The role of observability in modern businesses

Observability builds on three pillars, logs, metrics and traces, and reaches from infrastructure and networks to data, machine learning, applications and security.

This ebook covers the practical hurdles and the trends shaping the field, profiles eight platforms including Datadog, Grafana and Splunk, lists implementation steps from SLO-aligned goals onward, and closes with three CodiLime case studies.

The main topics covered in this e-book:

Logs, metrics and traces compared, including span-based distributed tracing and sampling
Six observability types, from infrastructure and network to ML and security
Eight platforms profiled: AppDynamics, Datadog, Dynatrace, Grafana, Kentik, New Relic, Selector AI, Splunk
Implementation steps: SLO-aligned goals, centralized collection, near real-time monitoring
Three case studies, including reliability-as-code flow control in Python and Golang

The role of observability in modern businesses — document render

Why download this e-book?

How does observability go further than monitoring?
The ebook sets out the differences between monitoring and observability, and the three pillars observability is built on: logs, metrics and traces.
What does it change for the business?
Observability helps teams detect, resolve and prevent issues before they impact end users, and lowers mean time to resolution. It also links system performance to customer experience, revenue and overall business health.
How do you implement it?
Practical tips run from clear goals aligned with SLOs and the logs, metrics and traces to collect, to choosing tools, centralizing data collection and near real-time monitoring with alerts.
What trends are shaping it?
The ebook covers tool consolidation, cloud-native adoption, machine learning for anomaly detection and root cause analysis, and the push for more flexible pricing. Case studies show observability applied to reliability as code, a monitoring data portal and automated cloud onboarding.