Over the years, as companies have moved from monolith to cloud-native architectures, maintaining high availability has become more challenging. After all, today’s IT ecosystems are complex, distributed and ephemeral, making it increasingly difficult (and, in many cases, downright impossible) for DevOps practitioners and SREs to identify and fix issues manually.
To help these teams monitor performance and manage incidents in these ever-complex IT infrastructures, vendors have introduced different types of point solutions:
- Monitoring: Monitoring solutions collect raw data indicating how well (or how poorly) a system or component is performing. Typically this is in the form of metrics, events, and logs.
- Observability: Observability tools help IT teams gain a more complete view across their systems and monitor the flow of data and requests through services.
- Incident management: Incident management software orchestrates the process for restoring a system to normal operation through notification, triage, escalation, resolution, and documentation.
How AIOps optimizes point solutions
Monitoring, observability and incident management point solutions bring particular expertise to their specific domain. In other words, they typically solve one problem in the incident lifecycle extremely well.
But there’s a problem: point solutions lack connectivity. They only provide siloed data that can leave significant gaps in understanding a system’s overall performance. Further, disparate solutions naturally create inefficiencies — multiplying the number of places an incident can live and failing to link issues that are often system-wide.
With operations and SREs under pressure to ensure the availability of complex IT ecosystems, teams need more sophisticated insights than narrowly-focused point solutions can provide. They need robust tools that enable continuous insights across an entire IT stack.
Enter artificial intelligence for IT Operations (AIOps). Domain-agnostic AIOps platforms are purpose-built to connect monitoring, observability and incident management tools and provide teams with a comprehensive solution to achieving availability.
By acting as the connective tissue between point solutions, AIOps technology analyzes and adds value to massive amounts of data across otherwise siloed tech stacks. By converging all systems and ingesting various types of data, AIOps tools give DevOps and SRE teams:
- One summary dashboard: Domain-agnostic AIOps solutions ingest all types of monitoring data and condense this information into a single, visual representation of system health.
- One place for incident lifecycle collaboration: An AIOps platform serves as the single location for teams to work together on resolving complex, multiservice incidents. The technology gives DevOps and SRE teams full visibility into the incident timeline from detection, notification and resolution.
- Apply system-wide intelligence: Connecting monitoring solutions with an AIOps solution allows teams to apply intelligence across their integrated tool stack. The technology adds key context to data, enabling DevOps and SRE teams to understand interdependencies and relationships. And its alert correlation helps make connections between data from multiple sources so teams can identify root causes faster.
In short, an advanced AIOps platform enables teams to see and understand everything necessary for them to ensure the top performance of their digital apps and services. And this holistic approach to monitoring and incident management produces significant results. With the full picture of system health and a streamlined incident workflow, DevOps and SRE teams can reduce mean time to resolution (MTTR) and build time back into their days to focus on more fulfilling, value-adding initiatives.
Of course, there’s a caveat. If an AIOps tool covers all domains, it will ingest a tremendous amount of data. Accordingly, it must be engineered to scale. The requirement for robust engineering is why most AIOps vendors do not actually provide insights across an entire IT stack.
But Moogsoft is not like most AIOps vendors. Moogsoft’s founders built their platform with convergence and scale in mind, allowing for true connectivity across all metrics data.