4 Steps to Making Observability Real for Your Team

Without hybrid observability powered by AI, it’s stressful not having complete visibility into your application. Plus, it contributes to risky deployments. Yet we hear that many developers have poor visibility into what powers production code. Without transparency into their apps, developers cannot see:

• How code connects to underlying infrastructure and cloud services.
• What is causing errors within code.
• What users are experiencing along the journey.

You can try navigating tickets, permissions, and dashboards that don’t tell the right story, but there are ways to solve this problem.

Here are some Hybrid Observability best practices your team should implement to improve visibility into your application’s code. 

Step 1: Find the Right Monitoring Solution

Traditional application monitoring tools tend to present issues and performance from the app only – ignoring the underlying on-prem or cloud infrastructure resources and severely limiting developers visibility into troubleshooting when problems arise. 

So, the first thing devs can do to achieve observability within your team is to confirm you’re using the right solution. 

Here are a few simple questions to gauge whether or not your monitoring solution is hindering your ability to ship code with confidence:

• Can you see the impact of your software releases within the monitoring tool? 
• Does your monitoring tool provide code-level visibility? Do you know if the error exists within your application, infrastructure, network, or storage?   
• Can your team use the tool on its own to be successful? Or does it require asking another team for permission to make changes?  
• Does the tool show how users are experiencing the issue? Do you measure against established baselines? Without this, it will be challenging to prioritize the right bugs.

A monitoring solution that works WITH your team, not against, is just one way to improve visibility into a product. 

Step 2: Manage Alerts Before the User Experience Suffers

We understand that receiving too many alerts can be not only disruptive and time-consuming, but it takes your attention away from what’s really important – solving issues before it’s too late. Triaging alerts helps you become aware of the most critical issues for smooth operations and user experience.

In order to separate the business-critical alerts from the rest, you shouldn’t have to re-instrument your metrics within your monitoring solution. Make sure you can easily display metrics already being tracked. With this in mind, pick one or two metrics that your users deeply care about and focus alerts here. Here are a couple of examples: 

• 95% latency is > 1s
• Request failure rate is > 0.1%

Criteria like this let you know there is a serious impact on the user experience. Hook these alerts up to existing ticketing systems or page on-call teams to hop on mission-critical issues.

This proactive observability best practice will help minimize bad user experiences. After you know which metrics are worth monitoring, focus on which errors actually need attention.   

Step 3: Understand Errors Before It’s Too Late

It’s easy to get overwhelmed with the urge to fix every error that may be impacting the user experience. You must understand the critical errors, but keep an eye on anomalies and minor errors before they bubble up. 

Investing in an error-monitoring tool will help identify non-critical errors so your team can focus more time on addressing the priority issues and reducing the risk of a severe incident.

This is what observability is about – understanding your application from its internal signals to know how the system works and not a fantasy that looks great on dashboards.

Step 4: Follow the Dots for Faster Troubleshooting

When an incident occurs, you need to know where to start, especially if it spans different calls, systems, and microservices.  

Here is how to get started at troubleshooting in a situation full of unknowns:  

• Lean into auto-instrumentation to record traces that capture real-time events across the application.
• Follow the traces to underlying logs to better understand an issue.
• See interaction patterns between microservices and application components.  
• Correlate traces to monitored infrastructure resources and network calls.

Satisfy these use cases with a centralized observability platform with these use cases in mind. 

Achieve Hybrid Observability Powered by AI with LogicMonitor

At LogicMonitor, we expand what’s possible for businesses through monitoring and observability software. LogicMonitor seamlessly monitors everything from networks to applications to the cloud, empowering developers to focus less on problem-solving and more on innovation. Our cloud-based platform helps you see more, know more, and do more.