Ask most enterprise IT teams how many observability signals they collect, and the honest answer is usually “a lot, from a lot of places, and we ingest everything.” Ask which of those signals they actually trust to make a decision under pressure, and the room goes a little bit quiet. There’s a gap between the volume of telemetry an organisation gathers and the completeness of the picture it can actually act on. And more often than not, that gap comes down to a simple problem: most teams are strong in one or two signal types and quietly weak in the rest.
At amasol, we define observability through four essential signals: logs, traces, metrics, and events. Each one answers a different question. Logs tell you what happened. Traces tell you where it happened. Metrics tell you how much, and whether it matters. Events tell you when to act. Individually, each is useful. Together, they’re the difference between reacting to an incident and understanding your systems well enough to stay ahead of one. The trouble is that very few organisations are equally mature across all four, and the missing signal is usually the one you needed most when something broke.
Logs: what happened
Logs are the richest forensic record you have. When something goes wrong, they’re where you go to reconstruct the sequence of events, the error that fired, the request that failed, the state the system was in. In cloud-native and distributed environments, that forensic value is enormous, but it comes with a catch. Log volume scales faster than anyone expects, and raw logs on their own are just text. The challenge isn’t collecting them, it’s turning them into operational intelligence you can use for troubleshooting, compliance, and optimisation, rather than a haystack you search through after the fact. A team that’s strong on logs but weak elsewhere tends to be very good at explaining what went wrong, after it has already gone wrong. That’s valuable, but it’s a bit backward-looking. Logs explain the incident you already had and not the one forming now.
Traces: where it happened
Modern IT environments are distributed across dozens of services, often instrumented with multiple tools that don’t talk to each other. When a transaction slows down or fails, the hard question isn’t whether something broke, it’s where in the chain it broke. Traces follow a request end to end, across services and dependencies, so you can see exactly which hop introduced the latency or the failure.
Traces also do something subtler that’s easy to overlook. They expose your blind spots. When you trace a business process from start to finish, the gaps become visible: the unmonitored system, the interrupted monitoring chain, the handoff nobody had instrumented. You can’t fix what you can’t see, and traces are often the signal that reveals just how much you weren’t seeing. Without them, teams spend the first part of every incident not diagnosing the problem but arguing about which component to blame.
Metrics: how much, and whether it matters
Logs and traces tell you what and where. Metrics tell you how much. They’re the quantitative layer that lets you manage performance, capacity, and cost, and crucially, they’re what connects technical behaviour to business outcomes. A spike in response time is a metric. So is the checkout completion rate it affects, and the cloud bill the underlying infrastructure generates.
This is where observability stops being purely an engineering concern. When metrics are high-resolution and tied to real business context rather than generic out-of-the-box thresholds, they’re what let IT say “this degradation cost us conversions” instead of “the API was slow.” They turn operational reality into something leadership can act on. A team without strong metrics can describe its incidents in detail but struggles to answer the only question the business actually cares about: how much did this matter, and was it worth what we spent to prevent it?
Events: when to act
Events are the earliest indicators of change or risk in your systems. They’re the signal that something is shifting before it becomes a full incident. And they’re also where most organisations drown. Modern environments generate enormous alert volumes, and without correlation and context, those alerts pile up into noise that teams learn to ignore by instinct rather than logic.
The point of event intelligence isn’t more alerts, it’s fewer and better ones. Correlated, contextualised events are what move a team from reacting once a problem is already visible to acting while there’s still a window to prevent it. This is the signal that most directly determines whether your observability practice is proactive or just an expensive way of confirming bad news. Get events right, and the absence of an alert becomes trustworthy in itself. Get them wrong, and every quiet dashboard is just a question mark.
Why one or two isn’t enough
These four signals aren’t a menu you pick from. They’re a system, and the value comes from the combination, not the individual parts. Logs without traces tell you what failed but not where in a distributed flow. Traces without metrics show you the path but not whether the impact was material. Metrics without events tell you something changed, but they don’t always provide the context or prioritization needed to act quickly. Events without logs raise the alarm but leave you without the forensic detail to understand the cause. Each missing signal is a blind spot, and blind spots are exactly where the slow, expensive incidents live: the ones nobody caught early because the signal that would have caught them wasn’t part of the picture.
This is why partial visibility, the state most organisations are actually in, feels like observability right up until the moment it fails you. You have a lot of data, too much in our opinion. What you don’t have is the complete view that lets you understand what is happening, why it’s happening, and what’s likely to happen next.
See the full picture at the Business Observability Forum
This is exactly what we’ve built this year’s forum around. The opening keynote, Trust Your Signals, frames the day, and the closing panel brings the signals back together as a business priority. In between, four masterclasses each take one signal in depth: logs as operational intelligence, traces for end-to-end visibility, metrics for IT-Reliability, and events as the move from reactive to proactive, led by the practitioners and partners who work with each of them every day. You choose which sessions to go deep on, but the day as a whole is built to leave you with the complete picture, not four separate topics.
And that’s the real reason to be in the room. This isn’t a webinar you half-watch with your inbox open. It’s a full day where everyone is actually there in person: our consultants, our partners, our sales team, and our leadership, right up to our CEO, CTO, and VPs. Importantly, our customers are there too, so you’re not just talking to us, you’re also exchanging ideas with peers who are dealing with the same challenges in real environments. You can ask the hard questions face to face, get into the detail of your own setup, challenge what you hear, and follow a thread as far as you want to take it. The format gives you a freedom that a screen never does. You’re not raising a hand in a chat box, you’re having real conversations with the people who build, run, and use these systems every day.
It’s also the best way to see how amasol actually operates as a company, how we think, how we approach a problem, and whether we’re the kind of partner you’d want in the room when it counts. That’s hard to judge from a website or a sales call. It’s a lot easier across a table. The motto this year is Trust Your Signals. You can only do that when you have all four, and when they work together. Come see the full picture, and the people behind it.
Join us in Munich on the 11th of June 2026, from 10:00 to 17:00. Click the link to view the agenda and register. The date is close now, so secure your place while you still can.
About the author
Makasy Tan is a Marketing Specialist focused on observability. He translates complex infrastructure topics into clear and actionable narratives for engineering and business audiences. He believes effective communication prioritizes simplicity and clarity over complexity.
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