Speaker 1: You know, it's funny. If you just like look at
Speaker 1: your phone right now, chances are one of your apps
Speaker 1: just updated in the background. Oh yeah, you probably didn't
Speaker 1: even notice, right, you didn't even notice. You open it up,
Speaker 1: there's a new feature, maybe a fresh layout, and the
Speaker 1: application just works.
Speaker 2: It's totally seamless, it really is.
Speaker 1: And you know, have you ever wondered how these modern
Speaker 1: tech giants actually managed to update their software seamlessly, like
Speaker 1: multiple times a day without breaking the internet.
Speaker 2: Especially when you compare it to the old days exactly?
Speaker 1: I mean, think back to that shared pain of older
Speaker 1: software development, the kind that took literally years to release
Speaker 1: a single massive update, and when.
Speaker 2: It finally did arrive, it was inevitably full of bugs.
Speaker 1: Always. So welcome to today's deep dive. If you're our
Speaker 1: learner today, your mission is simple. We are giving you
Speaker 1: the ultimate shortcut to understanding exactly how that modern seamless
Speaker 1: engine works.
Speaker 2: We're basically looking at the difference between a finely tuned,
Speaker 2: continuously running engine and well, a very fragile, very expensive
Speaker 2: house of cards.
Speaker 1: Couldn't have said it better. We're pulling from excerpts of
Speaker 1: the book Azure DevOps explained by Shujazl, Stefano, d'miliani and
Speaker 1: Amit Malik.
Speaker 2: And our goal here isn't to just throw a dictionary
Speaker 2: of technical jargon at you. I mean nobody.
Speaker 1: Wants that, definitely not.
Speaker 2: We want to decode what DevOps actually is at its core,
Speaker 2: because it represents this massive fundamental shift in how teams
Speaker 2: build products and deliver value.
Speaker 1: Right, and we'll be looking at how Microsoft's Azure DevOps
Speaker 1: platform takes those high level, sort of abstract ideas and
Speaker 1: turns them into a mechanical, daily reality for developers.
Speaker 2: It's the practical application of the philosophy.
Speaker 1: Okay, left untack this because before we can really appreciate
Speaker 1: the specific tools Microsoft built, we have to understand the
Speaker 1: pain points they were trying to.
Speaker 2: Solve, right, exactly, you have to look at the history.
Speaker 1: Yeah, for anyone who has been in the industry a while,
Speaker 1: the old waterfall methodology is uh, well, it's a familiar ghost.
Speaker 2: A very haunting one for some people.
Speaker 1: True, we don't need to rehash the entire rigid process
Speaker 1: of moving from requirements to design to implementation. But the
Speaker 1: fatal flaw was always the isolation.
Speaker 2: The silos. Development and IT operations were treated as totally
Speaker 2: separate kingdoms. They shared almost no cross platform knowledge whatsoever, which.
Speaker 1: Is wild to think about now.
Speaker 2: It really is. Developers would write the code on their machines,
Speaker 2: make sure it worked in their highly specific local environment,
Speaker 2: and then essentially toss it over a brick wall to
Speaker 2: the system administrators. Good look, pretty much. Those administrators were
Speaker 2: then tasked with the near impossible job of integrating and
Speaker 2: deploying that foreign code into the real world infrastructure.
Speaker 1: Which is why the customer's roll, or really the lack thereof,
Speaker 1: was such a massive disaster in that model completely. I mean,
Speaker 1: a company could spend a year building a complex system
Speaker 1: based on a design document created on day one, but
Speaker 1: by the time the customer finally sees the working software,
Speaker 1: their needs have entirely changed, and.
Speaker 2: That leads to massive, expensive redesign.
Speaker 1: Right it sounds like the waterfall method is basically like
Speaker 1: paying a contractor to build a house, leaving the country
Speaker 1: for a year and just hoping it looks good when
Speaker 1: you get back.
Speaker 2: That is a terrifying thought.
Speaker 1: Isn't it. But DevOps, on the other hand, is like
Speaker 1: reviewing the house room by room as it's being built,
Speaker 1: so you know you can actually change the paint color
Speaker 1: before it dries.
