Imagine a universe where billions of messages, calls, and financial transactions happen every second. Each message reaches its recipient flawlessly, phone calls remain uninterrupted, and funds are transferred instantly. What ensures such impeccable performance? No, it's not magic—it's virtual machines—the unsung heroes of digital infrastructure.
Among them stands out one remarkable machine — BEAM. Created decades ago, it looks like an invention from a distant future. It powers stable operations for giants like WhatsApp, Discord, financial services, and IoT systems. Even after all these years since its inception, BEAM continues to impress with its performance and reliability.
This article is not intended as an in-depth exploration into the inner workings of BEAM or its implementation details. We won't delve into byte code flow or provide specific internal code snippets here. Instead, this piece aims to give you a general understanding of what BEAM does, why it's important, and how it can benefit your business under heavy loads. For those who want to dive deeper into BEAM’s internals, I recommend reading the book — The BEAM Book: Understanding the Erlang Runtime System.
In today's era characterized by rapid development of real-time technologies, artificial intelligence, and mass parallel user connections, BEAM excels at providing high response speed, reliability even during failures, and quick adaptation to increasing load, making it an optimal solution for complex challenges. But let's start with the basics!
What Is a Virtual Machine? 🤔
Imagine writing a program that needs to run everywhere—on laptops, smartphones, servers, smart speakers, etc. How do you ensure compatibility across different operating systems and hardware configurations? The answer lies in using a virtual machine (VM). It's a special execution environment that interprets your code, acting as a bridge between your application and the underlying device. The VM takes intermediate code (like Java bytecode) and translates it into instructions suitable for each platform, freeing you from worrying about memory management or multithreading intricacies. In essence, a virtual machine serves as a universal adapter enabling your code to run anywhere!
Additionally, many virtual machines come equipped with useful tools such as automatic garbage collection, built-in performance optimizations, and data protection mechanisms. These features make app development significantly easier and more efficient. Without VMs, creating modern projects ranging from mobile games to large-scale cloud services would be much harder.
Why Are Virtual Machines Needed? 🌟
Virtual machines aren't just developer conveniences but powerful tools for building versatile, reliable, and scalable solutions. Let's explore their key advantages through practical examples:
Cross-platform Compatibility 📱💻
Write once, run anywhere. An example is a banking app written in Java running seamlessly both on bank servers and client Android phones thanks to JVM. This saves time and resources, especially valuable in enterprise-level development involving diverse platforms.Resource Management 🧹
Virtual machines handle resource allocation, including memory control (via garbage collection), threading, and hardware interaction. For instance, in the Erlang VM (BEAM), each process gets isolated memory areas, preventing issues caused by individual process crashes. Such architecture minimizes bugs and simplifies coding tasks, relieving developers from manually managing memory allocation and deallocation.Security 🔒
By isolating executable code from the OS, virtual machines create secure sandboxes protecting against potential threats posed by harmful programs. This feature is crucial in environments like AWS Lambda or Google Cloud Functions, where thousands of code fragments from various users execute simultaneously on shared hardware.Optimization ⚡
Many VMs dynamically optimize code execution while applications are running. One prominent example is Just-In-Time compilation (JIT), which makes browser engines like V8 incredibly fast. Starting with version OTP 24, BEAM introduced its own JIT mechanism, further enhancing performance. These techniques prove invaluable when dealing with repetitive computations common in highly loaded web apps.Support for Complex Systems 🌐
Some VMs are specifically designed to support concurrency, distributed computing, and fault tolerance. For example, popular game server infrastructures, like those powering League of Legends, rely heavily on BEAM, efficiently handling millions of concurrent player connections with minimal latency and high reliability.
Thus, virtual machines allow developers to focus directly on product functionality rather than low-level technicalities, accelerating development processes and reducing costs.
Popular Virtual Machines: Who's Who? 🦸♂️
JVM (Java Virtual Machine): Used for Java, Kotlin, Scala. Ideal for large business systems (banking solutions), web servers (Spring Framework), and Android platforms.
- Pros: Extensive ecosystem (huge library availability), Just-In-Time compilation technology.
- Cons: High initial RAM usage, comparatively slow startup times.
- Fact: Adopted by nearly 90% of Fortune 500 companies worldwide.
