How To Build Out a Successful Multi-Cloud Strategy
While a multi-cloud approach can deliver serious value in terms of resiliency,
flexibility and cost savings, making sure you’re choosing the right providers
requires a comprehensive assessment. Luckily, all main cloud vendors offer
free trial services so you can establish which ones best fit your needs and
see how they work with each other. It will pay to conduct proofs-of-concept
using the free trials and run your data and code on each provider. You also
need to make sure that you’re able to move your data and code around easily
during the trials. It’s also important to remember that each cloud provider
has different strengths—one company’s best option is not necessarily the best
choice for you. For example, if your startup is heavily reliant on running
artificial intelligence (AI) and machine learning (ML) applications, you might
opt for Google Cloud’s AI open source platform. Or perhaps you require an
international network of data centers, minimal latency and data privacy
compliance for certain geographies for your globally used app. Here’s where
AWS could step in. On the other hand, you might need your cloud applications
to seamlessly integrate with the various Microsoft tools that you already use.
This would make the case for Microsoft Azure.
How data and technology can strengthen company culture
Remote working exposed another potential weakness holding back teams from
realising their potential – employee expertise that isn’t being shared. Under
the lockdown, many companies realised that knowledge and experience within
their workforce were highly concentrated within specific offices, regions,
teams, or employees. How can these valuable insights be shared seamlessly
across internal networks? A truly collaborative company culture must go beyond
limited solutions, such as excessive video calls, which run the risk of
burning people out. Collaboration tools that support culture have to be chosen
based on their effectiveness at improving interactions, bridging gaps and
simplifying knowledge sharing. ... While revamping strategies in recent
months, many companies have started to prioritise customer retention and
expansion over new customer acquisition, given the state of the economy. Data
and technology can help employees adapt to this transition. Investing in tools
that empower employees gives them the confidence, knowledge and skills they
need to deliver maximum customer value. This in turn boosts customer
satisfaction as staff deliver an engaging and consistent experience each time
they connect.
Cloud environment complexity has surpassed human ability to manage
“The benefits of IT and business automation extend far beyond cost savings.
Organizations need this capability – to drive revenue, stay connected with
customers, and keep employees productive – or they face extinction,” said
Bernd Greifeneder, CTO at Dynatrace. “Increased automation enables digital
teams to take full advantage of the ever-growing volume and variety of
observability data from their increasingly complex, multicloud, containerized
environments. With the right observability platform, teams can turn this data
into actionable answers, driving a cultural change across the organization and
freeing up their scarce engineering resources to focus on what matters most –
customers and the business.” ... 93% of CIOs said AI-assistance will be
critical to IT’s ability to cope with increasing workloads and deliver maximum
value to the business. CIOs expect automation in cloud and IT operations
will reduce the amount of time spent ‘keeping the lights on’ by 38%, saving
organizations $2 million per year, on average. Despite this advantage,
just 19% of all repeatable operations processes for digital experience
management and observability have been automated. “History has shown
successful organizations use disruptive moments to their advantage,” added
Greifeneder.
A New Risk Vector: The Enterprise of Things
The ultimate goal should be the implementation of a process for formal review
of cybersecurity risk and readout to the governance, risk, and compliance
(GRC) and audit committee. Each of these steps must be undertaken on an
ongoing basis, instead of being viewed as a point-in-time exercise. Today's
cybersecurity landscape, with new technologies and evolving adversary trade
craft, demands a continuous review of risk by boards, as well as the constant
re-evaluation of the security budget allocation against rising risk areas. to
ensure that every dollar spent on cybersecurity directly buys down those areas
of greatest risk. We are beginning to see some positive trends in this
direction. Nearly every large public company board of directors today has made
cyber-risk an element either of the audit committee, risk committee, or safety
and security committee. The CISO is also getting visibility at the board
level, in many cases presenting at least once if not multiple times a year.
Meanwhile, shareholders are beginning to ask the tough questions during annual
meetings about what cybersecurity measures are being implemented. In
today's landscape, each of these conversations about cyber-risk at the board
level must include a discussion about the Enterprise of Things given the
materiality of risk.
FreedomFI: Do-it-yourself open-source 5G networking
FreedomFi offers a couple of options to get started with open-source private
cellular through their website. All proceeds will be reinvested towards
building up the Magma's project open-source software code. Sponsors
contributing $300 towards the project will receive a beta FreedomFi gateway
and limited, free access to the Citizens Broadband Radio Service (CBRS) shared
spectrum in the 3.5 GHz "innovation band." Despite the name "good-buddy,"
CBRS has nothing to do with the CB radio service used by amateurs and truckers
for two-way voice communications. CB lives on in the United States in the
27MHz band. Those contributing at $1,000 dollars will get support with a
"network up" guarantee, offering FreedomFi guidance over a series of Zoom
sessions. The company guarantees they won't give up until you get a
connection. FreedomFi will be demonstrating an end-to-end private cellular
network deployment during their upcoming keynote at the Open Infrastructure
Summit and publishing step-by-step instructions on the company blog. This
isn't just a hopeful idea being launched on a wing and a prayer. WiConnect
Wireless is already working with it. "We operate hundreds of towers, providing
fixed wireless access in rural areas of Wisconsin," said Dave Bagett,
WiConnect's president.