Speaker 2: If we connect this to the bigger picture, that visual
Speaker 2: perfectly captures the business value. This evolution into DevOps, which
Speaker 2: merges development, IT, operations, and quality assurance. It's entirely about
Speaker 2: breaking projects down into smaller iterative phases.
Speaker 1: Right.
Speaker 2: The sprints exactly sprints. By reviewing daily builds and having
Speaker 2: end of sprint demos, the customer is deeply involved the
Speaker 2: whole time.
Speaker 1: So they aren't just waiting around for a year.
Speaker 2: No, they get a stronger sense of ownership, and it
Speaker 2: guarantees that the development is strictly tied to actual current
Speaker 2: market needs rather than some outdated assumptions from twelve months ago.
Speaker 1: That makes so much sense. So that's the underlying philosophy.
Speaker 1: But the book book lays out six core principles that
Speaker 1: actually make this function in reality.
Speaker 2: With the commandments essentially.
Speaker 1: Yeah, and instead of just listing them out like a
Speaker 1: table of contents, let's imagine how this works in practice.
Speaker 1: The text uses a sample sandbox project called tailwind Traders,
Speaker 1: which is like a retail e commerce.
Speaker 2: App, a great real world example to ground this in.
Speaker 1: Right, So let's say tailwind Traders wants to roll out
Speaker 1: a new dark Mode feature. Under the first two principles
Speaker 1: customer centric action and creating with the end in mind,
Speaker 1: the team isn't just writing code in a vacuum.
Speaker 2: No, they're acting like a true product company. They're building
Speaker 2: short feedback loops with real users to see if dark
Speaker 2: mode actually improves the shopping experience.
Speaker 1: And that leads directly into the third principle, which is
Speaker 1: end to end responsibility.
Speaker 2: Which is a huge cultural shift.
Speaker 1: Huge because in the old siloed days, the front end
Speaker 1: developer builds the dark mode toggle, throws it over the wall,
Speaker 1: and goes home for the weekend.
Speaker 2: And if that toggle causes the entire payment gateway to
Speaker 2: crash on a Friday night, it's the operations team that
Speaker 2: gets the panic phone calls at two in.
Speaker 1: The morning, which is so unfair. But DevOps changes that
Speaker 1: dynamic entirely. The rule is basically, if you build it,
Speaker 1: you run it.
Speaker 2: Yes, if you build it, you maintain it until it's
Speaker 2: end of life.
Speaker 1: That drastically changes how carefully someone writes code, doesn't it
Speaker 1: Knowing you are the one who has to wake up
Speaker 1: at two am to fix a memory leak you created
Speaker 1: adds a whole new level of accountability.
Speaker 2: It forces a cultural shift toward higher quality naturally, but
Speaker 2: to make that work, you have to adopt the fourth principle,
Speaker 2: which is cross functional autonomous.
Speaker 1: Teams, right moving away from the specialists exactly.
Speaker 2: You have to move away from the hyper specialized IT
Speaker 2: culture where you have like one database person, one security person,
Speaker 2: and one front end person. DevOps requires what the industry
Speaker 2: calls T shaped profiles.
Speaker 1: T shaped profiles. I love that visual. The vertical stem
Speaker 1: of the T represents your deep expertise in one area,
Speaker 1: right like maybe writing front end.
Speaker 2: Code, Yes, your core competency.
Speaker 1: But then the horizon unkle bar represents a broad baseline
Speaker 1: of skills across other disciplines, so that front end developer
Speaker 1: also needs to understand the basics of database indexing, automated testing,
Speaker 1: and server administration, which.
Speaker 2: Means the team can function independently. They aren't constantly waiting
Speaker 2: on external specialists to unblock them.
Speaker 1: They can just handle the entire life cycle of that
Speaker 1: dark mode feature.
Speaker 2: Themselves exactly, which brings us to the final two principles,
Speaker 2: continuous improvement and automating everything.
Speaker 1: Yeah, I noticed the book places a massive emphasis on
Speaker 1: eradicating waste through automation, specifically they highlight infrastructure as code
Speaker 1: or IAC.
Speaker 2: Infrastructure's code is basically the silver bullet for one of
Speaker 2: the most persistent headaches in software.
Speaker 1: Development, the snowflake environment.
Speaker 2: The dreaded snowflake environment. Without IAC, teams can figure their
Speaker 2: deployment servers manually over time. An administrator might tweak a
Speaker 2: registry key here or updata specific library there just to
Speaker 2: get something working.
