Good Read - Managing your IT career in 30's

Great Read from Quora. Usually I share my readings / learnings. This post was compelling, practical to manage work in 30s.

Read Quote of Michael O. Church's answer to What do software developers age 30 and over know now that they wish they had known in their 20s? on Quora


Read Quote of Michael O. Church's answer to Since programmers on average produce $500,000 for the tech companies they work for, why aren't they paid more? on Quora


Happy Reading!!!

Good Read - IOT Startup Ideas

IOT Startup Ideas - 50 Sensor Applications for a Smarter World. This covers all below categories

• Smart City
• Smart Environment
• Smart Water
• Smart Metering
• Security
• Retail
• Logistics
• Industrial Control
• Agriculture
• Farming
• Home Automation
• eHealth

Lot of Startup Ideas!!

Happy Learning!!!

QA Tools (Eliminate Repetitive Efforts)

Very Interesting post Reusable Software? Just Don't Write Generic Code

I echo similar thoughts on developing tools. I personally prefer smaller utilities / tools than a large consolidated Suite. This again depends on knowledge depth / design exposure. Some of Advantages of smaller components / utilities are

• Working throw away solution solves current hunger while prioritizing on next set of applicable changes
• Smaller components with dedicated code ownership would help in better maintenance, customization
• Usually tools developed by one person ends up modified by someone else in team. The time to learn a complex solution which solves lot of use cases needs greater functional knowledge and time

When we develop / consolidate different framework we would end up implementing

• Abstraction layers
• Inheritance

Level / Depth of it depends on skillset, exposure. The intent of the post was to minimise efforts to maintain tools developed. Considering the team skills, functional knowledge, ownership aspects, maintainable tools would be a better option than developing a large suite over extended period of time

Interesting line reposted from the post

"Writing small components will give your software a high chance of survival: all individual components are easy to use and understand, and are usable on their own in various use cases"

Happy Learning!!!

Databases - IOT - CES

CES notes on IOT had a interesting tag line posted in MEMSQL blogpost

Tag line copied from the post

Also, vast landscape of DB products in multiple categories (RDBMS, NOSQL, In-memory, Hadoop, Stream processing) check-out 451 research paper. Depending on the application needs you can identify top products to evaluate / get started

Data Platforms Landscape 

Updated Data Platforms Landscape Map – October 2014 http://t.co/qhJawLQhNX Free download - now fully indexed pic.twitter.com/cH3QL5GFcm
— Matt Aslett (@maslett) November 18, 2014

NoSQL LinkedIn Skills Index – December 2014

NoSQL LinkedIn Skills Index – December 2014 http://t.co/bCvR4ipSGG
— Matt Aslett (@maslett) December 18, 2014

Current State

It is remarkable how many database vendors are struggling despite apparently pre-emptively designing their products to be perfect for IoT
— Matt Aslett (@maslett) December 11, 2014

Happy Learning!!!

Productivity Tools list for Developer / DevOps / QA

Compiled list of Productivity Tools for Developer / DevOps / QA

• MTPutty
• Rapid Environment Editor
• Agent Ransack
• Heidisql
• SSMS Tools Pack
• Programmers Notepad
• TextPad
• Notepad++
• SOAP UI
• SSMS Tools Pack
• HeidiSQL
• Atlantis SQL Server
• Snip-it Utility
• Mtail

Happy Learning!!!

RDBMS Vs CEP

Came across this slide in presentation in link. Below slide on RDBMS vs CEP processing was very clear in terms of compared attributes, representation of facts. Many thanks to author.

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Open Source Test Tools Vs Commercial Test Tools

I have never had the taste of working with record - playback tools. I have mostly developed custom tools / scripts for qa tasks / deployment tasks. I work in different streams Database DEV - QA - Tools Development - Performance & Big Data too. Working on different areas provides a different perspective than doing repetitive things. My perspective of QA evolves with reusable scripts for data generation / scripts that simplify / eliminate repetitive tasks during deployment / configuration / testing / validating.

I have worked with Selenium, Coded UI, Custom developed Automation test frameworks. I have observed new engineering efforts for Automation test framework in every company I worked for. Either the code base becomes too big to manage / modify or new folks hired move towards develop from scratch than maintenance efforts. It is questionable ROI calculation. When the quality of DEV is poor every small bug in QA might show up as hundreds of bugs. How much of this bugs can actually be identified by basic QA check by DEV is another point to consider measuring QA bugs.

QA efforts are often viewed as commodity efforts where focus is mainly to deliver and repetitive cycles of testing are acceptable. Instead of such a model joint DEV-QA effort would always help to identify most bugs before releasing it to QA.

Both Open Source Tools Vs Commerical tools helps address test automation challenges. One instance. Working with WINCE apps, Its very difficult to automate hardware - software integration workflows. Testcomplete tool eliminated most of this efforts with emulating the actions on Mymobiler which in turn mimics real user on WINCE installed hardware.

