3 Reasons Why Traceability Should Be a DevOps Priority
One thing that has to be central to your strategy is traceability. You may
have come across the term a few times before. It’s commonly used elsewhere in
the business world, especially with regard to supply chains. Basically, what
it means is keeping track of a commodity or product at every stage of the
production process. Records of the product’s entire manufacturing and
distribution history are kept so that the sources of any problems can later be
determined and dealt with. Traceability thereby ensures that suppliers can act
quickly and decisively in the event of a product recall, for example. Another
advantage of traceability is that it provides additional transparency, which
helps to maintain consumer confidence. As consumers are becoming increasingly
aware of how products are sourced and manufactured, this is now an important
consideration. It reassures consumers that manufacturers and suppliers are
aware of their concerns and that they’re looking out for their best interests.
You can see already, then, how much of this also applies to mobile DevOps.
Traceability in DevOps is about ensuring clarity, accountability and the best
possible end product for the consumer.
After this COVID winter comes an AI spring
Companies emerging from this recession will adapt processes to “vaccinate”
their systems against the next pandemic. In response to supply-chain
disruptions, Volkswagen is considering increasing its 3D printing capabilities
in Germany, which would give the automaker a redundant parts source. The
government-run Development Bank of Japan will subsidize the costs of companies
that move production back to Japan. Bringing production back onshore while
controlling costs will require significant investment in robotics and AI. Even
companies that don’t have their own production capacity, such as online
retailers, plan to use AI to improve the reliability of complex global supply
chains. So a surge in demand for AI talent is inevitable. ... One relatively
new risk that managers must tolerate pertains to data. Even companies that are
not yet exploiting their data effectively now recognize it as a valuable
resource. As startups deploy AI software systems that prove more accurate and
cost-effective than human beings, their early-adopter customers must be more
willing to trust them with proprietary data. That will allow AI companies to
train new products and make them even smarter.
Tackling Fragmentation in Serverless Data Pipelines
Within the AWS ecosystem, a number of services stitched together provide this
experience. And on the analytics team at Equinox Media on which I sit, we’ve
embraced this architectural pattern to it’s fullest — foregoing
self-maintained, provisioned servers to handle data processing — and opting
instead for a parade of SQS queues, SNS topics, Kinesis streams, and of
course, Lambda functions. As a result, diagrams of our data pipelines bear a
visual resemblance to a 6th grader’s Rube Goldberg project. And as the
metaphor suggests, this paradigm presents new organizational challenges to
keep maintenance costs low. When adopting the serverless platform, one thing
you’ll quickly notice is a proliferation in the number of code repositories
your team is maintaining. This is the result of the a common development
pattern that calls for a 1:1 ratio of Lambda functions to repos. And while
there are benefits to having your business logic fragmented into digestible,
bite-sized chunks of code; there are a number of supporting services that are
best not replicated and distributed among them.
Create Symbiotic Relationships with AI in Business
When humans have specific types of problems, we’ve built and trained machines
to solve those problems. Examples include machine learning or ML. The ML
algorithms that can identify cancer in brain images. The algorithms can also
determine the best placements or designs for online ads, and there are deep
learning systems that can predict customer churn in business. At the moment,
we can only imagine how much more productive we will become as we form
symbiotic relationships with AI. Routine tasks that currently take hours or
days could be abbreviated to 10 or 15 minutes with the aid of a digital
partner. From simple exercises like finding a new restaurant to more expert
tasks such as cancer detection, we will increasingly rely on machines for
everyday tasks. Dependence on machines might begin as a “second pair of eyes”
or “ a second opinion,” but our commitment to machines (and AI) will evolve
into full-on digital collaborators. ... Machine learning could bring about a
revolution in how we solve problems to which the principle of “optimal
stopping” applies.
Battling Cybercriminals on the ‘Digital Frontline’
People have a degree of protection when they are sitting amongst their
colleagues. When suspicious emails come in, it is far easier to speak to a
colleague and verify its authenticity. However, as people are now working from
home, and they are isolated and often alone, that becomes much harder. Where
web and email has been the traditional vector for these kinds of attacks, we
are now seeing phishing attempts across multiple platforms, including social
media and SMS. Every nation is being targeted and phishing emails appear in
almost every language. In many ways, this is the largest set of cyber
campaigns we have ever seen. Many of these emails offer falsified information
or promises of help related to the pandemic. In one campaign found by
Proofpoint, they even promise cures – which is something that malicious actors
know the public are interested in and are likely to immediately pay attention
to. These attackers are after personal information from anyone and everyone
such as login credentials, name, date of birth and government ID details, or
want to trick victims into installing malware on systems. A mixture of old,
reskinned and relatively new malware is being used to attack users. We are
looking at a cybercrime gold rush.
