Dashboardcalm-forestSession ses_2b658c64

Session ses_2b658c64

Full ID: ses_2b658c641ffe9xFXNL2RFQdYGL
Messages: 30
Distillations: 0
Time range: 2026-04-01 15:26:29 — 2026-04-01 17:08:12

Conversation (30 messages)

We added some performance metrics into our product but don't have proper dashboard to track this. A few things that come to my mind are:

  1. How long do we take for auto completion
  2. How long do we take for org/project/dsn discovery
  3. How many files we scan or directory levels we travers for DSN discovery
  4. What's the average latency before and after getting the real result for a command call (like if I do issue view or issues list what's the overhead of the pre-actions like determining the org, project etc and what's the overhead of rendering?

I think getting p90 or p75 and maybe p50 or averages would be good. What do you think? Can you also find or think of other metrics we should be tracking? <system-reminder> Plan mode is active. The user indicated that they do not want you to execute yet -- you MUST NOT make any edits (with the exception of the plan file mentioned below), run any non-readonly tools (including changing configs or making commits), or otherwise make any changes to the system. This supersedes any other instructions you have received.

Plan File Info:

No plan file exists yet. You should create your plan at /home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/.opencode/plans/1775057189310-sunny-otter.md using the write tool. You should build your plan incrementally by writing to or editing this file. NOTE that this is the only file you are allowed to edit - other than this you are only allowed to take READ-ONLY actions.

Plan Workflow

Phase 1: Initial Understanding

Goal: Gain a comprehensive understanding of the user's request by reading through code and asking them questions. Critical: In this phase you should only use the explore subagent type.

  1. Focus on understanding the user's request and the code associated with their request

  2. Launch up to 3 explore agents IN PARALLEL (single message, multiple tool calls) to efficiently explore the codebase. ...

plan · 2026-04-01 15:26:29

I'll start by exploring the codebase to understand the existing telemetry/metrics infrastructure and what performance data we're already collecting.

task
task_id: ses_2b6589f1bffe73YkgHXl5gMG9X (for resuming to continue this task if needed)

<task_result>
I now have a thorough understanding of the entire telemetry infrastructure. Here is my complete report:

---

## Telemetry & Metrics Infrastructure Report

### 1. Core Telemetry Setup

**Primary file:** `/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/lib/telemetry.ts` (1185 lines)

#### Initialization Flow

1. **Entry point:** `cli.ts` line 124 dynamically imports `withTelemetry` from `telemetry.ts`
2. **`withTelemetry()`** (line 94) is the outermost wrapper for all CLI command execution:
   - Checks `SENTRY_CLI_NO_TELEMETRY !== "1"` to allow opt-out
   - Calls `initSentry(enabled, options)` (line 99)
   - Calls `initTelemetryContext()` to set user/instance IDs (line 105)
   - Drains deferred completion telemetry queue (lines 109-120)
   - Creates a root transaction span `cli.command` with `Sentry.startSpanManual` (line 123)
   - ...
task
task_id: ses_2b65886d2ffdmzvTMH99xXXmtW (for resuming to continue this task if needed)

<task_result>
Now I have a comprehensive picture. Here is my detailed analysis:

---

## Detailed Analysis of Auto-Completion, DSN Discovery, Project Resolution, and Command Execution

### 1. Auto-Completion System

#### Fast-Path Dispatch
- **File**: `/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/cli.ts`, lines 22-27 and 404-411
- The `startCli()` function at line 404 checks if `args[0] === "__complete"` and dispatches to `runCompletion()` **before any heavy imports**.
- `runCompletion()` (line 22) sets `SENTRY_CLI_NO_TELEMETRY = "1"` to skip loading `@sentry/node-core` (~280ms), then dynamically imports only `./lib/complete.js`.
- This is explicitly designed to avoid Stricli boot, telemetry, auth checks, and API calls.