Effort involved to automated WINCE App deployed on a device vs using a tool like test complete to completely eliminate the pain-point in writing WIN32 calls (Send message, Send Keys) is worth evaluating before thinking of license cost.

Overall its a mix of Open Source Tools, Commercial Tools, In-House scripts, Quality practices in coding, unit testing only can ensure a Quality product. Responsibilities are not just for one function but every function need to be accountable / responsible to deliver a Quality Product.

Automation tools are primarily viewed as Record / Playback, Automation Framework Implementation. More than it they can be also leveraged for

• Throw Away Scripts to Aid Functional Testers to eliminate repetitive tasks
• Automation tool can be used to support system activities during functional testing - Monitoring, Screen Capture, Aid Testing by Simulating user events during tests / Support long running tests  
• Extend it for Support / UAT Environments for for Deployment / Installation where installation involves several client / server / web components installation
• Aid Automated Deployments / Un-Installations

Happy Learning!!!

Testrail - TCM Tool

This post in on Analysis of Testrail and migrating existing test cases using Testrail

Testrail has a great web interface to organize and create test cases. The factors that makes Testrail competitive candidate are

• Ease of creating / managing test cases
• Migration Support for existing test cases
• API support for automated migration / test case creation / execution / update results
• Test Case execution out of box reports
• Integration with bug tracking tools
• Hosted / In-Premise Model
• Existing Github projects for .NET / Java / Other languages Automation / Migration Support
• Great Tech Support

Test Case Migration Efforts

Different aspects involved in test case migration efforts for any TCM tool 

1. Test case template - Identify required fields inbuilt, custom fields for test case template. Develop, Modify and Evaluate templates to arrive at Test Case Template
2. Organizing Test Cases  (Test Suites) - Feature wise, Release related test cases. Analyse, Identify structure and arrive, evaluate it (Functional, Regression, Features Areas) plus release specific cases
3. Migration Efforts - Based on template, test case structures prepare custom xml cases for all migration test cases
1. Validate, arrive at approach to validate all migrated cases
2. For attributes identified from Test case template what are values to be filled for existing test cases in case if they were not used
4. Default values for unused fields (Drop down list / custom values)
5. Automation Integration, Defect / Bug Tracking Tools Integration
6. Automation Test cases - Identify, Automation Test cases, Templates, Details
7. QA Reports - Analyse available reports and custom report needs in Test Rail. Email based reporting on metrics, daily test case execution etc
8. Custom Tools - Write Test cases in Excel and upload directly from excel to test rail. This tool can be used for writing test cases, update test results directly from excel to Testrail
9. QA Process document Develop Process document (guidelines / best practices) on adding test cases, updating functional, regression, release related test cases, using Test rail (Permissions), Test case reviews using Test rail
10. Test Results Archival / Maintenance - Test results / test runs / Test cases archival / maintenance approach
11. Hosting – local hosting / cloud based Pros / cons of local hosting / cloud hosting
12. Security / Administration / Configuring users - Admin related aspects, identifying roles / permissions for users
13. Identifying Pilot projects for Test Rail evaluation period after finalizing above areas Pilot projects for usability, tracking, upgrading before complete migration

Happy Learning!!!

HBase Overview Notes

Limitations of Hadoop 1.0

• No Random Access --> Hadoop for more batch access (OLAP)
• Not suitable for Real-time Access
• No Update - Access Pattern is WORM (Write Once Read Multiple Times Hadoop best suited)

Why HBase

• Flexible Schema Design --> Add a new column when a row is added
• Multiple versions of a single cell (Data)
• Columnar storage
• Cache columns at client side
• Compression of columns

Read  v/s Write

• For Availability (Compromise on Write) vs Consistency (Compromise on Read)

Hbase

• NoSQL Class on Non-Relational Storage Systems
• In RDBMS it is Rowkey based allocations, HBase it is columnar storage
• Hbase needs HDFS for replication
• ZooKeeper - Taking all requests from client. Client will communicate from zookeeper Client -> ZooKeeper -> HMaster
• Region Server - It Serves the region. Region Server processor runs on slaves (Data Nodes)

Happy Learning!!!

Pig Overview Notes

Pig

• Primarily for semi structured data
• So called 'Pig' as it processes all kinds of data
• Pig is data flow language not a procedural language
• Map Reduce - Java Programmers, Hive - for TSQL folks, Pig (Rapid Prototyping & increased productivity)
• Pig is on client side, need not be on cluster
• Execution Sequence - Query Parser -> Semantic Checking -> Logical Optimizer (Variable level) -> Logical to physical translator -> Physical to M/R translator -> MapReduce Launcher
• Ping Concepts - Map - array, Tuple - ordered list of data ,Bag - Unordered collection of tuple
• Pig - for client side access, Hive will work only within cluster, semi structured data
• Hive - Best suited for SQL style analytics, structured data
• MR - Audio Video Analytics Map Reduce Approach is the only option

Happy Learning!!!