Millions of people experienced the frustration and failures of the Obamacare website when it first launched. Because the code for the back end is not open source, the exact technicalities of the initial failings are tricky to determine. Many curious programmers and web designers have had time to examine the open source coding on the front end, however, leading to reasonable conclusions about the nature of the overall difficulties.

Lack of End to End Collaboration
The website was developed with multiple contractors for the front-end and back-end functions. The site also needed to be integrated with insurance companies, IRS servers, Homeland Security servers, and the Department of Veterans Affairs, all of whom had their own legacy systems. The large number of parties involved and the complex nature of the various components naturally complicated the testing and integration of each portion of the project.

The errors displayed, and occasionally the lack thereof, indicated an absence of coordination between the parties developing the separate components. A failed sign up attempt, for instance, often resulted in a page that displayed the header but had no content or failure message. A look at end user requests revealed that the database was unavailable. Clearly, the coding for the front end did not include errors for failures on the back end.

Bloat and the Abundance of Minor Issues
Obviously, numerous bugs were also an issue. The system required users to create passwords that included numbers, for example, but failed to disclose that on the form and in subsequent failure messages, leaving users baffled. In another issue, one of the pages intended to ask users to please wait or call instead, but the message and the phone information were accidentally commented out in the code.

While the front-end design has been cleared of blame for the most serious failures, bloat in the code did contribute to the early difficulties users experienced. The site design was heavy with Javascript and CSS files, and it was peppered with small coding errors that became particularly troublesome when users faced bottlenecks in traffic. Frequent typos throughout the code proved to be an additional embarrassment and were another indication of a troubled development process.

NoSQL Database
The NoSQL database is intended to allow for scalability and flexibility in the architecture of projects that will use it. This made NoSQL a logical choice for the health insurance exchange website. The newness of the technology, however, means personnel with expertise can be elusive. Database-related missteps were more likely the result of a lack of experienced administrators than with the technology itself. The choice of the NoSQL database was thus another complication in the development, but did not itself cause the failures.

Another factor of consequence is that the website was built with both agile and waterfall methodology elements. With agile methods for the front end and the waterfall methodology for the back end, streamlining was naturally going to suffer further difficulties. The disparate contractors, varied methods of software development, and an unrealistically short project time line all contributed to the coding failures of the website.

Like me, I believe most people go about their business never to give a serious thought about their assumed private correspondence when using Gmail to email friends, colleagues and business associates.  As it turns out, your daily banter may not be so private after all.  A recent article in Fortune Magazine, “Judge Rejects Google Deal Over Email Scanning” caught my attention and an immediate thought dominated my curiosity…Google email and scanning scam.  

In essence, the article describes Googles’ agreement to change the way it scans incoming messages so that it no longer reads emails while they are in transit, but only when they are in someone's inbox! So, what exactly does that mean? Judge Koh, a San Francisco federal judge, said she's not so sure about that. Her ruling claims the settlement does not provide an adequate technical explanation of Google's workaround, which involves scanning in-transit emails for security purposes, and then later parsing them for advertising data. The judge also proposed a legal settlement to pay $2.2 million to lawyers, but nothing to consumers.

My interest in this story is not so much about the proposed settlements or the specific details about how Google or any of the web giants settle claims based on vague legal language. It is however, more about the naiveté of myself and perhaps many others that never question how the email scanning process really works. I wonder, do most of us really care that Gmail uses contents of our mail to display targeted ads?

In the ever changing landscape of software programming, it is not surprising that developers and employees have a different set of preferences for desired skills.  However the number one language that developers want to learn according to a survey of developers by technical recruiter, Hacker Rank is Python. This is not a surprise considering that Python has been in demand for several years and programmers tend to really enjoy this language for clear syntax, good OOP support and great shortcuts. Python, named “the language of the year” in 2007 and 2010 in the TIOBE Index and has climbed to #4 status in May of 2018.

According to the study, employers want developers who:

-  Have problem-solving skills, such as the ability to break down large, complex problems.
- Are proficient in their programming language and debugging.
- Can design systems.
- Can optimize performance.
- Have experience in reviewing and testing code.
- Are proficient in database design

Surprisingly, formal education is not the deciding factor when it comes to what companies care about the most. People with computer degrees or certifications on a resume are not necessarily a first choice for hiring managers. Others that have years of experience even if those individuals are partially self-taught in the field stand to be taken seriously in the field.   For those individuals with a passion to learn and master a skill, there are ample opportunities with smaller to mid-sized companies.

Some interesting FAQ’s from the study:

    On average, developers know 4 languages, and they aspire to learn 4 more.
    Younger developers between 18 and 24 plan to learn 6 languages.
    Folks older than 35 only plan to learn and additional 3 languages.
    The top languages developers said they will learn were, Go, Python, Scala, Kotlin, and Ruby.
    There is a large gap between employers seeking developers that know React than there are folks that can do it.

So, Why Learn Python?
It is now the most popular introductory teaching language in U.S. universities.  Python is easy to use, powerful, and versatile, making it a great choice for beginners and experts alike. It allows you to think like a programmer and not waste time understanding difficult syntax that other programming languages can command. And, because of its rapid growth, many developers contribute to the Python community and share Python libraries making creativity that much more a reality

Unless you have a great product, service or idea for which people are willing to wait, chances are highly likely that these potential clients will leave your website should your response time take too long to their incoming requests.  Ignore your application’s performance and you are more likely to be dumped by your users sooner than expected.

To improve the performance of an ASP.Net application you need to optimize your front-end UI (user interface) code as well as the back-end database. You can also think of the following tips as a brief best practices guide for the ASP.net performance optimization. So, whether you are a developer, UI designer or member of the deployment team, the following tips may help you. No matter what’s your role in the project or what you do to boost performance of your application, always remember that your goal should be to:

·          Minimize the amount of data you sent across the network.

·          Reduce the number of server requests.

Here you go (in no particular order)

At Database level