How to manage IT infrastructure in a fast-growing company: the DataRobot experience
With Jamf, we offered a new form of employee communication with IT through the
IT Self-Service application. In fact, it is a portal for company employees to
change the status quo in established business processes within the company. Our
position: IT Self-Service is an employee’s first IT companion and the first line
of IT help. The main idea of this service is to create conditions to reduce the
load on the IT-team and reduce the number of open tickets to HelpDesk. This
means more efficient use of the company’s IT resources. ... Since classical
DevOps engineers were at the origin of the company’s IT onboarding process
automation, the scenario of computer preparation for onboarding was implemented
with the world’s most popular DevOps configuration management system, Ansible.
It’s written in Python using the declarative markup language YAML. The approach
was respectable because it solved the problem of preparing computers for both
macOS/Ubuntu platforms with a platform-dependent branching of the deployment
script.
How to make your APIs more discoverable
API discoverability is a key aspect of any API management initiative. The
discoverability of an API directly impacts its adoption and usage. A typical big
enterprise with multiple development teams might build hundreds of APIs that
they would want to reuse internally or share with partners that build
complementary applications. If the teams are not able to discover existing APIs,
they might build a new API with the same functionality. It might lead to a
duplication of efforts and underutilization of the existing API. It is also an
unscalable practice to contact the API developer each time someone wants to use
the API. There needs to be a better and more hands-off way for internal teams
and partners to discover and understand the usage of these APIs without directly
contacting the developers who built them. API discoverability does not just mean
making it easy to find an API by providing an inventory. It should also address
some key aspects that are important for an API consumer, such as understanding
the API through documentation, request and response format, sign-up options, and
the business terms and conditions (in case of a partner) of using the API.
The long-term answer to fixing bias in AI systems
Some of these [long-term fix] recommendations are hard. For instance, one way
these systems get biased is they're obviously being run by for-profit
organizations. The usual players are Google, Facebook and Amazon. They are
banking on their algorithms trying to optimize user engagement, which on the
surface seems like a good idea. The problem is, people don't engage with things
just because they are good or relevant. More often, they engage with things
because the content has certain kinds of emotions, like fear or hatred, or
certain kinds of conspiracy. Unfortunately, this focus on engagement is
problematic. It's primarily because an average user engages with things that are
often not verified, but are entertaining. The algorithms essentially end up
learning that, OK, that's a good thing to do. This creates a vicious cycle. A
longer-term solution is to start breaking the cycle. That needs to happen from
both sides. It needs to happen from these services, the tech companies that are
targeting for higher engagement. They need to start changing their formula for
how they consider engagement or how they optimize their algorithms for something
other than engagement.
Great leaders ask great questions: Here are 3 steps to up your questioning game.
Having a good arsenal of questions at one’s disposal is a must for any leader,
but the one staple of any leader is the open-ended question. Asking open-ended
questions is like adjusting the lens of a camera, opening the aperture to create
a wider field of view. This wider field sets a tone of receptivity, signaling
that you are open to new information, in learning mode, and ready for a dialogue
not a monologue. ... You may have heard the term active listening. It involves
paying close attention to words and nonverbal actions and providing feedback to
improve mutual understanding. But have you ever stopped to consider passive
listening? Passive listening also involves listening closely to the speaker but
without reacting. Instead, passive listening leaves space for silence. By
combining both of these modes, we achieve what we call effective listening. ...
One of the most powerful response techniques is the ability to ask questions.
Questions frame the issue, remove ambiguity, expose gaps, reduce risk, give
permission to engage, enable dialogue, uncover opportunities, and help to
pressure-test logic.
The 10 Immutable Laws of Testing
The bug count measures what annoys our users the most - Bugs aren’t a measure of
quality (that’s measured by things like fitness for purpose, reliable delivery,
cost and other stuff). But bugs are what annoy our users most. If you don’t
believe me, consider this: over 60% of users delete an app if it freezes,
crashes or displays an error message. Cue P!nk. Bugs exist because we write them
into our code: Complexity defeats good intentions - We all know where bugs
come from: Developers writing code (enabled by users who want new
functionality). Bugs are the visible evidence that our code is sufficiently
complicated that we don’t fully understand it. We don’t like creating bugs and
wish we didn’t do it and have developed some coping skills to address the
problem … but we still write bugs into our code. Bugs (like tchotchkes)
accumulate over time—every time we add or change functionality, to be precise
- Everyone has an Aunt Edna where the inevitable result of her going out is
that she brings home some new thing to put on a shelf. The inevitable result of
creating software is more bugs (and, yes, more/better functionality).