Speaker 1: Just putting bandew right and.
Speaker 2: Fast forward a year. That server is a snowflake. It's
Speaker 2: a completely unique, manually configured setup that is virtually impossible
Speaker 2: to reproduce.
Speaker 1: So when you try to deploy new software into it,
Speaker 1: it inevitably crashes because it expects some undocumented, forgotten tweak exactly.
Speaker 2: But I know you had some thoughts on automating everything.
Speaker 1: I do. Yeah, I have to push back on this
Speaker 1: a little bit. Automating everything sounds incredibly efficient on paper, sure,
Speaker 1: But if we completely remove the human element from that
Speaker 1: final button press, if we just let code provision servers
Speaker 1: and deploy software automatically, aren't teams flying completely blind.
Speaker 2: That's a very common fear.
Speaker 1: I mean, what happens when a sudden, unexpected error occurs
Speaker 1: in the wild. Doesn't the human element act as a
Speaker 1: safety net.
Speaker 2: It's a natural concern, but automated configuration management actually enforces
Speaker 2: safety rather than removing it. Tools like Azure Automation, or
Speaker 2: even third party integrations like Chef and Puppet. They don't
Speaker 2: just mindlessly push code.
Speaker 1: Okay, so what do they do?
Speaker 2: They operate on a principle of desired state enforcement. You
Speaker 2: write a text file that says, this server must always
Speaker 2: have precisely these three ports, open and run this exact
Speaker 2: version of this software.
Speaker 1: Oh I see, So it's constantly checking the reality against
Speaker 1: the blueprint.
Speaker 2: Constantly, like every few minutes. If a human accidentally logs
Speaker 2: in and changes a setting, or if a malicious actor
Speaker 2: tries to alter the environment, the automated tooling detects that
Speaker 2: the server has drifted from its desired state.
Speaker 1: And it just fixes it.
Speaker 2: It instantly overwrites the change to correct it. It resolves
Speaker 2: unexpected variations far faster and more consistently than a human. Ever.
Speaker 2: Could it really eliminates the variability of human error entirely?
Speaker 1: Okay? Wow, that is a brilliant mechanism. It actually makes
Speaker 1: it safer, much safer. So having laid that philosophical groundwork,
Speaker 1: let's move from the abstract principles to the tangible tools.
Speaker 1: We're talking about the Microsoft as your devop.
Speaker 2: Suite, the actual tool belt. Right.
Speaker 1: The text outlines four phase of the app life cycle plan, develop, deliver,
Speaker 1: and operate.
Speaker 2: And the suite is designed to map directly to those phases.
Speaker 2: For planning, you have Azure boards. For developing, you have
Speaker 2: Azure repos handling source control.
Speaker 1: And the text points at a critical distinction here with
Speaker 1: repos right, Azure supports both GET and Team Foundation Version
Speaker 1: Control or TFC.
Speaker 2: Yes, and the distance is architectural.
Speaker 1: I found that comparison really interesting because Git is a
Speaker 1: distributed system. Every single developer has a complete local copy
Speaker 1: of the repository right on their.
Speaker 2: Machine, the entire history, all the branches, everything right, so.
Speaker 1: They can commit changes offline, experiment locally, and only sync
Speaker 1: with the main project when they are totally ready.
Speaker 2: Whereas TFC is centralized, the developers only have the current
Speaker 2: working version on their local machine, all the historical data,
Speaker 2: the branching, and the merging that is all maintained purely
Speaker 2: on the central server.
Speaker 1: Is anyone still using TFFC.
Speaker 2: Modern teams overwhelmingly default to GET for its speed and flexible,
Speaker 2: but TFPC is still supported for legacy enterprise environments.
Speaker 1: The big older companies.
Speaker 2: Right, organizations that require strict centralized audit controls over every
Speaker 2: single code change often still rely.
Speaker 1: On it makes sense, so once the code is in
Speaker 1: the repository, we move to the delivery phase. With Azure pipelines,
Speaker 1: this is the CICD engine, continuous integration and continuous delivery.
Speaker 2: This is the real heartbeat of DevOps.
