Operations | Monitoring | ITSM | DevOps | Cloud

AI Won't Be Productive By Default (And That's OK)

Remember when we thought deploying from our laptops was efficient? When FTPing files directly to production at 2 AM felt like peak productivity? We’ve been here before. As AI transforms how we write code, we’re about to learn the same lesson all over again — but this time with much bigger bills.

Instrument LangChain and LangGraph Apps with OpenTelemetry

In our previous blog, we talked about how LangChain and LangGraph help structure your agent’s behavior. But structure isn’t the same as visibility. This one’s about fixing that. Not with more logs. Not with generic dashboards. You need to see what your agent did, step by step, tool by tool, so you can understand how a simple query turned into a long, expensive run.

Getting Started with AI Agent Monitoring From Sentry

Sentry has released AI Agent monitoring, and in this video you can see the fast path to getting started with it using the Vercel AI SDK and Anthropic Claude. AI Agent Monitoring uses tracing to let you see details around how AI interactions are happening inside your application. You can see the back and forth conversation flow, token usage, model usage, durations, and much more. Agent Monitoring is out now, take it for a spin, let us know what you think in Discord!

Boost Your AI Projects with GPUs: Live Expert Insights Webinar

Are you ready to supercharge your AI initiatives? Join our live webinar on July 16, 2025, at 05:00 PM, where Kunal Kushwaha, Ben Norris, and Kendall Miller will dive into the world of GPUs and their critical role in AI. Get ready to explore the latest insights and trends in GPU technology, including: This webinar is perfect for AI enthusiasts, startup founders, and engineers looking to stay ahead of the curve.
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The Agentic Network: How AI Agents Are Transforming Infrastructure from Liability to Living Intelligence

Modern enterprises depend on networks that are increasingly complex, dynamic, and opaque. Yet, instead of confronting this complexity head-on, most organizations fall into the trap of superficial control, layering more monitoring tools atop their stack in hopes of achieving resilience. In reality, this only fragments visibility, deepens operational silos, and leaves a crucial layer of the digital enterprise, the network, under-managed and misunderstood.

How AI-driven Anomaly Detection Fortifies Compliance in Multi-Cloud Infrastructures

In a multi-cloud environment, each cloud platform brings its unique tech stack to record events, manage services, set up configurations, manage user access and permissions, etc. While this allows you to leverage the best-of-breed services from different cloud vendors, the complexity of this setup makes it challenging to detect and respond to anomalies across clouds in real-time.

AI for Data Analytics: Unlocking the Power of Data Insights

According to McKinsey, 78% of organizations have implemented AI in at least one core function, with data analytics leading that transformation. AI no longer supports analytics from the sidelines; it now directs how data is queried, modeled, and delivered. It forecasts outcomes, detects anomalies, and reveals real-time insights, often before a dashboard loads. For SQL developers and DBAs, this marks a new phase in data work.

How to Use AI for MySQL: Optimizing Queries and Database Management

Imagine telling your database to get the best five customers by order from six months ago, and you get a well-optimized query instantly. Zero coding. No Googling syntax. Just results. Welcome to the future of database management with MySQL AI. MySQL Artificial Intelligence is a strategic solution transforming the traditional method of managing databases.