Speaker 1: Welcome to the deep dive. We're jumping straight into what
Speaker 1: it takes to build and deliver software better, not just
Speaker 1: you know, the coding itself, but the whole process getting
Speaker 1: it out there efficiently, securely, all.
Speaker 2: Of that exactly. And we've got a really rich set
Speaker 2: of information we're drawing from mostly this comprehensive guide. It
Speaker 2: looks at everything from managing projects right inside GitHub to
Speaker 2: some pretty advanced security practices. It even digs into how
Speaker 2: team structures well, how they influence the software itself, and to.
Speaker 1: Give us a wider perspective, we're also pulling in some
Speaker 1: industry reports, articles, that kind of thing. They provide some
Speaker 1: real world context, some data to back things up. Yeah.
Speaker 2: Absolutely so for you listening, our goal here is to
Speaker 2: cut through the noise, really pull out the key insights
Speaker 2: on how to well level up your software delivery.
Speaker 1: Whether you're writing code, managing.
Speaker 2: A team, or maybe just curious about how modern software
Speaker 2: development actually works. We're aiming to give you that core
Speaker 2: knowledge without burying you in details.
Speaker 1: Okay, so the question, the central mission for today is
Speaker 1: what are the most effective practices, the best tools that
Speaker 1: software teams can leverage right now to speed things up?
Speaker 2: Speed up development, speed up delivery.
Speaker 1: But and this is key while keeping quality and security
Speaker 1: absolutely top priorities.
Speaker 2: Exactly, And the guide we're using really kicks off with
Speaker 2: this idea, this fundamental point. Software development is a team
Speaker 2: sport totally and right at the heart of that teamwork,
Speaker 2: you find the poll request.
Speaker 1: Ah, the poll request, So when a developer wants to
Speaker 1: propose changes, that's the mechanism, that's it. The guide walks
Speaker 1: through it, creating them draft prs for work in progress
Speaker 1: code owners. Code owners, yeah, saying who needs to look
Speaker 1: at what? And required reviews. Obviously can't merge without those checks.
Speaker 2: We won't get bogged down in every single click. But
Speaker 2: it sets the stage for collaboration.
Speaker 1: But what's really interesting is the emphasis on making those
Speaker 1: code reviews effective.
Speaker 2: Yes, the guide really hammers this home well. Structured commits
Speaker 2: are key. Each commit should tackle one single logical change,
Speaker 2: and the commit message it needs to be clear what
Speaker 2: did you do and why did you do?
Speaker 1: It makes total sense trying to review a giant commit
Speaker 1: with mixed up changes and a vague message like fixed
Speaker 1: stuff forget.
Speaker 2: It impossible, right, And it specifically warns against mixing, refactoring,
Speaker 2: you know, just cleaning up code with adding new business
Speaker 2: logic in the same commit Oh yeah, that.
Speaker 1: Just muddies the waters for the reviewer completely.
Speaker 2: Keep them separate. Reviewers can focus on the actual functional change,
Speaker 2: understand its impacts.
Speaker 1: Makes the whole process way more efficient, and you're more
Speaker 1: likely to catch issues early.
Speaker 2: Exactly, it's just good practice.
Speaker 1: Okay, let's think about how teams actually work today. So
Speaker 1: often they're spread out right, different places, different time zones.
Speaker 2: Distributed teams are becoming.
Speaker 1: The norm, and the Guide spends some time on this
Speaker 1: shift towards asynchronous communication.
Speaker 2: It's interesting if you look at the history communication shifts
Speaker 2: used to take generations. Now it feels like every few years, smartphones,
Speaker 2: the Internet, it's pushed us towards preferring ACNC stuff quick messages,
Speaker 2: emails where you don't always expect an instant reply.
Speaker 1: I remember when waiting a day for an email reply
Speaker 1: was totally normal. Now it's like, if you don't hear
Speaker 1: back in.
Speaker 2: An hour, you start wondering, right, But for distributed teams,
Speaker 2: that expectation of instant replies that can actually slow things.
Speaker 1: Down oddly enough, become a bottle lick.
Speaker 2: Hey, exactly, And that's where ACNC workflows really shine. The
Speaker 2: guide highlights a few best practices here. One big one
Speaker 2: prefer chat platforms over email for work discussions. Why is
Speaker 2: that keeps the conversation history all in one place. If
Speaker 2: someone's offline, the info isn't just stuck in their personal inbox,
Speaker 2: anyone can catch up.
Speaker 1: Yeah, email threads could become absolute monsters. The other really
Speaker 1: interesting suggestion was making most meetings optional.
