4 key devsecops skills for the generative AI era
CIOs and IT leaders must prepare their teams and employees for this paradigm shift and how generative AI impacts digital transformation priorities. Nicole Helmer, VP of development and customer success learning at SAP, says training must be a priority. “Companies should prioritize training for developers, and the critical factor in increasing adaptability is to create space for developers to learn, explore, and get hands-on experience with these new AI technologies,” she says. The shift may be profound and tactical as more IT automation becomes productized, enabling IT to shift to more innovation, architecture, and security responsibilities. “In light of generative AI, devops teams should deprioritize basic scripting skills for infrastructure provisioning and configuration, low-level monitoring configurations and metrics tracking, and test automation, says Dr. Harrick Vin, chief technology officer of TCS. “Instead, they should focus more on product requirements analysis, acceptance criteria definition, software, and architectural design, all of which require critical thinking, design, strategic goal setting, and creative problem-solving skills.”
Don't neglect API functional testing
The first step to building a successful API functional testing strategy is to
understand each API, its functions and its requirements. API requirements are
often found within API documentation, but specific and necessary details are
sometimes omitted. Work with the API developers to ensure documentation
includes the expected behavior under all scenarios, error conditions and
status codes, the API's purpose and objective, and how the API affects the
application workflow. As a QA tester responsible for functional API testing,
create a test plan and approach. Next, select an API testing tool that enables
testers to create and execute both automated and manual tests. Many existing
QA and developer tools include an option for API testing. Check the
capabilities of your existing tools before adding another. Next, create a test
plan, and develop test cases. Once the test cases are created, organize them
into all working combinations. One option is to create tests and then execute
them. Or, within many tools, testers can quickly test as they go. In other
words, you can be testing each request as you develop the test.
Decentralization stands as one of the most profound principles championed by
blockchain. While the term often evokes images of intricate algorithms and
cryptographic nodes, its implications on leadership and organizational
structuring are profound. At its core, decentralization heralds a departure
from the age-old top-down management models. Consider the rise of
decentralized finance (DeFi) platforms, which are disrupting traditional
banking systems. Instead of a centralized authority making decisions, these
platforms empower their users through consensus mechanisms and democratized
governance. Compound, a leading DeFi platform, is a testament to this.
It operates with a decentralized governance model where token holders
propose, discuss, and implement changes to the platform. This not only
ensures transparency, but also inculcates a deep sense of ownership among
its participants. This decentralization isn't just confined to the crypto
realm. Businesses are realizing the value of distributed decision-making.
For instance, the Spotify model of team organization, where squads, tribes,
chapters, and guilds collaborate across functions, exemplifies a shift from
rigid hierarchies to fluid, decentralized structures.
Shaping finance through technological prowess
In the present scenario, technology stands as the cornerstone of well-informed
decision-making for CFOs. The integration of data analytics and artificial
intelligence can equip CFOs with robust tools to dissect vast data sets,
enabling them to make precise predictions and optimise resource allocation.
For instance, predictive analytics has emerged as a powerful instrument that
can enable CFOs to anticipate market trends and customer behaviour, thereby
guiding financial strategies with unprecedented precision. Consider a scenario
where a CFO of a manufacturing company leverages data analytics to optimise
inventory management. By analysing historical sales data, production rates,
and external market factors, the CFO can use tools to predict demand
fluctuations and adjust inventory levels accordingly. This approach may not
only minimise excess inventory costs but also ensure that the company is
well-prepared to meet customer demands swiftly. The financial decision-making
process has transitioned from a reactive stance to one driven by data-driven
insights, propelling the company toward financial agility.
Soon, every employee will be both AI builder and AI consumer
The time could be ripe for a blurring of the lines between developers and
end-users, a recent report out of Deloitte suggests. It makes more business
sense to focus on bringing in citizen developers for ground-level programming,
versus seeking superstar software engineers, the report's authors argue, or --
as they put it -- "instead of transforming from a 1x to a 10x engineer,
employees outside the tech division could be going from zero to one." ...
Automated platforms and generative AI -- leveraged within an open and
supportive corporate culture -- may amplify many human skills, they continue.
"10x engineers could become much less rare. Especially as generative AI
continues to bolster developer productivity and opens up a future of increased
workplace automation, many of today's hindrances may not be relevant in the
next five to 10 years." It's all about fostering a superior "developer
experience," not just within IT shops, but across the enterprise as well. "As
technology itself continues to become more and more central to the business,
technology tasks and required talent will likely become central as well.
..."
How CTOs can win over the board room
Now is the time for engineering leaders to showcase engineering’s value.
