Generative AI has already shown its huge potential, but there are many applications that out-of-the-box large language model (LLM) solutions aren’t suitable for. These include enterprise-level applications like summarizing your own internal notes and answering questions about internal data and documents, as well as applications like running queries on your own data to equip the AI with known facts (reducing “hallucinations” and improving outcomes).
VictoriaMetrics is an open-source time-series database (TSDB) written in Go, and I’ve had the pleasure of working on it for the past couple of years. TSDBs have stringent performance requirements, and building VictoriaMetrics has taught me a thing or two about optimization. In this blog post, I’ll share some of the performance tips I’ve learned during my time at VictoriaMetrics.
At Grafana Labs, we want to empower our fellow Grafanistas and the community to get the most out of the Grafana LGTM Stack (Loki for logs, Grafana for visualization, Tempo for traces, and Mimir for metrics). As part of this effort, we recently launched a new Grafana developer portal. And now, we’re pleased to announce the launch of the Saga Design System, which establishes a shared visual language for all of Grafana Labs’ offerings.