langfuse-migration-deep-dive
A guide for migrating data and platforms between Langfuse instances or other observability tools.
Install
mkdir -p .claude/skills/langfuse-migration-deep-dive && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/9310" && unzip -o skill.zip -d .claude/skills/langfuse-migration-deep-dive && rm skill.zipInstalls to .claude/skills/langfuse-migration-deep-dive
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Execute complex Langfuse migrations including data migration and platformKey capabilities
- →Export traces, scores, prompts, and datasets from source instances
- →Import data into target Langfuse instances
- →Validate migration success by comparing trace counts
- →Implement dual-write patterns for zero-downtime migration
- →Execute rollback procedures to source instances
How it works
The skill utilizes the Langfuse client API to programmatically export data from a source instance and import it into a target instance. It includes validation scripts to ensure data parity and dual-write patterns to maintain observability during the transition.
Inputs & outputs
When to use langfuse-migration-deep-dive
- →Migrate from LangSmith to Langfuse
- →Move Langfuse from cloud to self-hosted
- →Perform cross-instance data migration
- →Implement zero-downtime dual-write patterns
About this skill
Langfuse Migration Deep Dive
Current State
!npm list langfuse @langfuse/client 2>/dev/null | head -5 || echo 'No langfuse packages'
Overview
Comprehensive guide for complex migrations: cloud-to-self-hosted, LangSmith-to-Langfuse, cross-instance data migration, and zero-downtime dual-write patterns.
Prerequisites
- Understanding of source and target Langfuse instances
- API keys for both source and target
- Git branch for migration work
- Rollback plan documented
Migration Scenarios
| Scenario | Complexity | Downtime | Data Loss Risk |
|---|---|---|---|
| Cloud to Cloud (different project) | Low | None | None |
| Cloud to Self-hosted | Medium | Minutes | Low |
| Self-hosted to Cloud | Medium | Minutes | Low |
| LangSmith to Langfuse | High | Hours | Medium |
| SDK v3 to v4+ (no data migration) | Low | None | None |
Instructions
Step 1: Export Data from Source Instance
// scripts/export-langfuse.ts
import { LangfuseClient } from "@langfuse/client";
import { writeFileSync, mkdirSync } from "fs";
const source = new LangfuseClient({
publicKey: process.env.SOURCE_LANGFUSE_PUBLIC_KEY,
secretKey: process.env.SOURCE_LANGFUSE_SECRET_KEY,
baseUrl: process.env.SOURCE_LANGFUSE_BASE_URL,
});
async function exportAll(outputDir: string) {
mkdirSync(outputDir, { recursive: true });
// Export traces
let page = 1;
let allTraces: any[] = [];
let hasMore = true;
console.log("Exporting traces...");
while (hasMore) {
const result = await source.api.traces.list({ limit: 100, page });
allTraces.push(...result.data);
hasMore = result.data.length === 100;
page++;
await new Promise((r) => setTimeout(r, 200)); // Rate limit
}
writeFileSync(`${outputDir}/traces.json`, JSON.stringify(allTraces, null, 2));
console.log(` Exported ${allTraces.length} traces`);
// Export scores
page = 1;
let allScores: any[] = [];
hasMore = true;
console.log("Exporting scores...");
while (hasMore) {
const result = await source.api.scores.list({ limit: 100, page });
allScores.push(...result.data);
hasMore = result.data.length === 100;
page++;
await new Promise((r) => setTimeout(r, 200));
}
writeFileSync(`${outputDir}/scores.json`, JSON.stringify(allScores, null, 2));
console.log(` Exported ${allScores.length} scores`);
// Export prompts
console.log("Exporting prompts...");
const prompts = await source.api.prompts.list({ limit: 100 });
writeFileSync(`${outputDir}/prompts.json`, JSON.stringify(prompts.data, null, 2));
console.log(` Exported ${prompts.data.length} prompts`);
// Export datasets
console.log("Exporting datasets...");
const datasets = await source.api.datasets.list({ limit: 100 });
const fullDatasets = [];
for (const ds of datasets.data) {
const items = await source.api.datasetItems.list({ datasetName: ds.name, limit: 1000 });
fullDatasets.push({ ...ds, items: items.data });
await new Promise((r) => setTimeout(r, 200));
}
writeFileSync(`${outputDir}/datasets.json`, JSON.stringify(fullDatasets, null, 2));
console.log(` Exported ${fullDatasets.length} datasets`);
}
exportAll("./migration-export");
Step 2: Import Data to Target Instance
// scripts/import-langfuse.ts
import { LangfuseClient } from "@langfuse/client";
import { readFileSync } from "fs";
const target = new LangfuseClient({
publicKey: process.env.TARGET_LANGFUSE_PUBLIC_KEY,
secretKey: process.env.TARGET_LANGFUSE_SECRET_KEY,
baseUrl: process.env.TARGET_LANGFUSE_BASE_URL,
});
async function importAll(inputDir: string) {
// Import prompts first (no dependencies)
console.log("Importing prompts...");
const prompts = JSON.parse(readFileSync(`${inputDir}/prompts.json`, "utf-8"));
for (const prompt of prompts) {
await target.api.prompts.create({
name: prompt.name,
prompt: prompt.prompt,
type: prompt.type,
config: prompt.config,
labels: prompt.labels,
});
console.log(` Imported prompt: ${prompt.name}`);
await new Promise((r) => setTimeout(r, 100));
}
// Import datasets
console.log("Importing datasets...");
const datasets = JSON.parse(readFileSync(`${inputDir}/datasets.json`, "utf-8"));
for (const ds of datasets) {
await target.api.datasets.create({