#### Completion Engine
- **File**: ...
task
task_id: ses_2b6586e09ffeADtRG0i5Ogg0Z9 (for resuming to continue this task if needed)

<task_result>
Now I have a comprehensive picture. Here is the full report:

---

## Complete Telemetry & Self-Monitoring Report

This project uses Sentry's own product extensively to monitor the CLI itself -- error tracking, distributed tracing, custom metrics, session tracking, structured logs, and a deferred telemetry queue for shell completions.

---

### 1. Sentry SDK Initialization

**Primary file:** `/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/lib/telemetry.ts`

**DSN (line 85-86 of constants.ts):**
- `/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/lib/constants.ts` line 85-86
- DSN: `https://1188a86f3f8168f089450587b00bca66@o1.ingest.us.sentry.io/4510776311808000`
- This is Sentry's own org (`o1`), hosted on `us.sentry.io`. Safe to hardcode since DSNs only allow sending events. ...
claude-opus-4-6 · 2026-04-01 15:26:29 · ~16.1K tokens

Excellent! I now have a thorough understanding of the existing telemetry infrastructure. Let me read a few key files to deepen my understanding of areas where we could add more metrics.

read
<path>/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/lib/telemetry.ts</path>
<type>file</type>
<content>94: export async function withTelemetry<T>(
95:   callback: (span: Span | undefined) => T | Promise<T>,
96:   options?: { libraryMode?: boolean }
97: ): Promise<T> {
98:   const enabled = getEnv().SENTRY_CLI_NO_TELEMETRY !== "1";
99:   const client = initSentry(enabled, options);
100:   if (!client?.getOptions().enabled) {
101:     return callback(undefined);
102:   }
103: 
104:   // Initialize user and instance context
105:   await initTelemetryContext();
106: 
107:   // Flush deferred completion telemetry (queued during __complete fast-path).
108:   // Best-effort: never block CLI execution for telemetry emission.
109:   try {
110:     const { drainCompletionTelemetry } = await import(
111:       "./db/completion-telemetry.js"
112:     );
113:     for (const entry of drainCompletionTelemetry()) {
114:       ...
read
<path>/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/lib/command.ts</path>
<type>file</type>
<content>490:       warning(
491:         `Tip: use --help for help (e.g., sentry ${pathSegments.join(" ")} --help)\n\n`
492:       )
493:     );
494:     stdout.write(`${formatHelpHuman(result)}\n`);
495:     return true;
496:   }
497: 
498:   // Wrap func to intercept logging flags, capture telemetry, then call original.
499:   // The wrapper is an async function that iterates the generator returned by func.
500:   // biome-ignore lint/complexity/noExcessiveCognitiveComplexity: Central framework wrapper — flag cleanup, env-based JSON, output rendering, and error handling are all tightly coupled.
501:   const wrappedFunc = async function (
502:     this: CONTEXT,
503:     flags: Record<string, unknown>,
504:     ...args: unknown[]
505:   ) {
506:     applyLoggingFlags(
507:       flags[LOG_LEVEL_KEY] as LogLevelName | undefined,
508:       ...
read
<path>/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/lib/dsn/code-scanner.ts</path>
<type>file</type>
<content>665: 
666: /**
667:  * Main scan implementation with Sentry performance tracing and metrics.
668:  */
669: function scanDirectory(
670:   cwd: string,
671:   stopOnFirst: boolean
672: ): Promise<CodeScanResult> {
673:   return withTracingSpan(
674:     "scanCodeForDsns",
675:     "dsn.detect.code",
676:     async (span) => {
677:       // Create ignore filter with built-in patterns and .gitignore
678:       const ig = await createIgnoreFilter(cwd);
679: 
680:       // Collect all files to scan (also collects directory mtimes)
681:       let collectResult: CollectResult;
682:       try {
683:         collectResult = await collectFiles(cwd, ig);
684:       } catch {
685:         span.setStatus({ code: 2, message: "Directory scan failed" });
686:         return { dsns: [], sourceMtimes: {}, dirMtimes: {} };
687:       }
688: ...
claude-opus-4-6 · 2026-04-01 15:29:35 · ~3.4K tokens

