You probably assume your observability stack pays for itself. Better monitoring should mean fewer outages, faster resolutions, and less revenue at risk. The investment should justify itself.
But in mid-market Azure environments, the math often breaks.
I have seen teams spend more on monitoring than on the outages they’re trying to prevent. A $ 600K observability bill to protect against potentially $ 300K of annual downtime. Years of logs no one queries. Tool stacks are so fragmented that 97% of alerts get ignored.
That’s because observability economics were built for enterprises with million-dollar-per-hour outages. Yet, mid-market companies inherit the same “collect everything, retain forever, alert on anything” playbook without the business justification.
In this edition, I reveal how observability outgrew its value and where you can cut costs without increasing risk.
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You’re paying to store logs nobody reads
What teams believe
More data is always better. If we need it someday, we should collect and keep it. You can’t troubleshoot what you didn’t log.
What actually happens
Teams instrument everything because they fear missing something critical. Every HTTP request, every database query, every function call gets logged or traced. Retention policies default to 30, 60, or 90 days, sometimes longer, “just in case.”
But teams typically investigate issues within a few days. Older data accumulates.
Azure Application Insights charges around $2.30 per GB ingested. A single busy application can easily generate a gigabyte of telemetry per day with verbose logging enabled.
That’s roughly $70 per month for one app, modest until you multiply it across dozens of microservices or cloud functions.
So what can you do about it?
Start with a data usage audit. Azure Monitor and Log Analytics track which queries you actually run. Look at the past 90 days. You’ll likely find entire categories of telemetry that were never touched; maybe debug-level logs, maybe per-container metrics when you only ever look at cluster-level aggregates.
For high-volume applications, enable adaptive sampling in Application Insights. It automatically throttles telemetry when traffic spikes, ensuring predictable ingestion costs while maintaining statistical accuracy.
Separate hot from cold data. Keep 30 days of critical logs in Log Analytics for fast querying. Move anything older to Azure’s archive tier at roughly one-fifth the cost, or export to blob storage if you need it for compliance but rarely access it.
You’re paying five separate bills for overlapping features
What teams believe
We need infrastructure monitoring, application performance monitoring, log aggregation, real-user monitoring, and security event tracking; that’s just how modern observability works.
What actually happens
Grafana’s survey reveals that more than half of companies use six or more observability tools, with 11% reporting the use of 16 or more. Each adds its own fees, agents, training, and complexity; often monitoring the same systems from different angles.
Teams admit they use only “one or two features” of each suite, paying for unused capacity while data remains siloed.
Engineers end up in “swivel-chair monitoring,” jumping between dashboards and missing key signals. For lean mid-market IT teams, maintaining 5–7 tools turns monitoring from simplification into overload.
Case in point:
A mid-market SaaS company developed into a tool sprawl. DevOps utilized Azure Monitor, developers added a third-party APM, security employed a SIEM, and also used two niche tools.
Five platforms meant duplicate agents, overlapping data, and endless alerts. When the CTO and CFO reviewed costs, they decided to consolidate around Azure’s native stack since they were already Azure-first.
Once Azure Monitor and Application Insights covered the essentials, they retired other tools, resulting in annual savings of 20–30% in both licenses and operations.
Engineers were also more productive with fewer dashboards. They traded some advanced APM features for simplicity and integrated pricing, but for a mid-market firm, “good-enough” visibility at lower complexity was the smarter investment.
So what can you do about it?
Audit your stack. List every observability tool, what teams actually use, and where features overlap. Many teams discover they’re paying twice for logs or collecting the same performance data in multiple systems.
Consolidate into Azure-native tools where practical. For Azure-first companies, Azure Monitor, Application Insights, and Log Analytics typically cover 80% of their needs at a lower cost and with less operational overhead, often making them a better fit than maintaining several specialized platforms.
Be stricter about new tools. Before adding anything, ask: “What’s the full three-year cost including engineering time?” If you can’t answer that, it’s likely unmanaged spend waiting to happen.
You’re paying for thousands of alerts nobody acts on
What teams believe
More alerts mean better coverage. If something goes wrong anywhere in our systems, we’ll know immediately and can respond fast.
What actually happens
Research shows many DevOps teams get 2,000+ alerts weekly, yet only about 3% require immediate action. The rest is either of low priority or non-actionable.
That constant flood creates alert fatigue. Engineers stop reacting with urgency because most alerts don’t matter, and that desensitization is dangerous.
Teams burn hours triaging noise, and in several postmortems, critical early signals were buried inside the clutter. Alert fatigue hurts productivity and quietly erodes reliability.
So what can you do about it?
Reduce alert noise. Review which alerts led to real action, turn off the rest, raise thresholds, and merge duplicates so that one issue triggers one alert, not multiple alerts.
Shift to SLO-based alerting. Use Azure Monitor to alert only when customer-facing objectives (like 99% of API calls under 200ms) are at risk, not on every minor metric change.
Use ingestion caps. Set daily Log Analytics limits to prevent a misconfigured service from flooding you with 100 GB of logs or generating an alert storm, which could result in a surprise bill.
Observability remains absolutely vital for businesses. You must know what’s happening in your systems. But it needs to be done efficiently and sustainably.
Ready to audit where your observability spending is actually going? Our Azure Cost Optimization Assessment will give you a clear roadmap to bring visibility and spend into alignment.
