Optimizing User Experience Makes a Huge Difference in Customer Satisfaction

May 13, 2021

Image: Optimizing User Experience Makes a Huge Difference in Customer Satisfaction

With remote shopping and a large range of SaaS services experiencing heavy demand during COVID, the lingering question is whether this will be a fading fad or a new normal. Many businesses have had to optimize or even reinvent their websites and applications to improve performance under new levels of heavy demand. This has driven demand for automatic and precise performance monitoring and an increased demand for rapid problem remediation.

Many issues can impact application performance, leading to a worsening end user experience. This is especially true for modern container-based cloud native applications. As applications have shifted away from Service Oriented Architectures (SOA) connecting a small set of monolithic services to a highly distributed architecture featuring a wide array of microservices, performance monitoring emphasis has shifted from primarily profiling code stacks in dev environments to continuously profiling in production while also observing latency between services and API endpoints.

With microservices and containers, the complexity of monitoring performance has increased significantly, fueled by cloud elasticity, where service instances dynamically expand and contract as needed. With that, a remote call surge can happen at any point in time and can impact application performance, especially if performance issues aren’t detected rapidly.

In order to mitigate some of this complexity, practitioners have turned to Smart Endpoints and Dumb Pipes to reduce the number of remote calls to a more manageable volume. Despite that, the volume of calls is still formidable and comprises the most likely locations where performance issues might occur. Manual observability and profiling, which requires instrumentation and configuration, just can’t keep up with the increased call volume of dynamic cloud applications.

That’s why the performance management focus has expanded to Enterprise Observability. Enterprise Observability combines automated End User Monitoring, Observability, Profiling, and Context to address dynamic, cloud-native requirements. Enterprise Observability automatically measures the most significant factors – infrastructure loading, connection availability, latency, etc. that can impact mobile and browser end user experience.

Important Enterprise Observability factors for End User Monitoring:

  1. Automatically monitor starting at the user interface for all application, web and mobile users
  2. Automatically observe website beacons, JavaScript, page action, application service, endpoint, and perspective errors and show the user interactions and the end-to-end traces associated with them
  3. Automatically display individual user transactions for rapid problem remediation
  4. Automatically correlate context, and drill down to root cause
  5. Automatically profile application and service code to identify performance hotspots

You may have noted a common theme in the list above – Automatically. Automation is not a, but the critical ingredient for delivering consistently outstanding application performance that leads to the best possible end user experience in the Age of Cloud Native.

But, automation alone isn’t enough, To ensure that you don’t miss any anomalies that can impact end user performance, the information you gather needs to be granular and detailed. Enterprise Observability provides rich, granular data – metrics, events, traces, and logs (METL) at no more than 1 second granularity throughout the entire service lifespan. The combination of automation, granular detail, context and analytics embodied in the Six Pillars below are necessary to ensure the health of highly dynamic cloud applications.

The Six Pillars of Enterprise Observability

  1. Automatic and continuous discovery & mapping
  2. Precise high-fidelity visibility
  3. Cloud, container and microservice native
  4. Real-time full stack application data model
  5. AI-assisted monitoring and troubleshooting
  6. Integration into Dev and CI/CD pipelines

Without the full Enterprise Observability capabilities described above, there could be an End User Monitoring visibility gap until the tool catches up with the scale-out. If a container service is only invoked for 30 seconds, for example, those tools could miss observing the container service completely – especially if manual instrumentation or data sampling are involved.

Only anEnterprise Observability platform that provides full automation across all observability and APM capabilities can help you ensure outstanding End User performance for all of your cloud applications to keep your user’s delighted.

Check out our demo for resolving front-end performance issues with Instana.

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Instana, an IBM company, provides an Enterprise Observability Platform with automated application monitoring capabilities to businesses operating complex, modern, cloud-native applications no matter where they reside – on-premises or in public and private clouds, including mobile devices or IBM Z.

Control hybrid modern applications with Instana’s AI-powered discovery of deep contextual dependencies inside hybrid applications. Instana also gives visibility into development pipelines to help enable closed-loop DevOps automation.

This provides actionable feedback needed for clients as they to optimize application performance, enable innovation and mitigate risk, helping Dev+Ops add value and efficiency to software delivery pipelines while meeting their service and business level objectives.

For further information, please visit instana.com.