Operations | Monitoring | ITSM | DevOps | Cloud

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.

OpenLLMetry extends the industry-standard OpenTelemetry framework with features specifically for monitoring large language model (LLM) and GenAI application behavior.

There’s a new kind of thinking happening in the world. It doesn’t come with memories, emotions, or doubt. It doesn’t hesitate. It doesn’t wonder. However, it appears to be thinking. Ask it a question, and it responds in perfect grammar. Ask for help, and it gives you options. You could almost believe it understands. Almost. This is what happens when machines are trained to speak like us, but without ever needing to understand us.

Ever look at your to-do list at the end of the day and realize it’s grown longer, not shorter? We get it—there’s always more to do and never enough time. But if you’re a Sumo Logic user, reading this blog will be a win for your day because we’re giving you six ways to slash the time you spend on tasks in your platform.

Platform teams are struggling with observability noise, bloated storage costs, and lack of clarity during incidents. Most teams capture everything all the time, leading to expensive, overwhelming, and often unnecessary data volumes. In Telemetry for Modern Apps, Mezmo teamed up with Checkly to demonstrate how synthetic monitoring triggers and responsive telemetry pipelines can help reduce costs while maintaining the context needed during incidents.

You're running Kafka on Confluent Cloud. You care about lag, throughput, retries, and replication. But where do you see those metrics? Confluent gives you metrics, sure, but not all in one place. Some live behind a metrics API, others behind Connect clusters or Schema Registries. You either wire them manually or give up. What if you could stream those metrics to a platform built for high-frequency, high-cardinality time series, and do it in minutes?