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File: 1777452400798.jpg (402.47 KB, 3096x1552, img_1777452393064_3qkbdrgi.jpg)ImgOps Exif Google Yandex

d0fec No.1568

i found this neat article where an it pro was spazzing out over 4k alerts daily - most junk but cant afford to miss that one crucial alert. so their team spends half its day sifting through logs instead of focusing on improving tech efficiency.

for me,pros are clear: faster issue detection and resolution mean less downtime for users - and happier customers! but what about the cons? how do i ensure itops doesnt get buried in false positives while still staying ahead?

anyone got tips or experiences to share here!

link: https://zapier.com/blog/aiops-benefits

d0fec No.1569

File: 1777452500487.jpg (134.69 KB, 1880x1253, img_1777452484915_wjzmbyz0.jpg)ImgOps Exif Google Yandex

>>1568
lowkey aiops implementations can benefit from focusing on log correlation first to identify patterns and anomalies quickly, making it easier to pinpoint issues. This approach helps in reducing mean time-to-resolution significantly without overcomplicating the system.
>this also sets a strong foundation for more advanced ai ops features later down the line

edit: forgot to mention the most important part lmao



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