Vespa.ai VS Grafana

Vespa.ai Reviews

Grafana Reviews

Vespa.ai mentions (19)

• Code Search Is Hard

  If you're serious about scaling up, definitely consider Vespa (https://vespa.ai). At serious scale, Vespa will likely knock all the other options out of the park. - Source: Hacker News / about 1 month ago

• Simple Precision Time Protocol at Meta

  Yahoo released their geographic data catalogue under open license and it still lives on as https://whosonfirst.org/ Afaik https://en.wikipedia.org/wiki/Apache_ZooKeeper started at Yahoo https://vespa.ai/ was Yahoo's search engine for news and other content product, now spinned off (https://techcrunch.com/2023/10/04/yahoo-spins-out-vespa-its-search-tech-into-an-independent-company/). - Source: Hacker News / 3 months ago

• Are we at peak vector database?

  I think https://vespa.ai/ has the right approach in this space by focusing on being hybrid - vectors alone aren't great for production use cases, it's the combining of vectors+text that lets you use ranking to get meaningful result. (I'm an investor so I'm biased; but it's also the reason why I invested). - Source: Hacker News / 4 months ago

• Show HN: RAGatouille, a simple lib to use&train top retrieval models in RAG apps

  So what’s the catch? Why is this not everywhere? Because IR is not quite NLP — it hasn’t gone fully mainstream, and a lot of the IR frameworks are, quite frankly, a bit of a pain to work with in-production. Some solid efforts to bridge the gap like Vespa [1] are gathering steam, but it’s not quite there. [1] https://vespa.ai. - Source: Hacker News / 4 months ago

• Creating an advanced search engine with PostgreSQL

  When it comes to search I cannot disagree more. https://vespa.ai is a purpose built search engine. If you start bolting search onto your database, your relevance will be terrible, you'll be rewriting a lot of table stakes tools/features from scratch, and your technical debt will skyrocket. - Source: Hacker News / 10 months ago

Grafana mentions (197)

• Docker Log Observability: Analyzing Container Logs in HashiCorp Nomad with Vector, Loki, and Grafana

  Monitoring application logs is a crucial aspect of the software development and deployment lifecycle. In this post, we'll delve into the process of observing logs generated by Docker container applications operating within HashiCorp Nomad. With the aid of Grafana, Vector, and Loki, we'll explore effective strategies for log analysis and visualization, enhancing visibility and troubleshooting capabilities within... - Source: dev.to / 2 months ago

• Golang: out-of-box backpressure handling with gRPC, proven by a Grafana dashboard

  To help us visualize these scenarios, we'll build a Grafana Dashboard so we can follow along. - Source: dev.to / about 1 month ago

• Monitoring, Observability, and Telemetry Explained

  Visualization and Analysis: Choose a tool with intuitive and customizable dashboards, charts, and visualizations. A question to ask is, "Are the visualization features of this tool user-friendly and adaptable to our team's specific needs?" Tools like Grafana and Kibana provide powerful visualization capabilities. - Source: dev.to / about 1 month ago

• 4 facets of API monitoring you should implement

  Prometheus: Open-source monitoring system. Often used together with Grafana. - Source: dev.to / 2 months ago

• How to collect metrics from node.js applications in PM2 with exporting to Prometheus

  In example above, we use 2 additional parameters: code (HTTP response code) and page (page identifier), which provide detailed statistics. For example, you can build such graphs in Grafana:. - Source: dev.to / 3 months ago