Month: March 2019

Machine Learning using TensorFlow and PyCharm Series: Part 1: Setting up environment and writing our first TensorFlow program

TensorFlow is an open source computation framework for building machine learning models. Its design make use of lessons learnt from earlier machine learning frameworks — Torch, Theano, Caffe, and Keras. Torch is the earliest machine learning framework that made of the term Tensor. Theano makes use of Graph data structure to store operations and compile them to high-performance code. Caffe is a high performance framework written in C++ and makes feasible to execute applications on different devices. Keras provides an easy to use API to interface with various machine learning frameworks like Theano.

Continue reading “Machine Learning using TensorFlow and PyCharm Series: Part 1: Setting up environment and writing our first TensorFlow program”

Eclipse Memory Analyzer: Solution to Use the -data parameter Exception

If you launch Eclipse MAT and get following error

java.lang.IllegalStateException: The platform metadata area could not be written: /private/var/folders/9q/zhpkyd3s4y9d5t1nv_5hszww0000gp/T/AppTranslocation/DF264CA5-4EEF-4916-A3FA-881B111294E5/d/mat.app/Contents/MacOS/work/.metadata.  By default the platform writes its content
under the current working directory when the platform is launched.  Use the -data parameter to
specify a different content area for the platform.

Then you should open the MemoryAnalyzer.ini in your favorite editor and add the -data argument as shown below.

The location of MemoryAnalyzer.ini depends on your platform. If you are using Mac, then it is inside the app folder like mat.app/Contents/Eclipse/MemoryAnalyzer.ini

-startup
../Eclipse/plugins/org.eclipse.equinox.launcher_1.5.0.v20180512-1130.jar
-data
/Users/shekhargulati/dev/tmp/mat
--launcher.library
../Eclipse/plugins/org.eclipse.equinox.launcher.cocoa.macosx.x86_64_1.1.700.v20180518-1200
-vmargs
-Xmx4096m
-Dorg.eclipse.swt.internal.carbon.smallFonts
-XstartOnFirstThread

Markov chains in Java: Suggest what Narendra Modi will say using Markov chains

Recently, I read an article[1] on Markov chains. In the post, author showed how we can build autocomplete functionality using them. The article piqued my interest to learn more about Markov chain and I started looking for an example application that I can build using it. I decided to build a web application that will suggest me what Indian prime minister Narendra Modi[2] will say after a word/pair of words/triplet for words.

I am not a supporter of Narendra Modi style of leadership. The reason I chose him is because I could easily find text of all his speeches on the web [3].

This post is divided into three sections:

  1. What is Markov chain?
  2. Create dataset for the application
  3. Build the application that uses Markov chain

Continue reading “Markov chains in Java: Suggest what Narendra Modi will say using Markov chains”

Istio Minikube Tutorial: Deploying a hello world example application with Istio in Kubernetes

Last couple of days I was playing with Istio and I couldn’t find a working upto date tutorial that can teach me how to run a basic hello world application with Istio in Kubernetes.

Istio is an open source service mesh that provides a uniform way to integrate microservices, manage traffic flow across microservices, enforce policies, and aggregate telemetry data.

In this quick tutorial you will learn how to install Istio on Minikube and then deploy a helloworld sample application on it.

Continue reading “Istio Minikube Tutorial: Deploying a hello world example application with Istio in Kubernetes”

Issue #26: 10 Reads, A Handcrafted Weekly Newsletter For Software Developers

The time to read this newsletter is 180 minutes.

