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When thinking about cost governance, for example, in an on-premises
infrastructure world, costs increase in increments when we purchase equipment,
sign a vendor contract, or hire staff. These items are relatively easy to
control because they require management approval and are usually subject to
rigid oversight. In the cloud, however, an enterprise might have 500 virtual
machines one minute and 5,000 a few minutes later when autoscaling functions
engage to meet demand. Similar differences abound in security management and
workload reliability. Technologies leaders with legacy thinking are faced with
harsh trade-offs between control and the benefits of cloud. These benefits can
include agility, scalability, lower cost, and innovation and require heavy
reliance on automation rather than manual legacy processes. This means that the
skillsets of an existing team may be not the same skillsets needed in the new
cloud order. When writing a few lines of code supplants plugging in drives and
running cable, team members often feel threatened. This can mean that success
requires not only a different way of thinking but also a different style of
leadership.
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Observers recently recentred the debate on a particular aspect of space
security, namely anti-satellite (ASAT) technologies. The destruction of assets
placed in outer space is high on the list of issues they identify as most
pressing and requiring immediate action. As a result, some researchers and
experts rolled out propositions to advance a transparent and cooperative
approach, promoting the cessation of destructive operations in both outer space
and launched from the ground. One approach was the development of ASAT Test
Guidelines, first initiated in 2013 by a Group of Governmental Experts on Outer
Space Transparency and Confidence-Building Measures. Another is through general
calls to ban anti-satellite tests, to not only build a more comprehensive arms
control regime for outer space and prevent the production of debris, but also
reduce threats to space security and regulate destabilising force. Many space
community members threw their support behind a letter urging the United Nations
(UN) General Assembly to take up for consideration a kinetic anti-satellite
(ASAT) Test Ban Treaty for maintaining safe access to Earth orbit and decreasing
concerns about collisions and the proliferation of space debris.
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Leveraging connections in data is a prominent way of getting value out of data.
Graph is the best way of leveraging connections, and graph databases excel at
this. Graph databases make expressing and querying connection easy and powerful.
This is why graph databases are a good match in use cases that require
leveraging connections in data: Anti-fraud, Recommendations, Customer 360 or
Master Data Management. From operational applications to analytics, and from
data integration to machine learning, graph gives you an edge. There is a
difference between graph analytics and graph databases. Graph analytics can be
performed on any back end, as they only require reading graph-shaped data. Graph
databases are databases with the ability to fully support both read and write,
utilizing a graph data model, API and query language. Graph databases have been
around for a long time, but the attention they have been getting since 2017 is
off the charts. AWS and Microsoft moving in the domain, with Neptune and Cosmos
DB respectively, exposed graph databases to a wider audience.
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So where will observability head in the next two to five years? Fong-Jones said
the next step is to support developers in adding instrumentation to code,
expressing a need to strike a balance between easy and out of the box and
annotations and customizations per use case. Suereth said that the OpenTelemetry
project is heading in the next five years toward being useful to app developers,
where instrumentation can be particularly expensive. “Target devs to provide
observability for operations instead of the opposite. That’s done through
stability and protocols.” He said that right now observability right now, like
with Prometheus, is much more focused on operations rather than developer
languages. “I think we’re going to start to see applications providing
observability as part of their own profile.” Suereth continued that the
OpenTelemetry open source project has an objective to have an API with all the
traces, logs and metrics with a single pull, but it’s still to be determined how
much data should be attached to it.
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Many scaling methods require knowledge of critical values within the feature
distribution and can cause data leakage. For example, a min-max scaler should
fit training data only rather than the entire data set. When the minimum or
maximum is in the test set, you have reduced some data leakage into the
prediction process. ... The one-dimensional frequency plot shown below each
distribution provides understanding to the data. At first glance, this
information looks redundant, but these directly address problems when
representing data in histograms or as distributions. For example, when data is
transformed into a histogram, the number of bins is specified. It is difficult
to decipher any pattern with too many bins, and with too few bins, the data
distribution is lost. Moreover, representing data as a distribution assumes the
data is continuous. When data is not continuous, this may indicate an error in
the data or an important detail about the feature. The one-dimensional frequency
plots fill in the gaps where histograms fail.
