Enterprises Face Growing Technical Debt
There is not one single factor causing technical debt. Many issues within an
organization contribute to the problem, including reliance on stale technology,
pressure to deliver in the short term, constant change, developer churn and
incorrect architectural decisions. The top cause of technical debt is too many
development languages and frameworks, cited by 52% of respondents as a big or
critical problem. Legacy technology can weigh an IT department down. But, it’s
not necessarily only old tech getting in the way—it could be that IT is
supporting too many competing agendas.The second top cause is a high turnover
rate within developer teams. In today’s competitive climate, quality engineers
are in short supply, and hiring can be challenging. It is thus difficult to
attract and nourish steady engineering talent. If developers frequently leave
for greener pastures, especially before documenting their procedures, best
practices can easily be lost and efficient use of technology is stunted. The
study found that other common causes include accepting known defects to meet
deadlines, using outdated programming languages and frameworks and dealing with
challenges in serving new markets or segments. No code software — the most effective path to closing the IT skills gap
The tech sector has long been governed by a certain subset of society and has
lacked diversity. According to Diversity in Tech, 15% of the tech workforce are
from BAME backgrounds and gender diversity is at 19%, compared to 49% for all
other jobs within the UK. Considering the tech industry is growing almost three
times as rapidly as the rest of the UK economy, tech and software development is
a lucratively paid and in demand industry for those with the skills. However,
there is no doubt it’s exclusionary. While this is a recognised issue many are
keen to rectify, movement towards change is slow on the uptake. Socioeconomic
dynamics mean privileged groups prevail. Change must happen at grassroots level.
If children don’t have access to devices at home, attend schools with archaic
software and hardware, or aren’t equipped with a support mechanism or role
models, they will find themselves on the back foot for a career in tech. Roles
such as software development take time to train and prepare for, meaning they
can be hard to break into without background experience. Also, the lack of
gender diverse and BAME role models within the tech industry perpetuates this
imbalance.
Google’s health care data-sharing partnership is a problem
Privacy concerns are not just related to the fact that stolen data could
potentially harm patients and consumers, however. They are also tied to the
simple reality that individuals feel as though they have no say in how their
personal data is acquired, stored, and used by entities with which they have
not meaningfully consented to share their information. According to the Pew
Research Foundation, more than half of Americans have no clear understanding
of how their data is used once it has been collected, and some 80% are
concerned about how much of their data advertisers and other social media
companies have collected. ... The legitimate concerns of consumers
combined with a massive and growing amount of data theft make agreements like
the one between Google and HCA unwise, despite potential benefits. While the
data that Google will have access to will be anonymized and secured through
Google’s Cloud infrastructure, it will be stored without the consent of
patients, whose deeply personal information is in question. This is because
privacy laws in the United States allow hospitals to share patient information
with contractors and researchers even when patients have not consented.What Is A Convolutional Layer?
Most of the classification tasks are based on images and videos. We have seen
that to perform classification tasks on images and videos; the convolutional
layer plays a key role. “In mathematics, convolution is a mathematical
operation of two functions such that it produces a third function that
expresses how another function modifies the shape of one function.” If you try
to apply the above definition, the convolution in CNN denotes the operation
performed on two images which can be represented as matrices are multiplied to
give an output that is used to extract features from an image. Convolution is
the simple application of a filter to an input image that results in
activation, and repeated application of the same filter throughout the image
results in a map of activation called feature map, indicating location and
strength of detected feature in an input image. .... The CNN is a special type
of neural network model designed to work on images data that can be
one-dimensional, two-dimensional, and sometimes three-dimensional. Their
application ranges from image and video recognition, image classification,
medical image analysis, computer vision and natural language processing.Krustlet Brings WebAssembly to Kubernetes with a Rust-Based Kubelet
By enabling WebAssembly, Krustlet offers increased density, faster startup and
shutdown times, smaller network and storage footprints, and all of these are
features that not only support microservices but also operation on the edge
and in IoT environments. In addition, WebAssembly also offers the ability to
run on multiple architectures without being recompiled, has a security model
that distrusts the guest by default, and can be executed by an interpreter and
streamed in, meaning it can be run on the smallest of devices. “Krustlet,
potentially combined with things like SUSE/Rancher’s k3s, can make inroads
into IoT by providing a small-footprint extension to a Kubernetes cluster.
This points to a sea change occurring in Kubernetes. When some folks at Google
first wrote Kubernetes, they were thinking about clusters in the data center.
