App Reliability with Azure: Smarter Monitoring without Expensive Tools

Applications need to work. Always. That sounds obvious, but in practice, application reliability is a constant challenge. Downtime costs money, sluggish performance frustrates users, and unexpected errors create stress for IT teams. 

Many organisations turn to comprehensive, high-cost monitoring platforms, such as Dynatrace. Is that always necessary, though? At CloudFuel, we don’t think so. We rely on the power of Azure-native tools to establish app reliability. This approach is often smarter, more flexible, and more cost-effective. In this article, we’ll explain how we do it, and how our approach compares to ‘all-in-one’ platforms. 

Our approach to app reliability 

At CloudFuel, we use a three-phase methodology. This structure helps us to work together with the customer step by step towards a more reliable application environment. 

Phase 1 

It all starts with a clear understanding of the current situation and goals. In this first phase, we dive deep into discussions with the client. 

1. Intake and expectations
   What are the specific concerns? Does the client want a general overview or are there particular issues like slowness or downtime? We need to clarify expectations. That is crucial. 
2. Architecture and infrastructure analysis
   We examine the technical setup of the application. What does the infrastructure look like? What architectural decisions have been made? This matters because certain design choices (or lack thereof) can impact performance. 
3. Identifying workloads
   We map out the different workloads: the specific processes or tasks the application handles. A common example is an app that generates payslips monthly and tax statements annually. That yearly task is a heavy workload that only runs once a year. If it shares infrastructure with the daily tasks, it can slow down the entire app during that time. We look for those kinds of ‘hidden’ intensive processes. 
4. Current monitoring setup
   What is the client using today? Which tools? What data is being collected? 
5. Action plan
   Based on all that information, we create a concrete action plan for the next phase.

At this stage, we’re not yet installing tools or collecting data. It’s all about understanding, analysis, and planning. 

Phase 2

In the second phase, we roll up our sleeves and start implementing and improving monitoring and reliability. This involves several steps: 

Standardising and centralising 

We often see a mix of tools and approaches used by internal teams and external partners. Everyone has their own way of doing things, leading to fragmented monitoring that isn’t very effective. Our first step is therefore usually to standardise and centralise. We’re bringing everything together in one place, with one clear set of guidelines. 

The power of Azure-native tools 

Here’s where we differ from platforms like Dynatrace. We believe strongly in the flexibility and strength of Azure’s native ecosystem. We use a core set of tools: 

• Azure Monitor: The central hub for monitoring data in Azure. 
• Log Analytics: For storing and analysing logs. 
• Application Insights: Focused on app performance and diagnostics. 
• OpenTelemetry: An open standard for collecting telemetry (logs, metrics, traces) from apps (promoting vendor neutrality). 
• Grafana: For powerful, flexible dashboards and visualisations (also available as a managed service in Azure). 

With those five tools, we can cover almost all monitoring and alerting needs for most scenarios. Yes, expensive tools such as Dynatrace may have highly specific, complex features that are hard to replicate. The key question remains, though: do you really need those? 

Quite often, you’ll pay for a costly suite while only using a fraction. Our approach is more cost-effective and focuses on what truly adds value. For instance, we add business context to monitoring so the impact of technical issues on the business becomes much clearer.

Starter packs for a quick launch 

We’ve developed ready-to-go starter packs: sets of alerts and dashboards that provide immediate insights into basic infrastructure metrics (CPU, RAM, slowest DB queries, etc.). This gives you a solid start. Later, we fine-tune them per application and workload. We also offer an IaC Starter Pack (Infrastructure as Code), so new alerts and dashboards can be deployed consistently and automatically.

Health analysis: How healthy is the app? 

Now that we have data, we analyse the application’s health. We assess four key areas: 

1. Observability: Do we see everything we need to see? 
2. Availability: Is the app and its components available? 
3. Scalability: Can the app handle variable loads? Do we spot workloads that might cause issues during peak times? 
4. Fault tolerance: How well does the app handle failures? Can it recover on its own?

Health modelling: Intelligent monitoring 

Now this is a crucial step! Without health modelling, monitoring is just a good intention. We define what ‘healthy’, ‘degraded’ (reduced performance), and ‘unhealthy’ means per workload. 90% CPU usage might be fine for one workload while critical for another. By implementing this model: 

• We make reliability measurable, 
• We avoid alert fatigue: too many irrelevant alerts will ultimately just be ignored. We only want alerts for real issues or risks, 
• We fine-tune the alerts from the starter packs and add new, specific ones.

Phase 3 (optional)

If the client wants complete peace of mind, we also offer managed services. 

Alert and incident management 

We receive and analyse alerts 24/7, create incidents in our system, and handle them. Azure platform issues? We resolve them immediately. Application issues? We escalate them to the appropriate development teams or partners. The client doesn’t have to worry about a thing. 

Problem management 

We identify recurring problems and proactively suggest solutions to prevent them from happening again. 

Quarterly review 

Optionally, we offer a quarterly review to discuss: 

• Triggered alerts and handled incidents, 
• Trends in performance and reliability, 
• Logging and monitoring costs, 
• New workloads or applications, 
• The need to adjust the health model, 
• Application errors and their trends. 

Ready for reliable applications? 

Want to learn more about how CloudFuel can improve your app reliability using Azure-native tools? Struggling with slow applications, unexpected downtime, or fragmented monitoring? 

Get in touch! We’d be happy to explore your situation (non-binding) and show how our approach can help you gain better insight, control, and reliability without the costs of expensive, monolithic tools.