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Strategic Investor Relations for Technology Companies

Need for the PADS Framework Emerges

network complexity

This post is an excerpt of our new report “The PADS Framework for Application Performance and User Experience”.  You can download the free report here.

The PADS (Performance Analytics and Decision Support) Framework is a more strategic approach to linking next-generation performance management and big data analytics technologies.  It establishes best practices for assuring user experience, reducing risk and improving decision making.  The Framework provides real-time intelligence that enables companies to build customer satisfaction and loyalty, and improve operational efficiency.

The PADS Framework cuts through increased complexity to better understand the properties of system components and their place in the overall application delivery chain.  It does this through a higher-level assessment of their relationships to each other as well as to the wider system and environment.

The PADS Framework promotes DevOps practices for improved application governance by breaking down IT and business unit data silos.  It facilitates collaboration and communication in a more productive and cost efficient environment by consolidating multiple functions often performed separately.

Holistically integrated platforms work in concert, as application performance management (APM) data and operational analytics provides physical and logical knowledge of the computing environment to allow for more powerful and granular data queries, discovery and manipulation.  By correlating real-time streams of machine data and other types of big data with the historical data contained in legacy systems, the platform allows users to gain a more complete perspective.  Modeling and mapping capabilities enable faster drill-down and mean time to resolution.

A New Approach to User Experience for New Computing Architectures

New distributed computing architectures and approaches to agile application development have made computing far more scalable and dynamic than ever before.  They leverage shared services and cloud infrastructure to create loosely coupled and asynchronous applications.

DevOps practices promise to drive meaningful ROI for organizations consolidating infrastructure, migrating to cloud-based services or developing Web and mobile applications.  Yet the more business processes come to depend on multiple applications and the underlying infrastructure, the more susceptible they are to performance degradation.

Performance has historically been measured at the individual component or system level, such as a network device or connection, a firewall or load balancer, a database or a web application server.  As environments become more complex, the sum-of-the-parts approach does not accurately reflect true user experience.

Analyzing or mitigating risk in only one component of the system does not prevent disastrous events or failures.  In fact, they can be amplified, as one component affects another and then another, spreading risk throughout the system.

More enterprises have recognized the need for a new generation of performance analytics techniques that go beyond the scope of traditional monitoring tools, which were designed for smaller and more static environments.  Widespread adoption of virtualization technologies and associated virtual machine migration, balancing between public, hybrid and private cloud environments, and the traffic explosion of latency-sensitive applications such as market data, streaming video and voice-over-IP necessitates a new approach.

Leveraging gains in processing power and storage capacity, IT teams can extract and analyze more performance-related data points across the application delivery chain to gain deeper intelligence.  They can understand what levels of performance (i.e. speed and availability) are needed from their cloud and mobile applications in order to deliver fast, reliable and highly satisfying end-user experiences.

Aiming for Better Application Governance

Understanding key fundamental business drivers and working in concert with application owners – and each other – IT teams can meet end-user performance expectations to enable strategic initiatives and positively impact financial results.  Optimizing performance allows IT to evolve toward a process-oriented service delivery philosophy.  In doing so, IT also aligns more closely with strategic initiatives of an increasingly data-driven enterprise.  This is all the more important as big data sources and applications become integral to decision-making.

Through a unified approach, IT can help their companies leverage technology investments to discover, interpret and respond to the myriad events that impact their operations, security, compliance and competitiveness.  Teams that have adopted a unified approach use 30% fewer tools yet experience far fewer service interruptions, discover performance problems proactively and typically spend a fraction of the time on problem resolution than most of their peers who either have too many tools or none at all.

A clear linkage has emerged with how improvements in user experiences are driving financial benefits.  But in order to realize the benefits of engaged employees and satisfied customers, application performance must been stellar – consistently.

Get the free download here.