduce minor overhead due to context switching, especially in CPU-bound workloads. https://golang.org/doc/go1.14#runtime

GC Safepoints in Go are specific points during the execution of a program where the garbage collector can safely interrupt running goroutines to perform memory management tasks. Frequent safepoints can add overhead, especially in programs with many goroutines or memory allocations. https://en.wikipedia.org/wiki/Safepoint

Channel Overflow occurs when a buffered channel in Go becomes full, causing the sender to block until there is space available. Properly sizing buffered channels based on the expected workload helps prevent channel overflow, which can lead to performance bottlenecks in high-concurrency applications. https://golang.org/doc/effective_go#channels

Goroutine Leaks happen when goroutines are spawned but never terminate, consuming system resources indefinitely. These leaks can degrade performance over time, especially in long-running programs, by exhausting available memory and increasing scheduler overhead. https://golang.org/doc/effective_go#goroutines

Memory Bound refers to a situation in which the performance of a Go program is limited by memory bandwidth rather than CPU speed. Optimizing memory access patterns, reducing memory allocations, and using cache-friendly data structures can improve performance in memory-bound applications. https://en.wikipedia.org/wiki/Memory_bound_function

Stack Growth in Go refers to the automatic resizing of goroutine stacks as needed during execution. While stack growth allows goroutines to use memory efficiently, frequent stack growth and shrinking can introduce performance overhead in programs with highly variable memory needs. https://golang.org/doc/faq#stack

Channel Fan-In is a concurrency pattern where multiple goroutines send results to a single channel. Efficient use of fan-in can improve throughput in parallelized tasks by consolidating the output of multiple goroutines into a single result stream. https://blog.golang.org/pipelines

Select Timeout in Go is used to prevent blocking indefinitely on a select statement. By introducing timeouts, developers can improve the performance of concurrent programs by ensuring that goroutines don't get stuck waiting for events that may never occur. https://golang.org/doc/effective_go#timeouts

Syscall Latency refers to the time taken for a Go program to execute system calls. Minimizing syscall latency through batching or avoiding unnecessary system calls can significantly improve performance in I/O-intensive programs. https://golang.org/pkg/syscall/

Goroutine Preemption is the ability of the Go scheduler to interrupt long-running goroutines to ensure other goroutines get CPU time. While this improves fairness, frequent preemption can introduce minor overhead due to context switching between goroutines. https://golang.org/doc/go1.14#runtime

Cache Misses occur when data needed by a goroutine is not found in the CPU cache and must be fetched from a slower memory tier, such as main memory. Reducing cache misses by using cache-friendly data structures and algorithms can improve performance in memory-bound Go applications. https://en.wikipedia.org/wiki/CPU_cache

Concurrent Map Access in Go refers to the use of maps by multiple goroutines without proper synchronization, which can cause data races and lead to unpredictable behavior. To avoid performance degradation and data corruption, sync.Map or external synchronization mechanisms like mutexes should be used for concurrent map access. https://golang.org/pkg/sync/#Map

Write Contention occurs when multiple goroutines attempt to write to the same shared resource, leading to performance bottlenecks. Properly managing write contention by using locks, atomic operations, or reducing shared resources improves concurrency and overall performance. https://golang.org/pkg/sync/#RWMutex

Syscall Interruption happens when a goroutine performing a system call is interrupted by the Go scheduler or a goroutine preemption. This can introduce delays in I/O-bound applications, as interrupted system calls may need to be retried, affecting throughput and latency. https://golang.org/pkg/syscall/

Garbage Collection Root Set refers to the set of memory objects that are reachable from outside the heap, which the garbage collector must scan during each GC cycle. Reducing the size of the root set can improve GC efficiency and reduce garbage collection pauses in Go applications. https://en.wikipedia.org/wiki/Tracing_garbage_collection

Channel Throttling is a technique used to control the rate at which goroutines send data through a channel to avoid overwhelming the receiver. Implementing channel throttling improves performance by preventing bottlenecks and maintaining a steady flow of data in high-throughput systems. https://golang.org/doc/effective_go#channels

Deadlock Detection in Go involves identifying and resolving situations where two or more goroutines are waiting for each other to release resources, causing the program to halt. Preventing deadlocks through proper design of synchronization mechanisms like mutexes or channels is essential for maintaining performance. https://en.wikipedia.org/wiki/Deadlock