But why think only in terms of the data center?” asks Butcher. “Imagine a
world where the pod could be dynamically moved as close to the user as
possible — down to a thermostat or a gaming console or a home router. And
then, as the person left home, that app could ‘leave’ with them, hopping to
the next closest place — yet still within the same cluster. Certainly, that’s
tomorrow’s world, but Krustlet is a step toward realizing it.”Top 5 Cloud Security Challenges Teams Face In 2021
Unfortunately, many teams don’t think about security, and sometimes even
overall governance, until it’s too late. Whether they don’t have the budget,
think they don’t yet have the scale, or it’s just not top of mind,
procrastinating on cloud security can expose an organization to breaches,
non-compliance, and other high-risk issues. On the flip side, organizations
might have initially taken too heavy-handed of an approach and implemented
such strict controls that it prevents them from fully realizing the promise of
cloud and DevOps in the future. Thinking about cloud security should happen
early, which includes implementing not just the right tools, but also the
right processes and people. And it’s never too early to start, because
security needs to be woven into your process from the beginning. ...
Organizations wanting to keep on top of their cloud security need to
prioritize constant education and upskilling, not just around traditional
security applied to the cloud but also around industry best practices and
cloud fundamentals, too. Identify team members willing to go deeper and pair
them with industry experts within the organization, or take advantage of free
educational tools from the major cloud providers to keep your team’s knowledge
base wide and ever-evolving.Embrace integrations and automation as you build a security program
In enterprise systems, automation refers to the ability to take a human
operated task and reduce it to a data model, then create a script of code for
repeatability. Compliance has typically been a labor-intensive practice. When
considering the variety and amount of human labor required to meet compliance
objectives, the concept of automation often cannot be broadly applied. Audit
evidence collection, via an integration, lends itself well to an automated
solution. This form of automation can also ensure the timeliness of evidence
collection activity. However, this represents only a tiny percentage of the
labor required to pass an audit. All organizations can realize benefits from
automated compliance concepts by considering which tasks would traditionally
require a consultant. Is that task repeatable across consultants? For example,
performing an annual risk assessment. Another example is mapping exercises
between an organization’s cybersecurity policies and controls against a common
standard such as ISO 27001 or SOC 2. People are still required to ensure that
the quality of these tasks are acceptable. 6 Steps Companies Can Take to Strengthen Their Cyber Strategy
With more than a year of remote work for hundreds of thousands of people, many
companies historically known for having on-premise based infrastructures are
now shifting to multi-cloud strategies. Multi-cloud strategies are valuable
because they provide the best possible cloud service for each workload. Today,
our cyber security group is partnering with our digital transformation team to
enable multi-cloud adoption in a way that advances and streamlines our
specific business operations. Cyber leaders should develop risk controls
upfront when ushering in multi-cloud strategies so that they don’t hinder the
pace of adoption, while also protecting the company’s assets and data. ...
Biometrics are a significant game-changer in cyber protection. It’s much
harder for a threat actor to break into a system designed on behavioral
attributes -- like how quickly people type, how they move their mouse, or what
applications they have open -- than a system reliant on static passwords. In
fact, we’re working with our data science team to pilot our own data models,
leveraging new technologies available in the industry to replace passwords
internally over time.Why big data doesn’t exist — it’s all about the value
Over the past decade there has been an abundance of cases where well-known
brands, which typically sit on a mammoth amount of historic data, have
collapsed due to not handling it effectively. Companies including retailer
Toys “R” Us, book chain Borders, and more recently, department store
Debenhams, failed to optimise operations quickly enough to stay relevant in a
highly competitive digital environment. Had they responded to what their data
analysis was telling them, the outcome of these businesses could have been
different. Adopting technology that can process and manage data as well as
provide visualisations about what is happening within the organisation in real
time can deliver greater insight into everything from product materials and
production rates to customer shopping habits and market trends. By knowing
what’s working and what’s not, businesses can make decisions based on the
evidence the data shows, rather than relying on ‘gut instinct’. The pandemic
is an excellent example of how the valuable data over big data can be used to
drive decisions, as many businesses were forced to accelerate their digital
strategies to remain viable. Management consultancy Mckinsey reports that the
crisis brought about years of change to the way all companies and sectors do
businessLeveraging Small Teams to Scale Agility - a Red Hat Case Study
Doing Agile does not always mean being Agile. The starting state of this group demonstrated this in the way they were working. They’d had training and had wound up with a rotating cast of characters in scrum teams with 10+ boards. After I arrived, we did another training cycle on Agile. This occurred after the team had committed to doing Agile and helped everyone to acquire the tools for success. Even with their previous challenges, like many teams new to Agile they got excited. Knowledge is power. But even helping move the team members from novice to amateur still left them struggling with concepts like capacity. They, like many teams, struggled to understand what their team capacity level was. They tended to overcommit the volume of work to be completed in each Sprint. This is where a Scrum master can support by helping guide a team to maturity as they learn to deliver value and be responsible for it as a team. It would have been impossible for me to do my work if my manager and the team didn’t trust me. I started with the trust given to me by my manager and the trust of the functional managers as a platform to build on.Quote for the day:
"If you don't understand people, you don't understand business." -- Simon Sinek
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