The Log Management Cost Trap: Part III — Search
The article discusses the challenges of log management, particularly focusing on the search aspect. It highlights the competing requirements of real-time troubleshooting and large-scale historical analysis. The author emphasizes the need for a balanced approach to ensure efficient querying while managing costs.
- ▪Log data search has two distinct use cases: real-time troubleshooting and large-scale historical analysis.
- ▪Real-time troubleshooting requires immediate visibility into log data, while historical analysis focuses on efficiently scanning large datasets.
- ▪Bronto uses AWS Lambda for bursty workloads to support demanding full-scan queries while keeping costs low.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3933240) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Patrick Londa for Bronto Posted on May 19 • Originally published at bronto.io The Log Management Cost Trap: Part III — Search #logging #devops #infrastructure #observability The Log Management Cost Trap (3 Part Series) 1 The Log Management Cost Trap: Ingestion 2 The Log Management Cost Trap: Part II — Storage 3 The Log Management Cost Trap: Part III — Search Authored by Benoit Gaudin In Part I (Ingestion) and Part II (Storage) of this series, I explored the challenges of designing,…
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