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What is gProfiler?

gProfiler combines multiple sampling profilers to deliver an extensive visualization of CPU usage, highlighting stack traces from processes in native applications such as those developed in Golang, Java, and Python. Furthermore, it allows users to transmit their insights to the Granulate Performance Studio, which aggregates data across various instances over time, offering a holistic view of the performance of your entire cluster. To upload these results, users are required to register on the website and acquire a unique token. This mechanism not only facilitates effective monitoring but also enhances the analysis of performance metrics across your systems. By doing so, developers can identify bottlenecks and optimize resource utilization more efficiently.

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.

Media

Media

Integrations Supported

Go
Java
Python
ClickHouse
Confluent
Cursor
Erlang
Fluent Bit
Google Chat
JavaScript
Kubernetes
Kyverno
Node.js
Prometheus
Terraform
Terragrunt
Traefik
Zed
ilert
incident.io

Integrations Supported

Go
Java
Python
ClickHouse
Confluent
Cursor
Erlang
Fluent Bit
Google Chat
JavaScript
Kubernetes
Kyverno
Node.js
Prometheus
Terraform
Terragrunt
Traefik
Zed
ilert
incident.io

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided
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

Granulate

Date Founded

2018

Company Location

Israel

Company Website

docs.granulate.io/granulate-the-basics/the-gprofiler

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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