There’s not a single business that hasn’t been impacted by resource tightening
over the last year. While CFOs are increasingly focusing on cost optimization
within their businesses, they continue to prioritize growth, according to a
survey by Gartner. Engineering leaders must show how they’re driving this
growth. Engineering leaders who couldn’t clearly show major business impact
were the first to see cuts during 2022 recession concerns. While the rest were
forced to “do more with less,” they were at least able to sustain critical
projects and fight for their headcount. Why? Because they clearly communicated
the importance of specific investments and projects to the business’s success.
No one can argue the last year has been easy for leaders across the board. But
I believe good is coming from these challenges. It has forced engineering
leaders to scrutinize their investments and allowed them to identify their
most critical assets, enabling them to innovate even during economic
uncertainty.
Data Privacy Paradox: Balancing Innovation with Protection in the Age of AI
While AI’s potential for progress shines bright, its foundation rests upon a
vast ocean of personal data – our online activity, location trails, and even
social media whispers. This dependence raises a chilling specter: data
surveillance. The specter of governments and corporations peering over our
digital shoulders, gleaning insights into our lives, fuels fears of mass
surveillance and the potential misuse of this sensitive information. This
specter chills not only with its invasive nature, but also with its chilling
implications for individual freedoms and potential abuses of power. But the
concerns go beyond the watchful eye of Big Brother. AI’s algorithms, trained
on vast datasets, can become unwitting vessels of algorithmic bias. Imagine a
credit scoring system fueled by biased data, unfairly disadvantaged certain
demographics. Or a criminal justice system where AI-powered predictions
exacerbate existing prejudices. These are not dystopian nightmares; they are
real possibilities if we fail to address the inherent biases that can creep
into the heart of AI. Furthermore, the inner workings of these algorithms
often remain shrouded in a veil of secrecy.
Why You Are So Resistant to Change — And How to Overcome It
As an entrepreneur, your ability to change and adapt is arguably the single
most important contributor to long-term success. Stagnant businesses simply
can't flourish, grow or (like those heart patients unwilling to modify their
habits) survive. Ask yourself, how receptive are you to transformation in
yourself, your processes, and your entire organization? Now is the time to
evolve as a business owner. Start with an unwavering desire for continuous
improvement. The next step is finding that emotional connection and the people
or groups who can support you on your journey of change. For business leaders,
these relationships are often found outside of one's own company in the form
of peer advisory boards or mastermind groups. Peer advisory boards provide
business owners with the requisite support and emotional connection that act
as catalysts for forward progress and even innovation. As the president and
CEO of such an organization, I get to witness the transformative power of
connection all the time. It is truly amazing to see what can happen between
owners and executives who care about each other's welfare and respect, support
and elevate each other on their paths to transformation.
Open Source in 2024: More Volatility, More Risk, More AI
But there’s plenty in the way of increased international cooperation around
tech – or indeed, international cooperation around anything. To paraphrase a
former British prime minister, the greatest challenge for a leader is,
“Events, dear boy. Events” If the last three years have been event-packed,
2024 will be equally so, not least because of an unprecedented number of
elections due, including the U.S. presidential race. These elections become
cybersecurity incidents themselves. But they could also herald and shape
further regulation and legislation that could directly affect the open source
world Both the U.S. and E.U. have been putting in place legislation and
regulation around AI, but it is 2024 that will see how these efforts start
playing out in the real (virtual) world. The European Union’s Cyber Resiliency
Act will also come into effect in 2024. Recently announced revisions have
reportedly made it less overtly problematic for open source, but the final
text is yet to be released. At the same time, the U.S. has already been
turning the technology screws on China and Russia, choking off exports of GPUs
to the former, for example, and enforcing wide-ranging sanctions on the
latter.
Infrastructure, Operations Leaders Must Focus on DevOps, SRE Initiatives
Rajesh Ganesan, president of IT ManageEngine, notes data breaches and data
privacy law violations can do irreparable damage to an organization's
reputation. “By making privacy and data governance a top priority in 2024,
I&O leaders can ensure their organizations are compliant with privacy laws
and protected against data breaches,” he explained in an email interview. “It's
crucial that every employee in the organization takes personal responsibility
for data privacy.” Ganesan points out if organizations have the financial means,
it is wise to invest in private data centers. “Organizations that invest in
their own domain controller and security operations can control their security
posture and make sure poor levels of security from the public service provider
does not affect them,” he says. Not only are these companies protected from any
breaches that occur in a public cloud environment, but they also have an easier
time complying with legislation, as specific control measures can be put in
place.
Quote for the day:
"Don't judge each day by the harvest
you reap but by the seeds that you plant." --
Robert Louis Stevenson
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