Speaker 1: Let's look at the actual mechanics here, the nuts and
Speaker 1: bolts of it all. When a developer finishes coding that
Speaker 1: dark mode feature we talked about for tail intraders, they
Speaker 1: don't just like email a ZIP file to a manager,
Speaker 1: definitely not.
Speaker 2: They hit commit in Azure.
Speaker 1: Reposts, and that commit acts as a digital tripwire. Right
Speaker 1: a human doesn't review it to trigger the next step exactly.
Speaker 2: The repository sends an automated webhook to Azure pipelines. Pipelines
Speaker 2: instantly wakes up, reads a configuration file, and spins up
Speaker 2: a pristine, temporary virtual machine.
Speaker 1: A brand new environment every time.
Speaker 2: Every single time, it injects the new dark mode code
Speaker 2: into a copy of the tailin traders app, compiles it
Speaker 2: and runs perhaps thousands of automated security and functional tests
Speaker 2: in a matter of seconds.
Speaker 1: And if even one test fails.
Speaker 2: The pipeline halts. It destroys the virtual machine and alerts
Speaker 2: the developer exactly which line of code broke.
Speaker 1: But if it passes.
Speaker 2: If it passes, the pipeline automatically packages it and deployed
Speaker 2: it to the live production server.
Speaker 1: It's totally seamless.
Speaker 2: Add in Azure test plans for the manual exploratory testing
Speaker 2: by stakeholders and Azure artifacts for sharing packaged code dependencies
Speaker 2: across different teams, and you have the full life cycle.
Speaker 1: And the text also mentions these cool extensions like ARM outputs,
Speaker 1: which uses Azure Resource Manager to dynamically read those infrastructure
Speaker 1: blueprints we.
Speaker 2: Talked about, yes, the IIC files right.
Speaker 1: And team project health which gives visual cues right on
Speaker 1: the dashboard. All these tools are just highly interconnected.
Speaker 2: They feed data into one another continuously. That's a closed loop.
Speaker 1: Here's where it gets really interesting listening to the mechanics
Speaker 1: of these tools triggering one another. It's honestly like operating
Speaker 1: a high end futuristic restaurant kitchen.
Speaker 2: Okay, I like where this is going.
Speaker 1: Think about it. Azure Boards is the order ticket rail
Speaker 1: telling the kitchen staff exactly what needs to be cooked.
Speaker 1: As your repos is the pantry holding all the raw
Speaker 1: ingredients and the history of every recipe ever created. As
Speaker 1: your pipelines is the automated cooking conveyor belt that perfectly
Speaker 1: times the preparation and tests the temperature of the meat.
Speaker 1: Test plans are the head chefs doing the final taste
Speaker 1: testing before the dish.
Speaker 2: Leaves the kitchen and Azure artifacts.
Speaker 1: Those are the signature sauces you bottle up and share
Speaker 1: with other restaurant branches so they don't have to reinvent
Speaker 1: the recipe.
Speaker 2: That is a highly accurate way to map the ecosystem,
Speaker 2: Honestly it is. And the most vital part of that
Speaker 2: kitchen analogy is the automated feedback loop. How soon, well,
Speaker 2: if the head chefs using test plans discover the soup
Speaker 2: is too salty, they don't just throw it away and
Speaker 2: yell at the cooks. That feedback loop instantly goes back
Speaker 2: to the pantry Azure repos to log the air, adjust
Speaker 2: the recipe blueprint, and trigger the pipeline's conveyor built to
Speaker 2: cook a new, corrected badge for the very next bowl
Speaker 2: exactly and all without the restaurant ever closing its doors
Speaker 2: to the public.
Speaker 1: It's an incredible system. But to really give you the learner,
Speaker 1: a practical understanding of how a team actually starts their
Speaker 1: day in this environment, we need to zoom in tightly
Speaker 1: on chapter two's focus.
Speaker 2: Which is Azure boards, right.
Speaker 1: Because before you can automate the kitchen, you have to
Speaker 1: organize the chaos.
Speaker 2: You absolutely do the very first thing a team must
Speaker 2: do when creating a project in Azure DevOps is choose
Speaker 2: a process template.
Speaker 1: And this isn't just a minor setting, No, this.
Speaker 2: Decision dictates the entire organizational vocabulary and hierarchy of your
Speaker 2: work tracking system. Azure provides four main options out of
Speaker 2: the box, Basic, Agile, Scrum, and CMMI.
