Grafana Labs to Oodle AI Migration Guide

Risk-Free Migration. 3x Cost Savings. Superior DevEx.

Grafana Labs
Oodle AI
Cost
Expensive
3x cheaper
Cardinality
Performance & Cost Limitations
Designed for High Cardinality
Log Search
Complex LogQL
Intuitive OpenSearch UI + free text search
Experience
Disjointed signals
Easily correlate across signals

Plus, AI-powered debugging helps teams resolve incidents faster.

For detailed comparisons: Grafana Managed Metrics | Grafana Managed Loki

Cure.fit
"It took less than 6 hours including calls to achieve 3x cost reduction."

Kunal Khandelwal

Platform Engineering Lead, CureFit

Workorb
"Switching to Oodle AI was seamless and efficient as we moved away from Grafana Labs."

Nilesh Bansal

Co-founder and CTO, Workorb

Reliability

99.9% availability guarantee

< 1 minute ingestion latency for Logs, Metrics and Traces

Status Page

Security

ISO, SOC2 Type2 & GDPR compliant

RBAC & SSO/SAML integration

Single-tenant deployment option

Trust Center

24x7 Support

Response SLA:

Critical: 15m | High: ~1h | Other: <1d

Private Slack, Intercom & Email

"The best thing about Oodle is the team. They're always there to help out." — Suman, CTO, Fello AI

Public FinTech & Cybersecurity Unicorns trust Oodle to detect issues before their customers

CureFit
Fello
FinTech
Distacart
Cybersecurity
Workorb
HappyPath
Fuel
CureFit
Fello
FinTech
Distacart
Cybersecurity
Workorb
HappyPath
Fuel

Migration Journey

Run both systems in parallel, verify everything works, then switch.

No Data Loss
Zero Downtime
Dashboards & Alerts Preserved
1

Ingestion & Setup

⏱️ 2 hours for 1 engineer

✅ Configure double-write

✅ 1-click dashboards & alerts import

2

Verification

⏱️ 2 weeks (calendar time), ~1 day per team

✅ Validate dashboards

✅ Test queries & alerts

3

Cutover

⏱️ 2 hours for 1 engineer

✅ Activate Oodle alerts

✅ Stop Grafana ingestion

Step 1

Ingestion & Setup

Effort: 2 hours for 1 engineer

Overview

In this phase, you'll configure your observability agents to send data to both Grafana and Oodle simultaneously. This double-write approach ensures zero risk - your existing Grafana setup remains unchanged while you validate Oodle in parallel.

Key benefit: Continue using your current agents (Prometheus, Vector, OTel). No new agents to deploy.

Double-Write Architecture - Data flowing to both Grafana and Oodle

Prerequisites

  • Access to update exporters
  • Grafana URL & API Key
  • AlertManager yaml/url
  • Docker installed

1.a Configure Double-Write

Add Oodle as an additional destination for your observability data.

Metrics

  • Prometheus Remote-Write: Add Oodle as an additional remote write endpoint to prometheus.yml:
    remote_write:
      - url: https://<OODLE_ENDPOINT>/v1/prometheus/<INSTANCE_ID>/write
        name: oodle-remote-write
        headers:
          X-API-KEY: <API_KEY>
  • OTel: Send metrics via OpenTelemetry
  • CloudWatch: Direct integration for AWS metrics
  • Grafana Alloy Agent: Native support for Grafana agents
  • Grafana Pre-built Integrations: Kubernetes, MySQL, PostgreSQL, MongoDB, Redis, Elasticsearch, NGINX, Apache, HAProxy, AWS, GCP, Azure, Kafka, RabbitMQ, and 100+ more
See docs for Metrics ingestion →

Logs

  • Vector: Add the following configuration to your Vector configuration file:
    sinks:
      oodle:
        type: http
        inputs: [<sources...>]
        uri: https://<OODLE_ENDPOINT>/ingest/v1/logs
        encoding:
          codec: json
        compression: gzip
        headers:
          X-OODLE-INSTANCE: "<OODLE_INSTANCE>"
          X-API-KEY: "<OODLE_API_KEY>"
        request:
          retry_attempts: 3
          timeout_secs: 60
  • Fluent Bit: Configure Fluent Bit to send logs to Oodle endpoint
  • Fluentd: Configure Fluentd to send logs to Oodle endpoint
  • OTel: Use OpenTelemetry for log ingestion
  • Kubernetes: Direct K8s log integration
  • Promtail: Run parallel Promtail instance
  • AWS CloudWatch Logs: Direct CloudWatch integration
See docs for Logs ingestion →

Traces

  • OTel: Add Oodle exporter to OTel Config file:
    exporters:
      otlphttp/oodle:
        traces_endpoint: "https://<OODLE_INSTANCE>.collector.oodle.ai/v1/otlp/traces"
        headers:
          "X-OODLE-INSTANCE": "<OODLE_INSTANCE>"
          "X-API-KEY": "<OODLE_API_KEY>"
  • Grafana Alloy Agent: Native support for Grafana trace collection
  • Direct SDK Configuration: Language-specific SDKs (Go, Java, Python, Node.js, etc.)
See docs for Traces ingestion →

1.b Migration

Migrate your existing Grafana dashboards and alerts with a 1-click import process.

Dashboards

What gets imported: All datasources, panel configurations, visualizations, variables, annotations, dashboard organization, folders, time ranges, and refresh intervals.

  1. Navigate to Settings → Integrations → Grafana in Oodle
  2. Enter the Grafana instance URL
  3. Enter the Grafana Service token key
  4. Run docker command
  5. All dashboards and datasources are listed with their import status.
  6. Any pending configurations are flagged with instructions to fix & retry where applicable

Note: Loki dashboards are not supported for automated import at the moment. Oodle team will handle these migrations end-to-end for you.