Synchronous vs. Asynchronous I/O refers to the two methods of handling I/O operations in Go. Synchronous I/O blocks the calling goroutine until the operation completes, while asynchronous I/O allows the program to perform other tasks while waiting. Choosing between these methods impacts the performance of I/O-bound applications. https://en.wikipedia.org/wiki/Asynchronous_I/O

Work Stealing Scheduler is a feature in the Go runtime that enables idle goroutines to “steal” work from other busy goroutines. This helps balance workload across available CPU cores, improving system utilization and reducing the time required to complete concurrent tasks. https://en.wikipedia.org/wiki/Work_stealing

Channel Buffer Sizing refers to choosing the appropriate size for a buffered channel in Go. Correct channel buffer sizing improves performance by reducing the likelihood of goroutines blocking during send and receive operations, especially in high-concurrency applications. https://golang.org/doc/effective_go#channels

Adaptive Spinning is a strategy used in lock algorithms in Go where a goroutine will spin for a short period of time before blocking, in hopes that the lock becomes available. Adaptive spinning improves performance by avoiding the overhead of goroutine suspension and context switching when the lock is briefly unavailable. https://en.wikipedia.org/wiki/Spinlock

Memory Profiling in Go is the process of analyzing how memory is allocated and used by a program. Using tools like pprof, developers can identify excessive memory usage or memory leaks, enabling them to optimize memory management and reduce garbage collection pressure. https://golang.org/pkg/runtime/pprof/

Read Contention happens when multiple goroutines attempt to read from a shared resource simultaneously, causing delays. While read contention is typically less severe than write contention, managing it with proper synchronization techniques, such as read-write locks (RWMutex), improves concurrent read performance. https://golang.org/pkg/sync/#RWMutex

Garbage Collection Sweeping Phase is the final stage of Go's garbage collection process, where memory that is no longer in use is reclaimed. Efficient sweeping reduces the time the garbage collector spends pausing the program, improving overall performance. https://en.wikipedia.org/wiki/Tracing_garbage_collection#Phases

Backoff Algorithm in Go refers to delaying the retry of a failed operation, such as sending data through a channel, to avoid overwhelming the system. Implementing a backoff algorithm helps manage load in high-concurrency environments, improving performance and stability. https://en.wikipedia.org/wiki/Exponential_backoff

Thread Local Storage (TLS) refers to memory allocated specifically for each thread. Although Go relies on goroutines instead of traditional threads, managing thread-local data properly can improve performance, especially in Cgo calls where TLS is used. https://golang.org/doc/go1.6#cgo

Race Condition Avoidance involves using synchronization techniques such as channels, mutexes, or atomic operations to prevent multiple goroutines from accessing shared data concurrently in unsafe ways. Avoiding race conditions ensures program correctness and improves performance by preventing erratic behavior. https://golang.org/doc/articles/race_detector.html

Concurrent Garbage Collection in Go allows the program to continue executing while the garbage collector is running in the background. This minimizes GC pauses and improves performance, especially in applications with high memory usage. https://golang.org/doc/go1.5#garbage_collection

Network Latency refers to the time it takes for data to travel from one point to another in a network. In Go, minimizing network latency through optimizations like connection pooling, minimizing round trips, and optimizing I/O handling improves the performance of networked applications. https://en.wikipedia.org/wiki/Network_latency

Lock-Free Programming in Go refers to using algorithms that avoid locks to synchronize access to shared resources. By reducing reliance on locks, lock-free programming minimizes contention and improves performance in highly concurrent systems. However, it is difficult to implement correctly. https://en.wikipedia.org/wiki/Non-blocking_algorithm

Context Package in Go is used to carry deadlines, cancellation signals, and other request-scoped values across API boundaries and between goroutines. Using the context package effectively ensures better control over long-running operations, reducing resource leaks and improving program performance. https://golang.org/pkg/context/

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Linux/UNIX commands for assessing system performance include:

uptime the system reliability and load average
Top (Unix) | top for an overall system view
Vmstat (Unix) | vmstat vmstat reports information about runnable or blocked processes, memory, paging, block I/O, traps, and CPU.
Htop (Unix) | htop interactive process viewer
dstat, atop helps correlate all existing resource data for processes, memory, paging, block I/O, traps, and CPU activity.
iftop interactive network traffic viewer per interface
nethogs interactive network traffic viewer per process
iotop interactive I/O viewer
Iostat (Unix) | iostat for storage I/O statistics
Netstat (Unix) | netstat for network statistics
mpstat for CPU statistics
tload load average graph for terminal
xload load average graph for X
/proc/loadavg text file containing load average