Now let me look at the resolve-target to understand where pre-command overhead happens, and the response-cache to understand API caching:

read
<path>/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/lib/resolve-target.ts</path>
<type>file</type>
<content>940:  * 1. Explicit org and project - both must be provided together
941:  * 2. SENTRY_ORG / SENTRY_PROJECT env vars
942:  * 3. Config defaults
943:  * 4. DSN auto-detection
944:  * 5. Directory name inference - matches project slugs with word boundaries
945:  *
946:  * @param options - Resolution options with org, project, and cwd
947:  * @returns Resolved target, or null if resolution failed
948:  * @throws Error if only one of org/project is provided
949:  */
950: export async function resolveOrgAndProject(
951:   options: ResolveOptions
952: ): Promise<ResolvedTarget | null> {
953:   const { org, project, cwd } = options;
954: 
955:   // 1. ...
read
<path>/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/lib/resolve-target.ts</path>
<type>file</type>
<content>1: /**
2:  * Target Resolution
3:  *
4:  * Shared utilities for resolving organization and project context from
5:  * various sources: CLI flags, environment variables, config defaults,
6:  * and DSN detection.
7:  *
8:  * Resolution priority (highest to lowest):
9:  * 1. Explicit CLI flags
10:  * 2. SENTRY_ORG / SENTRY_PROJECT environment variables
11:  * 3. Config defaults
12:  * 4. DSN auto-detection (source code, .env files, environment variables)
13:  * 5. Directory name inference (matches project slugs with word boundaries)
14:  */
15: 
16: import { basename } from "node:path";
17: import pLimit from "p-limit";
18: import type { SentryProject } from "../types/index.js";
19: import {
20:   findProjectByDsnKey,
21:   findProjectsByPattern,
22:   findProjectsBySlug,
23:   getProject,
24:   listProjects,
25: } from ...
claude-opus-4-6 · 2026-04-01 15:29:42 · ~1.5K tokens

Now I have a thorough understanding of the codebase. Let me design the dashboard plan.

task
task_id: ses_2b65541d9ffeZKW9TZDyYVt1hR (for resuming to continue this task if needed)

<task_result>
Now I have comprehensive understanding of the codebase. Let me produce the full dashboard plan.

---

# Sentry CLI Performance Dashboard Plan

## Part 1: New Metrics/Spans to Add

### 1. Target Resolution Span (Essential)

**Span**: `resolve.target` (op: `resolve`)
**File**: `src/lib/resolve-target.ts` — `resolveOrgAndProject()` and `resolveAllTargets()`
**Attributes**:
- `resolve.method` — which priority step succeeded: `"flags"`, `"env_vars"`, `"defaults"`, `"dsn"`, `"inference"`, `"none"`
- `resolve.cache_hit` — boolean, whether DSN/project cache was used
- `resolve.dsn_count` — number of DSNs resolved (for monorepo path)

```typescript
// In resolveOrgAndProject(), wrap the entire function body:
return withTracingSpan("resolveOrgAndProject", "resolve", async (span) => {
  // ... existing logic, setting span.setAttribute("resolve.method", ...) at each return point
}, { ...
claude-opus-4-6 · 2026-04-01 15:29:48 · ~5.8K tokens

Now I have a comprehensive picture. Let me write the plan file.

write
Wrote file successfully.
claude-opus-4-6 · 2026-04-01 15:32:38 · ~34 tokens

Now let me ask some clarifying questions before finalizing:

question
User has answered your questions: "Should the dashboard be created programmatically (e.g., via Sentry API / `sentry-cli`), or will you create it manually in the Sentry UI? This affects whether we need to write dashboard creation code."="Use `sentry dashboard` commands (create, widget add etc)", "For the 'nice-to-have' metrics (completion result count, API response time distribution), should we include them in the initial implementation or defer?"="Include all (Recommended)", "The plan currently adds cache outcome counters to 4 cache systems (DSN, project, region, HTTP response). The HTTP response cache already has `cache.get`/`cache.put` spans with hit/miss attributes. Should we still add a separate counter metric for easier dashboard queries?"="Add counter everywhere (Recommended)". You can now continue with the user's answers in mind.
claude-opus-4-6 · 2026-04-01 15:33:52 · ~308 tokens

Great, the dashboard will be created using the CLI's own sentry dashboard commands. Let me explore those commands to understand the API and available widget types.

task
task_id: ses_2b6268fe4ffeIsA9iPM32RgCEq (for resuming to continue this task if needed)

<task_result>
Now I have a comprehensive picture. Here is the complete reference:

---

## Dashboard CLI Commands: Complete Reference

### Available Commands

The dashboard command tree has 6 commands:

