Insights from Logs, Metrics, and Traces >
1. Getting Started with vuSmartMaps™
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9. Monitoring and Managing vuSmartMaps™
This section discusses the fundamental pillars of observability: Logs, Metrics, and Traces, demonstrating how they empower end-customers to gain valuable insights for issue resolution and identification. We’ll delve into the specific ways vuSmartMaps™ uses these components to provide a comprehensive understanding of system behavior. By spotlighting real-world use cases, we’ll demonstrate the practical value that vuSmartMaps brings to organizations to enhance their observability capabilities.
Logs serve as the primary source of truth for contextualized actionable insights when seamlessly integrated into vuSmartMaps, allowing precise navigation through typical logs, syntax intricacies, semantics, and session states. Once ingested, vuSmartMaps delves deep into various log types, extracting meaningful information to diagnose issues and optimize system performance. The extraction of syntax and semantics transforms logs, enhancing observability and ensuring seamless performance.
Logs are integral to deriving performance insights and storytelling in the context of transaction flow and the application architecture. Improved telemetry and advanced observability use diverse logs, offering insights that significantly impact customer experiences and align business, technology, and operations teams. Observability platform vuSmartMaps, with its ability to ingest diverse logs, tackle data quality gaps and dispersion through correlation, contextualization, and insights. Effective logging practices, including structured logging and unique identifiers, enhance traceability, enabling pinpointing issues and optimizing system performance. The journey towards enhanced telemetry and observability, though challenging, is substantially rewarding, ensuring data tells a compelling narrative aligned with business objectives.
Use Case: In a financial institution, a payment transaction fails. vuSmartMaps analyzes transaction-specific logs, including payment gateway logs and transaction processing logs comprehensively. This detailed examination reveals the exact touchpoint, such as the payment gateway or the core banking system, where the failure occurred. This level of specific insights allows for swift intervention and resolution, significantly reducing the mean time to resolve (MTTR) for payment transaction issues by up to 30%.
Metrics form the quantitative backbone of vuSmartMaps’ observability approach, empowering organizations to gain insights into infrastructure performance. The platform seamlessly ingests data through observability sources, supporting a diverse range of network devices such as routers, switches, firewalls, and more from multiple OEMs. This yields a rich collection of Key Performance Indicator (KPI) metrics, offering in-depth visibility into infrastructure performance and availability.
vuSmartMaps covers a spectrum of infrastructure components, including servers, middleware, JVM, databases, and storage, providing comprehensive insights through the consistent collection of KPI metrics. Furthermore, vuSmartMaps supports a wide array of databases, including MySQL, MSSQL, Oracle, PostgreSQL, and various NoSQL databases, ensuring a unified approach to analyzing and observing complex infrastructure components.
Differentiating across availability, performance, and configuration metrics, vuSmartMaps provides a deep understanding of an organization’s technological complexities. Availability metrics give visibility into the system’s operational status, performance metrics delve into the efficiency of operations, and configuration metrics offer insights into the setup and arrangement of infrastructure components. These metrics empower organizations to tailor their observability to specific needs and challenges, fostering a proactive and informed operational environment.
Use Case: A cloud-based service provider experiences sudden spikes in network traffic. With metrics, vuSmartMaps reveals the network device experiencing bottlenecks, allowing the team to adjust resources dynamically. It leads to a remarkable 20% reduction in the time required to identify and address network bottlenecks and also results in substantial cost savings for the cloud service provider.
Traces play a pivotal role in elevating application observability within the robust framework of vuSmartMaps. Harnessing tracing libraries tailored for popular programming languages (Java, NodeJS, Go, and .NET), collects trace data essential for both infrastructure and application observability. Traces, especially when focusing on the crucial RED metrics – Request Rate, Error Rate, and Duration (Latency), augment application observability within the vuSmartMaps framework. Tailored tracing libraries for popular programming languages ensure the collection of vital trace data essential for both infrastructure and application observability.
The integration of automatic topology mapping further enhances the efficiency of the observability process, reducing Mean Time To Detect (MTTD) and Mean Time To Resolution (MTTR). Transaction visibility with traces and logs facilitates Root Cause Analysis (RCA) for intricate application scenarios. In the nuanced landscape of application performance, vuSmartMaps relies on traces to provide detailed analysis of slow and error transactions. This feature becomes instrumental in the swift identification, taking only seconds, and resolution, achievable within minutes, of performance issues, proactively ensuring optimal user experiences.
The APM component of vuSmartMaps conducts a deep analysis of application errors. By presenting error stack traces, APM delivers a comprehensive report of active stack frames at the point of error occurrence, simplifying the often intricate task of pinpointing the cause of errors with the help of flame graph. vuSmartMaps APM identifies issues and enhances overall application observability in digital ecosystems.
Use Cases:
With the amalgamation of Logs, Metrics, and Traces, vuSmartMaps achieves unified observability. The platform provides comprehensive visibility, enabling data-driven decisions. The business journey observability platform unifies the cloud, infrastructure, logs, traces, and transactions with advanced capabilities to understand transaction sessions and micro-transaction states.
vuSmartMaps offers comprehensive observability for computing, network, storage, and cloud, enhanced with event correlation, enrichments, and richer data mining for faster root cause analysis (a speed increase of ~50%, translates into substantial cost savings). The log analytics of vuSmartMaps serve as a powerful resource. Acting as a log aggregator, it enables analytics, anomaly identification, and prediction of potential issues.
These Logs, Metrics, and Traces ultimately transform into insightful information for end-customers through visualizing interactive dashboards, configurable alerts, and analytical reports. The combination of these elements ensures a robust and holistic observability framework, facilitating proactive issue resolution and informed decision-making.
As we uncover the transformative capabilities of Logs, Metrics, and Traces within vuSmartMaps, we invite you to explore complementary domains through our featured blogs. Dive into the world of advanced log analytics for middleware, where compliance and operational efficiency are boosted through sophisticated log analytics. Explore how vuSmartMaps streamlines lending operations, offering real-time insights for faster, smarter loan processing. Embrace the future of trading with insights on navigating SEBI’s LAMA Framework. These use cases provide a unique perspective on vuSmartMaps’ role in optimizing observability, tailored to the specific challenges.
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VuNet’s Business-Centric Observability platform, vuSmartMaps™ seamlessly links IT performance to business metrics and business journey performance. It empowers SRE and IT Ops teams to improve service success rates and transaction response times, while simultaneously providing business teams with critical, real-time insights. This enables faster incident detection and response.