Products and Platforms
TCS ERP on Cloud
TCS ERP on Cloud for SAP Landscape Migration and Modernization
HIGHLIGHTS
- Organizations use commercial off-the-shelf applications (COTS) or custom applications to run their business operations. Custom apps are developed to meet an organization’s exclusive needs and challenges.
- Custom apps are known for seamless integration, affordability due to eliminated license and maintenance fees, enhanced security through internal data processing, and better scalability; they can integrate with legacy systems more effectively than COTS applications.
- Like COTS applications, custom-made applications must be monitored and managed effectively. Businesses can transform their custom application monitoring with a well-thought-out strategy by following industry-wide best practices.
- Enterprise observability solutions can help IT teams to monitor distributed systems efficiently, identify and fix performance issues while tracing the source of the issue, and break down silos by enabling visibility into the entire application stack.
Overview
Organizations may choose between COTS and custom-made applications to transform into digital enterprises. Custom applications are those developed in-house or by third-party software development vendors. They are generally developed using various programming languages (e.g., C, Java, C#, or Python) and frameworks (e.g., React, Angular, or Laravel).
COTS software may not have all the features that meet specific requirements, while a homegrown application can be tailor-made to suit their unique needs perfectly without compromising functionality or performance. Custom applications also often provide enhanced security measures as data is processed internally within the organization rather than being sent over an external network for processing. Homegrown apps can integrate better with internal systems and legacy systems. While developing an application from scratch may seem costly initially, it might be more affordable in the long run than using licensed software, which has added costs for upgrades, maintenance fees, or support contracts over time.
Need for monitoring
Monitoring and observability are crucial for managing homegrown enterprise software.
- Homegrown systems, while potentially cost-effective initially, often lead to significant operational complexities due to the lack of standardized toolchains typically provided by off-the-shelf solutions.
- Performance degradation can go unnoticed without consistent monitoring and observability practices until it severely impacts user experience or system throughput.
- Without insights into the inner workings, troubleshooting issues becomes a daunting task.
- Resource mismanagement resulting from unmonitored usage can lead to unexpected costs from overusing CPU and memory, especially without prompt adjustment mechanisms or alerts.
- Without insights into user experience, organizations may not be able to identify performance gaps and fail to connect app performance with user experiences and business outcomes.
Hence, custom-made applications need to be monitored to ensure their peak performance. With the help of full-stack observability solutions such as TCS Enterprise Manager, organizations can expect faster issue detection, mean time to detect (MTTD) and resolution, mean time to repair (MTTR), efficient use of resources, better end-user experience, and better security posture.
Best practices
Businesses can transform their custom application monitoring strategy from reactive to proactive, ensuring performance optimization, improved user experience, and business outcomes. Here are some of the best-recommended practices:
- Monitor the entire application health, including the underlying infrastructure health, servers, networking interfaces, databases, etc., using native APIs or third-party tools to identify problems before they impact the user. Establish alerts for critical resource thresholds for metrics to detect issues early, e.g., CPU utilization > 80% or disk space < 10 GB remaining on a shared drive.
- Define the performance metrics by observing the application's operational parameters under stable conditions. Set up a baseline for application behavior and leverage the metrics, events, logs, and traces (MELT) data to detect anomalies. Implement distributed tracing for complex applications with multiple services, which helps track the flow of requests and identify blockages across service boundaries.
- Invest in AI/ML and automation for faster remediation, increased efficiency, and improved operations. AI can automatically detect anomalies, provide actionable insights, integrate all data sources, and trigger automated alerts for potential issues. While streamlining incident response, it can also help in automating remediation without any manual intervention.
- Define custom dashboards or reports tailored to your organization's needs. Use profiling libraries to identify performance bottlenecks and hotspots in code execution paths during development or testing phases, and then optimize the application accordingly using best practices such as caching strategies and query optimization techniques.
- Review monitoring KPIs regularly to align with evolving user needs and business objectives. Log important events and errors throughout the application, ensuring logs are comprehensive but not too verbose to cause log flooding. Collect relevant metrics, such as request counts, response times, and error rates, among others, from various points in the application using lightweight and non-intrusive methods like asynchronous instrumentation or custom libraries to avoid performance impacts.
- Reduce complexity and streamline the monitoring process by eliminating dependency on multiple tools. Invest in an APM solution for full-fledged observability of custom applications, which allows for real-time monitoring, seamless third-party integration, efficient monitoring of distributed systems, identify and fix performance issues while tracing the source of the issue, break down silos by enabling visibility into the entire application stack, and establish correlation and automation at the same time using advanced AI/ML.
Conclusion
By incorporating these strategic monitoring methods as part of the initial development cycle alongside investment into a dedicated APM tool, enterprises can expect not only improved user experiences and system reliability but also significant financial benefits through reduced outage costs with shortened MTTD/MTTR.
