Integrations without ownership create mute fatigue and missed coverage during incidents.
Elastic
Implement Elastic ingest and integrations your teams will operate day two
Elastic rollouts often ship pipelines and integrations faster than ownership models. Agents multiply, Kibana spaces sprawl, and nobody documents what runs where — so confidence stalls after the first wave.
Scoped delivery Ingest pipelines Kibana spaces Handover included
Why this matters
Why this matters
Useful ingest paths, integrations, and space standards shorten incidents and make Elastic spend defensible to engineering leadership.
Kibana space and role standards speed onboarding — ad hoc folders do the opposite.
Elastic Agent and OTel collector sprawl need governance as estates grow.
What you get
Clear outputs you can use
Scoped Elastic implementation: agents and integrations, ingest pipelines, Kibana spaces and permissions, and optional IaC artefacts — with platform and SRE handover.
- ✓ Deployed agents, ingest pipelines, and integrations for agreed services or domains
- ✓ Kibana spaces, roles, and permissions model documentation
- ✓ Optional IaC or GitOps patterns your platform team can extend
Why teams talk to GKC
Calm, practical, and grounded in the environment you already have
SOW tied to service or domain count — expansions are change-controlled
Built for incident and security workflows first — not vanity dashboard walls
Works with Elastic Cloud or self-managed deployments as scoped
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.
1
Agree scope and standards
We confirm services, SLO intent, space structure, naming, and integration expectations with platform and service owners.
2
Build and validate
Pipelines, agents, and integrations are implemented with review on representative scenarios before broader rollout.
3
Hand over for day-2
You receive runbooks, standards, and backlog for the next domain wave or optimisation work.
Questions teams often have
Common questions
Our dev teams build their own dashboards. Why GKC?
We often deliver platform standards and golden patterns — your teams extend within guardrails instead of reinventing ingest and alert patterns.
Will you migrate every Splunk sourcetype?
Migration parity is a separate, explicitly scoped conversation. This engagement delivers agreed integrations — not unlimited recreation.
Does this include SIEM rule development?
Detection engineering is out of phase-1 scope. Implementation assumes security ingest paths are workable or fixes are a named dependency.
Related services
If this is close, these may be relevant too
Elastic
Elastic Architecture & Sizing Design
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.
Elastic
Elastic Observability Optimisation
Bounded Elastic observability optimisation: APM and synthetics hygiene, SLO and alert rationalisation, and dashboard patterns for top incident workflows — with measurable before/after targets.
OpenTelemetry (OTEL)
Collector Deployment & Hardening
Bounded collector deployment and hardening: HA patterns, gateway and agent tiers, tail sampling, observability of collectors, and handover runbooks for platform owners.
Data Trust and Enablement
Data Onboarding Accelerator
The Data Onboarding Accelerator helps teams bring new data sources into the platform more quickly by clarifying the work, surfacing blockers, and defining the most useful path forward.
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.