In cloud computing, observability refers to the use of software tools and techniques to collect, correlate and analyze performance data from a distributed application and its underlying infrastructure. This information is then used to monitor, troubleshoot and debug the application, with the goal of meeting customer experience expectations, service level agreements and other business requirements.
Cloud observability provides the tools and insights necessary to see the inner workings of Cloud Native distributed systems. As systems increase in complexity, we rely more on data such as logs, metrics, and traces to understand what is happening. Using tools specifically designed for multicloud environments will make harnessing the full potential of your multicloud infrastructure a seamless and empowering experience.
Cloud observability in cloud-native environments is all about gaining deep insights into the performance and health of applications and systems running in the cloud. It works by collecting data from various sources such as logs, metrics, traces, and events. Logs provide records of events and activities, metrics offer numeric measurements of system performance, traces enable end-to-end tracing of requests in microservices architectures, and events notify about important occurrences.
This data is collected, stored, and analyzed using purpose-built tools and services. Cloud providers often offer observability solutions, like Amazon CloudWatch, Azure Monitor, and Google Cloud Monitoring, that seamlessly integrate with their platforms. Observability enables engineers to create dashboards and reports for visualizing system behavior. It also allows for setting up alerts to notify teams when specific conditions or anomalies occur. This is essential for rapid issue resolution. When problems do arise, observability data helps in root cause analysis. Engineers can trace back through logs, metrics, and traces to pinpoint the exact cause of an issue, whether it's in application code, infrastructure, or dependencies. Continuous monitoring and refinement are key in cloud observability, as it provides ongoing insights for architectural changes, optimizations, and capacity planning. In essence, cloud observability ensures that your cloud-native applications run smoothly, perform well, and deliver a great user experience while facilitating efficient troubleshooting and improvement.
Cloud Monitoring primarily focuses on tracking and measuring key performance indicators (KPIs) and the health of infrastructure and services. It relies on predefined, preplanned metrics and thresholds to generate alerts when predefined conditions are met. This approach is more about answering the already known questions. It provides a basic level of visibility and can detect known issues, but may miss problems at a deeper, non-superficial level
Cloud Observability is a more comprehensive and proactive approach. It involves collecting and analyzing a broader set of data, including logs, metrics, traces, and events. Observability aims to answer not just if something is working but why it might not be working optimally. It provides deeper insights into the behavior of systems, making it easier to troubleshoot complex issues, trace the root causes of problems, and gain a holistic understanding of system performance. Observability is especially valuable in dynamic, cloud-native environments where traditional monitoring may fall short.
Cloud monitoring tackles the "known problems" where Cloud observability covers issues that may be underlying, and under the surface.
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