In this video, we offer an overview and demo of Grafana Cloud Frontend Observability, our real user monitoring (RUM) solution that delivers actionable insights into the end-user experience of web applications.

Haley Wang, a software engineer at VictoriaMetrics, presented at KubeCon China 2024 on August 22nd, 2024! In her talk, "Building a High-Performance Time Series #Database from Scratch: Optimization Strategies," Haley shared valuable insights and strategies for optimizing time series databases.

A service desk dashboard is your de facto control center for everything related to Service Management. It should be clear, detailed, versatile, and offer a single-glance way to get the necessary information. Otherwise, you risk mismanaging your IT assets and operations because you missed valuable data points. You need your ITSM dashboard to: See how you can fully customize your ITSM dashboard on InvGate Service Desk and start measuring your service desk KPIs quickly!

Reduce node counts to drive down infrastructure costs (on-prem and in the cloud). Get an overview of common issues that drive excess cost and understanding the 3 core strategies for tackling them. Done right, you can reduce node counts, which in turn impacts infrastructure cost and potentially reduces expensive software licenses such as OpenShift. In this 20-min session we cover the 3 core strategies.

The presenter delves into advanced concepts, emphasizing the importance of time series in campaigns using bot hierarchies. They highlight the collection and branching of surveys based on user feedback, and the use of generative AI. The exploration and configuration of survey results, including filtering and splitting based on attributes, are demonstrated. The creation of custom dashboards with device data is introduced. The talk also touches on sustainability and green IT initiatives.

Join us as John teaches us the "Top 10" tips and tricks for more effective searches in Sumo Logic.

An LLM differs from a function in that it takes output and imputes, or infers, a function and its arguments. We first consider how this process works within Selector for an English phrase converted to a query. We then step through the design of Selector's LLM, which relies on a base LLM trained with English phrases and SQL translation, then fine-tuned, on-premises, with customer-specific entities. In this way, each of Selector's deployments relies on an LLM tailored to the customer at hand.

Selector translates English phrases to SQL queries through the use of an LLM. Each SQL query includes the table, or data set to be searched, along with filters, or conditions which prune the search results. We walk through a number of SQL queries and sample search results, before considering the LLM-based translation of a sample English phrase processed by Selector.

Selector's customer base includes 50 deployments across service providers as well as large enterprises in retail, media distribution, colocation services, and multi-cloud networking services. These customers aim to correlate events across their network, applications, and infrastructure; eliminate the need for human intervention in RCS and remediation; and democratize access to insights using conversational natural language interfaces. Selector delivers on these outcomes, while accelerating incident remediation through smart, actionable alerting and a GenAI-based conversational interface.

Steve, Grant and Ryan return to Simple Talks to discuss SQL Server and Postgres. The advocates share their experiences with both systems, highlighting what works and what doesn’t. From time series and Query Store to extended events, tooling and log shipping - this is a quick-fire deep dive into the pros, cons and differences between the two. There’s also conversation around making the transition from one system to the other, and Ryan reflects on his challenging introduction to Postgres…on the first day of a new job.