Both DevOps and DevSecOps use some degree of automation for simple tasks,
freeing up time for developers to focus on more important aspects of the
software. The concept of continuous processes applies to both practices,
ensuring that the main objectives of development, operation, or security are
met at each stage. This prevents bottlenecks in the pipeline and allows teams
and technologies to work in unison. By working together, development,
operational or security experts can write new applications and software
updates in a timely fashion, monitor, log, and assess the codebase and
security perimeter as well as roll out new and improved codebase with a
central repository. The main difference between DevOps and DevSecOps is quite
clear. The latter incorporates a renewed focus on security that was previously
overlooked by other methodologies and frameworks. In the past, the speed at
which a new application could be created and released was emphasized, only to
be stuck in a frustrating silo as cybersecurity experts reviewed the code and
pointed out security vulnerabilities.
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Corporate skilling programs have been founded on frameworks and models from
the world of academia. Even when we have moved to digital learning platforms,
the core tenets of these programs tend to remain the same. There is a standard
course with finite learning material, a uniformly structured progression to
navigate the learning, and the exact same assessment tool to measure progress.
This uniformity and standardization have been the only approach for
organizations to skill their employees at scale. As a result, organizations
made a trade-off; content-heavy learning solutions which focus on knowledge
dissemination but offer no way to measure the benefit and are limited to
vanity metrics have become the norm for training the workforce at large. On
the other hand, one-on-one coaching programs that promise results are
exclusive only to the top one or two percent of the workforce, usually
reserved for high-performing or high-potential employees. This is because such
programs have a clear, measurable, and direct impact on behavioral change and
job performance.
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The capability of governance across the whole SaaS estate is both nuanced and
complicated. While the native security controls of SaaS apps are often robust,
it falls on the responsibility of the organization to ensure that all
configurations are properly set — from global settings, to every user role and
privilege. It only takes one unknowing SaaS admin to change a setting or share
the wrong report and confidential company data is exposed. The security team
is burdened with knowing every app, user and configuration and ensuring they
are all compliant with industry and company policy. Effective SSPM solutions
come to answer these pains and provide full visibility into the company's SaaS
security posture, checking for compliance with industry standards and company
policy. Some solutions even offer the ability to remediate right from within
the solution. As a result, an SSPM tool can significantly improve
security-team efficiency and protect company data by automating the
remediation of misconfigurations throughout the increasingly complex SaaS
estate.
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Gamification is the beating heart of almost everything we touch in the digital
world. With employees working remotely, this is the golden solution for
employers. If applied in the right format, gaming can help create engagement in
today's remote working environment, motivate personal growth, and encourage
continuous improvement across an organization. ... In the connected workspace,
gamification is essentially a method of providing simple goals and motivations
that rely on digital rather than in-person engagement. At the same time, there
is a tacit understanding among both game designer and "player" that when these
goals are aligned in a way that benefits the organization, the rewards often
impact more than the bottom line. Engaged employees are a valuable part of
defined business goals, and studies show that non-engagement impacts the bottom
line. At the same time, motivated employees are more likely to want to make the
customer experience as satisfying as possible, especially if there is internal
recognition of a job well done.
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What happens if your cloud environment goes down due to challenges outside your
control? If your answer is “Eek, I don’t want to think about that!” you’re not
prepared enough. Disaster preparedness plans can include running your workload
across multiple availability zones or regions, or even in a multicloud
environment. Make sure you have stakeholders (and back-up stakeholders) assigned
to any manual tasks, such as switching to backup instances or relaunching from a
system restore point. Remember, don’t wait until you’re faced with a worst-case
scenario to test your response. Set up drills and trial runs to make sure your
ducks are quacking in a row. One thing you might not imagine the cloud being is
… boring. Without cloud automation, there are a lot of manual and tedious tasks
to complete, and if you have 100 VMs, they’ll require constant monitoring,
configuration and management 100 times over. You’ll need to think about
configuring VMs according to your business requirements, setting up virtual
networks, adjusting for scale and even managing availability and
performance.
Quote for the day:
"Leaders begin with a different question
than others. Replacing who can I blame with how am I responsible?" --
Orrin Woodward
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