An interesting exercise that tries to reduce risk of the failure and identify problems early.
The Project Team has been asked to answer couple of questions about the state of the Project. To make it more fair the Team has been split in two groups and each of groups has been asked independently, without knowing the answers of other group.
The result was quite unexpected, the answers where different for almost half of the questions. You can see it on the picture, same questions answered with different colors.
My christmas present, should be enough for couple of months.
Below are list of most usefull food supplements that have proven benefits (I'll add links to exams and proofs later).
Glucosamine Chondroitin MSM - joints support.
Liver detox - herbs extracts for better digestion.
Grape seeds - immune support, antioxidants.
Coenzyme Q10 - cardiovascular system.
Had business trip to Europe for 2 weeks, visited Barcelona, Berlin and Amsterdam.
I'd like share an approach we use at Qubell to ensure quality of our product. A set of practices that allows us to use Acceptance Testing in simple and efficient manner.
Note: this article is my personal opinion and can't be associated with Qubell's official view on the matter in any way.
Let's try to express the test case with plain english first. A little about the product itself
On the screenshot below you can see list of sample applications.
So, as I told in the previous article - the basic version of the Crawler worked well and proved to be usable. The problem - it was slow and unstable.
To make it fast we need to run it on multiple machines (about 5 - 20). And to make it stable we need to figure out how to make reliable system from unreliable components.
Multiple machines instead of just one make things a bit complex because couple issues arise:
Usually crawlers browse site pages, collect HTML from it, parse and extract some data.
Best feature of MongoDB is not it's performance but simple and flexible data model. So, let's say you build prototype - you concentrate on the big picture - the product itself and ignore little things like performance and db indexes.
Later you deploy your product into the wild users came and it starting to get slow. You need to add indexes, to do so you need to know data usage patterns. Doing it manually by searching codebase is boring and not very productive. Thankfully MongoDB has Profiler - all you need is to enable it and it will give you all details about slow queries and what indexes you need to add.
I like this approach very much, because it fits iterative & lean development very well - you always concentrate on the most important things at the moment. At the first step most important thing is to experiment with the product and features without being distracted by performance issues. And flexible data model of MongoDB comes very handy to that. Later you deploy product into production and can use its Profiler to zoom to more fine grained performance details.
I wanted to see benchmark that more or less close to real life, not just measuring how fast it can stream data via http.
So I created application that query some text from remote HTTP service (service delays each request for 200ms) and render HTML page using that text.
It simulates how Web Framework performs when it needs to wait for response from DB or other services, how fast its templating engine is and also how fast it is itself.
And hit it with
wrk -t2 -c100 -d10s http://localhost:3000 you can see results
on the picture.
3782 vs. 2914 hits, average response time is also very close.
We decided to spend one evening prototyping very simple and small but unusual thing for our product.
I choose to build very basic mobile prototype. Actually our app is already responsive and can work on mobile devices, but it doesn't looks very good. I wanted it looks like a native application.
How can we decide if medicine is good or bad? About couple of years ago I found very interesting statistics, but only recently had time to investigate it in details.
Countries with people having the longest life
So, we can roughly guess that if lifespan is big, then the medicine should be probably good too. Also, as soon as lifespan is also affected by lots of other variables like - climate, food, ecology, lifestyle, income and so on - we can decide that they are probably good too.
But, the fact that lifespan is a sum of many variables has a drawbacks:
I've read CouchDB Guide for the second time recently. Very interesting book, it's interesting to understand how CouchDB works internally, one of those rare books that creates a mind shift and expand it to the new territory. It's definitely worth the time spent even if I never will be using CouchDB.
Had a quick look at Node.js usage in production.
In most cases Node.js isn't used as a web framework for the core web product. It's used for additional specialized API or real-time extensions.
From my subjective experience with Node.js web frameworks - it's about the level of Ruby Sinatra. None of node.js web frameworks even closely compared to Ruby on Rails. Nor in terms of functionality nor in development productivity.
So, it seems for me that Node.js isn't suitable for general web development. It's a good fit for API, but not for web site or web applications (online project management and so on.).
And that's sad news, because I believe it has all features needed to build rich and high productive web framework like Ruby on Rails (Fibers can be used to mitigate callbacks).
Still, even if productivity with Node.js is less than with Ruby on Rails it's better than with Java web frameworks.
As I said before:
I believe Node.js has all features needed to build rich and high productive web framework like Ruby on Rails
So, here it is - http://monojs.org
In order to be able to sell the product it should do something useful and be in a working state. The only practically way to check if product works or not - is to check it according to the specification.
That's why product specification is important - it defines the goal, what the product should be and how to check if it works or not (it also helps to measure progress - how close current state to the goal).
Process of measuring how close the product to the specification and if it's working called testing, there are manual and automatic tests.
There's very huge difference between manual and automatic testing:
That difference dictates when and how apply manual or automatic testing.
These days lots of data available in digital form, ability to analyze and get meaning from that data become more important. Usually such job is called Data Analysis or Data Mining and the person who does that is called Data Analyst.
Actually, I wrote that article for my brother (who's Analyst and ask me about SQL) and decided to publish it because it may be also useful for others.
Main skills of Analyst are Mathematics, Statistics and Domain expertise. But in order to apply those skills he should be able to get the data itself. Widely supported way to get access to data is called SQL, and Analyst can benefit greatly if it knows basics of it.
SQL is a declarative language for querying and transforming data stored in relational database.