Migrate to v3

LangWatch v3 replaces Elasticsearch/OpenSearch with ClickHouse as the primary data store. This guide walks you through the full migration — the process is the same whether you’re coming from v1.x or v2.x.

This is a zero-downtime migration. Elasticsearch and ClickHouse run side-by-side during the transition. New data flows to ClickHouse immediately, and you migrate historical data at your own pace.

What Changed

Data store: Trace, span, and evaluation data is now stored in ClickHouse instead of Elasticsearch/OpenSearch
Architecture: New event-sourcing system for data processing
Helm charts: New composable overlay structure with clickhouse-serverless subchart
Environment: ELASTICSEARCH_* variables replaced by CLICKHOUSE_URL

Migration Steps Overview

Back up your databases
Deploy ClickHouse alongside your existing Elasticsearch
Upgrade LangWatch to v3
Migrate historical data from Elasticsearch to ClickHouse
Remove Elasticsearch

Prerequisites

Back up your databases — see Backups
Check release notes at github.com/langwatch/langwatch/releases
Test in staging before upgrading production
Verify your Elasticsearch cluster is healthy (all shards green)
Ensure you have enough disk space on the ClickHouse host for the migrated data

Step 1: Deploy ClickHouse

Add ClickHouse to your existing infrastructure. Your Elasticsearch instance stays running — both will operate in parallel during migration.

Docker Compose

Add the ClickHouse service to your compose.yml:

services:
  clickhouse:
    image: langwatch/clickhouse-serverless:0.2.0
    environment:
      CLICKHOUSE_PASSWORD: langwatch
    ports:
      - "8123:8123"
    volumes:
      - clickhouse-data:/var/lib/clickhouse
    deploy:
      resources:
        limits:
          memory: 2G
    healthcheck:
      test: ["CMD", "clickhouse-client", "--query", "SELECT 1"]
      interval: 5s
      timeout: 5s
      retries: 5

volumes:
  clickhouse-data:

Kubernetes (Helm)

The v3 Helm chart includes the clickhouse-serverless subchart automatically. No additional setup is needed — ClickHouse will be deployed when you upgrade the chart in Step 2.

Step 2: Upgrade LangWatch to v3

Docker Compose

Update your environment variables and pull the v3 images: Add CLICKHOUSE_URL to your app and workers environment in compose.yml:

services:
  app:
    environment:
      CLICKHOUSE_URL: http://default:langwatch@clickhouse:8123/langwatch
  workers:
    environment:
      CLICKHOUSE_URL: http://default:langwatch@clickhouse:8123/langwatch

Then pull and restart:

docker compose pull
docker compose up -d

Helm Chart

helm repo update

helm upgrade langwatch langwatch/langwatch \
  --namespace langwatch \
  --version 3.0.0 \
  -f values-production.yaml \
  --wait --timeout 10m

The Helm chart configures CLICKHOUSE_URL automatically from the ClickHouse values — no manual env var needed for either managed or external ClickHouse.

What Happens on Startup

PostgreSQL: Prisma migrations run automatically, including removing the old Elasticsearch feature flags
ClickHouse: Schema migrations create all required tables (event_log, stored_spans, trace_summaries, etc.)
New data starts flowing to ClickHouse immediately
Historical data in Elasticsearch remains readable until you migrate it

Keep your ELASTICSEARCH_NODE_URL configured during this phase. LangWatch v3 can still read from Elasticsearch for data that hasn’t been migrated yet.

Step 3: Migrate Historical Data

The es-migration tool reads documents from Elasticsearch and writes them to ClickHouse via the event-sourcing system. It runs outside of your LangWatch deployment — no Redis or BullMQ needed.

Setup

# Clone the repository
git clone https://github.com/langwatch/langwatch.git

# Navigate to the langwatch workspace
cd langwatch

# Install dependencies from the langwatch pnpm workspace
pnpm install

# Navigate to the migration tool
cd packages/es-migration

Configure

Set the required environment variables:

export ELASTICSEARCH_NODE_URL="http://localhost:9200"
export CLICKHOUSE_URL="http://default:langwatch@localhost:8123/langwatch"

# If your Elasticsearch requires authentication
export ELASTICSEARCH_API_KEY="your-api-key"

Point these at your actual Elasticsearch and ClickHouse instances. If they’re running in Docker or Kubernetes, you may need to set up port forwarding or use the internal network addresses.