V8 (JavaScript Engine): Powering Node.js and modern browsers. Optimized for web environments.
- Pros: Exceptional performance for client-side websites.
- Con: Not well suited for long-term server-based solutions, where BEAM shines.
CLR (.NET Common Language Runtime): Supports languages within the .NET family, notably C#. Strongly integrated with Microsoft technologies (Azure).
- Pros: Seamless integration with Windows platforms.
- Con: Limited cross-platform capabilities compared to JVM.
BEAM (Erlang VM): Designed for Erlang, Elixir, and other compatible languages (LFE, Alpaca). Best suited for highly scalable, resilient, and concurrent systems, excelling in messaging, telecommunications, and fintech.
- Pros: Capable of handling millions of simultaneous processes with minimal delays.
- Con: Smaller toolkit and framework libraries, though actively growing (Phoenix, Nerves frameworks).
Comparison Table:
| VM | Strengths | Weaknesses | Use Cases |
|---|---|---|---|
| JVM | Versatility, extensive ecosystem | Memory consumption, startup lag | Enterprise, Android |
| V8 | Speed for web clients | Unsuitable for backend servers | Node.js, Browsers |
| CLR | Integration with Microsoft tech | Dependence on MS ecosystem | .NET, Azure |
| BEAM | Concurrency, resilience | Fewer libraries & frameworks | Real-time, Telecom |
By 2025, with the rise of IoT and streaming data, BEAM has become particularly relevant for real-time applications.
Deeper Look Into BEAM 🌌
BEAM is a virtual machine engineered for programming languages like Erlang, Elixir, and others (such as LFE). Initially developed in the 1990s by Ericsson for telecommunication purposes, where reliability and capacity to manage massive traffic were critical, today BEAM forms the backbone of numerous high-performance services. It handles billions of daily messages (as seen in WhatsApp), supports millions of online gamers simultaneously (products like League of Legends), and keeps real-time chat services (Discord) functioning smoothly. As the need for high throughput, low latency, and robustness grows, BEAM proves indispensable in 2025 more than ever before.
History of BEAM: From Telco to Global Platforms 📜
Originally, BEAM stood for "Bogdan's Erlang Abstract Machine" named after Bogumil Hausman ("Bogdan"), who created its first iteration. However, over time, it became associated with another author—"Björn's Erlang Abstract Machine", reflecting contributions made by Björn Gustavsson, who maintains the current implementation. Both contributors played significant roles in shaping the system while working at Ericsson.
Before BEAM emerged, there was another virtual machine called JAM (Joe's Abstract Machine)—the first interpreter for the Erlang language. Developed by Joe Armstrong alongside Mike Williams in C, detailed insights are found in the developers' blog.
Therefore Bogumil (“Bogdan”) Hausman created TEAM (Turbo Erlang Abstract Machine). It compiled the Erlang code to C code, which was then compiled to native code using GCC.
Today, BEAM finds widespread use in finance (Klarna), advertising (AdRoll), notification systems (Pinterest), and Internet of Things (IoT) deployments (Nerves). With advancements such as Just-In-Time compiler introduction in OTP 24 and type improvement enhancements in Elixir v1.15+, BEAM remains a viable choice. Future plans include closer alignment with WebAssembly for supporting web applications.
What's So Great About BEAM? 🚀
BEAM distinguishes itself among other virtual machines due to unique characteristics essential for scalable and demanding applications. Below are its main advantages, supported by concrete figures and comparisons with similar solutions:
-
Fast and Lightweight Processes ⚡
Process creation in BEAM takes only microseconds, consuming approximately 2.5 KB per process, allowing millions of instances to coexist on a single machine. Compared to Java threads requiring megabytes of memory, BEAM offers superior efficiency.🧠 While asynchronous tasks in Rust are lightweight too, BEAM surpasses in building distributed solutions due to its actor model, isolated processes with negligible overhead, auto-failure recovery via supervisors, and hot code swapping without downtime.
