Published May 15, 2025
After an outage, a team finally agrees that monitoring needs attention. Someone opens a browser and searches for tools. Two hours later there are fourteen tabs, three free trials, and a spreadsheet of features that all look the same. The decision gets postponed again, because comparing tools feels harder than the outage did, and the next incident arrives before anyone has chosen.
Part 1 explained why the saas server monitoring landscape gets ignored until something breaks. This follow-up deals with the next problem: how to evaluate the options once you've decided to look, without losing weeks to it.
Feature lists make tools look interchangeable. Nearly every product claims dashboards, alerts, and integrations, so comparing on features alone tells you very little about how a tool will behave on your infrastructure at two in the morning.
There's also no clear owner. Choosing a monitoring tool isn't any one person's job, so it falls to whoever has a free hour. That person tends to pick what's familiar or what's cheapest to try, rather than what fits the team's real problems. The result is a tool that suits the person who chose it, not the people who'll be paged by it.
And the stakes feel low until they aren't. A tool that's merely adequate works fine on a calm day. Its weaknesses only show during an incident, which is the worst time to discover them. By then the tool is already in place, and nobody wants to reopen the decision mid-incident.
The first cost is a drawn-out search that never finishes, so the team keeps running on the same scattered consoles that failed it. Every week without a decision is another week of the same blind spots, and the team slowly gets used to them.
The second is choosing badly and living with it. A tool that doesn't cover one of your cloud providers, or can't route alerts to the right team, ends up supplemented by a second tool, then a third, each with its own logins and alert rules. Overlapping tools mean duplicate alerts, split ownership, and a bill that grows without the coverage improving.
The third is switching cost. Alert routing, thresholds, and habits all get built around the first tool you adopt. Moving later means redoing that work, which is why a rushed choice can be expensive for years. A short, structured evaluation costs far less than a long migration later.
Start from your own incidents, not from a feature list. Write down the last three or four times something went wrong and ask what you'd have needed to catch each one earlier. Those become your test cases.
Then, before you look at any product, list what you actually run: which cloud providers, how many servers, which public endpoints, and who needs to receive alerts. A tool that can't cover your real infrastructure is out, however good it looks, and so is one that can't send alerts where your team actually looks.
Run a short trial on real servers, not a sandbox. Connect a handful of production-like machines, trigger a real problem such as filling a test disk, and see how quickly the right person hears about it. A tool that takes hours to reach the right person during a test won't do better in a real outage. Pay attention to how much effort it takes to add the next server, because setup that's tedious tends to be skipped, which leaves exactly the gaps you were trying to close.
Finally, ask what the tool doesn't do. Every product has limits, and knowing them early lets you plan for them rather than discover them mid-incident. Ask vendors directly, and be wary of answers that avoid the question.
BigBell is built for infrastructure monitoring. It monitors AWS resources such as EC2, RDS, Lambda, and network load balancers, and Azure and GCP virtual machines. Linux servers on any host, including DigitalOcean, report CPU, memory, and disk through an installed agent. URL monitoring checks uptime and response time from outside your infrastructure, and SSL certificate expiry is tracked separately. Billing is tracked for AWS, Azure, and GCP.
Thresholds are set per resource with separate warning and critical values, and a configurable delay filters brief spikes. Resources are organized into projects, and alerts can be routed at the organization, project, or application level to email, Slack, Microsoft Teams, Google Chat, WhatsApp, SMS, or a phone call. A recovery notification is sent when a resource returns to normal.
It's worth being clear about the limits. BigBell doesn't aggregate logs, and DigitalOcean servers are added individually rather than discovered from an account. If those matter to you, plan for them. You can read more on the BigBell monitoring page.
Why is choosing a monitoring tool so hard? Because feature lists look alike and the differences only appear in real incidents. Testing against your own past incidents shows you more than any comparison table.
How long should an evaluation take? A couple of weeks is usually enough: a day to define your needs and a short trial on real servers. Longer than that tends to mean the decision is stalling.
What should I test during a trial? Add a few real servers, trigger a small problem on purpose, and watch how quickly the alert reaches the right person. Also note how easy it was to add each server.
Should I pick the cheapest option? Price matters, but a cheap tool that misses a provider or routes alerts badly costs more in the end. Weigh price against how well it covers your real infrastructure.
Is a native cloud console enough? For one provider and a small setup, it may be. Once you run several providers, separate consoles mean separate alerts and no single view.
Does BigBell monitor logs? No. BigBell focuses on servers, cloud resources, URLs, and costs rather than log aggregation.
Does BigBell cover DigitalOcean? Yes, through the installed Linux agent and URL checks. It doesn't connect to a DigitalOcean account, so each server is added individually.
Who should lead the evaluation? Someone who'll be on call for the result, ideally with input from the teams that own the infrastructure. A choice made by someone who never gets paged tends to miss practical details.
Do I need to replace every existing tool? Not necessarily. Start by covering the gaps your incidents exposed, and retire overlapping tools only once you trust the new one.
What if I already use another tool? Compare it against your incident list the same way. If it catches those incidents and your team trusts its alerts, switching may not be necessary.
What's the most common mistake when choosing a tool? Choosing on features alone. Test against your own incidents and your own infrastructure, since that's what decides whether the tool helps when something breaks.
How do I involve the rest of the team? Share the incident list and trial results, and ask each team that owns infrastructure whether their servers and alert needs are covered. Adoption is easier when people helped choose.
Related reading: multi-cloud server monitoring, Part 2, the DevOps monitoring checklist, and AWS server monitoring, 2027 refresh.
Want to test it against your own incidents? Book a demo.
