You already know that you can visualize your metrics from #Prometheus in #OpenSearch Dashboard's Discover Metrics experience (if not, check the comments).

But what if we could add some #AI sauce to detect anomalies and extrapolate forecasts?

Check out the new RFC for time series #anomalyDetection and #forecasting in @OpenSearchProject and chime in with your feedback.
https://github.com/opensearch-project/OpenSearch-Dashboards/issues/11439

#OpenSearchAmbassador #timeseries #metrics #monitoring #cloudnative
@Prometheus

Time Series Forecasting Analysis with Python
A practical workflow for finance data: clean the timeline, beat a baseline, and ship forecasts you can monitor.
This post walks through the real steps: missing dates, outliers, leakage-safe splits, baseline models, better models, and monitoring drift after deployment.

 https://medium.com/write-a-catalyst/time-series-forecasting-analysis-with-python-a8b518e54708

#python #timeSeries #finance #dataScience #forecasting

@programming @ai @socialsciences @pythonclcoding

Hey #plane bubble, is there any existing solution to store #ADSB using #tar1090 toolchain for longtime playback of all the surrounding plane movements? And to query it to get all flights within certain height, time patterns, ...? Preferably something to feed trajectories into #QGIS or #movingpandas ?

#aviation #flights #sdr #gis #timeseries #airplanes

Open call for participation at the Sensing Mountains 2026 edition of the international and interdisciplinary Innsbruck Summer School of Alpine Research. We are looking forward to meet you in Obergurgl (Austria).

https://www.uibk.ac.at/en/weiterbildung/sensing-mountains/

https://www.uibk.ac.at/en/geography/sensing-mountains/2026/

#sensingmountains #remotesensing #closerangesensing #laserscanning #photogrammetry #thermography #changedetction #timeseries #mountainresearch #geography #geomorphology #forestry #naturalhazards #earthobservation @uniinnsbruck

Congratulation to Maxime for his paper in ISME :
Beauvais M. et al.
Functional complementarity between vitamin B1 and B12 metabolisms shapes seasonal marine microbial communities
https://academic.oup.com/ismej/advance-article/doi/10.1093/ismejo/wrag029/8490303

#metagenomics #vitamin #plankton #bacteria #timeseries

Kunal Batra (@kunal732)

MLX-Swift-TS라는 SDK가 공개되었습니다. 이 도구는 Apple Silicon에서 시계열 파운데이션 모델을 완전 온디바이스로 실행하도록 설계되었으며, 작성자는 Datadog에서 사용된 'Toto' 시계열 파운데이션 모델과 제로샷 예측 가능성을 언급하며 온디바이스 시계열 예측 워크플로를 소개합니다.

https://x.com/kunal732/status/2026799368653643778

#mlx #timeseries #applesilicon #sdk

Kunal Batra (@kunal732) on X

Introducing MLX-Swift-TS https://t.co/9qmyqyISf6 An SDK for running time series foundation models fully on-device on Apple Silicon. When I joined @datadoghq , I was introduced to Toto, our time series foundation model, and got excited about zero-shot forecasting across

X (formerly Twitter)
Five Architectures for Time Series Forecasting with Large Language Models
Large Language Models are increasingly being applied to time series forecasting. Not as chatbots, but as prediction engines that leverage the pattern recognition capabilitie
https://www.hylkerozema.nl/2026/02/25/five-architectures-for-time-series-forecasting-with-large-language-models/
#DataScience #MachineLearningEngineering #DataScience #Forecasting #FoundationModels #LLM #MachineLearning #TimeSeries #Transformer
Five Architectures for Time Series Forecasting with Large Language Models – Hylke Rozema

fly51fly (@fly51fly)

MIT, Allen Institute for AI, Qube Research & Technologies 연구진이 'Reverso'라는 시간 시계열용 파운데이션 모델을 공개했다. Reverso는 제로샷 환경에서도 효율적인 예측을 수행할 수 있는 모델로, 고성능의 시계열 분석 및 경제·기상 데이터 예측 등에 활용될 가능성이 있다. 효율적 예측을 강조한 신개념 시계열 모델 연구로 주목받고 있다.

https://x.com/fly51fly/status/2025692807592296859

#timeseries #foundationmodel #forecasting #ai #research

fly51fly (@fly51fly) on X

[LG] Reverso: Efficient Time Series Foundation Models for Zero-shot Forecasting X Fu, Y Li, G Papaioannou, Y Kim [MIT & Allen Institute for AI & Qube Research & Technologies] (2026) https://t.co/I1S981s6nK

X (formerly Twitter)
Learning time series analysis through CDR - Negative PID

In January, we started attending police-led training on CDR analysis with IACA. Time series analysis, in particular, helps solve real-life crimes. Here's how.

Negative PID

This is a hands-on walkthrough of building a real-time dashboard with Quarkus + Redis TimeSeries.

Live ingestion via WebSockets, automatic downsampling, multi-resolution queries, and a simple browser UI.
Crypto is just the data source. The patterns apply to metrics, IoT, and event streams.

https://www.the-main-thread.com/p/real-time-crypto-dashboard-java-quarkus-redis-timeseries

#Java #Quarkus #Redis #TimeSeries #BackendEngineering #EventStreaming