Daily Tech Digest - October 15, 2021

9 common risk management failures and how to avoid them

Known for decades as the hub of technical innovation, Silicon Valley has evolved into a bastion of toxic "bro culture," according to Alla Valente, senior analyst at Forrester Research. She also cited other forms of toxic work culture when companies fail to mitigate risks that can alienate employees and customers. Facebook's lukewarm response to the Cambridge Analytica scandal, Valente argued, has significantly eroded its trustworthiness and market potential. Wells Fargo's executives turning a blind eye to the warning signs of the bank's predatory selling practices with their customers "was a strategic decision," Valente said. "It could have been fixed, but fixing culture is never easy." ... Efficiency and resiliency sit at opposite ends of the spectrum, Matlock said. Greater efficiency can lead to greater profits when things go well. The auto industry realized significant savings by creating a supply chain of thousands of third-party suppliers spread across multiple tiers. But during the pandemic, there were massive disruptions in supply chains that lacked resiliency. 


Mandating a Zero-Trust Approach for Software Supply Chains

SBOMs are a great first step towards supply-chain transparency, but there is more that needs to be done. As an analogy, many equate the SBOM to the ingredient labels on food. With that perspective, we can see parallels between our software supply chain and the food supply chain. Subsequently, the need for end-to-end provenance and resistance against tampering should be clear. For this reason, I am encouraged by Google’s proposed Supply-Chain Levels for Software Artifacts (SLSA) framework that moves us towards a common language that increases the transparency and integrity of our software supply chain. However, for some software that performs critical functions (e.g., security), food is an inadequate comparison. It may be more apt to compare this type of software to medicine. This analogy brings forth additional considerations. For example, the drug-facts label on medicines includes not just the ingredients, but also usage guidelines and contraindications (i.e., what to look for in case something goes wrong.) Furthermore, as we’ve all seen with the COVID-19 vaccine, medicines must undergo intensive review and testing before it is approved for use. 


Data Consistency Between Microservices

The root of the problem is querying data from other boundaries that will be immediately inconsistent the moment it’s returned, just as in my first example without a serializable transaction. If you’re making HTTP or gRPC calls to other services to retrieve data that you require to perform business logic, you’re dealing with inconsistent data. If you store a local cache copy that’s eventually consistent, you’re dealing with inconsistent data. Is having inconsistent data an issue? Go ask the business. If it is, then you need to get all relevant data within the same boundary that’s required. There are two pieces of data we ultimately needed. We required the Quantity on Hand from the warehouse. In reality in the distribution/warehouse domain, you don’t rely on the “Quantity on Hand”. When dealing with physical goods, the point of truth is actually what is actually in the warehouse, not what the software/database states. ... The system is eventually consistent with the real world. Because of this, Sales has the concept of Available to Promise (ATP) which is a business function for customer order promising based on what’s been ordered but not yet shipped, purchased but not yet received, etc.


5 ways CIOs are redefining teamwork for a hybrid world

Most CIOs face similar grand experiments as hybrid work environments are becoming permanent. They are evaluating which team structures have been successful remotely and are looking to replicate them, while balancing innovation, collaboration, mentorship, and culture transfer, which have traditionally been done in person. Some 30% of IT leaders surveyed by IDC say they prefer an “online-first” policy for collaboration, and practices that started during the pandemic will likely continue indefinitely. While many workers say they have been more productive working remotely, that doesn’t always equate to better teamwork. “We’ve squeezed a lot of innovation out of necessity, but some of that serendipitous innovation that occurs through creative collision has been less,” says Aaron De Smet, senior partner at McKinsey and Co., who spoke at the IDG Future of Work Summit in October. “Companies have started to get their heads around a hybrid workforce, but I don’t think they’ve cracked what hybrid interactions look like. More of the work people do is now part of a cross-functional team. It’s part of a collaborative effort … ” De Smet says. 


3 Signs You’re Ready For A Machine Learning Job When You’ve Come From Another Field

Your sense of direction is what lets you know where you are, or which way to go, even when lingering in unfamiliar territory. Religious people would often argue that a lack of direction is a result of not having a purpose, and to some degree, I agree. You shouldn’t have to wait to have a sense of purpose before you can be happy. Imagine how miserable life would be if that’s the case! When a person begins to question their sense of direction in regards to machine learning, it’s usually to do with a lack of appreciation for how far they’ve come. As you learn more, it’s harder to see the small increments you improve by and this may feel as though you are no longer learning — especially when you compare it to a time when you were learning something new every day. Given you meet the generic requirements of the machine learning role you want, then it’s time to apply for a job that challenges you differently from how you could if you were working alone. Start applying.


