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Step by step cost optimization in Coralogix

Coralogix Team Jun 23, 2025

5 mins read

Controlling observability spend should be simple, measurable and automated. Coralogix lets organizations see exactly where units are used, steer data into the right pipelines and alert long before limits are hit – all without compromising engineering insight.

1. Observe & Monitor

The first step in cost governance is line‑of‑sight:

Business question	Coralogix answer	Where to find it
Overall unit consumption over a given period	Totals and daily trend on Settings > Data Usage and the Data Usage Service API (resolution 6 h down to 1 h)	UI · CX Dashboards · API
Quota percentage (rounded) – e.g. 78 % of 100 %	Gauge widget on Data Usage page and cx_data_usage_units metric (units_used/units_quota*100)	UI · API
Unit split by pillar (High, Medium, Low) and by telemetry type (Logs, Metrics, Traces)	TCO Distribution dashboards plus API fields pillar and priority	UI
Usage by application and subsystem	Drill‑down grid and API application_name / subsystem_name	UI
Usage in units and GB per team	Data Usage page – Teams tab or API dimensions.team_id	UI
Platform adoption across telemetry types and frequency	Metrics panel showing daily active teams per pillar per telemetry using cx_data_usage_units	UI

** All data can be exported as scheduled reports to CSV or PDF for offline analysis.

2. Manage & Act

Once hot spots are visible, policies and rules keep spending predictable.

2.1 TCO Optimiser (Logs and Traces)

Redirect data between High, Medium and Low pipelines in seconds with the Logs TCO Optimiser and the Traces TCO Optimiser.
Precedence and per‑severity overrides ensure business‑ All critical events stay searchable.

2.2 Metrics Cost Optimiser

Use the Metrics Cost Optimiser to block high-cardinality series post-ingest while preserving history.

2.3 Dynamic Blocking & Parsing Rules

A Lambda-based Dynamic TCO App enforces temporary low-priority routing when quota approaches X percent and reverts at midnight UTC.
Dynamic Blocking rules can also be run on a timer.
Block rules and Remove-Field rules cut payload size by up to 90 percent.

2.4 Archive & Retention Controls

Per‑retention tag S3 lifecycle policies move older objects from Standard S3 → GIR → Glacier/Deep Archive, minimising S3 storage cost.

3. Automate & Alert

Policies and rules can be implemented as automated alerts and remediations.

Goal	Feature	Example
Be warned proactively before quota full consumption	Alert on cx_data_usage_units >= 80 %	Slack, e‑mail, webhook
Block noisy subsystems automatically	Dynamic Blocking script runs every 30 min (threshold > 100 k logs / day)	Threshold: >100 k logs/day
Treat quota like code	Terraform provider for TCO policies and alerts	resource “coralogix_tco_policy” …

4. Report & Analyse

Create feedback loops, so the entire organization is enabled to act on the information they have.

4.1 Cost attribution

$$ per team or BU – multiply units by contractual unit price in CX Dashboards or in Looker/BI table.
CSV Detailed Usage Report shows units, GB, severity, pipeline and cost centre for 30/90 days.

4.2 Associated AWS spend

S3 archive size is collected via AWS Cost Explorer integration and shown as native metric.
Compute usage for private VPC deployments shown in AWS Cost Explorer tag Coralogix-Compute.

4.3 Executive packs

Scheduled dashboards email weekly KPI summary to operations leadership – unit headroom, savings realised, adoption trend.

5. Macro‑Level Governance

Fine‑grained controls exist, but best practice is to operate with a buffer (for example 20‑30 percent above average daily usage) and manage at team or application level – not per gigabyte. This avoids operational drag while still preventing surprise invoices.

6. Conclusion

Coralogix couples deep visibility with policy automation to reduce total cost of ownership by up to two‑thirds. Organizations gain confidence that growth in telemetry will not translate into runaway bills.