Operations | Monitoring | ITSM | DevOps | Cloud

Modern AI agents are now highly advanced, frequently becoming essential components of engineering workflows and deployment pipelines. However, operating these systems often feels like trying to navigate a ship through a dense fog. When an agent errors, slows down, or consumes excessive resources, engineers find themselves adrift, lacking the navigational charts needed to diagnose the problem. The absence of deep insight makes debugging, performance tuning, and cost management unnecessarily difficult.

Learn what rogue devices are, why they’re risky, and how continuous discovery plus CMDB workflows shut them down.

Elasticsearch has long been the backbone of security analytics for organizations that need fast search, flexible dashboards, and scalable visibility across massive datasets. It powers everything from threat hunting to compliance reporting and real-time investigation. But anyone who has operated Elasticsearch at scale also knows a quiet truth: Elasticsearch is only as strong as the data you feed it. And getting clean, consistent, usable telemetry into Elastic is often the hardest part.

For ClickHouse to achieve the speed it's known for, it has historically relied on a trigger-based and incremental architecture for materialized views. This architecture is known to be very efficient but lacks flexibility, such as when working with data that needs to be backfilled rather than append-only.

InfluxDB is the go-to database for developers working with high-velocity time series data for use cases like application performance monitoring and real-time analytics. But InfluxDB exhibits its true power when combined with the right tools and integrations. The tools covered in this blog post can help at all stages of your workflow, from data collection to visualization and analysis, so you can get the most out of your InfluxDB deployment.

The Tigera team recently returned from KubeCon + CloudNativeCon North America and CalicoCon 2025 in Atlanta, Georgia. It was great, as always, to attend these events, feel the energy of our community, and hold in-depth discussions at the booth and in our dedicated sessions that revealed specific, critical shifts shaping the future of cloud-native platforms.

Last week’s KubeCon Atlanta made one thing abundantly clear, Kubernetes is quickly becoming the de facto platform for AI workloads – with the event lineup chock full of talks, workshops, and even co-located events dedicated to AI, machine learning and running data on Kubernetes natively – with approximately 50 (!) sessions in total focused on AI, ML, LLM, and GenAI topics.. What was until now mostly PoCs and aspirational is now truly delivering in production.

One of the most anticipated presentations at HAProxyConf 2025 came from gaming and user-generated content (UGC) innovators Roblox. Software Engineer Chris Jones and Senior Site Reliability Engineer Ben Meidel gave an enthusiastic and enjoyable presentation, detailing their journey from legacy hardware to a sophisticated, automated, and secure application delivery platform, with seamless, API-powered dynamic configuration and upgrades, supported by the HAProxy Enterprise Dynamic Update Module.