Case study
One Search Standard for an HR Platform Serving Thousands of Organizations
How SquareShift ran Elasticsearch workshops on index lifecycle management, cluster sizing, and Kibana governance to replace a fragmented search setup for an HR SaaS platform used by thousands of organizations.
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Client
A cloud-based HR SaaS platform used by thousands of organizations to manage payroll, scheduling, and talent data.
Industry
Human Resources
Services
Stack
Elasticsearch · Kibana · AWS · Index Lifecycle Management (ILM)
How SquareShift delivered it.
The challenge
The client's search configuration had grown fragmented across its payroll, scheduling, and talent modules, with no standard approach to index lifecycle management or sharding, and limited visibility into resource usage before any of it could be fixed.
What we delivered
SquareShift ran workshops covering ILM strategy, cluster sizing, transforms, and Kibana object organization, paired with AWS integration guidance, so best practices were learned through live training rather than handed over in a runbook alone.
The team introduced index templates and API key management, and guided the platform team through structuring dashboards and access control module by module.
The outcome
The platform now runs on a standardized ILM and sharding strategy across every module, with governed Kibana dashboards and access control in place instead of an ad hoc, fragmented setup. Teams that need search built into their product can read about our AI-powered search.
Best practices that live only in a runbook don't stick. Pairing the workshop with live cluster-sizing and index-template work is what actually changes how a team runs Elasticsearch afterward.
Platform & Software Engineering Practice Lead, SquareShift
