Splunk Observability Cloud's monitoring has significantly changed our day-to-day operations and decision-making, especially in drone operation and its monitoring, which is heavily dependent on real-time data insights and technological interventions. Many decisions must be made quickly and in a scalable manner, achievable only through a unified platform that delivers all these aspects. We are currently using several metrics to measure outcomes in terms of increased production efficiency and improved operating efficiency, along with insights into activities undertaken by farmers or data monitoring teams, all of which provide us with a transparent system within the ecosystem. Troubleshooting these issues helps our farmers and engineers prevent performance problems and downtimes. The core capabilities provided by Splunk Observability Cloud application platform have been well-documented, and it is crucial to note that there are no lapses or sampling errors in our organization's performance monitoring. We achieve 100% accuracy when monitoring application performance and providing data dashboards to our senior management. We have never missed a trace while analyzing transactions across different services offered to farmers. Infrastructure monitoring is equally vital for us, given our multiple servers and multi-cloud environments where various agricultural applications operate simultaneously and data flows seamlessly. All of this has only been possible because of Splunk Observability Cloud. Our digital enhancement experience has improved multifold, especially with the introduction of AI-powered insights over the past two to three years, allowing for pinpoint guidance in detecting anomalies, identifying root causes, and significantly reducing alert fatigue while enhancing overall efficiency. The best features of Splunk Observability Cloud include full-stack application monitoring, which is very easy to navigate. The platform consistently demonstrates no performance downtime, even on weekends, which bolsters our client's trust and confidence. Predictive analytics powered by AI insights provide us with real-time data matrices and insights, significantly improving our customer experiences and accelerating innovation. Identifying potential threats and issues, such as root causes, has become very straightforward, leading to our immense satisfaction and gratitude towards their responsive business team. Their multidimensional features provide unified security and substantially enhance visibility, which perfectly aligns with the concept of observability. One standout feature is full fidelity monitoring and proactive troubleshooting, especially with approximately twenty to twenty-five applications concurrently used across multi-cloud environments, managing data transfers and inputs efficiently. I recommend that more flexibility be included in launching applications and features. The database standard integration is incredibly beneficial, as is checking each data layer in a full-stack environment, something which Splunk Observability Cloud handles excellently. Splunk Observability Cloud positively impacts our organization by significantly increasing overall visibility and observability experiences for the entire team through numerous newly introduced features. Previously, we lacked visibility into query logs, but now we can track and trace these logs effectively for problem identification and troubleshooting. As a result, the reoccurrence of similar issues has dramatically decreased. We now have structured logs and tracking that are amazing, and the user experience, especially for our clients—primarily farmers using less developed Android phones—is vastly improved. The application performance monitoring criteria make navigating the platform easy and clear, allowing us to perform hygiene practices for coding. Our on-premises deployment has proven advantageous in monitoring the health of our cloud environment, and we are recommending this to others. The scalability as we have grown from three to twenty-five platforms has been seamless; our system hasn't crashed, indicating stability. The metrics from utilizing Splunk Observability Cloud clearly show improvement, especially in downtime reduction. Previously, we faced a systematic performance lag of around twenty to thirty percent, which has now reduced to just two to five percent—an improvement we can credibly showcase to our clientele. We now collect and track traces, query logs, and session data effectively, providing us with credible, quantifiable metrics for assessing business enhancements and current operational stages. Real-time visibility and data fetching for dashboards is an extraordinary addition that distinguishes our experience. There are several performance enhancement areas for Splunk Observability Cloud. For instance, Splunk Observability Cloud's IT service intelligence core part needs improvements as clients request more IT services performance matrices than the current system supports. Certain matrices are still unnoticed, creating false alarms that require enhancement. We previously used Datadog and other AWS observability solutions that were quite affordable. Currently, smaller businesses struggle to reap the benefits. UI navigation is easy but could use polishing for a better experience. Integration issues arise with some services taking longer than expected to connect properly, which is an area for improvement. An area needing improvement is the AI-driven anomaly and issue detection system, which occasionally generates many false alarms that consume our time. We also face challenges with metrics not communicating across different measurement platforms, which requires addressing regarding log-specific queries. Additionally, I suggest extending the trial period beyond thirty days to forty-five or sixty days, allowing more time for our team to understand the software's functionalities and business use cases.
