Bump github.com/cloudposse/atmos from 1.189.0 to 1.194.1

[dependabot]

Bumps github.com/cloudposse/atmos from 1.189.0 to 1.194.1.

Release notes

Sourced from github.com/cloudposse/atmos's releases.

v1.194.1

what

• Improved the heatmap performance on Docker, fixed critical performance issues with the --heatmap flag in Docker environments
• Renamed "Total" column to "CPU Time" throughout the performance heatmap display to clarify that it represents sum of self-times, not wall-clock time
• Added parallelism metric to both console and TUI displays showing CPU Time ÷ Elapsed ratio
• Improved TUI visualizations (bar chart and sparkline modes) to display average time per call instead of total CPU time for better user comprehension
• Enhanced TUI legend with live performance metrics (Parallelism, Elapsed time, CPU Time) displayed at the top
• Split TUI legend into three lines for improved readability
• Updated comprehensive documentation in website/docs/troubleshoot/profiling.mdx with explanations of all new metrics and display formats

why

Docker performance context

This PR improved the heatmap performance on Docker, fixed critical performance issues with the --heatmap flag in Docker environments.

The Docker Problem:

• Commands with --heatmap took ~60 seconds to start in Docker containers (vs instantly on macOS)
• Root cause: runtime.Stack() was called on every tracked function to get goroutine IDs
• In Docker, this syscall is significantly slower than on native macOS
• With thousands of tracked function calls during stack processing, overhead accumulated to ~1 minute

The Solution:

• Introduced "simple tracking mode" using a single global call stack instead of per-goroutine tracking
• Avoids expensive runtime.Stack() calls for single-goroutine execution (most Atmos commands)
• Result: ~19x faster (119µs vs 3ms for 1000 calls)

TUI improvements

Problem 1: Confusing Column Name The "Total" column name was ambiguous - users couldn't tell if it meant wall-clock time or CPU time. This caused confusion when trying to interpret performance data.

Problem 2: Missing Parallelism Context Users had no way to understand the relationship between CPU time and elapsed time. When CPU time exceeded elapsed time (e.g., 5 minutes of CPU time in 22 seconds), it looked wrong but was actually correct for parallel execution.

Problem 3: TUI Display Showed Confusing Values The bar chart displayed large total times (e.g., "2m47s") for functions called hundreds of thousands of times, making it appear slow when the average time per call was actually fast (e.g., 0.37ms). This was mathematically correct but user-unfriendly.

Problem 4: Cramped Legend The single-line legend was too wide and difficult to read in the TUI.

Solutions

Solution 1: Clear Terminology Renamed "Total" to "CPU Time" everywhere with consistent explanations that it represents "sum of self-time (excludes children)" to avoid confusion with wall-clock time.

... (truncated)

Commits

• 8464ef4 Fix and Improve Performance Heatmap (#1622)
• d72c802 Update aws identities Environment() block (#1623)
• e289fee Fix component inheritance: restore default behavior for metadata.component (#...
• 09f27f2 Add trace logging for all squelched errors (#1615)
• 9b5598a Improve performance heatmap (#1611)
• f69c0b4 fix: single quote support #1362 (#1560)
• 997216c Improve Atmos Auth (#1602)
• aefb2b3 Add short test mode to skip long-running tests (#1605)
• 41200b0 fix: redirect telemetry notice to stderr instead of stdout (#1426)
• 088e325 Add --version flag as alias for version command (#1600)
• Additional commits viewable in compare view

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[dependabot]

Superseded by #517.