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Guance assistant
- Data collectorData Collection Agent
DataKit is Guance’s data collection Agent. It collects metrics, logs, traces, objects, events, and custom data from hosts, containers, Kubernetes, cloud instances, and edge environments. Pipeline, consistent tags, and open protocols bring this data into your Guance workspace.
Features
Multi-dimensional data collection
Supports collecting data such as Metrics, Logs, and Traces from various infrastructures and technology stacks, and processing these data in a structured manner.
Kubernetes cloud-native technology support
Based on a cloud-native microservices architecture, it covers comprehensive data collection within the Kubernetes ecosystem.
Pipeline for observability data processing
Built-in easy-to-use data extraction and processing engine, Pipeline, is used to extract unstructured data, making querying and statistics convenient.
Broader technology stack support than Telegraf
Compared to Telegraf, which can only collect time-series data, DataKit covers a much broader range of data acquisition types, with simpler data collection configurations and better data quality.
Flexible deployment, simple and easy to use
Deploy DataKit in one step with hundreds of built-in integrations. Basic data collection can start automatically during installation.
Core Capabilities
DataKit handles collection, preprocessing, tag standardization, ecosystem compatibility, and deployment at scale, bringing observability data into a shared analysis context.
Deploy DataKit across hosts, containers, Kubernetes, databases, middleware, and cloud resources to collect metrics, logs, traces, objects, and events consistently, reducing discrepancies between separate collectors.
Use Pipeline to parse logs and text, extract fields, convert types, filter records, mask sensitive data, and enrich tags for more consistent search, alerting, and aggregate analysis.
Receive data from OpenTelemetry, Prometheus, Telegraf, Fluentd, and StatsD to bring existing collection workflows into Guance for unified analysis.
Deploy on Linux, Windows, macOS, Docker, Kubernetes, and cloud instances. Use collector election, GitOps, DataKit API, and command-line tools to reduce maintenance effort at scale.
Available platforms
Workflow
Deploy DataKit on hosts, containers, Kubernetes, or cloud instances. Start with infrastructure, critical applications, logs, and alert-related data.
Standardize service, environment, version, region, team, and business tags. Use Pipeline to process log fields, mask sensitive data, and improve data quality.
Correlate metrics, logs, traces, RUM, events, and alerts around the same resource to investigate an issue from its symptoms to its root cause.
Ecosystem integrationsFAQ
DataKit is Guance’s open-source, all-in-one data collection Agent for hosts, containers, Kubernetes, logs, traces, databases, middleware, networks, cloud resources, and custom business data.
Yes. DataKit collects data directly and can also receive data from OpenTelemetry, Prometheus, Telegraf, Fluentd, and StatsD, bringing existing collection workflows into Guance for unified analysis.
During collection, DataKit adds consistent tags for service, environment, host, container, Pod, and version. Pipeline processes unstructured logs so metrics, logs, traces, and alerts can be correlated around the same resource.
Yes, you can. DataKit supports custom data collection, PythonD, open APIs, and pipeline processing, making it suitable for integrating internal business metrics, operations script results, and specialized technology stack data into Guance.
