Wavefront 1.13.0

Wavefront 1.13.0


Wavefront is a cloud-native observability and analytics platform that provides full-stack visibility, insights, and alerting to ensure high availability and performance of applications and infrastructure. It is designed to collect, analyze, and visualize massive amounts of data in real-time, allowing organizations to quickly identify and resolve issues. Wavefront offers features such as anomaly detection, correlation analytics, distributed tracing, and customizable dashboards that provide a unified view of applications and infrastructure. It supports a wide range of technologies and integrations, making it a versatile solution for modern cloud environments.

  • Supports distributed tracing, metrics, and logs with real-time analytics
  • Offers a large ecosystem of over 250 integrations to collect data from various sources
  • Provides customizable dashboards, alerts, and anomaly detection capabilities
  • Enables collaboration and sharing of dashboards and data across teams
  • Offers advanced analytics and machine learning capabilities to detect issues and trends
  • Provides enterprise-grade security and compliance features

  • A DevOps team is responsible for maintaining multiple microservices running on Kubernetes. They use Wavefront to monitor the performance and health of each service, collect and analyze metrics and logs, and identify issues before they impact end-users. They also share custom dashboards and alerts across the team to improve collaboration and productivity.
  • A financial services company needs to monitor a large-scale distributed system with thousands of nodes, including on-premise and cloud environments. They use Wavefront to collect and analyze metrics and logs from various sources, detect anomalies and trends, and optimize system performance. They also leverage machine learning capabilities to automate the detection of issues and reduce manual efforts.

  1. Sign up for a Wavefront account and create an API token
  2. Install a Wavefront collector agent on the desired data source (e.g., Kubernetes, AWS, VMs)
  3. Configure the agent to send data to Wavefront using the API token
  4. Create custom dashboards and alerts based on the collected data
  5. Use the real-time analytics and machine learning features to identify issues and optimize system performance

  • Wavefront supports various data ingestion protocols, including Telegraf, StatsD, and OpenTelemetry
  • The platform uses a highly scalable and distributed architecture, with a cluster of ingest nodes and a query engine
  • Wavefront provides enterprise-grade security features, such as multi-factor authentication, role-based access control, and data encryption at rest and in transit
  • The platform supports integration with popular tools and frameworks, such as Kubernetes, Docker, and Prometheus
  • Wavefront offers various pricing plans based on data volume and retention requirements

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