Speaker 1: Basic is well exactly what it sounds like. It tracks
Speaker 1: simple epics, issues and tasks. Agile, which is actually what
Speaker 1: the tail in traders sandbox project defaults to, tracks features
Speaker 1: user stories and tasks.
Speaker 2: Scrum uses slightly different terminology, focusing on product backlog items
Speaker 2: and bugs to align strictly with the Scrum methodology.
Speaker 1: And then there's CMMI, which is a whole other beast.
Speaker 2: CMMI stands for capability, maturity, model integration. It is a
Speaker 2: highly formal, incredibly rigorous template. Not just user stories then No,
Speaker 2: Instead of just tracking user stories, attracts detailed requirements, mandatory
Speaker 2: change requests, risk assessments, and formal reviews.
Speaker 1: Which raises a really practical question. With so many templates available, Agile, Scrum, Basic,
Speaker 1: the super formal CMMI, how does a team know which
Speaker 1: one to pick without getting totally bogged down in like
Speaker 1: process for the sake of process.
Speaker 2: Right, why wouldn't everyone just pick basic and move as
Speaker 2: fast as possible?
Speaker 1: Exactly?
Speaker 2: What's fascinating here is that Azure boards forces teams to
Speaker 2: deliberately choose their level of bureaucracy right up front. It
Speaker 2: forces a conversation about regulatory.
Speaker 1: Reality, ragilatory reality.
Speaker 2: Give me an example. Sure, a small, fast moving startup
Speaker 2: building a social media app will likely choose basic or agile.
Speaker 2: Their primary risk is moving too slowly. They just need
Speaker 2: to track features and fixed bugs.
Speaker 1: But consider a major bank, right, or a healthcare company
Speaker 1: developing software that manages patient records.
Speaker 2: Exactly. They can't just move fast and break things.
Speaker 1: No, absolutely not.
Speaker 2: They must use CMMI. When a developer at a bank
Speaker 2: changes how an interest rate is calculated. Regulators require an
Speaker 2: auditable paper trail to prove what happened right, proving that
Speaker 2: a risk assessment was performed, that a formal change request
Speaker 2: was filed, and that multiple stakeholders signed off on the
Speaker 2: exact line of code. CMMI bakes that compliance directly into
Speaker 2: the daily workflow.
Speaker 1: It's about matching the digital tool directly to the organizational
Speaker 1: reality precisely. Let's look at the mechanics of the agile templates,
Speaker 1: since that's what so many modern teams use. The core
Speaker 1: unit of work is the work item. The text gives
Speaker 1: a great example of creating a user story. As a user,
Speaker 1: I want to edit my user profile.
Speaker 2: But in Azure Boards, this isn't just a digital sticky note.
Speaker 1: Far from it. The anatomy of that work item is
Speaker 1: incredibly deep.
Speaker 2: It functions as the single source of truth for that
Speaker 2: specific feature. You can add searchable tags like profile improvements,
Speaker 2: you track its state moving from new to active to closed.
Speaker 1: And it has its own internal social network for discussion,
Speaker 1: which I thought was really cool.
Speaker 2: It's very useful.
Speaker 1: You can just type the at at symbol to mention
Speaker 1: specific developers to ask a question or use the hashtag
Speaker 1: symbol to link the conversation directly to a specific pull
Speaker 1: request in the code repository.
Speaker 2: It keeps all the context attached to the work itself,
Speaker 2: rather than buried in some separate email chain or chat
Speaker 2: app where it gets lost.
Speaker 1: And crucially, the team assigns story points to the work item.
Speaker 2: Yes, and we should clarify this isn't a measurement of hours.
Speaker 1: Right, It's a numeric value that estimates the abstract complexity
Speaker 1: and effort required to build the feature over time. By
Speaker 1: tracking how many story points the team successfully completes in
Speaker 1: a two week sprint, the software calculates the team's velocity.
Speaker 2: Which gives project managers highly accurate, data driven forecasting for
Speaker 2: when future features will actually be delivered, rather than just guessing.
Speaker 1: All of these work items live in the backlog, which
Speaker 1: acts as the master roadmap. Project managers can literally drag
Speaker 1: and drop items up and down the list to instantly
Speaker 1: reprioritize what the team should focus on next.
