Updated: May 04, 2024
A Gartner article Monetising Observable Data Will Separate the Winners and Losers2 published in November 2022 predicts that by 2026, 70% of organisations leveraging observability will attain faster decision-making, giving them a competitive edge in key business or IT areas. The scope of Observability is usually limited to individual components or layers within the entire IT stack. This becomes a challenge when trying to achieve a 360-degree view of the system performance. This makes it difficult for the IT teams to identify the root causes of complex issues or optimise system-wide performance effectively.
FSO comprises several essential technologies and elements that operate in sync to give an exhaustive view of system behaviour across all IT ecosystem components.
Here is a list of all these key components:
Logs: includes all the chronological records of activities or events developed by diverse components within the IT infrastructure, servers, apps, networking devices, and databases. Logs contain valuable information, covering everything from user activities to system operations and security events. Logs analyses assist in detecting, troubleshooting and monitoring system health issues.
Metrics: are measurable performance and health insights of IT systems. These contain memory usage, response times, CPU usage, network traffic, disk Input/Output (I/O), and multiple other key performance indicators (KPIs). These metrics assist with system performance monitoring, trend identification, and resource optimisation.
Traces: consists of transactional records or activities, occurring between multiple services or components within a distributed system. Tracing allows IT teams to keep track of the request or transaction path across diverse containers, microservices, network layers and APIs. Traces are a great way of checking the dependencies, latency issues, and performance blockages across distributed architectures.
Distributed Tracing: can be termed as a digital detective that follows your transactional path as they travel through interconnected components and services amongst a distributed system. It operates through advanced techniques to capture and correlate the trace data from different services, revamping the complete end-to-end transactional flow. IT teams can obtain a visual representation of transactional paths, identify performance stoppages, and update system performance accordingly in complicated distributed environments.
Log Aggregation: produces log storage, collection, and analysis from varied sources into a centralised repository. This unified log aggregation approach helps streamline log management, improves searchability, encourages event correlation, and backs diligent monitoring and troubleshooting actions.
Operating multiple tools in separate silos leads to poor visibility for the team. As a result, the teams often struggle to find answers without a single source reliance. Full-stack observability is a one-stop solution for all these complexities. It helps to attain accurate and real-time feedback from integration or production systems and fix UX and application performance challenges more efficiently. The next possible concern after understanding full-stack observability would be its deployment. With top-notch integrators such as Proactive Data Systems, you can deploy full-stack observability with ease for a collaborative experience.
Amit Arora Head of Marketing
Marketer by day, fiction fanatic by night. Obsessed with the power of storytelling (AI is the wildest plot twist yet). I believe in creating drama through the written word, visuals, and experiences.