```
sentry dashboard list       # List dashboards in an org
sentry dashboard view       # View a dashboard with rendered widget data
sentry dashboard create     # Create a new empty dashboard
sentry dashboard widget add    # Add a widget to a dashboard
sentry dashboard widget edit   # Edit a widget in a dashboard
sentry dashboard widget delete # Delete a widget from a dashboard
```

All commands support `--json` for machine-readable output and `--fields` to select specific JSON fields.

---

### 1. ...
claude-opus-4-6 · 2026-04-01 16:21:08 · ~5.8K tokens

Now I have everything I need. Let me understand what datasets and query syntax the dashboard widgets support for our specific metrics. The key insight is that we're dealing with both spans (trace data) and custom metrics (Sentry metrics). Let me check what dataset options are available for custom metrics queries:

read
<path>/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/types/dashboard.ts</path>
<type>file</type>
<content>1: /**
2:  * Dashboard types and schemas
3:  *
4:  * Zod schemas and TypeScript types for Sentry Dashboard API responses.
5:  * Includes utility functions for stripping server-generated fields
6:  * before PUT requests, and strict input validation for user-authored widgets.
7:  */
8: 
9: import { z } from "zod";
10: 
11: import { ValidationError } from "../lib/errors.js";
12: import { logger } from "../lib/logger.js";
13: 
14: // ---------------------------------------------------------------------------
15: // Widget type and display type enums
16: //
17: // Source: sentry/src/sentry/models/dashboard_widget.py
18: // Also in: @sentry/api types (cli/node_modules/@sentry/api/dist/types.gen.d.ts)
19: // ---------------------------------------------------------------------------
20: 
21: /**
22:  * Widget types (dataset selectors) ...
claude-opus-4-6 · 2026-04-01 16:23:21 · ~1.3K tokens

Now I understand the dashboard CLI capabilities. The metrics dataset is available for custom Sentry metrics queries. Let me now finalize the plan with the exact CLI commands.

write
Wrote file successfully.

LSP errors detected in other files:
<diagnostics file="/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/test/types/dashboard.test.ts">
ERROR [133:50] No overload matches this call.
  Overload 1 of 2, '(expected: "count" | "avg" | "sum" | "min" | "max" | "p50" | "p75" | "p95" | "p99" | "count_unique" | "percentile" | "p90" | "p100" | "eps" | "epm" | "any"): void', gave the following error.
    Argument of type 'string' is not assignable to parameter of type '"count" | "avg" | "sum" | "min" | "max" | "p50" | "p75" | "p95" | "p99" | "count_unique" | "percentile" | "p90" | "p100" | "eps" | "epm" | "any"'.
  Overload 2 of 2, '(expected: "count" | "avg" | "sum" | "min" | "max" | "p50" | "p75" | "p95" | "p99" | "count_unique" | "percentile" | "p90" | "p100" | "eps" | "epm" | "any"): void', gave the following error. ...
claude-opus-4-6 · 2026-04-01 16:23:27 · ~2.0K tokens

The LSP errors are pre-existing in the test file and unrelated to our changes. The plan is ready. Let me summarize what we have:

Here's the plan summary:

Phase 1 — New Instrumentation (6 items, 9 files):

  1. Target resolution span + method counter — wraps resolveOrgAndProject() with a resolve span and emits resolve.method counter showing which resolution path succeeded (flags/env/defaults/DSN/inference)
  2. Env file scanning span — wraps DSN env file detection with a dsn.detect.env span
  3. Cache hit/miss counters — adds cache.outcome increment counter across all 4 cache systems (DSN, project, region, HTTP response)
  4. Command phase timing — adds phase.pre_ms, phase.exec_ms, phase.render_ms attributes to the root cli.command span, directly answering your question about overhead breakdown
