Migrate to Elastic from Splunk For Free
Reduce observability costs while Observata handles licensing, migration, and ongoing operations, helping you scale your observability efficiently with expert-led services.
Why Organizations Are Increasingly Migrating From Splunk to Elastic
Splunk provides observability, APM, and monitoring, but scaling introduces friction.
Costs rise with ingestion volume, cold data is harder to access, and integrating new tools requires expertise that in-house teams often lack.
Elastic overcomes these challenges by offering scalable clusters, searchable storage across all tiers, usage-based pricing, and vendor-neutral ingestion.
Splunk Limitations
- Ingestion-based pricing inflates costs as telemetry grows
- Tiered storage requires rehydration for cold data access
- Limited support for profiling
- Vendor lock-in through proprietary ecosystem
- Complex horizontal scaling for on-prem deployments
- High TCO for large-scale environments
Elastic Solutions
- Charges based on resource usage, offering better cost predictability
- Cold/frozen data remains searchable
- Includes native universal profiling
- Supports OpenTelemetry (OTel) and open integrations
- Natively supports distributed, horizontally scalable architecture
- Reduces total cost across infrastructure, licensing, and support
Splunk Limitations
- Ingestion-based pricing inflates costs as telemetry grows
- Tiered storage requires rehydration for cold data access
- Limited support for profiling
- Vendor lock-in through proprietary ecosystem
- Complex horizontal scaling for on-prem deployments
- High TCO for large-scale environments
Elastic Solutions
- Charges based on resource usage, offering better cost predictability
- Cold/frozen data remains searchable
- Includes native universal profiling
- Supports OpenTelemetry (OTel) and open integrations
- Natively supports distributed, horizontally scalable architecture
- Reduces total cost across infrastructure, licensing, and support
Elastic provides a structured path to resolve these challenges, and Observata’s experts ensure the migration occurs efficiently with operational support throughout.
Elastic Advantages That Support Scalable Observability
Elastic is designed to handle high-volume telemetry in modern IT environments. Its architecture reduces operational overhead, improves query performance, and enables teams to scale confidently as data volumes grow.
Horizontal scaling
Queryable cold & frozen tiers
Open Telemetry-first ingestion
Native profiling
Elastic Common Schema (ECS)
Flexible separation of ingestion, storage, & compute
Embedded AI/ML capabilities
Centralized dashboards through Kibana
Embedded AI/ML capabilities
Centralized dashboards through Kibana
Ensure Your Team is Ready for a Smooth Migration to Elastic
Migration from Splunk to Elastic involves thorough preparation to ensure data integrity, seamless operations, and scalability. Observata provides a structured approach covering everything from initial inventory to managing data pipelines and ensuring security compliance.
- Prepare Your Splunk Inventory for a Smooth Transition
- How to Move Data from Splunk to Elastic Efficiently
- Optimizing Your Data Pipelines & Schema for Elastic
- Managing Production Systems During Migration
- Ensuring Security & Compliance Throughout the Migration
Splunk Index Inventory
Identify all active indexes, source types, and field extractions
Data Volume Assessment
Estimate daily ingestion volume, historical data retention, and storage requirements
Saved Searches & Alerts
Capture key saved searches, alerts, and scheduled reports for migration
Forwarder & HEC Configurations
Map out forwarders and HEC tokens for seamless data flow
Access Controls & Permissions
Understand user roles and permissions for both Splunk and Elastic
Historical Data Export & Ingest
Extract data from Splunk and load it into Elastic via Logstash or Beats. This is typically done in batches, maintaining integrity and validation at each step.
Dual-Run Migration
During the migration, both Splunk and Elastic systems can run concurrently to ensure no data is lost. This allows for parallel ingestion, with checks and comparisons to ensure data consistency.
Data Schema Mapping
Align Splunk data formats (source types, fields, timestamp formats) with ECS to standardize data processing across multiple sources.
