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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Pydantic Logfire serves as an observability solution aimed at enhancing the monitoring of Python applications by converting logs into practical insights. It offers valuable performance metrics, tracing capabilities, and a comprehensive view of application dynamics, which encompasses request headers, bodies, and detailed execution traces. Built upon OpenTelemetry, Pydantic Logfire seamlessly integrates with widely-used libraries, ensuring user-friendliness while maintaining the adaptability of OpenTelemetry’s functionalities. Developers can enrich their applications with structured data and easily queryable Python objects, allowing them to obtain real-time insights through a variety of visualizations, dashboards, and alert systems. In addition, Logfire facilitates manual tracing, context logging, and exception handling, presenting a contemporary logging framework. This tool is specifically designed for developers in search of a streamlined and efficient observability solution, boasting ready-to-use integrations and user-centric features. Its flexibility and comprehensive capabilities make it a valuable asset for anyone looking to improve their application's monitoring strategy.

Description

Enhanced high-definition APM visibility through real user monitoring, synthetic monitoring, and OpenTelemetry offers a solution that is scalable, user-friendly, and simplifies the integration of insights from end users, applications, networks, and the cloud-native space. The rise of microservices within containerized environments on dynamic cloud infrastructures has resulted in a highly transient and distributed landscape at an unprecedented scale. Traditional methods of enhancing APM, which rely on sampled transactions, partial traces, and aggregate metrics, have become ineffective, as legacy APM solutions struggle to identify the reasons behind slow or stalling critical business applications. The Riverbed platform provides cohesive visibility across the contemporary application landscape, ensuring ease of deployment and management, while facilitating quicker resolution of even the most challenging performance issues. Riverbed APM is thoroughly designed for the cloud-native environment, offering extensive monitoring and observability for transactions that operate on the latest cloud and application infrastructures, ultimately enhancing operational efficiency and user experience. This comprehensive approach not only addresses current performance challenges but also positions organizations to adapt to future technological advancements seamlessly.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

OpenTelemetry
Amazon Web Services (AWS)
Disco.dev
Docker
EarlyCore
Google Cloud Platform
Kubernetes
Microsoft Azure
OpenAI
OpenStack
Python
Red Hat OpenShift
SQLAlchemy

Integrations

OpenTelemetry
Amazon Web Services (AWS)
Disco.dev
Docker
EarlyCore
Google Cloud Platform
Kubernetes
Microsoft Azure
OpenAI
OpenStack
Python
Red Hat OpenShift
SQLAlchemy

Pricing Details

$2 per month
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Pydantic

Country

United States

Website

pydantic.dev/logfire

Vendor Details

Company Name

Riverbed

Founded

2002

Country

United States

Website

www.riverbed.com/products/application-performance-monitoring/

Product Features

Application Performance Monitoring (APM)

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

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