ServiceOps Needs Observability Data Plus Human Insight
IT teams must keep pace as enterprise environments grow exponentially more complex. ServiceOps — short for service operations — offers a potential solution with a technology-enabled approach for frictionless collaboration between IT service management (ITSM) and IT operations (ITOps).
By unifying ITSM and ITOps, ServiceOps enables these teams to collaborate effectively to meet key IT priorities, including improved employee productivity, higher service availability and reduced operational costs. But to achieve these goals, ServiceOps requires a critical, difficult-to-achieve component: full context.
Unlocking the Potential of ServiceOps
Fragmented tools and systems, siloed workflows and inconsistent manual processes pose continual challenges for enterprise IT operations. Despite pouring millions of dollars each year into observability and ITSM solutions, teams still face the headaches of alert fatigue, reactive incident response and persistent outages.
By enabling seamless collaboration between ITSM and ITOps, ServiceOps can break down the operational and data silos that waste time and energy. When IT teams can streamline cross-functional efficiencies, the impact is wide-ranging, overwhelmingly positive and transformative.
Enterprise Management Associates (EMA) recently surveyed more than 400 global IT leaders to assess their organizations’ progress toward a ServiceOps model of IT service delivery. Their research found that service agents and ITOps engineers report significant productivity improvements: They can do more with the same level of staff. Team morale improves, thanks to a less stressful work environment. The benefits extend beyond service and operations to security, DevOps, end-user management and other teams.
Since ServiceOps leverages existing investments in technology stacks, implementing ServiceOps is often a natural outgrowth of initiatives already underway in most organizations, especially automation, AI, machine learning (ML), AI operations (AIOps) and cross-functional workflows.
To achieve the goals of ServiceOps, teams and systems require streamlined access to relevant institutional and historical information — in other words, context. However, achieving full context has been historically difficult. Too often, gathering and implementing the necessary contextual data is a lengthy, complex and burdensome process. Teams need easy access to institutional knowledge to drive productivity and operational efficiency. By leveraging advanced AI to correlate contextual data from across the IT infrastructure, full-context operations enables ServiceOps to deliver its ultimate goals and outcomes.
Full-Context Operations Enable ServiceOps
Context is a key to unlocking effective ServiceOps. By combining observability and other machine-generated data with historical, expert and institutional knowledge, full-context operations provide IT teams with the insights to support efficient incident management.
Full-context operations use AIOps to ingest, correlate and normalize complex data from across the IT infrastructure, and enrich it with contextual information. This gives ITOps and ITSM teams a unified picture of the IT environment, eliminating unnecessary noise and facilitating operator efficiency, consistent data and scalability, paving the way for effective ServiceOps.
According to EMA’s incident management report, full-context operations affect many of the top improvements and goals that EMA identified for ITSM teams in the near future:
- Automated cross-departmental workflows (34%)
- Better processes for interaction with other teams (33%)
- Automated ticket triage and routing, problem resolution suggestions and actions (30%)
Context enables positive outcomes from ServiceOps: improved collaboration, quick access to data to resolve incidents and reduced mean time to resolution (MTTR). When teams have context across all data sources and tools, they can use more advanced upgrades like automated workflows.
Platforms that enable full-context operations deliver the data, insights and processes to make every stage of incident management for cross-functional teams faster, more consistent and sustainable. With the full context of every incident available, each team responsible for incident management has the data to act quickly, reduce unnecessary escalations and increase efficiency.
For example, imagine that an organization experiences an outage due to a sudden traffic surge. ITOps teams typically spend hours sifting through disparate tools, troves of historical tickets and post-mortems, and siloed domain sources to gather the correct information. With full-context operations, teams instantly receive enriched alert data powered by GenAI insights. With the right contextual information — including issue history, change data and other maintenance knowledge — teams can quickly identify the root cause and resolve incidents.
The impact will be tangible and impactful for the ITOps industry. Full-context operations with platforms like BigPanda help ServiceOps meet top IT priorities, including higher productivity, faster time to find and fix problems (MTTD and MTTR), and easier team engagement and collaboration. Instead of being slowed by the inefficiencies of the IT ecosystem, ServiceOps teams can rely on full-context operations to focus their energy on what matters: digital transformation and innovation.