(Event monitoring - Event log analysis, Google Cloud's operations suite (formerly Stackdriver), htop, mpstat, macOS Activity Monitor, Nagios Core, Network monitoring, netstat-iproute2, proc filesystem (procfs)]] - ps (Unix), System monitor, sar (Unix) - systat (BSD), top - top (table of processes), vmstat), Moore’s law, Multicore - Multi-core processor, Multiprocessor, Multithreading, mutex, Network capacity, Network congestion, Network I/O, Network latency (Network delay, End-to-end delay, packet loss, ping - ping (networking utility) (Packet InterNet Groper) - traceroute - netsniff-ng, Round-trip delay (RTD) - Round-trip time (RTT)), Network performance, Network switch performance, Network usage - Network utilization, NIC performance, NVMe, NVMe performance, Observability, Operating system performance, Optimization (Donald Knuth: “Premature optimization is the root of all evil), Parallel processing, Parallel programming (Embarrassingly parallel), Perceived performance, Performance analysis (Profiling), Performance design, Performance engineer, Performance equation, Performance evaluation, Performance gains, Performance Mantras, Performance measurement (Quantifying performance, Performance metrics), Perfmon, Performance testing, Performance tuning, PowerShell performance, Power consumption - Performance per watt, Processing power, Processing speed, Productivity, Python performance (CPython performance, PyPy performance - PyPy JIT), Quality of service (QOS) performance, Refactoring, Reliability, Response time, Resource usage - Resource utilization, Router performance (Processing delay - Queuing delay), Ruby performance, Rust performance, Scala performance, Scalability, Scalability test, Server performance, Size and weight, Slow, Software performance, Software performance testing, Speed, Stress testing, SSD, SSD performance, Swift performance, Supercomputing, Tbps, Throughput, Time (Time units, Nanosecond, Millisecond, Frequency (rate), Startup time delay - Warm-up time, Execution time), TPU - Tensor processing unit, Tracing, Transistor count, TypeScript performance, Virtual memory performance (Thrashing), Volume testing, WebAssembly, Web framework performance, Web performance, Windows performance (Windows Performance Monitor). (navbar_performance)

Golang Vocabulary List (Sorted by Popularity)

