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Learn moreThe importance of observability
Observability helps teams understand why the system is abnormal, not just know it's already abnormal. It links metrics, logs, links, RUM, Profile, Kubernetes, cloud resources, alerts, and business metrics, enabling R&D, testing, operations, SREs, and business teams to collaborate around the same factual data.
Observability can help us achieve the following goals:
Digitalization drives productivity
In digital transformation, observability is not just about collecting data, but about enabling teams to describe systems, user experiences, and business processes in a unified language. It connects development, testing, operations, and business teams to the same data context, driving continuous improvements in product quality, service stability, and business efficiency.
Improving software engineering quality
During software development and release, applications often encounter slow requests, exception dependencies, interface timeouts, JS errors, slow database queries, and resource bottlenecks. Observability allows developers to quickly pinpoint issues from trace, log, profile, and version dimensions, rather than relying solely on reproduction and guesswork.
Enhance system reliability and maintainability
Observability helps teams continuously understand system performance and capacity trends, promptly identifying risks such as Kubernetes resource shortages, increased database load, queue accumulation, network latency, and third-party interface anomalies.
Quickly diagnose problems and pinpoint root causes
Observability Provides complete context related to issues by unifying data such as metrics, logs, link tracking, frontend experience, alert events, and business dimensions, helping teams shorten MTTR and distill processes into recapable chains of evidence.
Who needs to use observability platforms
Observability not only solves data collection issues but, more importantly, integrates development, testing, pre-release, and production environments into a consistent data management approach. Teams can use the same set of metrics, logs, links, and access experience data to verify release quality, locate faults, optimize capacity, and improve service experience.
Developer
When developers troubleshoot slow interfaces, service errors, or database bottlenecks, observability can bring APM Trace, logs, profiles, and dependencies into the same perspective, helping them optimize code and service performance more quickly.
Testers
Testers can use observable data to verify interface performance, error rates, resource consumption, and critical path performance before and after release. When problems arise, instead of relying solely on screenshots and verbal descriptions, traces, logs, and environmental information are handed over directly to R&D collaboration.
Operations personnel & SRE
In production environments, operations and SRE can observe hosts, containers, Kubernetes, cloud resources, alerts, and change events through a unified monitoring platform, and determine impact scope and processing priorities based on data.
Business staff
Business teams can understand service quality from application performance, access experience, and business events, such as whether key paths like registration, ordering, payment, and submission are affected by page performance, interface time, or system errors.
How companies build observability platforms
Observability construction usually starts with high-frequency fault scenarios, rather than redoing all monitoring at once. First, unify the data entry points for key systems, then gradually establish object models, alarm closed loops, troubleshooting processes, and review mechanisms.
Clarify the distinction between observability and traditional monitoring, and determine what types of data and platform capabilities the enterprise needs.
Build a unified monitoring platformBring scattered signals from Prometheus, ELK, SkyWalking, cloud monitoring, and business data into a unified context.
Access to APM application performance monitoringIdentify slow requests, error dependencies, and performance bottlenecks from service topology, trace, logs, and profiles.
Access 650+ technology stacksAccess hosts, containers, middleware, databases, cloud services, and custom data through DataKit and tech stack templates.