  5. Completion result count — emits the already-queued result_count as a metric alongside duration_ms
  6. API response time distribution — emits per-endpoint latency as a standalone metric

Phase 2 — Dashboard (27 widgets across 8 sections):

  • A: Overall CLI responsiveness (duration percentiles, per-command table, runtime split)
  • B: Completion latency (percentiles, by command, result counts)
  • C: Target resolution (duration, method distribution, method vs latency)
  • D: Command overhead breakdown (phase breakdown table, pre-command trend)
  • E: DSN detection (scan duration, root detection, file volume, traversal depth, reason breakdown)
  • F: Cache health (hits vs misses by type)
  • G: API dependency (response time, calls per command, by endpoint)
  • H: Seer AI outcomes + upgrade metrics

All widgets created via sentry dashboard create + sentry dashboard widget add commands. ...

claude-opus-4-6 · 2026-04-01 16:24:39 · ~671 tokens

Revise the plan with the metrics from https://github.com/getsentry/cli/pull/622

plan · 2026-04-01 16:25:50

Let me fetch the PR to understand what metrics were added.

bash
{"body":"## Summary\n\n- Upgrade `@sentry/node-core` from 10.44.0 to 10.47.0\n- Enable `nodeRuntimeMetricsIntegration` to collect CPU, memory, and event loop metrics\n- Regenerate tree-shaking patches for `@sentry/core` and `@sentry/node-core` against 10.47.0\n\n## Approach\n\nUses `nodeRuntimeMetricsIntegration` from `@sentry/node-core/light` instead of `bunRuntimeMetricsIntegration` from `@sentry/bun` to avoid adding a new dependency. The integration degrades gracefully on Bun — `monitorEventLoopDelay` is wrapped in try/catch, and all other APIs (`process.cpuUsage`, `process.memoryUsage`, `performance.eventLoopUtilization`) are Bun-compatible.\n\nCollection interval set to 5s (vs 30s default) since most CLI commands complete in <10s. Excluded from library mode to avoid keeping the host process event loop alive.\n\n## Metrics collected (`node.runtime.*`)\n\n| Metric | Type | Default |\n|--------|------|---------|\n| `cpu.utilization` | gauge | on |\n| `mem.rss` | gauge | on |\n| ...
claude-opus-4-6 · 2026-04-01 16:25:50 · ~1.1K tokens
bash
accepts at most 1 arg(s), received 2
claude-opus-4-6 · 2026-04-01 16:25:55 · ~17 tokens
bash
diff --git a/AGENTS.md b/AGENTS.md
index 87230528c..aaba6d2b2 100644
--- a/AGENTS.md
+++ b/AGENTS.md
@@ -965,6 +965,9 @@ mock.module("./some-module", () => ({
 <!-- lore:5ac4e219-ea1f-41cb-8e97-7e946f5848c0 -->
 * **PR workflow: wait for Seer and Cursor BugBot before resolving**: CI includes Seer Code Review and Cursor Bugbot as advisory checks (~2-3 min, only on ready-for-review PRs). Workflow: push → wait for all CI (including npm build) → check inline review comments from Seer/BugBot → fix valid findings → repeat. Bugbot sometimes catches real logic bugs, not just style — always review before merging. Use \`gh pr checks \<PR> --watch\` to monitor. Fetch comments via \`gh api repos/OWNER/REPO/pulls/NUM/comments\`.
 
+<!-- lore:019d49bf-65f3-7d79-bede-9f76e3e1ce1f -->
+* **Sentry SDK tree-shaking patches must be regenerated via bun patch workflow**: The CLI uses \`patchedDependencies\` in \`package.json\` to tree-shake unused exports from \`@sentry/core\` and \`@sentry/node-core\` ...
claude-opus-4-6 · 2026-04-01 16:25:59 · ~5.7K tokens

Now I have the full picture. PR 622 adds nodeRuntimeMetricsIntegration which automatically collects these node.runtime.* gauge metrics:

  • cpu.utilization
  • mem.rss, mem.heap_used, mem.heap_total
  • event_loop.utilization, event_loop.delay.p50, event_loop.delay.p99
  • process.uptime

