In this post, we’ll tackle another fallacy that limits the potential of observability—that it’s exclusively built for site reliability engineers (SREs).
Why is this a myth?
This misconception surrounding observability arises from the belief that it caters exclusively to site reliability engineers (SREs) and that they are the only role that can utilize the data gathered via observability solutions. In reality, observability goes far beyond any singular role or team within an organization.
The transition to cloud-native means more than adopting new technologies; it also entails a shift in how people work. This transformation is inherently sociotechnical in nature. While the microservices toolchain itself may not explicitly demand new social practices on the surface, realizing the full benefits of this technology requires a change in work habits. This need becomes apparent when teams progress several steps into the process, only to discover that their old approaches do not effectively address the management costs introduced by the new technology.
As systems, applications and microservices become more intertwined and complex, it also becomes more difficult to identify and address incidents. In the past, organizations may have relied on SREs to troubleshoot and remediate incidents. But now, IT is much more of a team sport, and the older approaches aren’t always effective or cost-efficient. But the bottom line is that the adoption of cloud-native design patterns makes it necessary to have observable systems.
Fact: All teams need access to the observability data
The truth is that all teams—DevOps, SRE, Platform, ITOps and Development—need and deserve access to the data they want with the context of logical and physical dependencies across mobile, web, applications and infrastructure.
An observability solution offers valuable insights to multiple stakeholders engaged in software development and operations, with benefits that extend to developers, operations teams, product managers and even business stakeholders. This inclusive approach enables rapid feedback on new and more frequent deployments, ensuring swift issue resolution and improved software quality.
Let’s explore some key use cases for these other roles within an organization:
Observability tools like distributed tracing can help developers understand the flow of requests through their applications and identify performance bottlenecks. For example, they can analyze traces to see how long each component of their application takes to process a request and optimize accordingly.
Developers can instrument their code by incorporating appropriate monitoring and observability mechanisms. This involves strategically placing code-level instrumentation points and logging statements throughout the application. By doing so, developers enable the collection of valuable data and insights during the runtime of their software.
By monitoring application logs, developers can identify and fix errors or exceptions in their code. They can use log aggregation and analysis tools to search for specific log entries and gain insights into the root causes of issues.
Observability allows operations teams to monitor system metrics and set up alerts for abnormal behavior. For example, they can monitor CPU usage, memory usage and network traffic to detect performance spikes or resource bottlenecks.
Using real-time monitoring and visualization tools, operations teams can track the health of distributed systems and detect anomalies or failures. They can identify the impact of specific events on system behaviour and respond promptly to mitigate any issues.
Observability data can provide product managers with valuable insights into user behaviour and application performance. For example, they can analyze user interaction data to understand how customers are using their product and identify areas for improvement.
By correlating business metrics with system performance metrics, product managers can assess the impact of technical changes on key business outcomes. For instance, they can analyze how changes in response times affect conversion rates or customer satisfaction.
Observability allows business stakeholders to monitor and analyze business metrics in real-time. For example, they can track revenue, customer engagement or conversion rates and correlate them with system performance indicators.
By understanding the relationship between system performance and business outcomes, stakeholders can make informed decisions. For instance, they can prioritize investments in infrastructure improvements.
Providing open access to observability data is crucial as IT systems evolve and job definitions expand. It’s how you give key stakeholders the data insights they need to benefit the organization. When it’s time to select an observability tool, that’s why it is essential to understand the pricing models and consider one that does not impose additional charges for extra users.
To build a more robust and innovative IT organization, it is imperative to separate observability fact from fiction. Understanding observability’s multifaceted benefits and embracing a broader range of data sources can help you unlock new possibilities for driving improved reliability and business outcomes.
IBM’s approach to enterprise observability
IBM’s observability solution, IBM Instana, is purpose-built for cloud-native and designed to automatically and continuously provide high-fidelity data—one-second granularity and end-to-end traces—with the context of logical and physical dependencies across mobile, web, applications and infrastructure. Our customers have been able to achieve tangible results using real-time observability.
If you want to enhance your observability practices with full-stack visibility and the ability to monitor your cloud dependencies in real-time, we invite you to request a demo.
Observability in action: Real stories from real customers
Ensuring scalability for business growth: “After implementing Instana, we had visibility into things that we never saw before,” says Marcus Sengol, SVP of Technical Operations at Leaf Group Ltd. “Instana makes it very easy for us to drill down into each of our top KPIs and metrics, allowing us to optimize different parts of our stack and locate performance issues. We’ve made improvements based on those metrics, and to this day, continue to do so.”
Driving optimization: “We were looking for something that would help us understand, at very high resolution, the performance of our solution. We wanted to be able to see, on a second-by-second basis, the peaks and troughs that can exist for a variety of reasons,” saysChris Eldridge, Director of Operations at Mayden.
Stay tuned for our next blog post, where we debunk another common myth: Observability is only useful for large-scale systems or complex architectures. Get ready to discover the broader benefits and applications that await.