SHORTEN THIS to 20 ITEMS! navbar_golang

Abstract Syntax Trees, Absolute Time, Advanced Go Concurrency Patterns, Alias Declarations, Alternate Package Names, Anonymous Fields, Anonymous Functions, Append Function, Array Types, Assertion of Types, Assignability Rules, Atomic Package, Augmented Assignment, Authentication with Context, Auto-Increment Versions, Backward Compatibility, Basic Types, Benchmark Functions, Binary Package, Blank Identifier, Block Statements, Boolean Expressions, Bridge Methods, Build Constraints, Build Tags, Builtin Functions, Byte Order, Byte Slices, Bytes Package, Caching Modules, Cancellation with Context, Cap Function, Channel Direction, Channel Operations, Channel Types, Channels, Character Literals, Closure Functions, Code Generation, Code Formatting, Code Review Comments, Collecting Garbage, Composite Literals, Composition over Inheritance, Concurrency Patterns, Conditional Compilation, Constant Declarations, Constant Expressions, Context Package, Continue Statements, Control Flow, Convert Function, Copy Function, Cross Compilation, Cyclic Dependencies, Cyclic Imports, Data Alignment, Data Race Detection, Deadlock Detection, Defer Statements, Deferred Function Calls, Deleting Map Entries, Dependency Management, Design Philosophy, Detecting Deadlocks, Directive Comments, Directory Structure, Discarded Errors, Documentation Comments, Dot Imports, Dynamic Linking, Effective Go, Empty Interface, Embedding Interfaces, Embedding Structs, Embedded Files, Encoding Binary, Encoding CSV, Encoding JSON, Encoding XML, Endianness, Enforcing Contracts, Error Handling, Error Interface, Error Types, Escape Analysis, Executable Packages, Exit Codes, Expvar Package, Exported Names, Expression Statements, Extending Interfaces, External Linking, Fallthrough Keyword, Fatal Errors, Field Tags, File Inclusion, File I/O, File Paths, First-Class Functions, Floating-Point Numbers, FMT Package, For Loops, Format Specifiers, Formatting Source Code, Function Declarations, Function Literals, Function Types, Functional Options, Garbage Collection, GC Tuning, Generics, Global Variables, Go Build Command, Go Command, Go Concurrency Patterns, Go Doc Tool, Go FMT Tool, Go Generate Command, Go Get Command, Go Install Command, Go Modules, Go Playground, Go Run Command, Go Test Command, Go Toolchain, Go Vet Tool, Go Workspaces, GOB Encoding, Godoc Documentation, Gofmt Formatting, Goroutine Leaks, Goroutines, Gosec Security Scanner, GOTRACEBACK Environment Variable, Gotype Tool, GOVERSION File, Gowork Files, Heap Allocation, Heap Dump, HTML Templates, IOTA Identifier, Iota Enumerations, IO Package, IO Reader, IO Writer, Import Declarations, Import Paths, Imports Formatting, Incremental Compilation, Indentation Rules, Index Expressions, Indexed Elements, Initialization Order, Init Functions, Input Validation, Integer Overflow, Integer Types, Integration Testing, Interface Assertions, Interface Embedding, Interface Satisfaction, Interface Types, Internal Packages, Internationalization, Interoperability with C, Invariably Safe Initialization, IO Utility Functions, JSON Marshalling, JSON Unmarshalling, Keywords, Lambda Functions, Language Specification, Lateral Type Inference, Lazy Initialization, Leaking Goroutines, Len Function, Linter Tools, Literal Types, Live Variable Analysis, Load Testing, Logging Conventions, Logging Package, Loop Control Statements, Magic Comments, Make Function, Map Types, Maps, Memory Allocation, Memory Model, Memory Profiling, Method Declarations, Method Expressions, Method Sets, Methods, Module Compatibility, Module Caching, Module Proxy, Module Replacements, Module Versions, Module-aware Mode, Modules, Mutexes, Named Return Values, Name Mangling, Name Resolution, Name Shadowing, Naming Conventions, Nesting Structs, Net HTTP Package, Net Package, Nil Interface, Nil Pointer Dereference, Nil Slices, Nil Values, Non-Blocking Channels, Number Literals, Object Files, Octal Literals, Open Source License, Operator Precedence, Optimization Flags, Order of Evaluation, OS Package, Package Documentation, Package Initialization, Package Names, Package Visibility, Packages, Packages with Main, Panic and Recover, Panic Defer Recover, Parallel Testing, Parsing Techniques, Path Separators, Performance Optimization, Performance Profiling, Pipeline Patterns, Plain Functions, Pointer Arithmetic, Pointer Receivers, Pointers, Polymorphism, Portability, Postfix Operators, Predeclared Identifiers, Predefined Constants, Preemption in Scheduler, Primitive Types, Print Functions, Profiling Tools, Project Layout, Protobuf Integration, Public and Private Identifiers, Punctuator Tokens, Race Conditions, Race Detector, Range Expressions, Range Loops, Read-Only Interfaces, Receiver Functions, Receiver Types, Recover Function, Recursion, Reflection, Regular Expressions, Relative Imports, Relocation Information, Remote Import Paths, Repeatable Builds, Replace Directive, Reserved Words, Resource Management, Response Writers, RESTful APIs, Return Statements, Reusing Code, Rune Literals, Runes, Runtime Package, Satisfying Interfaces, Scopes, Select Statements, Selective Imports, Self-Referential Functions, Semaphore Patterns, Send-Only Channels, Shadowing Variables, Short Declarations, Signals Handling, Signed Integers, Simple Statements, Single Assignment, Single Binary Applications, Slice Expressions, Slice Internals, Slice Length and Capacity, Slice of Slices, Slices, Source File Organization, Source to Source Compilation, Space Optimization, Spawned Processes, Specification Compliance, Split Package, Sprint Functions, Stack Traces, Standard Library, Static Analysis, Static Linking, String Conversions, String Formatting, String Literals, Strings Package, Struct Embedding, Struct Literals, Struct Tags, Struct Types, Structs, Subtests, Switch Statements, Synchronization Primitives, Syntactic Sugar, System Calls, Tab Characters, TCP Connections, Template Parsing, Template Rendering, Template Syntax, Templates Package, Ternary Operators, Testing, Testing Package, Text Templates, Third-Party Packages, Thread Safety, Time Package, Timeouts, TLS Configuration, Tokenization, Toolchain, Trace Tool, Tracing, Tracking Dependencies, Type Aliases, Type Assertions, Type Declarations, Type Embedding, Type Inference, Type Parameters, Type Switches, Typed Constants, Types, UID and GID, Unhandled Errors, Unicode Characters, Unicode Package, Unique Package Names, Unsafe Package, Unstructured Concurrency, Untyped Constants, Unused Imports, Unused Variables, Update Statements, URL Parsing, UTF-8 Encoding, Value Receivers, Variable Declarations, Variadic Functions, Vendor Directory, Vendoring, Version Control, Version Pinning, Visibility Rules, WaitGroup, Walkthrough Examples, Web Applications, Whitespace Rules, Wildcards in Imports, Write Barriers, Zero Initialization, Zero Values