Wealth is the ability to fully experience life. — Henry David Thoreau

  1. Don’t get clever with login forms: 10 mins read. This post points to a valid concern related to cleverness of login forms. Author through a set of examples explain why clever login forms end up confusing users. Another example of clever login experience that author does not cover is https://login.microsoftonline.com . I agree with author recommendations for login page:
    1. Have a dedicated page for login
    2. Expose all required fields
    3. Keep all fields on one page
    4. Don’t get fancy.
  2. Why Google Needed a Graph Serving System: 30 mins read. In this post, author shares his story of building a distributed graph database that can answer queries with relationship. The post goes over various Graph based systems developed at Google and why Google failed to build a distributed Graph database that does not suffer from depth join problem. This post highlights an interesting point related to Google’s struggle to build innovative solution because of their internal politics. Building a distribued graph database that does not suffer from depth join problem is a herculean task. Dgraph an open source database developed by the author along with others in community is trying to build such a system.
  3. You probably don’t need a single-page application: 10 mins read. I agree in entirety with the author that best solution to build web application is somewhere in middle i.e. building hybrid apps. Build SPA only for parts where you need rich interaction and keep most other pages server rendered.
  4. Google wants Cloud Services Platform to Borg your datacenter: 20 mins read. This post gives insight into why Google made the move to build and open source Kubernetes. Google knew they are going to have a hard time beating AWS and Azure. So, they built and released Kubernetes and hoped it becomes a successful project with big community. This means cloud just became an implementation detail and most big enterprises started considering Kubernetes as a choice of softwaere to build a modern hybrid datacenter. Google’s Cloud Service Platform(CSP) will give enterprises a hardened Kubernetes, Istio, Knative software distribution. CSP is going to be a game changer for Google Cloud. Also, many OpenShift users might consider going for CSP. Interesting time ahead!
  5. Four Techniques Serverless Platforms Use to Balance Performance and Cost: 30 mins read. This is the best article I have read on Serverless. It starts by helping reader understand architecture of Serverless platform and then it talks about elephant in the room — cold start problem associated with Serverless platforms. The article covers four techniques that is employed by different Serverless platforms to overcome cold start issue. The techniques mentioned in the post are following:
    1. Function resource sharing
    2. Function resource pooling
    3. Function prefetching
    4. Function prewarming.
  6. Lessons from 6 software rewrite stories: 20 mins read. Another amazing read for this week. This post through real examples explain when it is fine to rewrite software. If you are building software for long, you will have come across advice by Joel Spolsky that rewriting software is the single worst strategic mistake that a software company can make. The post author tells the other side of the story in this post. The key take away from the post is
    1. Once you’ve learned enough that there’s a certain distance between the current version of your product and the best version of that product you can imagine, then the right approach is not to replace your software with a new version, but to build something new next to it — without throwing away what you have.
  7. How to build a distributed throttling system with Nginx + Lua + Redis: 15 mins read. This post covers how to build API rate limiting system with Nginx, Lua, and Redis. Instructions mentioned in the post are clear and to the point.
  8. Monte Carlo Simulation with Python: 20 mins read. The post explains Monte Carlo simulation using a simple but realisitic example. As per wikipedia,
    1. Monte Carlo methods are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. Their essential idea is using randomness to solve problems that might be deterministic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches. Monte Carlo methods are mainly used in three problem classes: optimization, numerical integration, and generating draws from a probability distribution.
  9. 5 Ways To Process Feedback At Work Without Triggering A Stress Response: 10 mins read. This post covers an important aspect of professional life — taking feedback. The author suggests following:
    1. Keep an open mind about receiving feedback. Focus on how your work can be improved with some extra perspective.
    2. Don’t respond right away, take a few seconds to really process the feedback. You can assess rationally and logically, without undue emotion.
    3. Make sure you understand the feedback. In cases where you don’t, ask questions! The feedback giver should be happy to discuss specific points deeper to help clarify their suggestions.
    4. Be humble and gracious! Let them know you appreciate that they gave their time and energy to help make you more successful.
    5. Don’t let constructive criticism go in one ear and out the other. Take what you hear, implement it, and follow-up.
  10. How to Organize your Monolith Before Breaking it into Services: 15 mins read. This post talks about an intermediary stage between monolithic and microservices – a monolithic organized by domain without the entanglement or fragility of our original codebase. I agree with author in entirety that we should start with monolithic and modularise applications based on sub domains by applying DDD principles. If required in future, we can easily make these subdomain functional modules to services. It is great to read post like this as they provide valuable information that is usually missing in most posts found on the web.