Monitor apps using Vercel AI SDK with SigNoz and OpenTelemetry
Monitor apps using Vercel AI SDK with SigNoz and OpenTelemetry. This video talks about how to configure your AI apps to send data to SigNoz using OpenTelemetry.
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The latest News and Information on Application Performance Monitoring and related technologies.
Datadog Log Management: Analyze complex data sets
Datadog Sheets provides a spreadsheet-style interface for analyzing your telemetry data — you can perform lookups, build pivot tables, and create calculated columns using familiar spreadsheet functionality. This enables teams to join datasets, aggregate results, and explore trends without writing code.
Debug live production issues with the Datadog Cursor extension
The Datadog Cursor Extension uses the Datadog remote MCP Server to give developers access to Datadog tools and observability data directly from within the Cursor IDE. The Cursor Extension enables you to view live variable values that your logpoints capture during execution, and you can use the Cursor Agent to identify the lines of code responsible for the issue at hand. The Datadog Cursor Extension is now available in Preview.
Datadog IDP: Ship software quickly and confidently
Datadog Internal Developer Portal (IDP) helps developers quickly track down shared engineering knowledge, execute common production tasks in self-service manner, and evaluate the production-readiness of new service code.
Why Your Business Needs APM: 10 Key Benefits You Shouldn't Ignore
In today’s digital world, how well your applications perform has a big impact on how people see your business, and how well it runs. Whether you are in finance, e-commerce, SaaS, healthcare, or media, your users expect everything to work smoothly, all the time. Even a few seconds of slow performance can lead to lost sales, lower productivity, and unhappy customers. That’s why Application Performance Monitoring (APM) is so important.
Bits AI Dev Agent: Automatically identify issues and generate code fixes
The Bits Dev Agent is an AI-powered coding assistant in Datadog designed to reclaim developer productivity by autonomously monitoring telemetry data, identifying key issues, and generating production-ready pull requests. Developers receive asynchronous, context-rich PRs with clear explanations, allowing them to shift their focus from troubleshooting to reviewing solutions and building better code.
Introducing Bits AI SRE, your AI on-call teammate
Bits AI SRE is your AI on-call teammate, built to autonomously investigate alerts and coordinate incident response. Integrated with Datadog, Slack, GitHub, Confluence, and more, Bits analyzes telemetry, reads documentation, and reviews recent deployments to determine the root cause of alerts—often before you’ve even opened your laptop. In fact, if you're using Datadog On-Call, you can view Bits’s findings right from your phone—so you’re always one step ahead, no matter where you are.
Datadog Incident Response: Unify remediation and communication
With Datadog's new AI voice agent in Incident Response, you can quickly get up to speed on the issue and start taking action directly from your phone. Handoff notifications make it easy to jump straight to the relevant context and quickly communicate with other responders. Finally, our status pages enable you to automatically update users on your remediation progress.
What is Python Application Performance Monitoring? - [A Complete Guide]
A recent study looked at real-world Python programs and found something important: Python isn’t the main reason apps slow down. The real problems come from inside the code like poor logic, memory issues, and slow database queries. The problem is, these issues often go unnoticed. Your app may seem fine until users start complaining about slowness or things start breaking under pressure.
From Sequential Bottlenecks to Concurrent Performance: Optimizing Log Processing at Scale
We optimized log processing pipeline by moving from sequential to concurrent processing at the entry level, achieving 30% higher throughput and better resource utilization without increasing infrastructure costs. When customers start sending millions of logs per minute, you quickly discover whether your processing pipeline can actually scale with vertical scaling.