Grok/Dissect Plugins & Filtering
Configure Logstash or Beats to extract and transform data, applying enrichment as needed (e.g., geolocation, user info, asset IDs).
Index Templates
Define index mappings, retention policies, and ILM (Index Lifecycle Management) rules to optimize data storage and search performance.
Ingestion Pipeline Design
Set up efficient pipelines to ensure data flows seamlessly from Splunk to Elastic without data loss or transformation errors.
Staging Environment Setup
Mirror the production system in a staging environment to test migration paths, data integrity, and functionality.
Incremental Migration
Migrate data in phases, starting with low-risk or less critical data, then progressively move more important datasets.
Parallel Operation
Run Splunk and Elastic concurrently in a dual-feed model to monitor performance, validate data integrity, and ensure both systems are functioning.
Change Management
Implement version control, approval workflows, and rollback plans in case of unexpected issues.
Data Encryption
Ensure that data is encrypted during transit and at rest, using SSL/TLS for data flows and native encryption for storage.
Access Controls
Implement user roles, permissions, and access policies in Elastic, aligning with your organizational security standards.
Compliance Checks
Monitor compliance requirements (GDPR, HIPAA, etc.) and ensure that both Splunk and Elastic configurations meet regulatory guidelines.
Audit Logging
Track and log every migration step for traceability, using Elastic’s audit features to monitor access and changes.
By systematically assessing requirements and planning each step of the migration, Observata ensures your move from Splunk to Elastic is complete, efficient, and risk-free.
Splunk Index Inventory
Identify all active indexes, source types, and field extractions
Data Volume Assessment
Estimate daily ingestion volume, historical data retention, and storage requirements
Saved Searches & Alerts
Capture key saved searches, alerts, and scheduled reports for migration
Forwarder & HEC Configurations
Map out forwarders and HEC tokens for seamless data flow
Access Controls & Permissions
Understand user roles and permissions for both Splunk and Elastic
Historical Data Export & Ingest
Extract data from Splunk and load it into Elastic via Logstash or Beats. This is typically done in batches, maintaining integrity and validation at each step.
Dual-Run Migration
During the migration, both Splunk and Elastic systems can run concurrently to ensure no data is lost. This allows for parallel ingestion, with checks and comparisons to ensure data consistency.
Data Schema Mapping
Align Splunk data formats (source types, fields, timestamp formats) with ECS to standardize data processing across multiple sources.
Grok/Dissect Plugins & Filtering
Configure Logstash or Beats to extract and transform data, applying enrichment as needed (e.g., geolocation, user info, asset IDs).
Index Templates
Define index mappings, retention policies, and ILM (Index Lifecycle Management) rules to optimize data storage and search performance.
Ingestion Pipeline Design
Set up efficient pipelines to ensure data flows seamlessly from Splunk to Elastic without data loss or transformation errors.
Staging Environment Setup
Mirror the production system in a staging environment to test migration paths, data integrity, and functionality.
Incremental Migration
Migrate data in phases, starting with low-risk or less critical data, then progressively move more important datasets.
Parallel Operation
Run Splunk and Elastic concurrently in a dual-feed model to monitor performance, validate data integrity, and ensure both systems are functioning.
Change Management
Implement version control, approval workflows, and rollback plans in case of unexpected issues.
Data Encryption
Ensure that data is encrypted during transit and at rest, using SSL/TLS for data flows and native encryption for storage.
Access Controls
Implement user roles, permissions, and access policies in Elastic, aligning with your organizational security standards.
Compliance Checks
Monitor compliance requirements (GDPR, HIPAA, etc.) and ensure that both Splunk and Elastic configurations meet regulatory guidelines.
Audit Logging
Track and log every migration step for traceability, using Elastic’s audit features to monitor access and changes.
Our Unique Credit Model
Elastic licensing is included in Observata’s service, so no separate subscriptions are needed.
Our outcome-focused, credit-based model lets you pay only for the services you use, from migration to ongoing support, providing cost predictability and flexible scaling without the complexity of traditional billing.