Let me update the plan to incorporate these runtime metrics.

read
<path>/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/.opencode/plans/1775057189310-sunny-otter.md</path>
<type>file</type>
<content>1: # CLI Performance Dashboard Plan
2: 
3: ## Overview
4: 
5: Two-phase work: (1) add missing instrumentation to fill telemetry gaps, (2) create a Sentry dashboard using `sentry dashboard create` + `sentry dashboard widget add` commands.
6: 
7: ---
8: 
9: ## Phase 1: Add Missing Instrumentation
10: 
11: ### 1.1 Target Resolution Span + Method Counter
12: 
13: **File**: `src/lib/resolve-target.ts`
14: 
15: Wrap `resolveOrgAndProject()` (~line 950) in `withTracingSpan("resolveOrgAndProject", "resolve", ...)`:
16: - Set `resolve.method` attribute at each return point: `"flags"`, `"env_vars"`, `"defaults"`, `"dsn"`, `"inference"`, `"none"`
17: - Set `resolve.cache_hit` boolean attribute when DSN/project cache is used
18: - Emit `Sentry.metrics.increment("resolve.method", 1, { attributes: { method } })` at each ...
claude-opus-4-6 · 2026-04-01 16:26:04 · ~5.3K tokens
write
Wrote file successfully.

LSP errors detected in other files:
<diagnostics file="/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/test/types/dashboard.test.ts">
ERROR [133:50] No overload matches this call.
  Overload 1 of 2, '(expected: "count" | "avg" | "sum" | "min" | "max" | "p50" | "p75" | "p95" | "p99" | "count_unique" | "percentile" | "p90" | "p100" | "eps" | "epm" | "any"): void', gave the following error.
    Argument of type 'string' is not assignable to parameter of type '"count" | "avg" | "sum" | "min" | "max" | "p50" | "p75" | "p95" | "p99" | "count_unique" | "percentile" | "p90" | "p100" | "eps" | "epm" | "any"'.
  Overload 2 of 2, '(expected: "count" | "avg" | "sum" | "min" | "max" | "p50" | "p75" | "p95" | "p99" | "count_unique" | "percentile" | "p90" | "p100" | "eps" | "epm" | "any"): void', gave the following error. ...
claude-opus-4-6 · 2026-04-01 16:26:13 · ~2.0K tokens

The plan has been updated. Here's what changed:

Added from PR #622:

  • New Section H: Runtime Resource Usage with 5 widgets leveraging nodeRuntimeMetricsIntegration:
    • CPU Utilizationnode.runtime.cpu.utilization gauge
    • Memory Usage — RSS + heap_used + heap_total gauges on one chart
    • Event Loop Utilizationnode.runtime.event_loop.utilization gauge
    • Event Loop Delay — p50/p99 delay gauges (degrades gracefully on Bun)
    • Process Uptime — big number showing average command lifetime from the runtime perspective
  • The existing metrics inventory now documents all runtime metrics from PR #622
  • Verification step added for runtime metrics
  • Seer/Upgrades renumbered to Section I
  • Total grew from 27 to 32 widgets across 17 rows

The runtime metrics are particularly useful because:

  • CPU utilization catches regressions from expensive operations (DSN code scanning, JSON parsing)
  • Memory tracks heap growth (important for commands processing large API responses)
  • Event loop delay catches I/O blocking (sync file reads, heavy computation in the event loop)
  • Process uptime as a big number gives a quick sanity check on overall CLI session duration
claude-opus-4-6 · 2026-04-01 16:27:23 · ~407 tokens
  1. Let's make sure we don't add new metrics where we can simply look at span durations (such as API response times?)
  2. 32 widgets across 17 rows sounds a bit exessive and hard to follow by a human. Is there a way where we can combine some widgets using multiple series, area charts etc?
plan · 2026-04-01 17:03:35

Good points — let me reconsider both.