Actor Model 🎭
Processes behave independently, exchanging messages without sharing resources or causing blocking. Unlike Java threads, this greatly simplifies concurrent processing. Imagine a chat messenger like Discord where each room acts as an independent process freely accepting new messages regardless of other activities. Performance is impressive: BEAM can process roughly 100k messages per second on a single core.-
Let It Crash Philosophy 💥
BEAM embraces the principle of “let it crash”: if a process fails, it simply stops executing. Yet, thanks to careful design, failure goes largely unnoticed by end-users. Consider managing a busy restaurant where someone suddenly leaves mid-shift. Typically, chaos ensues, disrupting service. In BEAM, however, there's a supervisor-like manager immediately spawning a replacement process. Customers continue receiving orders promptly, unaware of any interruption.☎️ This philosophy proved effective back in the '90s when Ericsson used BEAM to maintain large telecommunication stations. If a component crashed, the overall system remained operational without disruption.
Hot Code Reloading 🔄
Applications can update themselves without halting ongoing operations. BEAM holds two versions of software modules simultaneously, switching almost instantaneously. In contrast, Java transitions require additional effort and may cause temporary delays. Successful implementations include payment gateway Klarna, updating continuously without a single second of downtime, ensuring continuous shopping experiences for customers.Distributed Systems 🌐
Individual nodes connect into unified clusters through network links. This setup enhances fault tolerance and horizontal scaling. Take Pinterest notifications: thousands of new servers easily join existing clusters, boosting total output without compromising individual node performance. Scalability extends to tens of thousands of nodes with minimal request latencies.Low Latency ⏱
Incremental garbage collection minimizes delays. The Phoenix framework, built atop BEAM, handles thousands of requests with millisecond-level responses. Other languages like Python occasionally experience longer pauses due to their garbage collection models, whereas BEAM consistently performs under heavy loads with low latency.Just-In-Time Compilation 🚀
Starting with OTP 24, BEAM introduces Just-In-Time compilation, improving computational-intensive task speeds by up to 20–30%. Although BEAM primarily focuses on concurrency, this optimization dramatically increases execution speed for computation-heavy tasks. Parsing JSON files now happens faster thanks to enhanced compiler optimizations.
Inside BEAM: How Does It Work? 🛠
1. Scheduler: Maestro of Multitasking 🎻
The scheduler in BEAM operates like a conductor leading an orchestra. Thousands of musicians (processes) play together, each needing their turn to perform. Nobody plays for too long—otherwise, music turns chaotic.
📖 Real-world Example: A single WhatsApp server handled millions of active connections simultaneously. Implementing this feat using conventional OS threads would have been impossible, yet BEAM manages it gracefully with its unique scheduling scheme.
How It Works:
- There is one scheduler per CPU core. On an eight-core server, eight schedulers operate.
- Every process receives a fixed number of steps ("reductions") before yielding control to another process.
- Processes fall into two queues: ready-for-execution and waiting-for-resources.
- Load balancing employs task stealing mechanics to redistribute workload evenly.
- Time-wheel structure stores active timers for efficient timing operations.
📌 Common Issue: Long-running Built-In Functions (BIFs) executed without yielding control can block scheduler activity.
2. Garbage Collection: Keeping Memory Clean 🧹
The garbage collector (GC) in BEAM works similarly to a diligent janitor silently cleaning tables in a bustling city full of restaurants. Each process has its dedicated storage area ("heap"). When unused objects fill a heap, cleanup occurs locally, leaving other processes unaffected.
BEAM implements generational garbage collection: newer elements ("young generation") frequently cleaned because they tend to die quickly, while older generations are checked less often.
📌 Common Issue: Accumulation of long-lived objects can lead to increased resource consumption. Monitor parameters like high_water carefully.
Large binary data (files, images) resides separately outside the GC zone, avoiding unnecessary bloat.
📖 Real-world Example: Discord manages millions of active channels on BEAM. Even if one particular chat accumulates transient data, the cleanup mechanism swiftly removes it without impacting other chats’ performance.
Algorithm Overview:
- Heap and stack expand towards each other until meeting, triggering cleanup.
- Two types of cycles exist: minor (frequent young-generation cleanups) and major (infrequent old-generation cleanups).
- Data copying technique moves values between two memory zones ("from space" → "to space").
✨ Carefully monitor memory growth dynamics in your processes. Rapidly expanding sizes might indicate presence of long-living objects requiring architectural adjustments.
