What is Full-Stack Observability?
Full-stack observability refers to the ability to determine the state of every asset within your IT environment at any point in time. It gives a comprehensive view of your complete IT stack, offering detailed insights into the code level of your applications and the specific endpoints they interact with.
Robust full-stack observability techniques aid in investigation, incident detection, and response while providing crucial insights for proactive enhancements to the security and efficiency of your IT infrastructure. It also provides a unified perspective of your IT environment, regardless of whether it operates on-premises, in the cloud, or a hybrid deployment model.
Benefits of Full-Stack Observability
With full-stack observability, you will be able to unlock new capabilities and optimize core functions of IT, security, and business leadership to give the following real-world benefits:
1. Remove Departmental Barriers
- Full-stack observability facilitates multiple IT, operations, and business teams to gather insights regarding technology performance and how it is affecting their key functions.
- It removes departmental barriers that existed in the traditional model where each department owned only a portion of the hybrid IT infrastructure.
- It optimizes productivity, ensures smoother operations, enhances cost efficiency, and facilitates real-time operational insights throughout the enterprise.
- Full-stack observability improves collaboration, decision-making, and adaptability of your teams across multiple departments from IT to DevOps, finance, and HR, within the evolving environments.
2. Consolidating Tools for Enhanced Efficiency
With full-stack observability, you will be able to consolidate your tools, streamline your operations, and enhance efficiency across multiple departments.
- It offers a unified view of all the critical metrics, which further leads to improved collaboration between IT and business leadership.
- Full-stack observability not only streamlines workflows but also ensures the attainment of business objectives. Consequently, it optimizes efficiency while simultaneously reducing complexity and costs.
- By removing the need to get licensed versions of multiple tools to get every insight into your IT environment, full-stack observability also leads to significant cost savings.
3. Optimizing Observability for DevOps
Full-stack observability helps the DevOps team to focus and monitor only the most critical events. It helps the DevOps team efficiently allocate its time for developing solutions that lead to improved business outcomes.
- It helps in monitoring the performance of applications and data flows in real-time through the data collected from systems across distributed networks.
- Full-stack observability empowers developers to swiftly detect and address performance issues within their code. This is made possible due to the automatic triggering of alerts when applications’ performance deviates from predefined baselines.
- It also helps DevOps teams understand the intricate service dependencies and how performance issues in one area impact performance in other areas. This understanding helps improve the overall customer experience by taking necessary corrective tips to prevent performance degradation.
- Lastly, full-stack observability serves as the centralized hub for visibility and management, and thus becomes the primary driver for app modernization and reduced downtimes.
Full-Stack Observability and AIOps
Full-stack observability has MELT capabilities. MELT capabilities are:
- Metrics: These indicate what is wrong with the system.
- Events: It is responsible for focusing on important alerts while ignoring the unimportant ones. It thus helps with noise suppression and auto resolution.
- Logs: These help in answering what caused the problem.
- Traces: It shows where the problem is.
Full-stack observability provides you with complete visibility and insights into your system; this data can then be loaded into AIOps tools. This will help quickly correlate events and recognize and resolve issues using AI/ML.
Thus, AIOps tools use the data from full-stack observability to swiftly and efficiently remove the problem areas, consequently decreasing the burden on the command center.
This will not only help in achieving your business objectives of reduced cost, enhanced productivity, and efficiency but also contribute to an improved customer experience.