Three Habits of Highly Effective Observability Teams in Microservices Architectures

As organizations transition to microservices and containerized architectures, the need to rethink operational tasks like security and observability becomes evident. In a world where developers, rather than operations teams, are responsible for keeping applications running, and systems are highly distributed, ephemeral, and interconnected, traditional approaches no longer suffice.

From a technology perspective, open-source standards have become the norm. Protocols like OpenTelemetry and Prometheus, along with agents like Fluent Bit, are widely adopted. According to the 2023 CNCF survey, Prometheus usage has increased to 57% in production workloads, with OpenTelemetry and Fluent both at 32% adoption.

However, open-source tools alone aren’t enough to transform observability practices. Through my experience working with organizations that have mastered observability at scale, I’ve identified three key habits that set highly effective observability teams apart. Let’s dive in.

1. Measure Thyself — Set Smart Goals With Service Level Objectives (SLOs)

Service Level Objectives (SLOs) were popularized by the Google SRE book in 2016. Yet, many organizations still struggle to implement them effectively. SLOs are specific performance goals, such as aiming for 99.9% uptime, while Service Level Indicators (SLIs) measure whether these goals are met. Error budgeting allows teams to balance reliability and innovation by permitting a certain amount of downtime or errors within the SLOs.

For example, Doordash uses SLOs to ensure timely food deliveries. High SLO burn could mean a merchant misses an order or a customer experiences app errors. By setting practical and achievable SLOs, teams can predict failures and act proactively.

Pro Tip: Start small by setting SLOs for key user journeys. Collaborate with SREs and business users to define realistic targets. Adjust SLOs as your system evolves.

2. Embrace Events — The Only Constant in Your Cloud-Native Environment is Change

In DevOps, change is inevitable. New code deployments, feature toggles, infrastructure updates, and external factors like traffic spikes or news events can all impact system performance. According to the Digital Enterprise Journal, 67% of organizations lack the ability to identify changes causing performance issues.

To stay ahead, teams must centralize change tracking. Events, often considered the fourth type of telemetry alongside metrics, logs, and traces, provide critical context for debugging. For instance, Dandy Dental improved observability by correlating system changes with behavioral shifts, enabling faster issue resolution.

Pro Tip: Integrate change tracking into your observability strategy. Use tools that centralize events from feature flags, CI/CD pipelines, and cloud infrastructure.

3. Adopt Hypothesis-Driven Troubleshooting — Enable Any Developer to Fix Issues Faster

When troubleshooting, developers start with a hypothesis. The faster they can prove or disprove it, the quicker they resolve the issue. Observability tools play a crucial role here, providing the context needed to form and test hypotheses.

For example, an AI software company used hypothesis-driven troubleshooting to investigate a high error rate. Within 10 minutes, they narrowed it down to a single region that missed a recent software deploy.

Pro Tip: Reduce Mean Time to Resolution (MTTR) by equipping developers with contextual alerts and tools that streamline hypothesis testing. For complex issues, leverage concurrency by involving multiple developers to test hypotheses simultaneously.

Taking the Next Step

If you’re ready to elevate your observability practices, these three habits—setting SLOs, embracing change tracking, and adopting hypothesis-driven troubleshooting—are a great starting point. At ZippyOPS, we specialize in helping organizations optimize their DevOps, DevSecOps, DataOps, and Cloud operations.

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By adopting these habits and leveraging ZippyOPS’ expertise, your team can achieve unparalleled observability and operational efficiency in your microservices architecture. Let’s build a future where your systems are as resilient as they are innovative.