Talos Data Platform Modernization Talos needed predictable, scalable AWS Glue pipelines to reduce failures, cost, and operational toil.
15 Apr. 2023 / Talos
Talos, an enterprise-grade multi-tenant data platform in the InsurTech ecosystem, operated over 200 AWS Glue jobs powering nightly, hourly, and on-demand pipelines. Rapid platform expansion had resulted in inconsistent job patterns, duplicated logic, manual deployments, and limited observability.
As data volumes and tenant complexity increased, these inefficiencies began impacting SLA reliability, compute costs, and engineering productivity.
Talos required a disciplined, governance-aligned modernization of its Glue ecosystem — without disrupting production stability.
Steady Rabbit deployed a Core-Flex Micro-GCC squad to standardize, refactor, and optimize the entire data pipeline foundation.
Within structured migration cohorts, we delivered:
The result: a predictable, scalable, enterprise-grade data engineering backbone that reduced operational firefighting and accelerated analytics delivery.
Talos – Enterprise Multi-Tenant Data Platform
InsurTech / Data Infrastructure
50–100 engineers operating on the platform
AWS Glue (200+ jobs), manual deployments, fragmented logging
Need to:
Talos operates a business-critical data environment where pipelines must execute reliably within strict SLA windows.
Engineering bandwidth was increasingly consumed by firefighting instead of building new analytics capabilities.
To support long-term scale, Talos required a structured modernization program aligned with enterprise governance controls and zero-disruption execution.
Pipeline Reliability
Significant reduction in job failures
across migrated workloads
→ Improved SLA adherence across nightly and hourly pipelines
Runtime & Performance Gains
Improved runtimes on critical ingestion and transformation jobs
→ Faster data availability for downstream
analytics
Compute Cost Optimization
Right-sized Glue resource allocation
Consolidated redundant jobs
→ Reduced overall compute cost footprint
Deployment Governance
Fully automated Git-based CI/CD pipeline
Dev → Test → Prod standardized workflow
→ Eliminated environment drift and manual release risk
Observability & MTTR
Structured logging across all migrated jobs
Retry & circuit-breaker patterns implemented
→ Faster root-cause identification and reduced MTTR
Operational Stability
Zero high-severity production
incidents during migration
No downtime during migration cohort
Engineering Productivity
Reduced operational toil
Teams
reallocated to analytics
innovation initiatives
Talos transitioned from an organically grown, fragile Glue estate to a predictable, scalable, enterprise-grade data engineering framework.
Hands-on specialists with deep experience in orchestration, runtime tuning, and large-scale ETL standardization
Hands-on specialists with deep experience in orchestration, runtime tuning, and large-scale ETL standardization
Hands-on specialists with deep experience in orchestration, runtime tuning, and large-scale ETL standardization
Hands-on specialists with deep experience in orchestration, runtime tuning, and large-scale ETL standardization
Hands-on specialists with deep experience in orchestration, runtime tuning, and large-scale ETL standardization
Steady Rabbit brought discipline and engineering rigor to a complex Glue ecosystem. Their structured modernization reduced operational noise and improved platform stability. Our teams can now focus on analytics innovation instead of pipeline firefighting.
