text stringlengths 0 59.1k |
|---|
### Scenario 2: Quality Issues |
**Problem:** Agent returns weird responses to some questions. |
**What You See in Langfuse:** |
- Evaluation dashboard shows low scores in certain categories |
- You inspect faulty traces and find patterns |
- You are aware of which prompts are faulty |
**Solution:** Rewrite prompts and check with A/B testing. |
### Scenario 3: Cost Optimization |
**Problem:** LLM costs monthly are 3x what they are supposed to be. |
**What You See in Langfuse:** |
- Cost dashboard shows which agents are expensive |
- Token usage analysis finds overly long prompts |
- You are aware of which conversations take too many tokens |
**Solution:** Model downgrade and prompt optimization reduce cost by 60%. |
## Production Best Practices |
### Monitoring Strategy |
When keeping an eye on your LLM application in production, take a layered approach. At the ground floor level, observe server health and database performance at the system level. The second level up, observe VoltAgent metrics and error rates at the app level. The third level up, observe Langfuse traces and quality scor... |
The multi-layered design enables you to see at a glance where problems are coming from. A server problem, app bug, AI quality defect, or business logic error - you can see each separately. |
### Alert Configuration |
Divide alerts into three categories. **Critical alerts** are situations that demand immediate action - system down, percentage of errors exceeded 5%, response time exceeded 10 seconds. When these types of alerts come in, you have to act immediately. |
**Warning alerts** are conditions worth watching out for. Quality score dropped more than 20%, cost increased by 50%, usage increased 200%. These are not critical conditions but could be problems if they continue as trends. |
**Info alerts** are conditions it is pleasant to be informed about. New user sign-up, changes in feature utilization, performance tuning. These alerts usually reflect positive trends. |
### Data Retention |
Clean your data into three buckets. **Hot data** is data of last 7 days, real-time dashboard, active debugging and real-time alerts. This data should be stored on the fastest available storage. |
**Warm data** is data of last 3 months - for trend analysis, monthly reporting and historical comparison. This data can be stored in relatively slower but accessible storage. |
**Cold data** is data stored long-term - for long-term research and analysis for compliance requirements. The data may be stored in the cheapest storage, access time may be longer. |
This solution has both cost optimization as well as maintains the performance. You can access any data whenever you require but incur unnecessary storage costs. |
## Security and Privacy |
### Data Protection |
Langfuse provides you with two methods of protecting your data. If you choose **Langfuse Cloud**, you have enterprise-grade security that is SOC 2 Type II compliant. GDPR compliant, it fully adheres to all European data protection laws. Your data remains in Europe with EU data residency and is protected by end-to-end e... |
The **self-hosted option** works best for those who require full control. Your data is completely in your control, you can implement your own security policies. You can host it on your own servers with on-premises deployment, even use it in air-gapped environments. |
### Processing PII |
:::important |
Automated scrubbing for protection of personal data exists. Email addresses, phone numbers, credit card numbers and social security numbers are automatically identified and masked. |
::: |
You can even implement domain-specific sensitive data custom filters. You can even have your own custom rules with configurable regex patterns, select what to protect with whitelist/blacklist approach. For example, you can automatically mask internal ID numbers, special codes or domain-specific data. |
## Team Collaboration |
 |
### Role-Based Access |
VoltAgent + Langfuse is not just a tool for developers, but it is a team tool. Different access levels and dashboards by role. |
**Developers** have the widest access. They get to view all the traces with trace access, view errors with debug information, view bottlenecks with performance information, resolve issues with error information. They get to utilize everything needed to resolve technical issues. |
**Product Managers** are more user experience focused. They consider how users interact with user experience metrics, learn what features are popular with feature usage statistics, check overall quality with quality dashboards, achieve success with business KPIs. |
**Data Scientists** are analytics-focused with respect to access. They can examine raw data with raw data access, measure AI model success with model performance, review experiments with A/B test results, perform deep analysis with statistical analysis. |
**Support Team** is user-focused. They can see customer history along with user conversation history, replicate issues using issue recreation, give feedback using quality feedback, manage crisis cases using escalation triggers. |
### Collaboration Features |
Ease-of-work features are available as well. With **shared dashboards**, you can create team-specific views, bookmark important traces, comment on observations, share insights. |
With the **notification system**, coordination of teams is ensured. You can share important notices to the team channel with Slack integrations, alert critical notices using email notifications, push to your own systems with customized webhooks, get alerted anywhere with mobile notifications. |
## Conclusion: Why VoltAgent + Langfuse? |
Building LLM apps is tough. But with VoltAgent + Langfuse, at least you know what's going on. |
With this combination, you have: |
- **Visibility**: You have visibility on everything |
- **Control**: You can control prompts from the center |
- **Quality**: You can do systematic testing |
- **Optimization**: You can optimize cost and performance |
- **Collaboration**: You can collaborate as a team |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.