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What is Phlare?

Grafana Phlare provides a platform for unifying continuous profiling data, ensuring features like high availability, multi-tenancy, and dependable storage solutions, which significantly improve your understanding of application resource utilization in detail. Being an open-source database, Grafana Phlare is designed to deliver fast, scalable, and effective storage along with advanced querying functionalities for profiling data. The creation of Phlare was sparked during a company-wide hackathon at Grafana Labs, with its official unveiling occurring in 2022 during ObservabilityCON. This tool aims to promote extensive continuous profiling within the open-source community, equipping developers with enhanced insights into how their codes consume resources. Such an initiative not only supports users in assessing the performance of their applications but also aids in optimizing their infrastructure costs, resulting in improved management of applications. Overall, Grafana Phlare represents a significant step towards empowering developers to make data-driven decisions about application performance and efficiency.

What is Dash0?

Engineering teams that adopt OpenTelemetry often hit the same wall: instrumentation is standardized, but the backend receiving it is not. Dash0 was built to close that gap. Every signal, whether a trace, a log record, a metric, or the resource emitting it, is stored against OpenTelemetry semantic conventions and correlated automatically. A request that ran long can be examined next to the log lines it produced and the pod it ran on, with no manual joins and no hopping between products. Ingestion happens through a standard OTLP endpoint. Nothing proprietary gets deployed, and existing instrumentation keeps working untouched. Because the wire format is open, data can be redirected to a different destination later without changes to application code. Prometheus users are treated as first-class. Full PromQL is supported, existing recording and alerting rules carry over, and Grafana dashboard definitions import directly. Cluster-level collection is handled by a dedicated Kubernetes operator covering workloads, nodes, and control plane components. Visualization runs on Perses, with dashboard, check, and alert definitions expressed declaratively and kept under version control. Investigations start broad and get narrow: heatmaps expose the shape of a latency distribution, then filters on high-cardinality attributes isolate the affected requests. Machine learning is applied to telemetry during processing rather than surfaced as a chatbot. Log AI assigns severity to records that arrive without it, discovers recurring patterns, and clusters similar entries, turning noisy third-party output into something queryable. For failing requests, the SIFT methodology structures the path from symptom to root cause. Consumption stays transparent throughout. Teams can identify which services, attributes, and log volumes are responsible for their bill and reduce them at the source, before the invoice arrives.

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Integrations Supported

Amazon Web Services (AWS)
Atlassian Insight
Bindplane
Cilium
Claude
Erlang
Fluentd
Google Cloud Platform
Istio
Java
Microsoft Teams
PagerDuty
Prometheus
Python
Ruby
Slack
Terraform
Terragrunt
Traefik
ilert

Integrations Supported

Amazon Web Services (AWS)
Atlassian Insight
Bindplane
Cilium
Claude
Erlang
Fluentd
Google Cloud Platform
Istio
Java
Microsoft Teams
PagerDuty
Prometheus
Python
Ruby
Slack
Terraform
Terragrunt
Traefik
ilert

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Open source
Free Version
Free Trial Offered?

Pricing Information

$0.00 per month
Completely transparent usage based pricing
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Grafana Labs

Date Founded

2014

Company Location

United States

Company Website

grafana.com/oss/phlare/

Company Facts

Organization Name

Dash0

Date Founded

2023

Company Location

United States

Company Website

www.dash0.com

Categories and Features

Categories and Features

Application Performance Monitoring (APM)

Baseline Manager
Diagnostic Tools
Full Transaction Diagnostics
Performance Control
Resource Management
Root-Cause Diagnosis
Server Performance
Trace Individual Transactions

Database Monitoring

Anomaly Detection
Autodiscovery
Capacity Planning
Dashboard
Dependency Tracking
Historical Trend Analysis
Multitenancy
Notifications / Alerts
Performance Monitoring
Permissions / Access Controls
Predictive Analytics
Prioritization
Query Analysis
Resource Optimization
Troubleshooting

IT Alerting

Alert Noise Reduction
Alert Routing
Dynamic Notifications
Enriched Incident Context
Escalation Policies
Incident History Audit
Multi-User Alerting
Multiple Alert Types
On-Call Management
Rich HTML Email Notifications

IT Infrastructure Monitoring

Alerts / Notifications
Application Monitoring
Bandwidth Monitoring
Capacity Planning
Configuration Change Management
Data Movement Monitoring
Health Monitoring
Multi-Platform Support
Performance Monitoring
Point-in-Time Visibility
Reporting / Analytics
Virtual Machine Monitoring

Log Management

Archiving
Audit Trails
Compliance Reporting
Consolidation
Data Visualization
Event Logs
Network Logs
Remediation
Syslogs
Thresholds
Web Logs

Website Monitoring

Availability Testing
Event Logs
Event-Based Notifications
FTP Monitoring
Mail Server Monitoring
Maintenance Scheduling
Performance Metrics
Real Time Monitoring
Transaction Monitoring
Uptime Reporting

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