SOFTware is HARD

The CRAM model suggests to investigate poor performance in a team member in this top-down order : C onstraints - is the member experiencing certain constraints in his/ her life that limits productivity or effectiveness? For example; married, birth, or death of a close one, debt or addiction issues. R esources - are there resource issues that prevents productive contribution? E.g. lack of test environment, IDE, tools, software licenses, hardware. A ptitude - is the team member cut-out for the role? Are there other more suitable roles available? M otivation - is the team member motivated to perform the role or is he/ she just passing time? Is it time to change the role or the job?

Here are some salient difference I gathered: SAN NAS Connection FC/ SCSI Ethernet Speed Typically faster (unless over Ethernet like FCoE or iSCSI) Typically slower Cost Typically higher Typically lower Intrusiveness Appears like locally attached storage to OS Remotely accessible filesystem using protocols like: NFS (Unix)/ CIFS (Windows)/ AFP (iOS) or even HTTP Can same unit be shared across different servers? No – every server mount will have its own exclusive blocks Yes. Concurrent access and locking is handled by the access protocols Unit of storage block-level file-level

Three aspects are typically handled by Web Access Management software: protect resources authenticate users authorise users The flow is depicted in the following Activity Diagram:

Some information regarding the proposed Personal Data Protection Bill 2012 (Singapore): Covers the regulation pertaining to the collection, use, disclosure, transfer & security of personal data. The PDP Bill consultation paper found here The proposed PDP Bill found here The Model Data Protection Code for the Private Sector found here A subsequent report of the above-mentioned Model Code by the NIAC found here The PDP bill interprets “personal data” to refer to data, whether true or not, about an individual who can be identified from that data; or from that data and other information to which the organisation is likely to have access The bill does not provide greater clarity to the definition of “personal data” and a prescriptive list of personal data would not be provided. Fortunately, the definition was largely adapted from the Model Code which provided certain implementation & operational guidelines with specific examples. An excerpt from the Model Code follows:

Just read about the 4 stages in competence that applies to learning and measuring competencies in new skills. It’s always good to know where one stands for each competency. From the lowest to the highest, they are:   Unconscious Incompetence Individual does not know the required skill/ competence exists, let along the relevance of it. Individual is incompetence and does not know it Call this individual ignorant, clueless To do : Need guidance to identify deficits “Don’t know what you don’t know”   Conscious Incompetence Individual recognises deficit in competency/ skill but is not addressing it/ not able to address it Appreciates the value of the competency/ skill Call this individual a beginner, a learner To do : Offer vast sources of learning resources and even training. Also allow for mistakes. “Know what you don’t know”   Conscious Competence Individual is able to demonstrate basic competency when required and at will Takes conscious effort/ concentration to

Around the world, Chrome appears to have overtaken IE for the desktop recently. Source: StatCounter Global Stats - Browser Market Share Singapore is heavily dominated by iOS but Android is catching-up fast! Source: StatCounter Global Stats - Mobile OS Market Share

Full presentation available here . A list of salient points follows: How to define success? Developers want Agility & Change Operations want Availability & Stability F1 car lifecycle Design –> Develop –> Test –> Deploy –> Support Support (Operations) need to always provide feedback to Design (Development) Engineers need to work hand-in-hand with Operations Success must be measured F1: Telemetry and monitoring are required to deliver drivers’ results IT Systems: Performance data collection and analysis as well as performance monitoring are required to deliver success Monitoring is critical in managing change Need to constantly monitor and manage impact of change. Need to provide feedback for where the car: Is fast – where things are done right Is slow – where to optimise and improve Failed – where to fix Three key aspects that impact application performance Concurrency Data volume Resources Where does one find the real bottlenecks? Not of

A mindmap review of the excellent book. Flash version can be found here