Showing posts with label logs. Show all posts
Showing posts with label logs. Show all posts

Thursday, June 11, 2020

[Links of the Day] 11/06/2020 : Metric Time-Series Database, Machine Learning for metrics, Causal Time series Analysis

  • Victoria Metrics : fast, cost-effective and scalable time-series database, if you need a backend for Prometheus, by example, this is the DB for you.
  • Sieve : a platform to derive actionable insights from monitored metrics in distributed systems. the platform is composed of two separate systems. One geared toward trace reduction and selection with intelligent sampling using a form of zero-positive learning. And a second system that extracts correlations between the services generating the traces.
  • Tigramite : causal time series analysis python package. It allows to efficiently reconstruct causal graphs from high-dimensional time-series datasets and model the obtained causal dependencies for causal mediation and prediction analyses [github]



Thursday, December 13, 2018

[Links of the Day] 13/12/2018 : Prometheus for Logs, Cloud Adoption framework, HR job title comparison website

  • Grafana Loki : this is actually really cool, like Prometheus but for logs. It seems like a good light-weight alternative to elasticsearch. 
  • Google Cloud Adoption Framework : Google is trying to sell you its cloud. Good white paper anyway, describing a form of a cloud maturity model for the enterprise.
  • Levels: If you ever wonder what a certain job title means and how it stacks vs other companies. Search no more! Levels is here to help you understand the intricate world of HR job title hierarchy.