Microservice Architecture: Why Containers And IoT Are A Perfect Fit
Apart from technical considerations, the way a software development team is
set up also plays a critical role in the software technology decision. A major
advantage of containerization is the great flexibility and manageability of
the overall development process. Although previous monolithic software
development often had cumbersome documentation requirements, hard-to-predict
timelines and complicated synchronization processes, the container-based
approach can deliver a different experience. If you're able to split up the
project in isolated containers, you can divide the team into smaller groups
with faster iterations and address additional feature requests more easily to
cater to modern agile processes. Containerization also bridges the two worlds
of cloud and embedded development by aligning the underlying technology,
unifying the development workflow and leveraging automation capabilities
containers provide. With that, it becomes much easier to support hybrid
workflows and reuse the same software. This is important for IoT projects if
customers have vastly different network environments, data ownership
requirements and solution approaches.
Automation with intelligence
For organisations to successfully integrate intelligent automation, they must
first acknowledge that transformation is necessary. It starts with making a
conscious choice about what they want to achieve, based on the ‘art of the
possible’. This decision is then fed into a robust and realistic intelligent
automation strategy. That is the ideal, but here is the reality: Only 26 per
cent of Deloitte’s survey respondents that are piloting automations – and 38
per cent of those implementing and scaling –have an enterprise-wide
intelligent automation strategy. There is a clear difference between
organisations piloting automations and those implementing and scaling their
efforts. The latter are more likely to reimagine what they do and incorporate
process change across functional boundaries. Those in the piloting stage are
more likely to automate current processes, with limited change – they may have
not yet taken advantage of the many technologies and techniques that can
expand their field of vision and open up even more opportunities. There
are other barriers to success: process fragmentation and a lack of IT
readiness were ranked by survey respondents at the top of the list (consistent
with responses in the past two years).
XDR: Unifying incident detection, response and remediation
The primary driver behind XDR is its fusing of analytics with detection and
response. The premise is that these functions are not and should not be
separate. By bringing them together, XDR promises to deliver many benefits.
The first is a precise response to threats. Instead of keeping logs in a
separate silo, with XDR they can be used to immediately drive response actions
with higher fidelity and greater depth knowledge into the details surrounding
an incident. For example, the traditional SIEM approach is based on monitoring
network log data for threats and responding on the network. Unless a threat is
simple, like commodity malware that can be easily cleaned up, remediation is
typically delayed until a manual investigation is performed. XDR, on the other
hand, provides SOCs both the visibility and ability to not just respond but
also remediate. SOC operators can take precise rather than broad actions, and
not just across the network, but also the endpoint and other areas. Because
XDR seeks to fuse the analysis, control and response planes, it provides a
unified view of threats. Instead of forcing SOCs to use multiple interfaces to
threat hunt and investigate, event data and analytics are brought together in
XDR to provide the full context needed to precisely respond to an incident.
The algorithms are watching us, but who is watching the algorithms?
Improving the process of data-based decisions in the public sector should be
seen as a priority, according to the CDEI. "Democratically-elected governments
bear special duties of accountability to citizens," reads the report. "We
expect the public sector to be able to justify and evidence its
decisions." The stakes are high: earning the public's trust will be key
to the successful deployment of AI. Yet the CDEI's report showed that up to
60% of citizens currently oppose the use of AI-infused decision-making in the
criminal justice system. The vast majority of respondents (83%) are not even
certain how such systems are used in the police forces in the first place,
highlighting a gap in transparency that needs to be plugged. There is a
lot that can be gained from AI systems if they are deployed appropriately. In
fact, argued the CDEI's researchers, algorithms could be key to identifying
historical human biases – and making sure they are removed from future
decision-making tools. "Despite concerns about 'black box' algorithms, in some
ways algorithms can be more transparent than human decisions," said the
researchers. "Unlike a human, it is possible to reliably test how an algorithm
responds to changes in parts of the input.
Microsoft patents tech to score meetings using body language, facial expressions, other data
Microsoft is facing criticism for its new “Productivity Score” technology,
which can measure how much individual workers use email, chat and other
digital tools. But it turns out the company has even bigger ideas for using
technology to monitor workers in the interest of maximizing organizational
productivity. Newly surfaced Microsoft patent filings describe a system for
deriving and predicting “overall quality scores” for meetings using data such
as body language, facial expressions, room temperature, time of day, and
number of people in the meeting. The system uses cameras, sensors, and
software tools to determine, for example, “how much a participant contributes
to a meeting vs performing other tasks (e.g., texting, checking email,
browsing the Internet).” The “meeting insight computing system” would then
predict the likelihood that a group will hold a high-quality meeting. ...
Microsoft says the goal is to help organizations ensure that their workers are
taking advantage of tools like shared workspaces and cloud-based file sharing
to work most efficiently. This also works to Microsoft’s advantage by
encouraging the use of its products such as Teams and SharePoint inside
companies, making future Microsoft 365 renewals more likely.
