salesforce-observability

Set up comprehensive observability for Salesforce integrations with metrics, traces, and alerts. Use when implementing monitoring for Salesforce operations, setting up dashboards, or configuring alerting for Salesforce integration health. Trigger with phrases like "salesforce monitoring", "salesforce metrics", "salesforce observability", "monitor salesforce", "salesforce alerts", "salesforce tracing".

claude-code
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salesforce-pack Plugin
saas packs Category

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salesforce-pack

Claude Code skill pack for Salesforce (30 skills)

saas packs v1.0.0
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Installation

This skill is included in the salesforce-pack plugin:

/plugin install salesforce-pack@claude-code-plugins-plus

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Instructions

Salesforce Observability

Overview

Set up comprehensive observability for Salesforce integrations.

Prerequisites

  • Prometheus or compatible metrics backend
  • OpenTelemetry SDK installed
  • Grafana or similar dashboarding tool
  • AlertManager configured

Metrics Collection

Key Metrics

Metric Type Description
salesforcerequeststotal Counter Total API requests
salesforcerequestduration_seconds Histogram Request latency
salesforceerrorstotal Counter Error count by type
salesforceratelimit_remaining Gauge Rate limit headroom

Prometheus Metrics


import { Registry, Counter, Histogram, Gauge } from 'prom-client';

const registry = new Registry();

const requestCounter = new Counter({
  name: 'salesforce_requests_total',
  help: 'Total Salesforce API requests',
  labelNames: ['method', 'status'],
  registers: [registry],
});

const requestDuration = new Histogram({
  name: 'salesforce_request_duration_seconds',
  help: 'Salesforce request duration',
  labelNames: ['method'],
  buckets: [0.05, 0.1, 0.25, 0.5, 1, 2.5, 5],
  registers: [registry],
});

const errorCounter = new Counter({
  name: 'salesforce_errors_total',
  help: 'Salesforce errors by type',
  labelNames: ['error_type'],
  registers: [registry],
});

Instrumented Client


async function instrumentedRequest<T>(
  method: string,
  operation: () => Promise<T>
): Promise<T> {
  const timer = requestDuration.startTimer({ method });

  try {
    const result = await operation();
    requestCounter.inc({ method, status: 'success' });
    return result;
  } catch (error: any) {
    requestCounter.inc({ method, status: 'error' });
    errorCounter.inc({ error_type: error.code || 'unknown' });
    throw error;
  } finally {
    timer();
  }
}

Distributed Tracing

OpenTelemetry Setup


import { trace, SpanStatusCode } from '@opentelemetry/api';

const tracer = trace.getTracer('salesforce-client');

async function tracedSalesforceCall<T>(
  operationName: string,
  operation: () => Promise<T>
): Promise<T> {
  return tracer.startActiveSpan(`salesforce.${operationName}`, async (span) => {
    try {
      const result = await operation();
      span.setStatus({ code: SpanStatusCode.OK });
      return result;
    } catch (error: any) {
      span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
      span.recordException(error);
      throw error;
    } finally {
      span.end();
    }
  });
}

Logging Strategy

Structured Logging


import pino from 'pino';

const logger = pino({
  name: 'salesforce',
  level: process.env.LOG_LEVEL || 'info',
});

function logSalesforceOperation(
  operation: string,
  data: Record<string, any>,
  duration: number
) {
  logger.info({
    service: 'salesforce',
    operation,
    duration_ms: duration,
    ...data,
  });
}

Alert Configuration

Prometheus AlertManager Rules


# salesforce_alerts.yaml
groups:
  - name: salesforce_alerts
    rules:
      - alert: SalesforceHighErrorRate
        expr: |
          rate(salesforce_errors_total[5m]) /
          rate(salesforce_requests_total[5m]) > 0.05
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Salesforce error rate > 5%"

      - alert: SalesforceHighLatency
        expr: |
          histogram_quantile(0.95,
            rate(salesforce_request_duration_seconds_bucket[5m])
          ) > 2
        for: 5m
        labels:
          severity: warning
        annotations:
          summary: "Salesforce P95 latency > 2s"

      - alert: SalesforceDown
        expr: up{job="salesforce"} == 0
        for: 1m
        labels:
          severity: critical
        annotations:
          summary: "Salesforce integration is down"

Dashboard

Grafana Panel Queries


{
  "panels": [
    {
      "title": "Salesforce Request Rate",
      "targets": [{
        "expr": "rate(salesforce_requests_total[5m])"
      }]
    },
    {
      "title": "Salesforce Latency P50/P95/P99",
      "targets": [{
        "expr": "histogram_quantile(0.5, rate(salesforce_request_duration_seconds_bucket[5m]))"
      }]
    }
  ]
}

Instructions

Step 1: Set Up Metrics Collection

Implement Prometheus counters, histograms, and gauges for key operations.

Step 2: Add Distributed Tracing

Integrate OpenTelemetry for end-to-end request tracing.

Step 3: Configure Structured Logging

Set up JSON logging with consistent field names.

Step 4: Create Alert Rules

Define Prometheus alerting rules for error rates and latency.

Output

  • Metrics collection enabled
  • Distributed tracing configured
  • Structured logging implemented
  • Alert rules deployed

Error Handling

Issue Cause Solution
Missing metrics No instrumentation Wrap client calls
Trace gaps Missing propagation Check context headers
Alert storms Wrong thresholds Tune alert rules
High cardinality Too many labels Reduce label values

Examples

Quick Metrics Endpoint


app.get('/metrics', async (req, res) => {
  res.set('Content-Type', registry.contentType);
  res.send(await registry.metrics());
});

Resources

Next Steps

For incident response, see salesforce-incident-runbook.

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