Credential requirements:

Elasticsearch: Use a read-only user or API key. The migration tool only reads from ES — a read-only credential protects your source data from accidental writes.
ClickHouse: Use a user with write access. The tool needs to insert into event_log and projection tables.

Disable ClickHouse TTLs Before Migrating

This step is critical. If you skip it, ClickHouse may immediately expire or offload historical data as it arrives during migration.

LangWatch uses TTL rules to manage data retention and tiered storage in ClickHouse. By default, data older than 49 days is moved to cold storage (or dropped if cold storage isn’t configured). When you migrate historical data from Elasticsearch, much of it will be older than 49 days — so ClickHouse would try to expire or offload it the moment it lands. Before starting the migration, set the TTL to a very high value so all migrated data stays in hot storage:

Docker Compose

Add to your app and workers environment:

services:
  app:
    environment:
      TIERED_STORAGE_DEFAULT_HOT_DAYS: "9999"
  workers:
    environment:
      TIERED_STORAGE_DEFAULT_HOT_DAYS: "9999"

Then restart:

docker compose up -d

Helm Chart

app:
  extraEnvs:
    - name: TIERED_STORAGE_DEFAULT_HOT_DAYS
      value: "9999"
workers:
  extraEnvs:
    - name: TIERED_STORAGE_DEFAULT_HOT_DAYS
      value: "9999"

Then upgrade:

helm upgrade langwatch langwatch/langwatch \
  --namespace langwatch \
  -f values-production.yaml \
  --wait --timeout 10m

The TTL reconciler runs on startup and updates the ClickHouse table metadata without reorganizing existing data. Any data that needs to be moved to a different storage tier due to the new TTL policy, will happen asynchronously and be managed by ClickHouse.

After Migration: Restore TTLs

Once the migration is complete, set TIERED_STORAGE_DEFAULT_HOT_DAYS back to your desired retention value and restart LangWatch. ClickHouse handles the offloading gracefully in the background.

We recommend setting TTL values to a multiple of 7 (e.g., 7, 14, 28, 49) to align with ClickHouse partition boundaries for more efficient data management.

Migration Targets

The tool migrates data in separate targets:

Target	Description
`traces-combined`	Traces and their evaluations
`simulations`	Simulation run events
`batch-evaluations`	Batch experiment evaluation data
`dspy-steps`	DSPy optimization steps
`all`	Run all primary targets in sequence

Testing Workflow

Start small and verify before running the full migration: 1. Dry-run a single batch — validate the mapping without writing anything:

pnpm tsx src/index.ts traces-combined --dry-run --single-batch

Review the output in ./dry-run-traces-combined.json to confirm the data looks correct. 2. Live single batch — process one batch and verify in ClickHouse:

pnpm tsx src/index.ts traces-combined --single-batch

3. Limited run — process a few thousand events to catch edge cases:

MAX_EVENTS=5000 pnpm tsx src/index.ts traces-combined

4. Full migration — migrate everything:

pnpm tsx src/index.ts all

For large history systems, we recommend running one target at a time instead of all, so you can apply the tuning profiles below for each target individually.

Recommended Tuning

Each target has different document sizes and volumes, so tuning per-target improves throughput. Traces and evaluations (large volume):

export BATCH_SIZE=5000
export SUB_BATCH_SIZE=2000
export CH_BATCH_SIZE=5000
export CONCURRENCY=1000
export CURSOR_REWIND_MS=21600000

DSPy steps (smaller documents):

export BATCH_SIZE=100
export CH_BATCH_SIZE=100
export CONCURRENCY=10
export CURSOR_REWIND_MS=21600000

Runtime Controls

Pause/Resume: Press p during migration to pause after the current batch. Press p again to resume.
Graceful shutdown: Ctrl+C finishes the current batch then exits. Press again to force quit.
ClickHouse backpressure: The tool monitors ClickHouse merge load and pauses automatically when it’s too high. It resumes when merges catch up.

Resume After Interruption

The migration saves progress to a cursor file (e.g., ./cursor-traces-combined.json). If interrupted, it resumes from the last checkpoint on restart. To start a target from scratch, delete its cursor file.

Verify the Migration

After migration completes, verify the data in ClickHouse:

# Connect to ClickHouse
clickhouse-client --host localhost --port 9000

# Check trace counts
SELECT COUNT(*) FROM langwatch.trace_summaries;

# Check event log
SELECT AggregateType, COUNT(*) FROM langwatch.event_log GROUP BY AggregateType;

Compare these counts against your Elasticsearch indices to confirm completeness. Note that you may wish to run a distinct check against the ProjectionId column on trace summaries as if there are any MergeTree Replacements that need to happen it could cause the count operation to report duplicates in the count.