Service Credits
Freely Utilize Credits
Clear Reporting
Frequently Asked Questions
Yes. Observata offers complimentary Splunk-to-Elastic migration for qualifying projects under our credit-based service model. The offer covers planning, data transfer, pipeline configuration, and dashboard conversion.
Terms depend on data size, infrastructure, and operational scope. Larger environments may require additional credits, which can be rolled over or allocated flexibly within our observability-as-a-service framework. You can Learn more about our HYPR Vision service, or talk to our experts
Elastic provides a more scalable and cost-efficient observability foundation for IT environments that need flexibility without tool fragmentation. Key advantages include:
- Searchable cold and frozen tiers, eliminating rehydration delays
- OpenTelemetry-first ingestion, enabling vendor-neutral data collection
- Horizontal scalability for predictable performance growth
- AI/ML-driven anomaly detection for faster root cause analysis
- Elastic Common Schema (ECS) for unified data correlation
- Lower total cost of ownership (TCO) compared to ingestion-based pricing models
Visit the Elastic Partnership page to explore how Elastic enhances observability and how Observata operationalizes it.
Migration timelines depend on the volume of telemetry, existing Splunk configuration, and data retention requirements. Under the HYPR Vision delivery framework, Observata defines the migration plan through a readiness assessment that includes:
- Data volume and throughput review
- Query and dashboard inventory
- Pipeline and schema validation
- Testing under dual-run conditions
Most migrations depend on operational scale and validation requirements. For a more detailed timeframe, speak to our experts.
Yes, Elastic’s Express Migration Program automates data transfer, dashboard translation, and capacity planning for supported workloads. These tools streamline the conversion of SPL queries to ES|QL, help recreate dashboards in Kibana, and validate data during ingestion.
However, configuring these tools requires the right expertise. For environments outside program coverage, Observata supplements automation with custom Logstash pipelines and schema mapping under the HYPR Vision service.
Yes. During a dual-run or phased migration, Splunk Universal Forwarders can redirect output to Logstash or Beats inputs configured for Elastic. This allows live data to flow to both platforms simultaneously, ensuring parity and validation before full cutover.
Observata configures these dual pipelines to maintain real-time ingestion, reduce downtime, and preserve Splunk’s logging format while converting to Elastic Common Schema (ECS).
- Not necessarily. Historical data can be exported in native JSON or CSV format and ingested directly into Elastic through Logstash, Elastic Agent, or custom ingestion pipelines. Observata validates index mappings, time fields, and retention policies before import to maintain search accuracy and performance.
Observata maps existing saved searches and alert conditions to Kibana alerts and Elastic rules. Alert logic such as thresholds, schedules, and notification channels are recreated using Elastic’s built-in rule engine and watcher framework. This process preserves operational monitoring while enabling integration with Elastic’s AI/ML-driven anomaly detection for advanced alerting.
Data integrity is maintained through a dual-run and batch-validated migration approach. Observata mirrors your data streams from Splunk to Elastic during migration, validating through:
- Document count parity checks
- Hash-based data integrity verification
- Controlled cutover windows for parallel operation
No data is decommissioned from Splunk until Elastic ingestion and indexing are verified. You can learn more about our processes on our Why Observata page.
Observata follows strict compliance and governance controls throughout migration. All transfers use end-to-end encryption (SSL/TLS) and role-based access controls (RBAC). We align with global frameworks, including GDPR, HIPAA, and SOC 2, where applicable.
Additionally, Observata’s services use continuous monitoring, audit logging, and access traceability. More details on our security and compliance practices can be found on the Cybersecurity + Observability page.
As part of the HYPR Vision service, Observata provides post-migration enablement sessions. These cover query writing in ES|QL, dashboard management in Kibana, and alert configuration. Customers receive operational handbooks, data model documentation, and optional on-call support through Observata’s credit-based service model.