Reliable Continuous Testing Requires Automation
Automation makes it possible to build a reliable continuous testing process that
covers the functional and non-functional requirements of the software.
Preferably this automation should be done from the beginning of product
development to enable quick release and delivery of software and early feedback
from the users. ... We see more and more organizations trying to adopt the
DevOps mindset and way of working. Velinov stated that software engineers,
including the QA engineers, have to care not only about how they develop, test,
and deliver their software, but also about how they maintain and improve their
live products. They have to think more and more about the end user. Velinov
mentioned that a significant requirement is and has always been to deliver
software solutions quickly to production, safely, and securely. That’s impacting
the continuous testing, as the QAs have to adapt their processes to rely mainly
on automation for quick and early feedback, he said.
Seven Principles I Follow To Be a Better Data Scientist
Data science is an ever-changing field, thus keeping up with the latest trend
and techniques is essential in ensuring consistent performance at work. For data
scientists who keep a full-time job, it is unrealistic to spend weeks learning
something new to be able to apply it to your working projects. We need to learn
fast, and one way to achieve this is through learning by doing. Rather than
getting lost in too many details and background information in a new concept,
the fastest way to fully grasp it is to follow a trustworthy practical tutorial
and replicate it, then try to make customized innovations to achieve better
results in your projects. Take an example of learning the Random Forest
algorithm. We sure need to know some basics about the algorithm — what it is,
where it can be used, etc. Then we just use it in a current project, following
some tutorials, and see what the results are. Blog posts with examples are great
sources to educate yourself fast, compared to textbooks, or online courses.
Lastly, we troubleshoot the results and look for ways to improve the application
of the algorithm.
What Good Security Looks Like in a Cloudy World
When it comes to security issues and fixes, it is extremely important to be able
to differentiate between new and old findings because this will also eventually
affect the next two pillars: prioritization and remediation. One of the things
DevSecOps tools have made possible is a real-time understanding of what’s
happening in our code, with processes aligned with developer workflows, such as
fixes at commonly accepted gates, like pull requests, and even earlier with
precommit hooks or in-IDE alerts. A similar approach to the way we prevent
issues from being merged into our code base through common CI gating can be
applied to runtime-related tools during the CD phase. In this way, you can
prevent runtime-related issues from reaching production, as well. So if we are
able to discover security flaws while we’re still coding or in predeployment to
production systems, these can be handled now and within the developer or
operational context and need never go into the backlog. This is a very important
distinction between our categories of security issues.
Avoiding the Top Mistakes Made by Tech Startups
Scaling too quickly increases a startup's burn rate, reducing the time it has to
demonstrate key metrics for its next funding round and other milestone events,
Yépez explains. Such a startup can also trash trusted customer relationships by
failing to deliver goods or services as promised. “That burned cash won’t come
back, and neither will that customer,” he cautions. Conversely, limited funding
forces some struggling businesses to assign staff members tasks that fall
outside of their skillsets. “These responsibilities often suffer from poor
execution and may have severe consequences for the startup,” says Thomas Dolan,
co-founder of 28Stone Consulting, an IT and fintech consulting firm. Many
startups also neglect to protect their intellectual property. In their rush to
go to market, some founders unwittingly disclose their core technology, or offer
their core technology, to potential investors and other external parties. Such
activity triggers deadlines for filing patent applications, says Kyle Graves, an
attorney at law firm Snell & Wilmer.
Becoming “cloud smart” — the path to accelerated digital innovation
“Cloud chaos” comes from a landscape of unknowns. What is our enterprise cloud
architecture? How do public and private clouds co-exist? What about edge
computing? How do we align legal and compliance requirements in the multi-cloud
world for heavily regulated industries such as fintech? Those daunting tasks and
risks reflect the multi-cloud complexity and chaos we constantly live in. Having
worked with many organisations transitioning away from “cloud chaos”, I see
similar challenges regardless of the size of the business. It takes a vast
amount of effort to architect and manage multi-cloud platforms. Think about
scalability, interoperability, consistency, and a unified user experience. Think
about the skill sets and knowledge required to build and operate cloud-native
apps. Also, think about automating and optimising cloud management, architect
cloud, and edge infrastructure. Think about connecting and securing apps and
clouds. And finally, think about app security, legal, and compliance among other
areas. These challenges keep CIOs up at night.
Quote for the day:
"Be willing to make decisions. That's
the most important quality in a good leader." --
General George S. Patton, Jr.
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