Golang: Golang Fundamentals, Golang Inventor - Golang Language Designer: Ken Thompson, Robert Griesemer, Rob Pike of Google, Go abstraction, Golang Glossary - Glossaire de Golang - French, Go agile, Go ahead-of-time (AOT), Go AI, Go algebraic data types, Go algorithms, Go Android, Go anonymous functions, Go AOP, Go AOT, Go APIs, Go arguments, Go ARM, Go arithmetic, Go arrays, Go aspect-oriented, Go assignment, Go associative arrays, Go async, Go asynchronous callbacks, Go asynchronous programming, Go automatic variables, Go automation, Go Avro, Go backend, Go backwards compatibility, Go block scoped, Go Booleans, Go Boolean expressions, Go buffer overflow, Go builds, Go built-in types, Go bytecode, Go cache, Go caching, Go call by reference, Go call by value, Go callbacks, Go call stack, Go casting, Go characters, Go Chocolatey, Go CI/CD, Go classes, Go CLI, Go client-side, Go closures, Go cloud (Go Cloud Native-Go AWS-Go Azure-Go GCP-Go IBM Cloud-Go IBM Mainframe-Go OCI), Go code smells, Go coercion, Go collections, Go command-line interface, Go commands, Go comments, Go compilers, Go complex numbers, Go composition, Go configuration, Go concurrency, Go concurrent programming, Go conditional expressions, Go conferences, Go constants, Go constructors, Go containers, Go control flow, Go control structures, Go coroutines, Go crashes, Go creators, Go currying, Go databases, Go data manipulation, Go data persistence, Go data science, Go data serialization, Go Built-In Data Types, Go data structures, Go data synchronization, Go dates, Go dates and times, Go deadlocks, Go debugging, Go declarative, Go deferred callbacks, Go delegates, Go delegation, Go dependency injection, Go design patterns, Go designers, Go destructors, Go DevOps, Go dictionaries, Go dictionary comprehensions, Go DI, Go distributed software, Go distributions, Go distros, Go DL, Go Docker, Go do-while, Go DSL, Go duck typing, Go dynamic binding, Go dynamic scope, Go dynamically scoped, Go dynamically typed, Go dynamic variables, Go eager evaluation, Go embedded, Go encapsulation, Go encryption, Go enumerated types, Go enumeration, Go enums, Go environment variables, Go errors, Go error handling, Go evaluation strategy, Go event-driven, Go event handlers, Go event loops, Go exception handling, Go executables, Go execution, Go expressions, Go FaaS, Go Facebook, Go fibers, Go fields, Go file input/output, Go file synchronization, Go file I/O, Go filter, Go first-class functions, Go fold, Go foreach loops, Go fork-join, Go floating-point, Go FP, Go frameworks, Go FreeBSD, Go frontend, Go functions, Go functional, Go functional programming, Go function overloading, Go garbage collection, Go generators, Go generator expressions, Go generics, Go generic programming, Go GitHub, Go global variables, Go GraphQL, Go gRPC, Go GUI, Go hashing, Go heap, Go heap allocation, Go hello world, Go higher-order functions, Go history, Go Homebrew, Go HTTP, Go idempotence, Go IDEs, Go import, Go imperative, Go immutable values, Go immutability, Go inheritance, Go influenced, Go influenced by, Go installation, Go integers, Go integration testing, Go interfaces, Go internationalization, Go interpreters, Go interprocess communication (IPC), Go iOS, Go IoT, Go IPCs, Go ISO Standard, Go iteration, Go JetBrains, Go JIT, Go JSON, Go JSON-RPC, Go JSON Web Tokens, Go JSON Web Token (JWT), Go Just-in-time (JIT), Go JWT, Go K8S, Go keywords, Go lambdas, Go language spec, Go lazy evaluation, Go lexically scoped, Go lexical scoping, Go libraries, Go linters, Go Linux, Go lists, Go list comprehensions, Go literals, Go localization, Go local variables, Go locks, Go logging, Go logo, Go looping, Go macOS, Go map, Go mascot, Go math, Go member variables, Go memoization, Go memory addressing, Go memory allocation, Go malloc, Go memory management, Go memory