Google Opens Up Spanner Database With PostgreSQL Interface

The integration of PostgreSQL into Cloud Spanner is deep; it is not just some conversion overlay. At the database schema level, the PostgreSQL interface for Cloud Spanner supports native PostgresSQL data types and its data description language (DDL), which is a syntax for creating users, tables, and indexes for databases. The upshot is that if you write a schema for the PostgreSQL interface for Cloud Spanner is that it will port to and run on any real PostgreSQL database, which means customers are not trapped on the Google Cloud is they use this service in production and want to switch. But customers do have to be careful. Spanner functions, like table interleaving, have been added to the PostgreSQL layer because they are important features in Spanner. You can get stuck because of these. ... The PostgreSQL interface for Cloud Spanner compiles PostgresSQL queries down to Spanner’s native distributed query processing and storage primitives and does not just support the PostgreSQL wire protocol, which allows for clients and myriad third-party analytics tools to interact with the PostgreSQL database.


The pursuit of transformation: Opportunities and pitfalls

Some transformations fail when there is a lack of alignment between the company’s strategy and its employees, customers and partners. There is a famous fable of an ant trying its hardest to change its trajectory but not realising that it is sitting on an elephant that’s going in the opposite direction. No matter how hard the little ant tries, it will not reach its destination as long as the elephant is not in alignment. All organizations have a culture and an emotional ethos, which if left unaddressed can sabotage the move to change. When Satya Nadella took over Microsoft in 2014, he had to first restructure the company to eliminate destructive internal competition so that all departments could focus on a common services goal. The result is a two and a half fold growth in the stock price over 5 years. On the other hand, when GE decided to launch GE Digital as a transformation vehicle, it did not release the subsidiary from the obligation of quarterly revenue and profitability targets. In addition, the company had to continue to meet GE’s software needs across business units, thereby not having the bandwidth to focus on true innovation and transformation. 


How Machine Learning can be used with Blockchain Technology?

Machine learning algorithms have amazing capabilities of learning. These capabilities can be applied in the blockchain to make the chain smarter than before. This integration can be helpful in the improvement in the security of the distributed ledger of the blockchain. Also, the computation power of ML can be used in the reduction of time taken to find the golden nonce and also the ML can be used for making the data sharing routes better. Further, we can build many better models of machine learning using the decentralized data architecture feature of blockchain technology. Machine learning models can use the data stored in the blockchain network for making the prediction or for the analysis of data purposes. let’s take an example of any smart BT-based application where the data is collecting by different sources such as sensors, smart devices, IoT devices and the blockchain in this application works as an integral part of the application where on the data the machine learning model can be applied for real-time data analytics or predictions. 


The tech recruiter – an unsung hero

The idiom ‘your first impression is your last impression’ holds true for recruiters. They have one opportunity to deliver that perfect elevator pitch to the candidate – convince them why your company provides the best opportunity for them- in the time it takes to ride an elevator. Landing the right impression will determine the candidate’s unalterable opinion and employment decision. To understand this better, let’s take a quick look at the talent landscape today. With the digitalization mega trend sweeping across Tech Inc., organizations are scurrying to bolster their workforce across technology skill sets. Economic Times reported that Indian IT firms plan to hire over 150,000 freshers in FY22 and NASSCOM remarked that India’s five largest companies are likely to hire 96,000 employees this year. Although this will be a huge boost for the $150 Billion industry, the demand-supply technology talent gap is only widening. Today, it is the candidates who hold the power and have the pleasure of the last word as prolonged notice periods allow them time to hedge their bets with the four-five job offers they have on hand. And the more skilled they are, the more offers they juggle.


Better Scrum Through Essence

First an anecdote from Jeff Sutherland – ‘The VP of one of the biggest banks in the country [USA] said recently: “I have 300 product owners and only three were delivering. The other 297 were not delivering”. And, he said, “I checked on where the three that were delivering, where they got the right way of working. They went to your class. So, you need to tell me what you are doing differently.” I said, “What we are doing differently is using Ivar’s work with Essence to really clarify to people what is working, what is not working, what you need to do next to improve things.” By using Essence on many Scrum Master courses we (Jeff, I and others) have also observed that of the 21 components of the original Scrum Essentials, the average team implements 1/3 of them well, 1/3 of them poorly and 1/3 of them not at all. With that level and quality of implementation it is not surprising that we are not always seeing the full potential that Scrum offers. At the heart of getting better Scrum through Essence are the use of the Scrum Foundation, the Scrum Essentials and the Scrum Accelerator practices to play games, facilitate events and drive team improvements.



Quote for the day:

"Leaders know the importance of having someone in their lives who will unfailingly and fearlessly tell them the truth." -- Warren G. Bennis

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