Wavefront

Wavefront is a cloud-native metrics analytics and Observability Platform (OP) (observability) used to collect, store, visualize, and alert on time-series data from modern applications and infrastructure.

• Cloud-native time-series metrics collection, storage, and analytics for applications and infrastructure (observability).
• Dashboards, visualizations, and query language for high-cardinality metrics exploration (observability).
• Alerting and monitoring for application performance, service health, and resource utilization (observability).
• Support for microservices, container, and Kubernetes environments with integrations into cloud and DevOps toolchains (cloud DevOps).
• Software-as-a-Service (SaaS) delivery model with scalable backend for ingesting and analyzing telemetry data at enterprise scale (observability).

More About Wavefront

Wavefront provides a cloud-based metrics analytics service (observability) that ingests high-volume time-series data from applications, services, containers, hosts, and cloud platforms. Enterprise teams use it to monitor service health, troubleshoot performance issues, and understand behavior across distributed systems. The service is positioned for organizations running microservices, Kubernetes, and hybrid or multi-cloud environments that require centralized visibility into metrics across multiple layers of the stack.

The platform focuses on ingesting numeric telemetry, including system metrics, application metrics, business KPIs, and custom events. Data is collected via agents, integrations, and APIs that connect to common infrastructure components, orchestration platforms, and cloud services. Once ingested, metrics are stored in a backend optimized for time-series workloads and high-cardinality datasets, enabling queries across large metric namespaces without pre-aggregation. This architecture is suited to dynamic environments where services and containers scale up and down frequently.

Wavefront offers dashboards and visualization capabilities (observability) that allow users to build charts and composite views for operations, Site Reliability Engineering (SRE), and development teams. A query language supports functions for mathematical operations, transformations, and aggregations over time, enabling analysis such as percentile calculations, rate computations, capacity forecasting, and correlation between metrics streams. These capabilities are used for incident investigation, release validation, and ongoing service-level monitoring.

Alerting features (observability) allow teams to define thresholds and conditions on metrics, with notifications routed through common collaboration and incident management tools. This supports use cases such as detecting latency regressions, error spikes, resource saturation, and anomalies in traffic or usage patterns. By centralizing alert logic on a unified metrics store, enterprises can align alerts with service level indicators and objectives.

In the broader observability and cloud DevOps landscape, Wavefront operates in the metrics-focused segment, often used alongside or integrated with logging and tracing tools. Its focus on time-series metrics positions it for scenarios where teams need real-time monitoring, capacity planning, and analytics on operational and business telemetry. For directory and taxonomy purposes, Wavefront is categorized under observability, application and infrastructure monitoring, cloud DevOps tooling, and SaaS-based metrics analytics platforms.