safety, Go message queues, Go metaclasses, Go meta-programming, Go methods, Go method overloading, Go MFA, Go ML, Go microservices, Go Microsoft, Go mobile dev, Go modules, Go modulo operators, Go monitoring, Go multiprocessing, Go multi-threaded, Go mutable values, Go mutability, Go mutex (Go mutual exclusion), Go namespaces, Go natural language processing (NLP), Go networking, Go network programming, Go NLP, Go non-blocking, Go non-blocking I/O, Go null, Go null reference, Go null coalescing operators, Go numbers, Go number precision, Go OAuth, Go objects, Go object code, Go object comparisons, Go object creation, Go object creators, Go object destruction, Go object destructors, Go object lifetime, Go object-oriented constructors, Go object-oriented programming, Go object serialization, Go observability, Go OOP, Go operators, Go operator overloading, Go optimizations, Go organizations, Go ORMs, Go packages, Go package managers, Go pass by reference, Go pass by value, Go parallel computing, Go parallel programming, Go parallelism, Go parameters, Go people, Go performance, Go persistence, Go pipelines, Go pointers, Go polymorphism, Go primitives, Go primitive data types, Go probability, Go procedural, Go processes, Go producer-consumer, Go programmers, Go programming, Go programming paradigm, Go program structure, Go program termination, Go Protocol Buffers (Protobuf), Go Protocol Buffers, Go Protobuf, Go proxies, Go public-key encryption, Go PKI, Go pure functions, Go race conditions, Go random, Go reactive, Go readability, Go records, Go recursion, Go reentrancy, Go refactoring, Go reference counting, Go reference types, Go referential transparency, Go reflection, Go regex, Go remote procedure calls (RPC), Go REPL, Go reserved words, Go REST, Go REST APIs, Go RHEL, Go RPCs, Go runtimes, Go safe navigation operators, Go SDK, Go secrets, Go security, Go serialization, Go serverless, Go server-side, Go sets, Go set comprehensions, Go side effects, Go signed integers, Go SMTP, Go Snapcraft, Go social media, Go sockets, Go source code, Go source-to-source compiler, Go SQL, Go SSL - Go SSL-TLS, Go Single sign-on (SSO), Go SSO, Go StackOverflow, Go stack, Go stack allocation, Go Stack overflow, Go standards, Go standard errors, Go standard input, Go standard library, Go standard operators, Go standard output, Go state, Go statements, Go strings, Go string concatenation, Go string functions, Go string operations, Go scheduling, Go scientific notation, Go scope, Go scope rules, Go scoping, Go scripting, Go static analyzers, Go statically scoped, Go static scoping, Go statically typed, Go static variables, Go statistics, Go strongly typed, Go structural typing, Go synchronization, Go syntax, Go systems programming, Go TCP/IP, Go TDD, Go testing, Go test frameworks, Go threads, Go thread-local storage (TLS), Go TLS, Go thread locking, Go thread locks, Go thread safety, Go thread scheduling, Go thread synchronization, Go times, Go timers, Go to JavaScript, Go tools, Go toolchain, Go transpiler, Go transpiling to JavaScript, Go truth values, Go tuples, Go type checking, Go type conversion, Go type inference, Go type safety, Go type system, Go web dev, Go while loops, Go work stealing, Go values, Go value types, Go variables, Go variable lifetime, Go variable scope, Go versions, Go virtual environments, Go virtual machine, Go Ubuntu, Go Unicode, Go unit testing, Go unsigned integers, Go usability, Go weakly typed, Go Windows, Go wrappers, Go written using, Go x86-64-Go AMD64, Go XML, Go YAML, Go Awesome list;

Go topics-Go courses-Go books-Go docs. (navbar_golang and navbar_golang_detailed)

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Table of Contents

Golang Performance Glossary

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Golang Vocabulary List (Sorted by Popularity)