Atomic Talk Title: Performance HaRboR

When it comes to the digital economy, avoiding downtime and measuring the availability, response time, and behaviour of every business transaction is crucial. I have observed that We can improve our execution analysis on the real time.
Instead of people wasting time in trying to put the production fires without the right checks, why don’t we build the right interface to Integrate all our automated performance scripts.
And that monitor’s all the hiccups during execution and helps us to improve computing processes and satisfy our customers.
So what I thought was irrespective of what tool we use for building scripts, we need to integrate that into the execution window. I am having single framework for test planning, scripting execution and analysis . Also it will check details of cloud with respect to application servers and Load generators.

So I call this interface as HaRboR (High-level analysis of response time and Bottleneck identification of Resources)

Open source model describing 4 pillars of HaRboR
1. Digital Experience Monitoring with AI enabled workload monitoring
2. Code Profiling
3. Transaction Tracing
4. Operations Analytics

As businesses go through digital transformations such as cloud migration and container orchestration the risk of app downtime goes up, making application performance management and monitoring is more important than ever.
HaRboR keeps in track of application downtime, detect anomalies, understand trends, optimize resource usage, and troubleshoot performance issues before they impact end users.
Enables us to gather insights that help ensure customer satisfaction and drive business growth.
HaRboR manages the overall performance, starting with code, application dependencies, transaction times, and user experience.
Monitoring is a small – but critical – part of it.
It ensures End-to-End Visibility of Your Application
It points out, typically via alert notifications, that there is a problem.
HaRboR measures – User satisfaction, Response time, Error rates, Number of application instances, Request rates, Application and server, virtual machine, or container CPU usage, Application availability/uptime (SLAs)

Talk Takeaways

• Open source model describing 4 pillars of HaRboR
  1. Digital Experience Monitoring with AI enabled workload monitoring
  2. Code Profiling
  3. Transaction Tracing
  4. Operations Analytics