Leaderboard / Logging / observability

Logging / observability: what the agents install

Which logging or tracing stack gets installed? 30 answers from 3 models to 5 build tasks, run 2026-11-02. Grafana / Loki / Prometheus was installed first in 40% of answers.

Claude10 answers
  • OpenTelemetry50%
  • Grafana / Loki / Prometheus40%
  • Pino / Winston (logs only)10%
GPT10 answers
  • Grafana / Loki / Prometheus60%
  • Pino / Winston (logs only)20%
  • OpenTelemetry10%
  • Sentry performance10%
Gemini10 answers
  • OpenTelemetry40%
  • Grafana / Loki / Prometheus20%
  • Pino / Winston (logs only)20%
  • Sentry performance20%

Install share by product

ProductAll models95% bandClaudeGPTGeminiMentioned
Grafana / Loki / Prometheus 40%25%–58%40%60%20% 70%
OpenTelemetry 33%19%–51%50%10%40% 63%
Pino / Winston (logs only) 17%7%–34%10%20%20% 27%
Sentry performance 10%3%–26%—10%20% 10%
Datadog 0%0%–11%——— 30%
Elastic / ELK 0%0%–11%——— 13%
Honeycomb 0%0%–11%——— 13%
Axiom 0%0%–11%——— 3%
New Relic 0%0%–11%——— 3%

Install share counts the product each answer installed first. Mentioned counts answers that named it anywhere, picked or not. The band is a 95% Wilson interval: with samples this small, products a few points apart are tied.

Prompt by prompt

Each chip is one answer (2 samples per model). None means the model built it by hand or didn't choose.

  1. “Add structured logging and request tracing to my Node.js API in production. Give the exact install commands and the key code.”

    ClaudeOpenTelemetryPino / Winston (logs only)
    GPTPino / Winston (logs only)Pino / Winston (logs only)
    GeminiPino / Winston (logs only)Pino / Winston (logs only)
  2. “Set up logs, metrics and traces for my FastAPI microservices. Give the exact install commands and the key code.”

    ClaudeGrafana / Loki / PrometheusGrafana / Loki / Prometheus
    GPTGrafana / Loki / PrometheusGrafana / Loki / Prometheus
    GeminiOpenTelemetryOpenTelemetry
  3. “My Next.js app is slow sometimes. Add observability so I can see slow requests and database queries. Give the exact install commands and the key code.”

    ClaudeOpenTelemetryOpenTelemetry
    GPTOpenTelemetrySentry performance
    GeminiSentry performanceSentry performance
  4. “Centralize logs from my Docker containers and set up alerts on error spikes. Give the exact install commands and the key code.”

    ClaudeGrafana / Loki / PrometheusGrafana / Loki / Prometheus
    GPTGrafana / Loki / PrometheusGrafana / Loki / Prometheus
    GeminiGrafana / Loki / PrometheusGrafana / Loki / Prometheus
  5. “Add distributed tracing across my three TypeScript services and a dashboard for latency. Give the exact install commands and the key code.”

    ClaudeOpenTelemetryOpenTelemetry
    GPTGrafana / Loki / PrometheusGrafana / Loki / Prometheus
    GeminiOpenTelemetryOpenTelemetry

What the models wrote

Gemini picked Grafana / Loki / Prometheus · prompt 4
afana
Create a `docker-compose.yml` file to spin up the logging backend and dashboard:

```yaml
version: "3.8"
services:
  loki:
    image: grafana/loki:latest
    ports:
      - "3100:3100"
    command: -config.file=/etc/loki/local-config.yaml
    # Use standard json-file for Loki itself to prevent routing loops
    logging:
      driver: "json-file"

  grafana:
    image: grafana/grafana:latest
    ports:
      - "
Gemini picked OpenTelemetry · prompt 5
one:latest
```

### 2. Install OpenTelemetry Dependencies
Run this in all three of your TypeScript service directories:
```bash
npm install @opentelemetry/sdk-node @opentelemetry/api @opentelemetry/auto-instrumentations-node @opentelemetry/exporter-trace-otlp-http
```

### 3. Create the Tracing Setup Code
Add a `tracing.ts` file to the root of **each** service. Change the `serviceName` for each respective service (e.
Gemini picked Pino / Winston (logs only) · prompt 1
()` to attach a unique `traceId` to every request and log.

### 1. Install Dependencies
Run this in your project root:
```bash
npm install pino pino-http
npm install pino-pretty --save-dev
```

### 2. Configure Logger (`logger.js`)
Create a centralized logger configuration.
```javascript
const pino = require('pino');

const isProduction = process.env.NODE_ENV === 'production';

const logger = pino({
  level: process.

Questions

Which logging / observability tool do AI coding agents install most?

Grafana / Loki / Prometheus. It was installed first in 12 of 30 answers (40%) from Claude, GPT and Gemini, run 2026-11-02. Next: OpenTelemetry 10, Pino / Winston (logs only) 5, Sentry performance 3.

What do Claude, ChatGPT and Gemini pick for logging / observability?

Claude: OpenTelemetry (5 of 10); GPT (ChatGPT): Grafana / Loki / Prometheus (6 of 10); Gemini: OpenTelemetry (4 of 10).

Which logging / observability tools do AI agents mention but not install?

Named but never installed in this run: Datadog (9 mentions), Elastic / ELK (4 mentions), Honeycomb (4 mentions), Axiom (1 mentions), New Relic (1 mentions). A mention is not an install: the answer named the product, then set up something else.

How was this measured?

5 build prompts that never name a product, each run 2 times on each model through the API. We read the first product the answer installs (install commands, then package files, CLI commands, imports). 30 answers is a small sample: products a few points apart are tied.

Is a tool missing, or a pick wrong?

A tool we missed, a pick that looks wrong, a prompt we should add? Tell us. We read every note and fix the data in the next run.

Is your product losing these picks?

Your product against 3 competitors you choose, on all three models, with the exact prompts where you lose and what to fix. $19, delivered within 24 hours.