Memory allocator limits for low‑traffic Erlang workloads

Question

The primary goal is to keep the memory footprint of a low‑traffic Erlang node minimal so that hosting costs can be reduced. Erlang’s lightweight processes normally require roughly 1.5 KB of heap, but the default runtime allocator (erts_alloc) can over‑allocate for short‑lived processes, inflating the resident set size on nodes that handle only a handful of concurrent processes.
Switching to the atomics allocator via the +M flag improves fragmentation and can lower the overall memory usage. However, this change may increase process spawn latency and alter garbage‑collection behavior, potentially hurting the responsiveness of the application. The trade‑off between fragmentation, memory usage, and spawn performance is not fully documented for low‑traffic scenarios.
Because the cost‑to‑performance balance is unclear, the choice of allocator remains an unresolved decision for cost‑constrained, low‑traffic workloads.
Key questions for investigation:

How does erts_alloc compare to atomics in terms of total resident memory on a node with <10 concurrent processes?
What is the measurable impact on process spawn latency and GC pause times when using atomics versus erts_alloc?
Are there documented thresholds or guidelines that recommend a particular allocator for low‑traffic deployments?

Tasadduq Burney · Answer

To minimize the resident set size (RSS) on an Erlang node with fewer than a dozen concurrent processes, the most effective strategy is to use the atomics allocator via the `+M` flag.

While the default erts_alloc is highly optimized for high-throughput process creation, it often over-allocates memory 'carriers' to reduce fragmentation under heavy load. In low-traffic scenarios, these carriers remain unused, leading to a high RSS relative to actual heap usage. The atomics allocator reduces this overhead by using atomic operations for memory management, which is more memory-efficient for idle or low-load nodes.

Comparison: erts_alloc vs. Atomics

Metric	erts_alloc (Default)	Atomics (+M)
Low-Traffic RSS	Higher (due to pre-allocated carriers)	Lower (tighter memory packing)
Process Spawn Latency	Lower (optimized for speed)	Slightly higher (atomic overhead)
GC Pause Times	Standard	Negligible difference
	Fragmentation	Potential in long-lived idle nodes	Minimized

Actionable Steps for Cost-Constrained Deployments

If your priority is cost reduction via lower memory footprints, follow these steps to validate the transition:

Establish Baseline: Start your application with default settings and record the RSS using ps -o rss -p [PID] while the node is idle.
Enable Atomics: Restart the BEAM with the flag: erlang -M -s inet -accept your_app_start.
Monitor Internal Memory: Use erlang:memory(total) in a distributed shell to compare the memory reported by the VM versus what the OS reports.
Test Latency: Run a script that spawns and terminates 1,000 processes in quick succession to ensure the spawn latency increase is acceptable for your specific request requirements.

Assumptions and Uncertainty

This analysis assumes you are running Erlang/OTP 24 or later, as allocator behavior has stabilized in recent versions. It is important to note that if your application uses large ETS tables or loads thousands of modules into memory, the memory savings from switching allocators may be statistically insignificant, as those structures exist outside the standard process heap allocation.

Does your application rely heavily on large ETS tables or a high number of dynamically loaded modules?

Memory allocator limits for low‑traffic Erlang workloads

1 answer

To minimize the resident set size (RSS) on an Erlang node with fewer than a dozen concurrent processes, the most effective strategy is to use the atomics allocator via the `+M` flag.

Comparison: erts_alloc vs. Atomics

Actionable Steps for Cost-Constrained Deployments

Assumptions and Uncertainty

Your perspective belongs here.

1 question comment

Memory allocator limits for low‑traffic Erlang workloads

1 answer

To minimize the resident set size (RSS) on an Erlang node with fewer than a dozen concurrent processes, the most effective strategy is to use the atomics allocator via the +M flag.

Comparison: erts_alloc vs. Atomics

Actionable Steps for Cost-Constrained Deployments

Assumptions and Uncertainty

Your perspective belongs here.

1 question comment

To minimize the resident set size (RSS) on an Erlang node with fewer than a dozen concurrent processes, the most effective strategy is to use the atomics allocator via the `+M` flag.