Introduction and Framing the Problem (5 minutes)
Analogy:
Imagine driving a car without a dashboard. You hear strange noises, but you have no clue whether it's the engine, tires, or something else. This is what debugging without metrics feels like—you’re guessing in the dark.

Points to Cover:
- Django’s Popularity: Django powers 32% of the web development market, making it crucial to ensure high availability and performance for production apps.
- The Real Problem: Beyond building great apps, developers face incident management challenges:
1. Handling user complaints ("It’s too slow!" or "It’s down!").
2. Being on-call at odd hours to identify issues under time pressure.
3. Searching through 100k+ logs to pinpoint the root cause.
4. Lack of actionable insights from logs and bad visualization tools.

Promise of the Workshop:
By using Prometheus and Grafana, we can equip developers with dashboards for their “car”—making debugging faster and more proactive.

The Developer’s Pain Points (15 minutes)
Analogy:
Think of your application as a sprawling city. Each endpoint is a street, and users are cars driving around. Without traffic cameras (metrics), you only know about a pile-up after hearing complaints. Monitoring tools are your traffic control system—they prevent jams and accidents by identifying patterns early.

Three Pain Points and Their Solutions:
Root Cause Analysis: Debugging Through 100k+ Logs

• Pain Point: Logs are necessary but overwhelming. Searching for a single error in a sea of logs is like finding a needle in a haystack.
  Solution:
• Use Prometheus to collect high-level metrics (e.g., request rates, error rates) for faster context.
  Pair logs with actionable metrics to narrow down problem areas.
• Demo: Show how Prometheus metrics help pinpoint a slow database query faster than sifting through logs.

On-Call Burnout: Incident Management Simplified

• Pain Point: On-call means being paged at midnight and scrambling to understand what’s going wrong.
  Solution:
• Set up alerting rules in Prometheus to flag anomalies (e.g., spikes in response time).
• Use Grafana visualizations for real-time diagnostics.
• Demo: Create an alert for high response time and show how Grafana graphs make root cause analysis visual and quick.

Supporting the Customer Care Team

• Pain Point: Customer complaints often lack clarity ("It’s slow!" isn’t helpful). Developers need to correlate vague feedback with system data.
  Solution:
• Use Grafana dashboards to generate insights that can be shared with non-technical teams (e.g., which endpoints are causing delays).
• Demo: Build a simple dashboard showing endpoint performance, request load, and error distribution.

Solution in Action: Demonstration with Django (25 minutes)

Workshop Flow:

• Integrating Prometheus with Django: Set up Prometheus to scrape metrics from a Django app.
• Customizing Metrics: Add custom metrics (e.g., monitor a critical feature).
• Visualizing in Grafana: Build panels for:
  • Request rates.
  • Error counts.
  • Database query times.
• Alerting in Practice: Configure an alert in Grafana based on a threshold (e.g., 95th percentile response time).

Showcase Scenarios:

• Identify a slow endpoint using visualized metrics.
• Demonstrate how alerts highlight performance degradation before users complain.
• Share how to use these dashboards to answer customer care queries efficiently.

Wrap-Up and Key Takeaways (5 minutes)

Reinforce the Analogy:

By integrating Prometheus and Grafana, you’ve turned your app from a car with no dashboard into a modern vehicle with GPS, traffic alerts, and maintenance reminders.

Key Learnings:

• Monitoring isn’t just about tracking metrics—it’s about faster debugging and better incident management.
• Prometheus and Grafana provide tools for proactive performance management.
• Applying these practices to Django apps makes developers' lives easier and customer experiences better.