LogoLogo
Log in|Playground
  • Welcome
    • Introduction
    • FAQ
  • Capabilities
    • Log Management
    • Infrastructure Monitoring
    • Application Performance Monitoring (APM)
      • Application Metrics
      • Traces
      • Supported Technologies
    • Real User Monitoring (RUM)
  • Getting Started
    • Requirements
      • Kubernetes requirements
      • Kernel requirements for eBPF sensor
      • CPU architectures
      • ClickHouse resources
    • Installation & updating
    • Connect Linux hosts
    • Connect RUM
    • 5 quick steps to get you started
  • Use groundcover
    • Monitors
      • Create a new Monitor
      • Issues page
      • Monitor List page
      • Silences page
      • Monitor Catalog page
      • Monitor YAML structure
      • Embedded Grafana Alerts
        • Create a Grafana alert
    • Dashboards
      • Create a dashboard
      • Embedded Grafana Dashboards
        • Create a Grafana dashboard
        • Build alerts & dashboards with Grafana Terraform provider
        • Using groundcover datasources in a Self-hosted Grafana
    • Insights
    • Explore & Monitors query builder
    • Workflows
      • Create a new Workflow
      • Workflow Examples
      • Alert Structure
    • Search & Filter
    • Issues
    • Role-Based Access Control (RBAC)
    • Service Accounts
    • API Keys
    • Log Patterns
    • Drilldown
    • Scraping custom metrics
      • Operator based metrics
      • kube-state-metrics
      • cadvisor metrics
    • Backup & Restore Metrics
    • Metrics & Labels
    • Add custom environment labels
    • Configuring Pipelines
      • Writing Remap Transforms
      • Logs Pipeline Examples
      • Traces Pipeline Examples
      • Logs to Events Pipeline Examples
      • Logs/Traces Sensitive Data Obfuscation
      • Sensitive Data Obfuscation using OTTL
      • Log Filtering using OTTL
    • Querying your groundcover data
      • Query your logs
        • Example queries
        • Logs alerting
      • Query your metrics
      • Querying you data using an API
      • Using KEDA autoscaler with groundcover
  • Log Parsing with OpenTelemetry Pipelines
  • Log and Trace Correlation
  • RUM
  • Customization
    • Customize deployment
      • Agents in host network mode
      • API Key Secret
      • Argo CD
      • On-premise deployment
      • Quay.io registry
      • Configuring sensor deployment coverage
      • Enabling SSL Tracing in Java Applications
    • Customize usage
      • Filtering Kubernetes entities
      • Custom data retention
      • Sensitive data obfuscation
      • Custom storage
      • Custom logs collection
      • Custom labels and annotations
        • Enrich logs and traces with pod labels & annotations
        • Enrich metrics with node labels
      • Disable tracing for specific protocols
      • Tuning resources
      • Controlling the eBPF sampling mechanism
  • Integrations
    • Overview
    • Workflow Integrations
      • Slack Webhook Integration
      • Opsgenie Integration
      • Webhook Integration
        • Incident.io
      • PagerDuty Integration
      • Jira Webhook Integration
    • Data sources
      • OpenTelemetry
        • Traces & Logs
        • Metrics
      • Istio
      • AWS
        • Ingest CloudWatch Metrics
        • Ingest CloudWatch Logs
        • Ingest Logs Stored on S3
        • Integrate CloudWatch Grafana Datasource
      • GCP
        • Ingest Google Cloud Monitoring Metrics
        • Stream Logs using Pub/Sub
        • Integrate Google Cloud Monitoring Grafana Datasource
      • Azure
        • Ingest Azure Monitor Metrics
      • DataDog
        • Traces
        • Metrics
      • FluentBit
      • Fluentd
      • JSON Logs
    • 3rd-party metrics
      • ActiveMQ
      • Aerospike
      • Cassandra
      • CloudFlare
      • Consul
      • CoreDNS
      • Etcd
      • HAProxy
      • Harbor
      • JMeter
      • K6
      • Loki
      • Nginx
      • Pi-hole
      • Postfix
      • RabbitMQ
      • Redpanda
      • SNMP
      • Solr
      • Tomcat
      • Traefik
      • Varnish
      • Vertica
      • Zabbix
    • Source control (Gitlab/Github)
  • Architecture
    • Overview
    • inCloud Managed
      • Setup inCloud Managed with AWS
        • AWS PrivateLink Setup
        • EKS add-on
      • Setup inCloud Managed with GCP
      • Setup inCloud Managed with Azure
      • High Availability
      • Disaster Recovery
      • Ingestion Endpoints
      • Deploying in Sensor-Only mode
    • Security considerations
      • Okta SSO - onboarding
    • Service endpoints inside the cluster
  • Product Updates
    • What's new?
    • Earlier updates
      • 2025
        • Mar 2025
        • Feb 2025
        • Jan 2025
      • 2024
        • Dec 2024
        • Nov 2024
        • Oct 2024
        • Sep 2024
        • Aug 2024
        • July 2024
        • May 2024
        • Apr 2024
        • Mar 2024
        • Feb 2024
        • Jan 2024
      • 2023
        • Dec 2023
        • Nov 2023
        • Oct 2023
Powered by GitBook
On this page
  • Generate the API key
  • Querying ClickHouse
  • Querying VictoriaMetrics
Export as PDF
  1. Use groundcover
  2. Querying your groundcover data

Querying you data using an API

Last updated 10 months ago

groundcover provides a robust user interface that allows you to view and analyze all your observability data from inside the platform. However, there may be cases in which you need to query the data from outside our platform using API communication.

Our proprietary eBPF sensor automatically captures granular observability data, which is stored via our integrations with two best-of-breed technologies. VictoriaMetrics for metrics storage, and ClickHouse for storage of logs, traces, and Kubernetes events.

Read more about our architecture .

Generate the API key

Run the following command in your CLI, and select tenant:

groundcover auth get-datasources-api-key

Querying ClickHouse

Example for querying ClickHouse database using POST HTTP Request:

curl 'https://ds.groundcover.com/' \
        --header "X-ClickHouse-Key: ${API_KEY}" \
        --data "SELECT count() from traces where start_timestamp > now() - interval '15 minutes' "

Command parameters

  • X-ClickHouse-Key (header): API Key you retrieved from the groundcover CLI. Replace ${API_KEY} with your actual API key, or set API_KEY as env parameter.

  • SELECT count() FROM traces WHERE start_timestamp > now() - interval '15 minutes' (data): The SQL query to execute. This query counts the number of traces where the start_timestamp is within the last 15 minutes.

Learn more about the ClickHouse query language .

Querying VictoriaMetrics

curl 'https://ds.groundcover.com/datasources/prometheus/api/v1/query_range' \
    --get \
    --header "apikey: ${API_KEY}" \
    --data 'query=sum(rate(groundcover_resource_total_counter{type="http"}))' \
    --data 'start=1715760000' \
    --data 'end=1715763600'

Command parameters

  • apikey (header): API Key you retrieved from the groundcover CLI. Replace ${API_KEY} with your actual API key, or set API_KEY as env parameter.

  • query (data): The promql query to execute. In this case, it calculates the sum of the rate of groundcover_resource_total_counter with the type set to http.

  • start (data): The start timestamp for the query range in Unix time (seconds since epoch). Example: 1715760000.

  • end (data): The end timestamp for the query range in Unix time (seconds since epoch). Example: 1715763600.

Example for querying the VictoriaMetrics database using the API:

Learn more about the promql syntax .

Learn more about VictoriaMetrics HTTP API .

here
here
query_range
here
here