What is Observability?
Let’s start with a simple question: What exactly is observability? At its core, observability is about understanding what’s happening within your systems. It’s not just about knowing that something is going wrong, but also being able to figure out why it’s happening. That means collecting signals from all layers of your stack: infrastructure, applications, processes, and even the integrations between systems.
In cloud native environments, with distributed and dynamic applications, you need observability to monitor performance, availability, and reliability. Unlike traditional monitoring, which focuses on predefined issues, observability helps teams explore the unknown: recognizing patterns, diagnosing complex problems, and predicting future issues. It provides in-depth insight into every layer of the stack, from infrastructure and containers to application code and user behavior.
With a robust observability setup, teams can respond more quickly to incidents, optimize performance, and improve the overall user experience. More importantly, it enables proactive operations by providing context-rich insights that go beyond isolated alerts. With microservices, Kubernetes, and hybrid cloud, observability becomes the foundation for managing complexity and building trust in production.
Observability and Elastic Cloud
There are several providers of observability solutions, including Elastic. Elastic Cloud offers a scalable observability solution built on the Elastic Stack (Elasticsearch, Kibana, Beats, and Logstash). With Elastic Observability, teams can consolidate all their telemetry data in a single central location, regardless of whether it comes from cloud infrastructure, applications, or end-user devices. The platform provides full visibility across the entire stack, with features such as real-time log analysis, metric visualization, distributed tracing, and machine-learning-based anomaly detection.
Because Elastic Cloud is offered as a fully managed service, setup, scaling, and maintenance are greatly simplified. This allows teams to focus on insights rather than infrastructure management. Native integrations with Kubernetes, Azure, AWS, and popular APM libraries, among others, ensure fast and efficient onboarding. Elastic’s flexible pricing and search capabilities help organizations establish a cost-effective observability practice that scales with their needs. Whether you’re resolving performance issues, ensuring availability, or optimizing systems—Elastic Cloud provides the depth and scale needed to truly understand what’s happening under the hood.
How to get started with Observability using Elastic Cloud
Getting started with Observability with Elastic Cloud begins with keeping the approach simple and pragmatic. Don't try to monitor everything right away. Start with uptime monitoring: simply check whether your systems and services are accessible. Tools such as Elastic Synthetics make this easy to implement and deliver immediate value. Once that's in place, you can expand to collecting basic infrastructure metrics such as CPU usage, memory, disk space, and network performance.
If you work in Azure, Elastic offers native integrations via VM extensions, allowing you to install agents and collect data without complex manual configurations. From there, you can add log collection and more detailed application-level monitoring step by step. Be aware, however, that every signal you bring in has a cost. Therefore, apply the 80/20 rule: focus on the 20% of systems and metrics that provide 80% of the insight.
However, implementing observability with Elastic Cloud isn’t just a technical exercise—it also requires clear internal processes, strong ownership, and collaboration between teams. One of the biggest challenges isn’t collecting data, but determining what to monitor, why it’s important, and who is responsible for it. Teams must align on shared priorities: Are we focusing on infrastructure uptime, application performance, or critical business processes? Next, establish ownership: Who defines and approves monitoring configurations, who manages dashboards, and who takes action when alerts are triggered? Without this structure, observability initiatives often get bogged down in fragmentation and yield little value.
As your observability practice matures, these questions become even more important. Elastic Cloud offers the flexibility and tooling to support a wide range of use cases, but it is internal clarity and governance that determine whether real value is extracted. Start small, test regularly, and build incrementally. Observability isn't something you "install" —it's something you grow into. With the right foundation, you'll not only create visibility into your systems, but also the confidence to act on those insights.
A practical example of implementing Observability with Elastic Cloud
In a recent project, I helped a client get started with Observability using Elastic Cloud. Nothing had been set up yet, so we really started from scratch: establishing a clear and simple process. Each team was asked what they wanted to monitor—whether it was infrastructure performance, uptime, or specific log data. Together with the infrastructure team, I assessed these requirements and deployed them using infrastructure-as-code, which helped keep everything consistent and manageable. This gave teams the freedom to focus on what was important to them without things getting too complicated.
The results were quickly apparent. Dashboards were not just attractive graphs, but actually helped teams identify and resolve issues. One team discovered virtual machines that no one was using, but which were incurring cloud costs without anyone noticing. Disabling these machines resulted in immediate savings.
Not everything went smoothly. One integration didn't support IPv6 well, so I built a custom pipeline to clean up the data. That took extra work, but it made the dashboards reliable and meaningful. That's exactly the point with Observability: you only get value out of it if you're willing to put in the effort. We built it step by step—from simple uptime checks to deeper metrics and logs. With the right tools, a solid process, and clear responsibilities, the customer now has a setup that works and grows with them.
Conclusion
Elastic Cloud is a mature observability platform, even in a complex environment like Azure. But no matter which tools you use, the principles remain the same: start with what’s simple, achieve quick wins, and expand from there.
Are you considering implementing Observability within your own environment? Whether you work with Azure, AWS, or a hybrid setup, we are happy to help you determine where to start and how to quickly realize value.
You can read about how SUE sets up an internal developer platform on the Platform Engineering page. The Platform Engineering Guide explains when such a platform is worthwhile.
