Hot/warm/cold and ILM choices track ingest volume and query patterns — design must reflect top services first.
Elastic
Design Elastic architecture your platform and security teams can scale
Elastic clusters fail quietly through index sprawl, weak ILM defaults, and ingest pipelines nobody owns. Without a design, cloud bills and incident triage both get harder at the same time — especially when observability and security share the same stack.
Why this matters
Why this matters
Tier, pipeline, and retention decisions are expensive to unwind after dashboards, detections, and alerts depend on them.
Ingest pipelines and Elastic Agent / OTel paths belong in the architecture, not as a late add-on.
Security and observability workloads on one stack need explicit boundaries — not political defaults.
What you get
Clear outputs you can use
Scoped Elastic architecture and sizing design: deployment tiers, ingest pipelines, ILM and retention guardrails, cross-cluster search where needed, and coexistence boundaries with Splunk or SaaS observability where applicable.
- ✓ Target-state Elastic architecture documentation (self-managed or Cloud)
- ✓ Ingest pipeline, ILM, and retention standards for agreed domains
- ✓ Implementation backlog for agents, integrations, Kibana spaces, and cross-cluster search
Why teams talk to GKC
Calm, practical, and grounded in the environment you already have
Cloud vs self-managed trade-offs without ideology — sized for your skills and cost model
Designed for OTel-native and Elastic Agent paths when you are headed that way
Does not mandate exit from Splunk or Datadog — boundaries documented where coexistence continues
What happens next
A straightforward first step
We keep the first step straightforward so you can understand fit, scope, and likely value before deciding what to do next.
Confirm scope and consumers
We agree teams, environments, compliance needs, and which workloads (logs, metrics, APM, security) are in phase one.
Design target state
Architecture covers tiers, ingest pipelines, ILM, Kibana spaces, and integration points with ITSM or SOAR where relevant.
Review and hand off
You receive documentation for platform and security leads with routed next steps on this hub or general services.
Questions teams often have
Common questions
We only need more indexes. Is full architecture overkill?
If scope is a single domain, implementation may be enough. This service fits when tiering, pipelines, and multi-team tenancy need definition before scale.
Elastic already gave us a reference design.
We tailor tiers, ILM, and ingest to your teams and billing reality — not a generic multi-tenant template.
Will this force Elastic Cloud?
No. We document cloud and self-managed options with honest trade-offs for your operations model.
Related services
If this is close, these may be relevant too
Elastic
Elastic Stack Assessment & Roadmap
A focused assessment of your Elastic posture: deployment model, use-case fit (observability vs security vs search), cost drivers, and a prioritised plan for the next 90 days — with factual coexistence notes where Splunk, Datadog, or other stacks remain in play.
Elastic
Elastic Implementation & Integration (Scoped)
Scoped Elastic implementation: agents and integrations, ingest pipelines, Kibana spaces and permissions, and optional IaC artefacts — with platform and SRE handover.
OpenTelemetry (OTEL)
OpenTelemetry Maturity Assessment
A bounded assessment of your OTel instrumentation, collector topology, and backend alignment — with a prioritised adoption and remediation plan.
Splunk Platform
Platform Health Check & Architecture Review
A bounded Platform health check: cluster topology, search and scheduler load, knowledge object hygiene, and prioritised recommendations ordered by risk and effort.
Next step
Start with a practical conversation
We can talk through the environment, what is making this feel urgent or uncertain, and whether this service is the right fit. If another starting point makes more sense, we will say so.