On #1: You're right. The http.client spans already capture per-request duration with URL/method/status as span attributes. Adding a separate api.response_time_ms distribution metric is redundant data. Same logic applies to any span where we already have span.duration. I'll drop metric 1.6 entirely.

On #2: Let me think about how to consolidate. Several widgets can be merged:

  • Duration percentile charts (p50/p75/p90) are already multi-series — those are fine
  • Cache hits + misses can be one stacked area with hit as a group-by dimension
  • Memory gauges (RSS, heap_used, heap_total) are already combined — good
  • Event loop utilization + delay could share a chart but they have different units (ratio vs seconds), so they need to stay separate
  • The traversal depth table and root reason breakdown can be merged into one table
  • Code scan duration + root detection duration can share one chart as two series
  • The resolution method distribution (counter) + resolution method vs latency (table) overlap — the table subsumes the area chart

Let me revise:

write
Wrote file successfully.

LSP errors detected in other files:
<diagnostics file="/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/test/types/dashboard.test.ts">
ERROR [133:50] No overload matches this call.
  Overload 1 of 2, '(expected: "count" | "avg" | "sum" | "min" | "max" | "p50" | "p75" | "p95" | "p99" | "count_unique" | "percentile" | "p90" | "p100" | "eps" | "epm" | "any"): void', gave the following error.
    Argument of type 'string' is not assignable to parameter of type '"count" | "avg" | "sum" | "min" | "max" | "p50" | "p75" | "p95" | "p99" | "count_unique" | "percentile" | "p90" | "p100" | "eps" | "epm" | "any"'.
  Overload 2 of 2, '(expected: "count" | "avg" | "sum" | "min" | "max" | "p50" | "p75" | "p95" | "p99" | "count_unique" | "percentile" | "p90" | "p100" | "eps" | "epm" | "any"): void', gave the following error. ...
claude-opus-4-6 · 2026-04-01 17:03:35 · ~2.3K tokens

Are the cache metrics the standard the Sentry SDKs already follow? I think they just add attributes/tags on the spans?

plan · 2026-04-01 17:07:04

You're right. The Sentry Cache Module spec already uses cache.get/cache.put spans with a cache.hit attribute — that's the standard pattern, and response-cache.ts already implements it. Adding a separate cache.outcome counter metric would be non-standard duplication.

Let me check what's already on those cache spans to confirm we can query them directly:

read
<path>/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/lib/telemetry.ts</path>
<type>file</type>
<content>1085:  * callers can set `cache.hit`, `cache.item_size`, etc. after the lookup.
1086:  *
1087:  * @param name - Span name (typically the cache key or a descriptive label)
1088:  * @param op - Cache operation: `"cache.get"` for reads, `"cache.put"` for writes
1089:  * @param fn - Function to execute, receives the span for dynamic attribute setting
1090:  * @param attributes - Initial span attributes (e.g., `cache.key`, `network.peer.address`)
1091:  * @returns The result of the function
1092:  */
1093: export function withCacheSpan<T>(
1094:   name: string,
1095:   op: "cache.get" | "cache.put",
1096:   fn: (span: Span) => T | Promise<T>,
1097:   attributes?: Record<string, string | number | boolean | string[]>
1098: ): Promise<T> {
1099:   return Sentry.startSpan(
1100:     { name, op, attributes, onlyIfParent: true },
1101:     ...
read
<path>/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/src/lib/response-cache.ts</path>
<type>file</type>
<content>370:   }
371: 
372:   let key: string;
373:   try {
374:     key = buildCacheKey(method, url);
375:   } catch {
376:     // Malformed URL (e.g., self-hosted with bad base URL) — skip cache lookup.
