Hi @everyone, You've already heard about Convex 1.25 and PlanetScale (scroll up), but the team's got a lot more ready for you to use: ## 📜 RAG Component Convex now has a Retrieval-Augmented Generation (RAG) component. You can now easily chunk, namespace, filter, and do surrounding data retrieval when working with large documents in your AI apps. [Use the component](https://www.convex.dev/components/rag) ## 🪵 Better scheduler logs Now you can get statistics on scheduled functions in log streams. For example, graph scheduled functions by count in Axiom: ``` dataset | where ['data.topic'] == "function_execution" | where isnotnull(['data.scheduler_info.job_id']) | summarize count() by ['data.function.path'] ``` Also, for example, graph the number of concurrent jobs ``` dataset | where ['data.topic'] == "scheduler_stats" | summarize max(['data.num_running_jobs']) by bin(_time, 1m) ``` [See the docs](https://docs.convex.dev/production/integrations/log-streams/#function_execution-events) ## 🗄️ Self-hosting Axiom, Datadog, Sentry, and other integrations We’ve open sourced our various log and data streams integrations. As more people start using self-hosted Convex for real-world applications, we want to provide you with additional tools to manage and scale. [See the latest self-hosted changelog](https://github.com/get-convex/convex-backend/blob/main/self-hosted/CHANGELOG.md#2025-07-01) [Sharable link](https://news.convex.dev/product-updates-volume-20/)

Indy•5mo ago

Hi @everyone, You've already heard about Convex 1.25 and PlanetScale (scroll up), but the team's got a lot more ready for you to use: 📜 RAG Component Convex now has a Retrieval-Augmented Generation (RAG) component. You can now easily chunk, namespace, filter, and do surrounding data retrieval when working with large documents in your AI apps. Use the component 🪵 Better scheduler logs Now you can get statistics on scheduled functions in log streams. For example, graph scheduled functions by count in Axiom:

dataset
| where ['data.topic'] == "function_execution" 
| where isnotnull(['data.scheduler_info.job_id'])
| summarize count() by ['data.function.path']

dataset
| where ['data.topic'] == "function_execution" 
| where isnotnull(['data.scheduler_info.job_id'])
| summarize count() by ['data.function.path']

Also, for example, graph the number of concurrent jobs

dataset
| where ['data.topic'] == "scheduler_stats"
| summarize max(['data.num_running_jobs']) by bin(_time, 1m)

dataset
| where ['data.topic'] == "scheduler_stats"
| summarize max(['data.num_running_jobs']) by bin(_time, 1m)

See the docs 🗄️ Self-hosting Axiom, Datadog, Sentry, and other integrations We’ve open sourced our various log and data streams integrations. As more people start using self-hosted Convex for real-world applications, we want to provide you with additional tools to manage and scale. See the latest self-hosted changelog Sharable link

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