Dashboard Migration Video

Alerts

What gets imported: Alert rule definitions and thresholds, evaluation intervals, notification policies, severity levels, labels, and annotations.

If you are using Grafana alerts, they are imported along with the dashboards.

Oodle supports alerts in Terraform. If you'd like to migrate to alerts-as-code, our team will help you set it up. Learn more.

If you are using Prometheus AlertManager:

  1. Navigate to Settings → Integrations → AlertManager Alerts
  2. Share prometheus.yml & alertmanager.yml files
  3. Alternatively, share a Prometheus instance URL & AlertManager URL for Oodle to scrape the alerts

Tip: Configure Oodle alerts to send to a separate Slack channel so you can compare alert behavior side-by-side before switching over.

Alert Migration Video
Step 2

Verification

Effort: 2 weeks calendar time, ~1 day per team

In this phase, the teams verify ingestion of all telemetry signals, dashboards, and alerts. Usually, the DevOps/Platform teams verify basic ingestion and critical dashboards, logs, & traces first. The verification is then passed on to individual application teams to verify their own dashboards and telemetry signals are working as expected.

The bulk of the time is coordination and asynchronous review, not hands-on work.

P.S. For larger companies with dozens of teams, it can be done under a month.

Week 1: DevOps & Platform Teams

  • Compare metric cardinality and data points
  • Spot-check high-priority dashboards, critical logs and traces
  • Run sample queries in both systems
  • Review if alert rules are being evaluated correctly (in test mode)

Week 2: Application Teams

  • Each app team reviews their dashboards in Oodle
  • Verify Log queries
  • Verify request flows on distributed traces
  • Check if alerts fire correctly (in parallel with Grafana)
Step 3

Turn Off Grafana Labs

Effort: 2 hours for 1 engineer

Once verification is complete and your team is confident, it's time for the final cutover. This is straightforward and reversible if needed.

Prerequisites

  • Alert notifications are working as expected
  • All critical dashboards validated in Oodle
  • Ensure sufficient historical data is available by
    • Double-writing for longer before cutover.
    • Request Oodle for a back-fill.

1. Activate Oodle Alerts

Change alert status by updating the notifiers and state

2. Deactivate Grafana Alerts

In Grafana/AlertManager, silence or disable alert rules to prevent alert storms during transition

3. Switch to Single-Write

Remove configs writing to Grafana Cloud for all telemetry signals

4. End Grafana Labs Subscription

Cancel your Grafana Cloud subscription and remove individual user licenses

Experience AI-Native Unified Observability

Everything Unified

  • Metrics, logs, traces, and Service Graph in a single interface
  • All your dashboards, preserved and working
  • All your alerts, firing reliably
  • No more jumping between Grafana, Loki, and Tempo
  • Automatic correlation across all data types

AI-Native Debugging

  • Ask questions in plain English: "Which services are impacted?"
  • AI surfaces relevant logs, traces, and metric anomalies automatically
  • Proactive anomaly detection catches issues before alerts fire
  • It's like having Cursor for debugging production
Unified observability experience with AI-powered debugging

Frequently Asked Questions

Common questions about migrating from Grafana Labs to Oodle AI

Do Oodle have integrations with AWS and GCP?

Yes. Oodle offers seamless AWS & GCP integrations including CloudWatch direct integration, AWS Firehose for logs, and monitoring support for all AWS services. You can continue using your existing AWS infrastructure while routing data to Oodle. Check out our docs.

Does Oodle support Grafana integrations?

Oodle supports Grafana pre-built integrations including Kubernetes, MySQL, PostgreSQL, MongoDB, Redis, Elasticsearch, NGINX, Apache, HAProxy, AWS, GCP, Azure, Kafka, RabbitMQ, and more.

How does duration vary based on my company size?

Small Companies (1-3 teams): 1-2 weeks total. Medium teams (4-10 teams): 2-3 weeks. Large companies (10+ teams): 3-4 weeks. The actual hands-on effort is ~1 day per team. The calendar time difference is primarily due to coordination and allowing sufficient validation time across multiple teams.

I just want 1 of the 4 signals (metrics, logs, traces, or service graph)

Absolutely! You can migrate signals incrementally. Many customers start with logs (the biggest pain point with Grafana Loki) and then migrate metrics and traces later. You can run hybrid setups indefinitely - there's no lock-in. Oodle's pricing is per-signal, so you only pay for what you use.

I have a lot of custom metrics and high cardinality

This is where Oodle truly shines! Unlike Grafana Labs which penalizes high cardinality heavily, Oodle is designed from the ground up for high-cardinality data. Our columnar architecture means you can have millions of unique time series without performance degradation or cost explosions. Customers often see better performance with Oodle even with 10x more cardinality than they had with Grafana.

Do you support Grafana plugins and custom visualizations?

Oodle has improved set of visualizations and also supports most Grafana plugins and custom visualizations that are open-source. Most customers find Oodle's native visualizations more powerful and easier to use.

Will I get cost attribution and usage attribution capabilities?

Yes! Oodle provides comprehensive cost and usage attribution dashboards out of the box. You can track usage and cardinality across teams, services, and regions to understand where your observability spend is going and optimize accordingly. Try our usage dashboard in the playground.

How can I migrate out of Oodle?

It's equally easy to migrate out of Oodle. Our paid customers can get in touch with Oodle, and we will provide an easy migrate-out experience (very similar to the migrate-in experience). We support exporting to Grafana-compatible systems for metrics and traces, and OpenSearch-compatible systems for logs. No lock-in, easy in and easy out.

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