What’s the difference between monitoring, observability and AIOps? Monitoring collects predetermined metrics, logs or traces from individual systems. Observability solutions aggregate and analyse data across individual devices and systems to provide insights into an application, program, network, or multi-layered infrastructure.
With AIOps, you gain all the benefits of end-to end monitoring across systems, the identification of performance faults, and the insights to recommend and even automate remediation actions. AIOps provides a way to encode institutional knowledge into a system that can transcend work done by each individual engineer. By automating correlation, analysis and remediation tasks, VIA AIOps minimizes human error and operational costs while improving efficiency.
If you want to continue a journey to augment, accelerate and automate incident resolution, you need an AIOps platform, not an observability platform.
AIOps adds an additional layer of intelligence beyond monitoring and observability capabilities. Here are some examples of the added intelligence features delivered by VIA Express, a Vitria AIOps solution that are not available in observability platforms.
- Real-time analytics, AI and machine learning deployed in the ingestion, enrichment, and correlation of metrics, events, logs and traces to not only detect anomalies but identify their root cause across service layers
- Generation of a Likely Fix Recommendation utilizing the history of fix/repair data from tickets and other knowledge bases to unleash the hidden knowledge in troves of unstructured data that have been difficult/impossible to leverage in the past
- Integration with existing workflows and tools, leveraging existing work processes to automatically route high-impact issues to the right fix team, reducing resolution time
- Predict and prevent incidents before customer impact using AI- and ML-driven predictive analytics
Orchestration across related systems to notify customer care agents and close tickets
VIA AIOps synthesizes observability data into actionable insights, aligning IT operations with business goals, enabling better decision-making. This addresses an issue that has been around for a long time, identifying an error condition and the impact it has on the service it supports. What seems like a catastrophic error in a monitoring or observability tool, might be only a minor issue in the scheme of a complex service delivered over a network of multiple, redundant containers. AIOps delivers the AI-driven insights that enable IT teams to make faster decisions better aligned to business priorities to identify and automate the response to a problem.
