Migrating from Datadog: A Practical Guide to Reducing Costs
Trending Topics January 10, 2026 · 5 min read

Migrating from Datadog: A Practical Guide to Reducing Costs

Step-by-step guide to migrating away from Datadog while maintaining observability. Reduce costs by 70-90% without losing visibility.

Datadog is a powerful platform, but its costs can spiral quickly. Many organizations find themselves paying $50k, $100k, or even $500k+ per month - often for features they don't fully use. If you're looking to reduce costs while maintaining visibility, here's a practical migration guide.

Why Organizations Migrate

Cost Growth

Typical Datadog cost trajectory:
  Year 1: $2,000/month (startup pricing)
  Year 2: $8,000/month (growth + features)
  Year 3: $25,000/month (more hosts, more data)
  Year 4: $60,000/month (scale + enterprise tier)

Common triggers:
  - Annual renewal with 40%+ increase
  - Budget cuts requiring cost reduction
  - Sticker shock after traffic growth

Feature Overlap

Many Datadog customers only actively use a fraction of what they pay for:

Commonly used:
  ✓ Log Management
  ✓ APM (basic tracing)
  ✓ Infrastructure monitoring

Often unused:
  ✗ Security monitoring
  ✗ Synthetics
  ✗ RUM
  ✗ Database monitoring
  ✗ Network monitoring

Migration Approaches

Option 1: Full Replacement

Replace Datadog entirely with alternatives:
  Logs → 401 Clicks / Loki / Elasticsearch
  APM → Jaeger / Tempo / SigNoz
  Metrics → Prometheus / VictoriaMetrics
  Dashboards → Grafana

Pros: Maximum cost savings (70-90%)
Cons: Most effort, potential gaps

Option 2: Partial Migration

Move high-volume/low-value to cheaper tools:
  Debug logs → 401 Clicks (90% of volume)
  Keep in Datadog: APM, critical dashboards

Pros: Moderate savings (40-60%), lower risk
Cons: Multiple tools to manage

Option 3: Optimization First

Reduce Datadog costs without migrating:
  - Filter noise before ingestion
  - Adjust retention policies
  - Remove unused integrations
  - Downgrade feature tiers

Pros: No migration effort
Cons: Limited savings (20-40%)

Step-by-Step Migration

Phase 1: Audit (Week 1-2)

1. Inventory current Datadog usage:
   - Which features are actively used?
   - Data volumes by source
   - Dashboard/alert usage patterns

2. Document critical capabilities:
   - Which dashboards are essential?
   - What alerts are actively used?
   - Who uses what features?

3. Calculate cost breakdown:
   - Cost per feature
   - Cost per data source
   - Cost per team

Phase 2: Select Alternatives (Week 2-3)

For log management:
  High volume, cost-sensitive → 401 Clicks
  Self-hosted → Loki + Grafana
  Enterprise features → Elastic Cloud

For APM/Tracing:
  Simple needs → Jaeger
  Full-featured → SigNoz, Tempo
  Vendor-managed → Honeycomb

For Metrics:
  Prometheus + Grafana (standard choice)
  VictoriaMetrics (high cardinality)
  InfluxDB (time-series focused)

Phase 3: Parallel Running (Week 3-6)

1. Set up new platform(s)

2. Configure dual shipping:
   # Ship to both Datadog and new platform
   logs → [Datadog, 401 Clicks]
   traces → [Datadog, Jaeger]
   metrics → [Datadog, Prometheus]

3. Verify data parity:
   - Compare log counts
   - Verify trace completeness
   - Check metric accuracy

4. Recreate critical dashboards:
   - Start with most-used dashboards
   - Document what can't be replicated
   - Train users on new interfaces

Phase 4: Gradual Cutover (Week 6-10)

Week 6: Move debug/info logs
  - Lowest risk
  - Highest volume
  - Quick cost impact

Week 7: Move non-critical traces
  - Keep APM for critical services
  - Move background jobs, batch processes