Step 4: Remove Elasticsearch

Once you’ve verified the migration:

Remove Elasticsearch environment variables from your configuration:
- ELASTICSEARCH_NODE_URL
- ELASTICSEARCH_API_KEY
Remove the Elasticsearch service from your compose.yml or Helm values
Restart LangWatch to apply the changes

Docker Compose

# After removing the elasticsearch service from compose.yml
docker compose up -d

Helm

helm upgrade langwatch langwatch/langwatch \
  --namespace langwatch \
  -f values-production.yaml \
  --wait --timeout 10m

Environment Variable Changes

Variable	v1.x / v2.x	v3.0
`ELASTICSEARCH_NODE_URL`	Required	Remove
`ELASTICSEARCH_API_KEY`	Optional	Remove
`CLICKHOUSE_URL`	—	Required

All other environment variables remain the same. See Environment Variables for the full reference.

Troubleshooting

Toxic documents

If a single Elasticsearch document is too large and crashes an ES shard during migration, the tool detects this, skips the problematic document, and logs its ID to ./skipped-toxic-docs.log. These documents may need manual handling.

Response too large

If an Elasticsearch response exceeds the Node.js string limit (~1 GB), the tool automatically halves the batch size and retries.

Transient Elasticsearch errors

For timeouts or connection issues, the tool uses exponential backoff (up to 5 retries) and reduces batch size if errors persist.

Migration seems slow

Check ClickHouse merge load in the progress output (ch_parts column)
Increase CONCURRENCY and BATCH_SIZE if your hardware can handle it
The tool auto-pauses when ClickHouse is under merge pressure — this is normal

Getting Help

Check the Troubleshooting guide
Open an issue at github.com/langwatch/langwatch/issues
Contact support

Overview

Configuration

Deployment

Infrastructure

Operations

What Changed

Migration Steps Overview

Prerequisites

Step 1: Deploy ClickHouse

Docker Compose

Kubernetes (Helm)

Step 2: Upgrade LangWatch to v3

Docker Compose

Helm Chart

What Happens on Startup

Step 3: Migrate Historical Data

Setup

Configure

Disable ClickHouse TTLs Before Migrating

Docker Compose

Helm Chart

After Migration: Restore TTLs

Migration Targets

Testing Workflow

Recommended Tuning

Runtime Controls

Resume After Interruption

Verify the Migration

Step 4: Remove Elasticsearch

Docker Compose

Helm

Environment Variable Changes

Troubleshooting

Toxic documents

Response too large

Transient Elasticsearch errors

Migration seems slow

Getting Help

Overview

Configuration

Deployment

Infrastructure

Operations

​What Changed

​Migration Steps Overview

​Prerequisites

​Step 1: Deploy ClickHouse

​Docker Compose

​Kubernetes (Helm)

​Step 2: Upgrade LangWatch to v3

​Docker Compose

​Helm Chart

​What Happens on Startup

​Step 3: Migrate Historical Data

​Setup

​Configure

​Disable ClickHouse TTLs Before Migrating

​Docker Compose

​Helm Chart

​After Migration: Restore TTLs

​Migration Targets

​Testing Workflow

​Recommended Tuning

​Runtime Controls

​Resume After Interruption

​Verify the Migration

​Step 4: Remove Elasticsearch

​Docker Compose

​Helm

​Environment Variable Changes

​Troubleshooting

​Toxic documents

​Response too large

​Transient Elasticsearch errors

​Migration seems slow

​Getting Help

What Changed

Migration Steps Overview

Prerequisites

Step 1: Deploy ClickHouse

Docker Compose

Kubernetes (Helm)

Step 2: Upgrade LangWatch to v3

Docker Compose

Helm Chart

What Happens on Startup

Step 3: Migrate Historical Data

Setup

Configure

Disable ClickHouse TTLs Before Migrating

Docker Compose

Helm Chart

After Migration: Restore TTLs

Migration Targets

Testing Workflow

Recommended Tuning

Runtime Controls

Resume After Interruption

Verify the Migration

Step 4: Remove Elasticsearch

Docker Compose

Helm

Environment Variable Changes

Troubleshooting

Toxic documents

Response too large

Transient Elasticsearch errors

Migration seems slow

Getting Help