A family of computer scientists developed a blueprint for machine consciousness
Defining consciousness is only half the battle – and one that likely won’t be
won until after we’ve aped it. The other side of of the equation is observing
and measuring consciousness. We can watch a puppy react to stimulus. Even
plant consciousness can be observed. But for a machine to demonstrate
consciousness its observers have to be certain it isn’t merely imitating
consciousness through clever mimicry. Let’s not forget that GPT-3 can blow
even the most cynical of minds with its uncanny ability to seem cogent,
coherent, and poignant. The Blums get around this problem by designing a
system that’s only meant to demonstrate consciousness. It won’t try to act
human or convince you it’s thinking. This isn’t an art project. Instead, it
works a bit like a digital hourglass where each grain of sand is information.
The machine sends and receives information in the form of “chunks” that
contain simple pieces of information. There can be multiple chunks of
information competing for mental bandwidth, but only one chunk of information
is processed at a time. And, perhaps most importantly, there’s a delay in
sending the next chunk. This allows chunks to compete – with the loudest, most
important one often winning.
AI in Practice, With and Without Data
Data-based methods work well for situations where new data observed do not
deviate too much from old data learned. In particular, data-intensive methods
showed astonishing results in the domains of image, speech, and language
understanding, and also in gaming. In fact, they are the quintessence
implementation of what Economy Nobel Prize Daniel Kahneman refers to as
System-1 in his theory about the mind. Based on this theory, the mind is
composed of two systems: System-1 governs our perception and classification,
and System-2 governs our reasoning and planning. ... To quote Daphne Koller,
“the world is noisy and messy” and we need to deal with noise and uncertainty,
even when data is available in quantity. Here, we enter the domain of
probability theory and the best set of methods to consider is probabilistic
graphical models where you model the subject under consideration. There are
three kinds of probabilistic graphical models, from the least sophisticated to
the most sophisticated: Bayesian networks, Markov networks, and hybrid
networks. In these methods, you create a model that captures all the relevant
general knowledge about the subject in quantitative, probabilistic terms, such
as the cause-effect network of a troubleshooting application.
Organizations with a culture of innovation fuelling business resilience
The study introduced the culture of innovation framework, which spans the
dimensions of people, process, data, and technology, to assess organizations’
approach to innovation. It surveyed 439 business decision makers and 438
workers in India within a 6-month period, before and since COVID-19. The India
study was part of a broader survey among 3,312 business decision makers and
3,495 workers across 15 markets in Asia Pacific region. Through the research,
organizations’ maturity was mapped and as a result, organizations were grouped
in four stages – traditionalist (stage 1), novice (stage 2), adaptor (stage 3)
and leaders (stage 4). Leaders comprise of organizations that are the most
mature in building a culture of innovation1. “Innovation is no longer an
option, but a necessity. We have seen how the recent crisis has spurred the
need for transformation; for organizations to adapt and innovate in order to
emerge stronger,” said Rajiv Sodhi, COO, Microsoft India. “We commissioned
this research to gain better understanding of the relationship between having
a culture of innovation and an organization’s growth. But now, more than
achieving growth, we see that having a mature culture of innovation translates
to resilience, and strength to withstand economic crises to recover,” he
added.
Cyber Resilience During Times of Uncertainty
Current cybersecurity strategies tend to center around stopping potential
threats from getting into your computing and communications infrastructure at
all. To be successful, it requires that no employee ever click on a bad link,
download the wrong file or work from an unsecured Wi-Fi network. However, this
approach is not realistic nor sufficient enough in today’s world, and
impossible in our collective future. That is why business leaders need to
rethink their cyber strategy to adapt to our constantly changing world. In
practice, the concept of cyber resilience is based on a bend-but-not-break
philosophy. It understands that despite significant defensive investments and
best efforts, cyber-criminals will occasionally get in. The cyber resilience
approach is based on the premise that if you organize your defenses to
prioritize resiliency over just computer security, you keep what’s most
important going – your business. No matter what your business might be –
whether it is churning out widgets or keeping the lights on – what’s key is to
keep your most valuable assets unaffected and operational. Implementing this
new goal, from the boardroom down, helps save money and improve results.
Governance Through Code for Microservices at Scale
Don’t go too far and take all decision making away from the development squads.
It’s natural to think that the more we implement and the fewer the choices
developers have to make the better. However, I’ve found that there is such a
thing as going too far. On one of my projects the architecture team was making
all of the decisions and creating frameworks/tools to govern through code. I
still recall vividly one of the developers coming to me and saying “If you
architects want to make all of the decisions and tell us how to implement
things, then put your cell phone number in Pager Duty! If you want me to be
accountable and be woken up at 3 AM when my code breaks in production, then I am
going to make the decisions.” A decentralized governance approach was necessary
and the role of the architect needed to be as a boundary setter. While the
Product Build Squad is designing and building the Microservices Framework and
the Developer Onboarding Tool (using an Inner Source approach with contributions
from other developers), development squads are already using the framework and
tool. Depending on how many development squads your project/program has, you
could have many Microservices with say Version 1.0 of the Microservices
Framework.
Quote for the day:
"Success is often the result of taking a misstep in the right direction." - Al Bernstein
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