Seamless Splunk to Elastic migration
Transition your infrastructure from Splunk to Elastic without operational friction, engineering overhead or upfront costs.
Request your custom migration planTransition your infrastructure from Splunk to Elastic without operational friction, engineering overhead or upfront costs.
Request your custom migration planTransition your infrastructure from Splunk to Elastic without operational friction, engineering overhead or upfront costs.
We execute your end-to-end migration at no extra charge, delivering a zero-downtime transition handled by senior engineers.
Splunk provides comprehensive visibility, but scaling ingestion-based pricing inflates budgets and makes cold data access difficult to manage.
Elastic resolves this by charging strictly for resource usage, delivering true cost predictability alongside a unified, horizontally scalable architecture.
While Splunk provides comprehensive visibility across enterprise environments, its legacy ingestion-based pricing models create severe financial strain and artificial data caps as telemetry volumes grow.
Moving to Elastic unifies your security and observability data onto a resource-based costing structure, allowing your teams to ingest, store and search everything without scaling penalties.
Ingestion-based pricing: Costs inflate linearly as your telemetry volumes grow, making comprehensive visibility financially unsustainable.
Restricted cold data: Legacy tiered storage requires slow, costly data rehydration just to access historical telemetry.
Limited profiling: Lacks native, continuous code-level profiling, leaving critical performance bottlenecks hidden.
Vendor lock-in: A proprietary ecosystem restricts data portability and limits infrastructure flexibility.
Resource-based costing: Achieve absolute predictability with pricing based on compute and storage, eliminating ingestion volume penalties.
Searchable frozen tiers: Keep deep historical data instantly queryable without the operational overhead or cost of manual indexing.
Native universal profiling: Optimise performance continuously at the code level with built-in, low-overhead profiling.
OpenTelemetry-native: Future-proof your architecture with native, out-of-the-box support for open frameworks and integrations.
Elastic is built to handle high-volume telemetry across modern IT environments, reducing operational overhead and improving query performance.
Add nodes to expand capacity smoothly without reconfiguring pipelines.
Access deep historical data instantly without the need for manual indexing.
Collect telemetry from multiple sources with zero vendor lock-in.
Obtain code-level insights for precise performance optimisation.
Standardise and correlate data across all infrastructure sources.
Optimise cost by separating ingestion, storage and compute.
Surface operational anomalies and automate alerting across telemetry streams.
Visualise logs, metrics, traces and profiling inside a single Kibana interface.
Run real-time threat detection and SIEM capabilities across your entire log estate without cost penalties.
Our senior engineers follow a structured, low-risk framework covering everything from initial inventory to live production cutover.
We execute every phase at no additional cost to you. This includes migration planning, pipeline configuration, data transfer and dashboard conversion.
Before moving data, we execute a complete audit of your existing Splunk footprint to map out the transition timeline:
Identify all active indexes, source types and field extractions.
Estimate daily ingestion volume, historical retention and storage footprints.
Recreate searches, alerts and reports as native Elastic rules, preserving thresholds and workflows.
Map out existing forwarders, HTTP Event Collector (HEC) tokens, user roles and access permissions.
To guarantee zero operational downtime and absolute data integrity, we run both platforms concurrently:
Route data to both systems simultaneously, configuring Splunk Universal Forwarders to output straight to Logstash or Beats.
Extract your historical data from Splunk and load it into Elastic in validated batches, maintaining strict consistency checks at every step.
We build high-efficiency streaming pipelines to ensure data flows seamlessly without loss or transformation errors:
Align Splunk source types, fields and timestamp formats with the Elastic Common Schema.
Configure Logstash or Beats to extract, transform and enrich data with geolocation and asset IDs.
Define index mappings, retention policies and ILM rules to optimise search performance.
Production workloads are transitioned systematically to mitigate risk:
Mirror production in a staging environment to thoroughly test migration paths and data integrity.
Move data progressively, starting with low-risk datasets before transitioning critical workloads.
Enforce version control, structured approval workflows and explicit rollback plans.
Your security posture is maintained throughout the entire transition:
Enforce SSL/TLS encryption for data in transit, backed by native encryption at rest across all tiers.
mplement granular user roles and access policies in Elastic aligned with your standards.
Monitor setups to ensure continuous compliance with GDPR, HIPAA and other frameworks.
Track the migration using Elastic’s native audit features to monitor access and modifications.
Transition to a high-performance data architecture without upfront overhead. Gain total transparency, expert engineering and a pricing model that scales perfectly with your growth.
Let’s talk architecture