Week 8: Move metrics
  - Infrastructure metrics
  - Custom business metrics

Week 9: Move remaining logs
  - Error logs
  - Audit logs

Week 10: Final cutover
  - Disable Datadog agents
  - Cancel/downgrade contract

Technical Migration Details

Migrating Logs

# Before: Datadog agent
datadog:
  logs_enabled: true
  logs_config:
    container_collect_all: true

# After: Vector to 401 Clicks
sources:
  docker_logs:
    type: docker_logs

sinks:
  401clicks:
    type: http
    inputs: [docker_logs]
    uri: https://ingest.401clicks.com/logs
    encoding:
      codec: json
    auth:
      strategy: bearer
      token: ${API_KEY}

Migrating Traces

# Before: Datadog APM
DD_TRACE_ENABLED=true
DD_APM_ENABLED=true
DD_TRACE_AGENT_URL=http://localhost:8126

# After: OpenTelemetry to Jaeger/401 Clicks
OTEL_TRACES_EXPORTER=otlp
OTEL_EXPORTER_OTLP_ENDPOINT=http://collector:4317
OTEL_SERVICE_NAME=my-service

Migrating Dashboards

# Export Datadog dashboards via API
curl -X GET "https://api.datadoghq.com/api/v1/dashboard/{dashboard_id}" \
  -H "DD-API-KEY: ${DD_API_KEY}" \
  -H "DD-APPLICATION-KEY: ${DD_APP_KEY}"

# Convert to Grafana format (manual or tools like grafana-dash-gen)
# Or rebuild in new platform using the JSON as reference

Handling the Gaps

Datadog Features Hard to Replace

Feature              Alternative Approach
─────────────────────────────────────────────
Unified platform     Accept multiple tools
Code-level APM       Jaeger + manual spans
Log patterns         Build queries manually
Dashboards           Grafana (learning curve)
Correlations         Manual correlation IDs

Mitigation Strategies

  • Correlation IDs - Ensure request IDs flow through all systems
  • Standardized naming - Use consistent service/resource names
  • Documentation - Write runbooks for common investigations
  • Training - Invest in team learning for new tools

Cost Comparison

Scenario: 50 hosts, 200GB logs/day, APM enabled

Datadog:
  Infrastructure: $1,125/month (50 × $23)
  Logs (200GB × 30): ~$20,000/month
  APM (50 hosts): ~$1,750/month
  Total: ~$23,000/month

Alternative Stack:
  401 Clicks (logs): $99/month (Scale plan, 100 GB/mo)
  Additional log volume: $1/GB overage
  Prometheus + Grafana: $500/month (managed)
  Jaeger (traces): $300/month (managed)
  Total: ~$900-1,500/month depending on volume

Note: 401 Clicks is ideal for teams with moderate log
volumes. For 200GB/day you may need to filter noise
before ingestion or use a hybrid approach (see above).

Savings: 70-90% depending on volume and approach

Migration to 401 Clicks

401 Clicks handles the log management portion of your migration:

  • Full-text search with regex and field queries
  • JSON log ingestion via HTTP API - works with any log shipper
  • Predictable flat-rate pricing (no surprise bills)
  • Real-time live tail and alerting built in
# Migrate logs to 401 Clicks
# 1. Get your API key from 401 Clicks dashboard
# 2. Update your log shipping:

# Laravel
LOG_CHANNEL=401clicks
FOUROHONE_CLICKS_API_KEY=your_key

# Or via log forwarder
vector:
  sinks:
    401clicks:
      type: http
      uri: https://ingest.401clicks.com/logs
      auth:
        strategy: bearer
        token: ${FOUROHONE_CLICKS_API_KEY}

Common Migration Mistakes

  1. Big bang migration - Go gradual, not all at once
  2. Skipping parallel run - Always verify before cutting over
  3. Ignoring team training - New tools need learning time
  4. Under-estimating dashboard rebuild - Budget time for this
  5. Forgetting alerts - Migrate alerting rules explicitly

Conclusion

Migrating from Datadog is a significant project but can yield massive cost savings - typically 70-90% for similar functionality. The key is methodical execution: audit thoroughly, run in parallel, migrate gradually, and invest in team training.

Start with the highest-volume, lowest-risk data (debug logs), prove the new platform works, and expand from there. Within 2-3 months, you can complete a full migration and significantly reduce your observability spend.

logging observability cost-optimization
A

Admin

Published on January 10, 2026

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