Why We Must Unshackle AI From the Boundaries of Human Knowledge
Artificial intelligence (AI) has made astonishing progress in the last decade.
AI can now drive cars, diagnose diseases from medical images, recommend
movies, even whom you should date, make investment decisions, and create art
that people have sold at auction. A lot of research today, however, focuses on
teaching AI to do things the way we do them. For example, computer vision and
natural language processing – two of the hottest research areas in the field –
deal with building AI models that can see like humans and use language like
humans. But instead of teaching computers to imitate human thought, the time
has now come to let them evolve on their own, so instead of becoming like us,
they have a chance to become better than us. Supervised learning has thus far
been the most common approach to machine learning, where algorithms learn from
datasets containing pairs of samples and labels. For example, consider a
dataset of enquiries (not conversions) for an insurance website with
information about a person’s age, occupation, city, income, etc. plus a label
indicating whether the person eventually purchased the insurance.
The Race for Intelligent AI
The key takeaway is that fundamentally BERT and GPT3 have the same structure
in terms of information flow. Although attention layers in transformers can
distribute information in a way that a normal neural network layer cannot, it
still retains the fundamental property that it passes forward information from
input to output. The first problem with feed forward neural nets is that they
are inefficient. When processing information, the processing chain can often
be broken down into multiple small repetitive tasks. For example, addition is
a cyclical process, where single digit adders, or in a binary system full
adders, can be used together to compute the final result. In a linear
information system, to add three numbers there would have to be three adders
chained together; this is not efficient, especially for neural networks, which
would have to learn each adder unit. This is inefficient when it is possible
to learn one unit and reuse it. This is also not how back propagation tends to
learn, the neural network would try to create a hierarchical decomposition of
the process, which in this case would not ‘scale’ to more digits. Another
issue with using feed forward neural networks to simulate “human level
intelligence” is thinking. Thinking is an optimization process.
Why Agile Transformations sometimes fail
The attitude regarding Agile adoption that is represented by top management
impacts the whole process. Disengaged management is the most common reason for
my ranking. There were not too many examples in my career when the bottom-up
Agile transformation was successful. Usually, top management is at some point
aware of Agile activities in the company, Scrum adoption, although they leave
it to the teams. One of the frequent reasons for this behavior is that top
management is not acquainted with the understanding that Agility is beneficial
for business, product, and the most important – customers/users. They consider
Agile, Scrum and Lean to be things that might improve delivery and teams'
productivity. Let's imagine the situation when a large number of Scrum Masters
reported the same impediment. It becomes an organizational impediment. How
would you resolve it when decision-makers are not interested in it? What would
be the impact on teams' engagement and product delivery? Active management
that fosters Agility and empirical way, and actively participates in the whole
process is a secret ingredient that makes the transition more realistic.
Another observation I have made is a strong focus on delivery, productivity,
technology and effectiveness.
The encryption war is on again, and this time government has a new strategy
So what's going on here? Adding two new countries -- Japan and India -- the
statement suggests that more governments are getting worried, but the tone is
slightly different now. Perhaps governments are trying a less direct approach
this time, and hoping to put pressure on tech companies in a different way. "I
find it interesting that the rhetoric has softened slightly," says Professor
Alan Woodward of the University of Surrey. "They are no longer saying 'do
something or else'". What this note tries to do is put the ball firmly back
in the tech companies' court, Woodward says, by implying that big tech is
putting people at risk by not acceding to their demands -- a potentially
effective tactic in building a public consensus against the tech companies. "It
seems extraordinary that we're having this discussion yet again, but I think
that the politicians feel they are gathering a head of steam with which to put
pressure on the big tech companies," he says. Even if police and intelligence
agencies can't always get encrypted messages from tech companies, they certainly
aren't without other powers. The UK recently passed legislation giving law
enforcement wide-ranging powers to hack into computer systems in search of
data.
Code Security: SAST, Shift-Left, DevSecOps and Beyond
One of the most important elements in DevSecOps revolves around a project’s
branching strategy. In addition to the main branch, every developer uses their
own separate branch. They develop their code and then merge it back into that
main branch. A key requirement for the main branch is to maintain zero
unresolved warnings so that it passes all functional testing. Therefore, before
a developer on an individual branch can submit their work, it also needs to pass
all functional tests. And all static analysis tests need to pass. When a pull
request or merge request has unresolved warnings, it is rejected, must be fixed
and resubmitted. These include functional test case failures and static analysis
warnings. Functional test failures must be fixed. However, the root cause of the
failure may be hard to find. A functional test error might say, “Input A should
generate output B,” but C comes out instead, but there is no indication as to
which piece of code to change. Static analysis, on the other hand, will reveal
exactly where there is a memory leak and will provide detailed explanations for
each warning. This is one way in which static analysis can help DevSecOps
deliver the best and most secure code. Finally, let’s review Lean and
shift-left, and see how they are connected.
Quote for the day:
'The mediocre leader tells; The good leader explains; The superior leader demonstrates; and The great leader inspires." -- Buchholz and Roth
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