Speaker 2: And from that backlog items are pulled onto the canbin board.
Speaker 1: That's the visual part, right.
Speaker 2: This provides the visual flow of the work through columns new, active, resolved,
Speaker 2: and closed.
Speaker 1: New is work prioritized but not yet started. Obviously, active
Speaker 1: is the code the team is writing right now.
Speaker 2: Resolved means the developer believes the code is done, but
Speaker 2: it's sitting in the testing phase, and closed means it
Speaker 2: has fully met the team's definition of done and is
Speaker 2: out there in the customer's hands.
Speaker 1: The text mentions that teams use a specific sprint taskboard
Speaker 1: view during their daily stand up meetings. They look at
Speaker 1: the active column, discuss what's in progress, and immediately flag
Speaker 1: any roadblocks.
Speaker 2: And when you are dealing with enterprise software, you might
Speaker 2: have thousands of these items floating around.
Speaker 1: Which sounds overwhelming, but Azur DevOps solves that noise with queries.
Speaker 2: Right, Yes, queries are essential. You can build a custom
Speaker 2: query to filter the database, for.
Speaker 1: Example, showing only the work items assigned to you, tagged
Speaker 1: with profile improvements that are currently stuck in the resolved state.
Speaker 2: It cuts through the overwhelming scale of the project to
Speaker 2: show you exactly what needs your attention today. It basically
Speaker 2: prevents anything from falling through the cracks.
Speaker 1: So to pull all these threads together. What we've learned
Speaker 1: from az your DevOps explained is that this isn't just
Speaker 1: a fancy suite of software tool not at all as
Speaker 1: your DevOps is the digital manifestation of a massive cultural shift.
Speaker 1: It takes these high minded principles, shared end to end responsibility,
Speaker 1: dismantling isolated silos, automating manual waste, and it provides a literal,
Speaker 1: tangible dashboard to ensure a team actually practices what they
Speaker 1: reach from.
Speaker 2: The Azure boards, keeping the human element aligned to repose,
Speaker 2: securing the code history to pipelines, executing the automated delivery
Speaker 2: trip wires.
Speaker 1: The platform essentially forces best practices into the muscle memory
Speaker 1: of the organization.
Speaker 2: That's a great way to put it. A company can't
Speaker 2: really slip back into isolated waterfall mindset when their entire
Speaker 2: daily tool set is mechanically built around short, iterative sprints,
Speaker 2: continuous integration, and transparent cross functional communication.
Speaker 1: So what does this all mean for you? Even if
Speaker 1: you aren't writing a single line of code today, Understanding
Speaker 1: this specific workflow is the ultimate shortcut to understanding how
Speaker 1: modern successful businesses operate. It really is the speed at
Speaker 1: which a company can move an idea from an Azure
Speaker 1: board's canban column, through an automated pipeline and into a
Speaker 1: customer's hands. That is the defining metric of success in
Speaker 1: the modern economy.
Speaker 2: And I'd like to leave you with a final thought
Speaker 2: to maul over applying these concepts beyond software.
Speaker 1: Oh, I like this.
Speaker 2: We've seen how the six principles of DevOps, like building
Speaker 2: cross functional skills, breaking down isolated silos, and using desired
Speaker 2: state automation to free up human creativity, how they radically
Speaker 2: transform enterprise teams. Sure, but what if you applied those
Speaker 2: exact same engineering principles to your own life?
Speaker 1: Wait?
Speaker 3: Really like personal DevOps exactly? Take a look at your
Speaker 3: personal projects or daily routines. What manual repetitive tasks are
Speaker 3: acting as your own personal snowflake environments holding you back
Speaker 3: from operating efficiently.
Speaker 1: During your own life. Like a highly optimized DevOps pipeline,
Speaker 1: I love that. Figure out what repetitive tasks need automating
Speaker 1: so you can focus your energy on the final product.
Speaker 1: And maybe, just maybe, if you get your own continuous
Speaker 1: integration pipeline running smoothly, the next time you update a
Speaker 1: habit or routine, it will deploy seamlessly in the background,
Speaker 1: just like those apps on your phone, without breaking a sweat.
Speaker 1: Thanks for diving deep with us. Today,