Automatically measure MTTR, impacted infrastructure, task completion, and more with new incident analytics.
Whether operations are running smoothly or you’re running into a number of hiccups, the question to IT is always the same – “What do we even pay you for?” Rather than viewing IT as a vital piece of the puzzle, organizations often view IT as a cost center, leading to warped perceptions of the importance of IT.
This article was originally published in The New Stack and is reposted here with permission. A consequence of living in a rapidly changing society is that the state of all systems changes just as rapidly, and with that comes inconsistencies in operations. But what if you could foresee these inconsistencies? What if you could take a peek into the future? This is where time-series data can help.
When it comes to centralizing logs to Elasticsearch, the first log shipper that comes to mind is Logstash. People hear about it even if it’s not clear what it does: – Bob: I’m looking to aggregate logs – Alice: you mean… like… Logstash? When you get into it, you realize centralizing logs often implies a bunch of things, and Logstash isn’t the only log shipper that fits the bill.