3. Register-Based Architecture: Faster and More Efficient 🧠
BEAM utilizes register-based architecture. Registers act as small, fast-access memory regions storing intermediate results of calculations. Each register holds specific values participating in computational operations. By keeping data close to the processor, registers enable swift access and high-performance operation.
Example: Simple addition (add(A, B) resulting value stored in registers X0 and X1).
Operational Principles:
- Registers X (up to 1024): Store function arguments.
- Registers Y: Local variables.
- Instructions like
moveandcall, direct memory addressing allowed. JIT compilation substantially improves performance.
📌 Common Issue: Overflowing registers — pay attention to function size and optimization strategies.
✨ Performance Tips: Minimize stack usage, utilize registers effectively for intermediate result storage.
4. Supervisors and Fault-Tolerance: Let It Crash! 💥
In typical systems, a failing process means disaster. In BEAM, however, this event aligns with the development philosophy.
Consider electrical networks: A vast grid where one substation breaks down. Normally, entire neighborhoods lose power. In BEAM, automated switches disconnect the faulty element and reconnect reserve units instantly, preserving normalcy throughout the city.
Supervisors form hierarchical structures. When child processes crash, parent supervisors decide whether to restart affected components individually or collectively.
Such architecture guarantees automatic restoration of system integrity.
Mechanisms involved: tree-structured supervision, one-for-one strategy, state monitoring (running, garbage collection).
📌 Common Issue: Ignoring supervisor role, opting for custom solutions instead of proven OTP libraries.
✨ Developer Advice: Design applications tolerant of errors, leave failure-handling logic to specialized supervisor mechanisms.
5. Dynamic Code Loading and Distributed Systems 🌍
BEAM allows live updates to running applications. Similar to a musician changing instruments mid-performance invisibly to listeners.
- Two module versions reside simultaneously: Old handles ongoing requests, new accepts fresh ones. Updates occur transparently without stopping the application.
-
Code Replacement: Achieved via command
:code.load_file(Module). Follow proper update rules to avoid disruptions. -
Distribution: Check remote node availability using
net_adm:ping(Node), leverage Mnesia database. Clustering examples exist in Kubernetes environments utilizing BEAM-powered virtual machines. - Scaling: Utilize OTP tools for cluster-wide node monitoring.
6. Scalability: BEAM Network Across Thousands of Nodes 🌐
BEAM isn't merely a standalone node but a connected network behaving as a unified whole. Individual network members interact seamlessly, forming a coherent distributed infrastructure.
Key benefits of this approach:
- Deploy clusters spanning multiple servers, enabling transparent communication between processes.
- Particularly beneficial in IoT systems and microservices architectures, where message delivery automatically distributes across appropriate servers.
📖 Real-world Case Study: Pinterest applied this technology to deliver notifications. As traffic grew, adding extra servers scaled the system effortlessly.
BEAM in 2025: Why Should You Pay Attention? 🚀
- Handling Massive Traffic: WhatsApp manages millions of simultaneous connections.
- Scalable Microservices: Effortless deployment and management in Kubernetes.
- Real-time Operations: Phoenix provides lightning-fast chat communications.
- Reliability and Resilience: Proven in big players like Klarna.
- IoT and AI: Nerves for IoT devices, TensorFlow compatibility via port mechanisms.
- Future Development: Enhanced performance through JIT compilation, WebAssembly support for web apps.
📖 Success Story: Pinterest reduced notification delay by 50%, leveraging BEAM.
BEAM — The Future That's Already Here! 🌌
As we stand in 2025, Elixir and Erlang occupy niche positions among commonly used development tools, drawing little public attention. Personally, I believe this situation is unfair given the truly amazing and innovative possibilities offered by these technologies. Despite the learning curve and project complexity, the rewards promise to be substantial!
Embrace the world of Elixir/Erlang, launch a new project, and experience the true power of the BEAM virtual machine! ✨
Final Note from the Author
Thank you very much for taking interest in this article! Hopefully, it helped clarify what BEAM is and why it's so widely adopted. Initially, I planned to write something more advanced and filled with technical details, but realized I'd struggle to top the comprehensive guide provided in the book The BEAM Book: Understanding the Erlang Runtime System. Thus, I've opted for a simpler explanation.
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