Where Tech Meets Community – Harnessing Tech For Good
Indeed, it is when talent, technology and collaboration come together, that
incredible advances can be achieved and at scale. This is exemplified in the
solidarity of the technology sector to make a difference, bringing people
closer across work, learning and entertainment despite lockdowns, and
combating the virus through telemedicine and AI-assisted diagnosis, alongside
helping to accelerate the research and drug development innovation curve. A
notable example is the rapid establishment of the HPC Consortium involving 11
tech firms assisting federal government, industry and academic leaders across
the world with access to expertise and high performance computing capacity.
With a mobilization such as this, it is no surprise that by early April 2020,
50 potential vaccines and nearly 100 possible treatment drugs were in
development. A feat that would have been unimaginable just a few weeks ago and
emergency initiatives and innovations like this can also lay the ground for
long term change, from business and education, to healthcare and government.
Prepare for the rise of the IT automation architect
IT automation architects are typically found in DevOps organizations. It's
fruitless to focus on a comprehensive automation strategy without a
cooperative, integrated DevOps structure already in place. Because of the
specialized nature of the job, architects are typically found in larger
enterprises or those, like many cloud-native startups, that have mature DevOps
practices. There's a wide variety of job titles and associated skills found
under the DevOps umbrella. For example, a recent DevOps skills report from the
DevOps Institute, a learning association for DevOps professionals, identified
more than a dozen DevOps job titles for which organizations are hiring.
"DevOps engineer/manager" was the most common title, cited by 51% of survey
respondents -- who were comprised of IT professionals, DevOps practitioners,
HR managers and consultants. "Automation architect" was the 9th most
cited job title at 15%. The following chart summarizes other notable job
titles and their response rates. When the same group of survey respondents was
asked to rate the importance of various skills to DevOps work, proficiency at
automation ranked at the top, with 66% citing it as very important and only 1%
listing it as optional or unimportant.
How the COVID-19 Pandemic Will Propel Humanity 20 Years Ahead in Tech
Once executives around the world realize that their employees can not only
work in online-first environments but are thriving and being even more
productive, with greater opportunities for collaboration with their peers,
they will embrace this “new” way of doing business. That, in turn, will unlock
many benefits of scale and productivity that were unimaginable in the previous
decades. The key driver of change will be that, now, every vendor or business
partner can be assumed an online-first operator, and dozens and hundreds of
legacy barriers will disappear practically overnight. Essentially, every
business on the planet not only can, but will run like a Silicon Valley
startup. Imagine, instead of attending five conferences a year, we can attend
and collaborate at 50 virtual conferences while being more efficient with our
time, given the removal of all that unnecessary travel. Imagine, if instead of
a few business development conversations in a given quarter, we are able to do
one hundred, now that the vast majority of our peers are in the same Slack or
Telegram groups. Imagine that instead of a few dozen local restaurants, we
will now have the choice to order from thousands.
Massive complexity endangers enterprise endpoint environments
In addition to heightening risk exposure, the failure of critical endpoint
controls to deliver their maximum intended value is also resulting in security
investments and, ultimately, wasted endpoint security spend. According to
Gartner, “Boards and senior executives are asking the wrong questions about
cybersecurity, leading to poor investment decisions. It is well-known to most
executives that cybersecurity is falling short. There is a consistent drumbeat
directed at CIOs and CISOs to address the limitations, and this has driven a
number of behaviors and investments that will also fall short.” “What has
become clear with the insights uncovered in this year’s report is that simply
increasing security spend annually is not guaranteed to make us more secure,”
said Christy Wyatt, President and CEO of Absolute. “It is time for enterprises
to increase the rigor around measuring the effectiveness of the investments
they’ve made. By incorporating resilience as a key metric for endpoint health,
and ensuring they have the ability to view and measure Endpoint Resilience,
enterprise leaders can maximize their return on security investments.”
Q&A on the Book Becoming an Effective Software Engineering Manager
It's all about getting oriented and understanding the team, the work they're
doing, and the company. I typically use a process which can be followed when
landing somewhere new. It involves creating a snapshot of the situation in
which you can begin to work with your team. This snapshot is formed of three
things: your own observations, your manager's observations, and your team's
observations. Your observations are what you see as you settle in and collect
information from your team and your manager. We outline a number of techniques
for new managers to ask questions to discover what's really going on inside
the team, what they're working on, and where there may be ambiguities or
frictions. These involve informal conversations, booking in weekly one-to-one
meetings, and diving deeper into what they're building and why. Then, as well
as doing this downward, we also do this upward by having the new manager ask
their manager about the same things. Do they think differently than what the
team reports? Why? Are they prioritizing well? If not, why not?
Quote for the day:
"There's a fine line between stubbornness and the positive side of that, which is dogged determination." -- @JebBush
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