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Description
OpenLIT serves as an observability tool that is fully integrated with OpenTelemetry, specifically tailored for application monitoring. It simplifies the integration of observability into AI projects, requiring only a single line of code for setup. This tool is compatible with leading LLM libraries, such as those from OpenAI and HuggingFace, making its implementation feel both easy and intuitive. Users can monitor LLM and GPU performance, along with associated costs, to optimize efficiency and scalability effectively. The platform streams data for visualization, enabling rapid decision-making and adjustments without compromising application performance. OpenLIT's user interface is designed to provide a clear view of LLM expenses, token usage, performance metrics, and user interactions. Additionally, it facilitates seamless connections to widely-used observability platforms like Datadog and Grafana Cloud for automatic data export. This comprehensive approach ensures that your applications are consistently monitored, allowing for proactive management of resources and performance. With OpenLIT, developers can focus on enhancing their AI models while the tool manages observability seamlessly.
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
Integrations
Docker
OpenTelemetry
Amazon Bedrock
Azure OpenAI Service
ChatGPT
Codestral
Codestral Mamba
GPT4All
Le Chat
Mistral NeMo
Integrations
Docker
OpenTelemetry
Amazon Bedrock
Azure OpenAI Service
ChatGPT
Codestral
Codestral Mamba
GPT4All
Le Chat
Mistral NeMo
Pricing Details
Free
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
OpenLIT
Country
India
Website
openlit.io
Vendor Details
Company Name
Riverbed
Founded
2002
Country
United States
Website
www.riverbed.com/products/application-performance-monitoring/
Product Features
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