Why Do Docker Stats and Go pprof Show Different Memory Usage in Go Applications?

Memory Usage Discrepancy: Docker Stats vs Go pprof

Introduction

When monitoring resource usage in containerized applications, discrepancies between metrics reported by tools like docker stats and those obtained via profiling can be encountered. This article aims to shed light on this issue, focusing on the specific case of memory usage analysis in Go applications.

Docker Statistics: cgroups

Docker employs cgroups to manage resource allocation for containers, and docker stats reflects the memory usage stats derived from these cgroups. Cgroups provide a system-wide mechanism for controlling the resources available to processes, including memory usage.

Go pprof: Profiling

Go pprof allows for the collection of real-time profiling data from running applications. It provides various metrics, including heap memory consumption.

Discrepancies in Memory Usage Reporting

Despite relying on different mechanisms for data collection, docker stats and Go pprof often report divergent memory usage values. This discrepancy stems from the varying scope of memory being measured.

• docker stats reports the total memory usage within the container, including page cache and resident set size (RES).
• Go pprof, on the other hand, primarily focuses on heap memory allocation.

Practical Implications

In scenarios where File I/O occurs, page cache growth can lead to a significant increase in the memory usage reported by docker stats. This is because page cache data is counted towards the overall memory consumption.

However, for container workloads, mechanisms are in place to reclaim unused memory, including page cache. As a result, docker stats memory usage may fluctuate and not always reflect the true utilization by the application.

Addressing the Discrepancy

To obtain a more accurate understanding of memory usage, consider the following:

• Monitor cgroups stats: Examine cgroups memory stats (/sys/fs/cgroup/memory/docker//memory.stats) for a detailed breakdown of memory usage, including page cache, RES, and swap.
• Set memory limits: Enforce memory restrictions using docker command-line options or Docker Compose configuration. This can help prevent excessive memory usage by the container, leading to a more predictable resource footprint.
• Review pprof data: Use Go pprof to identify memory allocations within the application code. This can pinpoint potential leaks or inefficient memory management practices.

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