Businesses have been focusing on digital experience for years. However, brands are increasingly expanding their priority beyond digital journeys and architectures to more carefully monitor website and app performance. An enjoyable customer experience requires reliable app/website availability and responsive performance. However, monitoring CPU/memory performance or tracking patterns on system availability and response time is often not sufficient to ensure a strong customer experience. Rather than focusing on symptoms, brands need to go deeper to understand the pulse of their internal IT systems and determine the root cause of problems. This in-depth analysis will help companies move toward zero downtime. Zero downtime, in turn, will positively impact every digital experience.
The Path to Observability
Most monitoring solutions in the market focus on configuring thresholds around the empirical metrics, looking for patterns and spikes. In the case of a breakdown, these systems send alerts and notify relevant stakeholders. Business stakeholders may think they have visibility into core IT processes, but the chosen set of empirical metrics may not tell the full story or capture all of the relevant key performance indicators, which will hamper data-driven decision-making.
Observability is about stitching a credible story about business and information system dependencies – from your business logic to your infrastructure – to achieve useable insights that eliminate downtime. With a strong observability program, organizations can prioritize business needs based on historical data, set automated baselines for business metrics, and monitor adherence to those metrics in real time.
Challenges to Achieve Observability
Observability is not an option; it is necessary in today’s business climate. However, achieving observability is not easy. For instance, monitoring microservices and containers in a multi-cloud or hybrid-cloud environment often causes compatibility issues. Various data sources and multiple information formats require different platform teams to collaborate. This will drive effort and cost up.
Some of the common challenges to implementing observability are:
- Manual and siloed monitoring with multiple tools leading to cluttered business process insights.
- No visibility on domain-specific business KPIs via IT metrics.
- No single source of truth, no single view, and low visibility into key business KPIs.
- Long war room discussions during critical service breakdown, leading to team burnout.
- Low adoption of industry-standard best practices to predict, recommend, and self-heal or auto-remediate incidents.
To drive operational efficiency and provide end-to-end visibility across technology (including application, data, and infrastructure) requires observability adoption across the organization. This adoption will depend on upskilled talent that can adapt to the latest tools and technology.
Unified dashboards also put organizations on a path to zero downtime in business operations. Enabling full-stack monitoring across the enterprise is a way to derive the best business value from investments in technology.
How Does Observability Help Business?
Insights on the key performance indicators in real-time are key to making data-driven decisions. For example, in a supply chain business process, the service owner might need to know the order fulfilment status, and the operations manager might need to monitor the live shipment status. Observability ensures that applications are closely monitored and provides comprehensive insights into proactive actions that can minimize application-related disruptions to business processes. Analysing historical data, meanwhile, empowers businesses to learn patterns and identify trends that trigger continuous improvement in business performance.
Best Practices and Recommendations
In today’s world, data is king. To deliver a seamless user experience, business or service owners need to focus on the customer’s needs before instituting major changes that impact their business. A fabric of consolidated databases, powered by AI, plays a pivotal role in identifying the patterns in customer behaviour and providing actionable insights to define achievable business targets.
Moreover, a unified dashboard with an end-to-end view of the business (including IT dependencies related to apps, infrastructure, databases, networks, etc.) also empowers businesses to thrive in a competitive environment.
A robust observability solution also includes the following Site Reliability Engineering (SRE) functions:
- Streamlined ways of measuring and tracking site reliable engineering (SRE) metrics like SLOs and SLIs.
- Capacity planning, proactive monitoring, and optimized application-level monitoring.
- Automated daily health checks based on custom dashboards and health rules.
- Reduced application onboarding time.
- Embedded GenAI capabilities in observability tools for anomaly detection, prediction, and event correlation.
- Banking: Mortgage application approval rate, commercial loan application processing cycle time, total volume of consumer loan applications.
- Supply Chain: On-time delivery supplier rate, undamaged supplier shipment rate, percentage of backorder liens, total inventory volume.
- Healthcare/Medicare: Claim first pass resolution rate, % of claims requiring manual resolution, % of claims completed within 15 days, total handle time by call reason.
Observability is the epicenter of business resilience. When it comes to observability, the road to success is always under construction, but no observability program can succeed without first aligning the right data. Increasingly, observability will also leverage AI as observability products meet core GenAI capabilities. As these capabilities mature, more and more businesses will find that zero downtime is well within reach.