name: ds.name,
description: ds.description,
metadata: { ...ds.metadata, migratedFrom: "source-instance" },
});
for (const item of ds.items || []) {
await target.api.datasetItems.create({
datasetName: ds.name,
input: item.input,
expectedOutput: item.expectedOutput,
metadata: item.metadata,
});
await new Promise((r) => setTimeout(r, 50));
}
console.log(` Imported dataset: ${ds.name} (${ds.items?.length || 0} items)`);
}
console.log("Import complete.");
console.log("Note: Traces and scores are historical -- they reference old trace IDs.");
console.log("New traces will be created by your application pointing to the target.");
}
importAll("./migration-export");
Step 3: Dual-Write for Zero-Downtime Migration
Write traces to both instances during transition:
// src/lib/dual-write-langfuse.ts
import { LangfuseSpanProcessor } from "@langfuse/otel";
import { NodeSDK } from "@opentelemetry/sdk-node";
// Create processors for both instances
const sourceProcessor = new LangfuseSpanProcessor({
publicKey: process.env.SOURCE_LANGFUSE_PUBLIC_KEY,
secretKey: process.env.SOURCE_LANGFUSE_SECRET_KEY,
baseUrl: process.env.SOURCE_LANGFUSE_BASE_URL,
});
const targetProcessor = new LangfuseSpanProcessor({
publicKey: process.env.TARGET_LANGFUSE_PUBLIC_KEY,
secretKey: process.env.TARGET_LANGFUSE_SECRET_KEY,
baseUrl: process.env.TARGET_LANGFUSE_BASE_URL,
});
// Both processors receive all spans
const sdk = new NodeSDK({
spanProcessors: [sourceProcessor, targetProcessor],
});
sdk.start();
// Migration timeline:
// Week 1: Dual-write enabled, verify target receives traces
// Week 2: Validate data parity between instances
// Week 3: Switch primary to target, keep source as backup
// Week 4: Remove source processor
Step 4: Validate Migration
// scripts/validate-migration.ts
import { LangfuseClient } from "@langfuse/client";
const source = new LangfuseClient({
publicKey: process.env.SOURCE_LANGFUSE_PUBLIC_KEY,
secretKey: process.env.SOURCE_LANGFUSE_SECRET_KEY,
baseUrl: process.env.SOURCE_LANGFUSE_BASE_URL,
});
const target = new LangfuseClient({
publicKey: process.env.TARGET_LANGFUSE_PUBLIC_KEY,
secretKey: process.env.TARGET_LANGFUSE_SECRET_KEY,
baseUrl: process.env.TARGET_LANGFUSE_BASE_URL,
});
async function validate() {
// Compare prompt counts
const sourcePrompts = await source.api.prompts.list({ limit: 100 });
const targetPrompts = await target.api.prompts.list({ limit: 100 });
console.log(`Prompts: source=${sourcePrompts.data.length}, target=${targetPrompts.data.length}`);
// Compare dataset counts
const sourceDatasets = await source.api.datasets.list({ limit: 100 });
const targetDatasets = await target.api.datasets.list({ limit: 100 });
console.log(`Datasets: source=${sourceDatasets.data.length}, target=${targetDatasets.data.length}`);
// Compare recent trace counts (dual-write period)
const since = new Date(Date.now() - 3600000).toISOString();
const sourceTraces = await source.api.traces.list({ fromTimestamp: since, limit: 100 });
const targetTraces = await target.api.traces.list({ fromTimestamp: since, limit: 100 });
console.log(`Recent traces (1h): source=${sourceTraces.data.length}, target=${targetTraces.data.length}`);
const variance = Math.abs(sourceTraces.data.length - targetTraces.data.length) / Math.max(sourceTraces.data.length, 1);
console.log(`Trace variance: ${(variance * 100).toFixed(1)}% (target: <5%)`);
}
validate();
Step 5: Cutover and Cleanup
// After validation passes:
// 1. Update environment variables to point to target
// LANGFUSE_PUBLIC_KEY=pk-lf-target-...
// LANGFUSE_SECRET_KEY=sk-lf-target-...
// LANGFUSE_BASE_URL=https://target.langfuse.com
// 2. Remove dual-write (use single processor)
const sdk = new NodeSDK({
spanProcessors: [targetProcessor], // Only target
});
// 3. Keep source instance running for 30 days (rollback window)
// 4. After 30 days, decommission source
Rollback Plan
set -euo pipefail
# If migration fails, switch back to source:
# 1. Update environment variables
export LANGFUSE_PUBLIC_KEY="pk-lf-source-..."
export LANGFUSE_SECRET_KEY="sk-lf-source-..."
export LANGFUSE_BASE_URL="https://source.langfuse.com"
# 2. Restart application
# 3. Verify traces flowing to source
Error Handling
| Issue | Cause | Solution |
|---|---|---|
| Export timeout | Too much data | Paginate with smaller page sizes |
| Import duplicates | Re-running import | Use idempotent creates with unique names |
| Dual-write divergence | One instance failing | Monitor both, alert on variance > 5% |
| Missing prompts | Not exported | Export prompts before datasets |
Resources
When not to use it
- →When migrating non-Langfuse observability data
- →When the source and target instances have incompatible schemas
Prerequisites
Limitations
- →Traces and scores are historical and reference old trace IDs
- →Export may timeout with large datasets
How it compares
This approach uses automated scripts for data transfer, whereas manual migration is prone to data loss and configuration errors.
Compared to similar skills
langfuse-migration-deep-dive side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| langfuse-migration-deep-dive (this skill) | 0 | 24d | Review | Advanced |
| distributed-tracing | 5 | 2mo | No flags | Intermediate |
| service-mesh-observability | 5 | 2mo | No flags | Advanced |
| terminal-context | 5 | 7mo | Review | Advanced |
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