Python is a programming language that lets you work quickly and integrate systems more effectively. No wonder why it showed up as most popular coding language of 2015 in the annual CodeEval’s annual publication where they publish data on the “Most Popular Coding Languages” based on hundreds of thousands of data points we’ve collected by processing over 600,000+ coding tests and challenges by over 2,000+ employers.
However, having a language that is flexible and easy to program is not good enough to delight your customers consuming services from the applications developed using Python language. In the current world, where every business is either a software defined business or working on a plan to become one, the application complexity has exploded. The dependencies of the applications on other applications, middleware, web services, databases and underlying infrastructure have increased dramatically. How the end-users are consuming these applications from web, mobile and now via connected devices & Internet of Things has changed dramatically. Users have no patience for applications with a sub-optimal experience.
In order to deliver exceptional end-user experience and delight your customers, you really need to understand every user interactions starting from end-user clients to application code to 3rd party services/databases and supporting infrastructure.
In this blog, I will discuss five things you can do to delight your customers by delivering exceptional end-user experience from your Python applications.
Get end-to-end visibility into your Python application environment: First of all you need to have a way to understand your application topology and dependencies on other web services, applications, databases and underlying infrastructure. You should be able to correlate various application components so that you can diagnose the root cause of any application issues that can impact end-user experience. You should be able to prioritize application performance issues based on the business impact of the transaction.
Monitor Applications at code-level depth: You need to have a strategy and tools in place to get in-depth application monitoring that allows you to drill down to the application code details visually. You should be able to easily locate hot spots and slow methods within your application code drilling down from the end user experience.
Manage performance of heterogeneous databases in context with your Python Application: In most, if not all, of the cases, your Python application interacts with one or more databases in order to deliver the information or services to your customers. Issues with database query or stored procedures and database optimization issues are some of the top reasons for poor performance performance. You need to have a way to understand how database performance is impacting your overall application.
Monitor end-user experience across the globe: You need to able to able to monitor your mobile and web user experience across the globe in context with your Python application performance so that you can address the issues before their impact the end-users. Once you find out that your end-users are not experiencing optimal performance, you should able to rapidly identify the exact offending line of code in Python application impacting the end-user and address them.
Correlate your Python application performance with underlying infrastructure: Finally, you need to understand infrastructure resource consumption in the context of application performance and end-user experience. After you learn that end-users experience is degrading, you need to understand that the application component causing the problem and then you may need to drill down into the underlying infrastructure in cloud (AWS, Azure, etc.) or on-premise virtual machines, containers, servers, network or storage.
AppDynamics recently introduced the Application Performance Management (APM) solution that addresses all of the above and a lot more for applications developed in Python.
With this new solution, currently under beta, you can monitor your Python applications in real-time, drill down into call stacks, correlate transactions traversing across your distributed environment, and diagnose performance bottlenecks while running in a live production or development environment.
This solution is an integrated part of AppDynamics Application Intelligence Platform that allows you to SEE everything through the lens of business transactions, ACT fast with BizDevOps Collaboration where everyone executes to the same playbook and KNOW the business impact with application analytics.
Learn more at the Python AppDynamics Application Performance Management web page and join the beta program.