Most security leaders can tell you their SIEM bill to the dollar. Far fewer can tell you, line by line, what they’re paying for. That’s a problem because in financial services, that bill grows faster than the security coverage it’s supposed to buy. Let’s break it down. The bill is a function of volume, and volume is not your friend Ingestion-priced SIEMs charge by how much data you send. That makes your security budget a direct function of log volume.

Windows Event Forwarding (WEF) gives you centralized log collection with tools that ship in every supported version of Windows. There are no agents to deploy and no licenses to buy: a collector server, a Group Policy Object (GPO), and a subscription are enough to start moving events. That makes WEF one of the most accessible routes to getting Windows logs into one place. It also has hard limits in platform coverage, in resource cost, and in the kinds of data it can carry.

If you run security operations, you’re probably evaluating Cribl for one reason. The volume of telemetry hitting your SIEM is outpacing your budget, and you want to filter and reshape it before you pay to index it. Cribl is good at that. It defined the category when it launched in 2018, and for many teams, it’s still the default. Cribl works. The decision turns on three narrower questions: whether your data problem matches the one Cribl solves, what deployment model you need, and what you’ll pay per gigabyte to get there.

Your detections, correlation rules, and search results are only as good as the underlying data structure. A raw log line is a string. A structured JSON event is a set of named fields you can filter, pivot, and alert on. Convert your logs to JSON at the collection layer before they reach your SIEM. Doing it early cuts ingest cost, keeps your schema consistent across sources, and makes your detections less fragile.

Teams usually choose a log analysis tool by comparing vendors. The more costly decision sits one level up: the category of tool. The wrong choice there surfaces months later as a source you can’t collect, data you can’t normalize, or a per-gigabyte bill for logs you never needed. Log analysis tools collect, parse, store, search, and visualize log data so teams can detect threats, investigate incidents, and troubleshoot systems. The term spans four distinct categories — collection agents, processing pipelines, storage and search engines, and analysis platforms — that each handle a different job in the same workflow.

Log rotation is supposed to be routine maintenance. But if your collector reads a file while another process renames, truncates, or compresses it, events can slip through the gap — and you often won’t notice until you go looking for a log that isn’t there. For a security team, that gap is a blind spot: a detection that never fired, an audit trail with a hole in it, a control you can’t prove was working.