377:     // The request will proceed without caching; fetch() itself will surface
378:     // the real error if the URL is truly broken.
379:     return;
380:   }
381: 
382:   return await withCacheSpan(
383:     url,
384:     "cache.get",
385:     async (span) => {
386:       const entry = await readCacheEntry(key);
387:       if (!entry) {
388:         span.setAttribute("cache.hit", false);
389:         return;
390:       }
391: 
392:       try {
393:         const policy = CachePolicy.fromObject(entry.policy);
394:         if (!isEntryFresh(policy, entry, requestHeaders, url)) {
395:           span.setAttribute("cache.hit", ...
claude-opus-4-6 · 2026-04-01 17:07:04 · ~2.0K tokens

Confirmed. The HTTP response cache already follows the Sentry Cache Module spec perfectly — cache.get/cache.put spans with cache.hit, cache.item_size, cache.key, and network.peer.address attributes. We can query these directly in the dashboard via span.op:cache.get with the cache.hit attribute.

Now let me check the DB-level caches to see if they also use cache spans:

grep
No files found
claude-opus-4-6 · 2026-04-01 17:07:13 · ~138 tokens

So the DB-level caches (dsn-cache, project-cache, regions) do not use withCacheSpan — they're just plain SQLite reads that happen to be auto-traced as db spans. The question is whether adding cache.get spans to those would be valuable, or whether it's overinstrumentation.

Given that these are fast SQLite lookups (sub-millisecond), wrapping them in cache spans probably isn't worth it. The important signal is whether the DSN/project resolution as a whole is fast or slow — which the new resolve span (1.1) already covers. If the cache is cold, the resolution span will be slow because it falls through to API calls.

I'll drop the cache counter metric (1.3) entirely. The HTTP response cache is already well-instrumented via the standard Sentry Cache Module spans, and the DB caches are better observed through the resolution span's latency.

claude-opus-4-6 · 2026-04-01 17:07:20 · ~287 tokens
read
<path>/home/byk/.local/share/opencode/worktree/0e8c2f3bbe145a3280d6fb6ed900a5121f382cf0/calm-forest/.opencode/plans/1775057189310-sunny-otter.md</path>
<type>file</type>
<content>1: # CLI Performance Dashboard Plan
2: 
3: ## Overview
4: 
5: Two-phase work: (1) add missing instrumentation to fill telemetry gaps, (2) create a Sentry dashboard using `sentry dashboard create` + `sentry dashboard widget add` commands.
6: 
7: ### Existing Metrics Inventory
8: 
9: **Custom distribution metrics** (`Sentry.metrics.distribution`):
10: - `completion.duration_ms` — shell completion latency (deferred queue), attrs: `command_path`
11: - `dsn.files_collected` — files found during DSN scan, attrs: `stop_on_first`
12: - `dsn.files_scanned` — files actually scanned for DSNs, attrs: `stop_on_first`
13: - `dsn.dsns_found` — DSNs discovered in code, attrs: `stop_on_first`
14: - `upgrade.delta.patch_bytes` — delta upgrade patch size, attrs: `channel`
15: - `upgrade.delta.chain_length` — delta upgrade chain ...
claude-opus-4-6 · 2026-04-01 17:07:33 · ~5.1K tokens
edit
Edit applied successfully.
claude-opus-4-6 · 2026-04-01 17:07:37 · ~13 tokens
edit
Edit applied successfully.
claude-opus-4-6 · 2026-04-01 17:07:46 · ~13 tokens

Now update the cache widget to use the existing cache.get spans instead of the dropped counter metric:

edit
Edit applied successfully.
claude-opus-4-6 · 2026-04-01 17:07:50 · ~48 tokens

Now update the implementation order and files modified sections:

edit
Edit applied successfully.
claude-opus-4-6 · 2026-04-01 17:08:00 · ~35 tokens

Now update the layout summary to reflect the cache row change:

edit
Edit applied successfully.
claude-opus-4-6 · 2026-04-01 17:08:12 · ~34 tokens