Speaker 2: Right, this is a big one. It forces you to
Speaker 2: ask is this meeting really necessary for everyone invited? The
Speaker 2: thinking is if people don't see clear value, they should
Speaker 2: feel okay skipping it.
Speaker 1: Which puts the pressure on the meeting organizer to make
Speaker 1: it worthwhile.
Speaker 2: Be focused, prepared, know that people are choosing to spend
Speaker 2: their time there.
Speaker 1: Now, obviously some meetings you need everyone for team building,
Speaker 1: big company updates.
Speaker 2: Of course, the guide acknowledges that it's not about eliminating meetings,
Speaker 2: but making them more intentional.
Speaker 1: Okay, so keeping all this work organized tracking it. The
Speaker 1: guide talks quite a bit about getub projects as a
Speaker 1: platform for that.
Speaker 2: Yeah, it's presented as really adaptable. You can add all
Speaker 2: sorts of work items, tasks, bugs, features.
Speaker 1: Whatever, and attach metadata.
Speaker 2: Exactly status, priority, who's assigned all that stuff? And it
Speaker 2: highlights two main views, the table.
Speaker 1: View good for data entry sorting right, and the board.
Speaker 2: View that visual canban style, drag and drop thing.
Speaker 1: Lots of teams love that visual overview is huge for
Speaker 1: seeing where things stand, spotting blockers.
Speaker 2: Quickly, and the guide mentions the beta version of projects
Speaker 2: is where things are headed even more flexible, easier to
Speaker 2: to share configurations across teams. That's the future direction and
Speaker 2: a core part of planning and tracking. In Geithub issues
Speaker 2: Right GitHub issues, the guide explains how they're used for
Speaker 2: well everything, tracking tasks, suggesting features, logging bugs, and they're collaborative,
Speaker 2: totally full history linked directly to commits, pull requests, even
Speaker 2: other related issues.
Speaker 1: So issues become the central hub for anything related to
Speaker 1: a specific piece of work or problem pretty much.
Speaker 2: And there are some neat features like creating hierarchies. Breaking
Speaker 2: down big tasks into smaller subtasks makes things more manageable and.
Speaker 1: The filtering and sorting powerful.
Speaker 2: The guide points out that every filter you apply just
Speaker 2: adds text to the search bar, so it's super transparent.
Speaker 2: You can quickly see status labels, linked prs.
Speaker 1: Everything and for consistency especially with lots of different types
Speaker 1: of issues flying around. The guide really pushes issue templates.
Speaker 2: Oh, this is smart. You can create templates using markdown
Speaker 2: for free form texts, or yammel or yamal for structured forms,
Speaker 2: text boxes, drop downs, check boxes. You can even make
Speaker 2: fields required.
Speaker 1: Ensure as you get all the essential info.
Speaker 2: Upfront, right standardizes things mix processing new issues much faster.
Speaker 1: Okay, let's zoom out a bit talk about the influence
Speaker 1: of open source and this related idea of inner source.
Speaker 1: The guide as a whole chapter on this.
Speaker 2: Yeah, and it gives some interesting historical context the free
Speaker 2: software movement. How open source became the preferred term in
Speaker 2: the late nineties, Eric.
Speaker 1: Raymond, Bruce Parrins the Open Source Initiative exactly.
Speaker 2: Linus Torvalds, creators of Pearl Python, getting those key figures
Speaker 2: on board early was huge.
Speaker 1: It's amazing how much foundational tech is open source now.
Speaker 1: But the guide makes a great point. It's not just
Speaker 1: about using open source code, No, it's.
Speaker 2: About learning from how those successful open source projects work,
Speaker 2: the collaboration models.
Speaker 1: And applying those principles inside your own company.
Speaker 2: That's inner source. Yeah, it can really boost collaboration between
Speaker 2: internal teams help share knowledge, but.
Speaker 1: The guide is bound, so it warns about risks too, right, license.
Speaker 2: Compliance big one, and understanding that if an open source
Speaker 2: component has a bug or vulnerability, well that's now potentially
Speaker 2: your problem too. Managing dependencies is.
Speaker 1: Critical, which leads to that strategic decision. Yeah, build it
Speaker 1: yourself insourcing or use external stuff outsourcing?
Speaker 2: Yeah, the guide suggests you really need to think is
Speaker 2: this software core to our business? Does it give us
Speaker 2: a competitive edge? If it is generally? Build it internally,
Speaker 2: maybe some cosourcing, but own that expertise long.
Speaker 1: Term makes sense. You don't outsource your secret sauce.
Speaker 2: But for non core stuff, outsourcing or leveraging good open
Speaker 2: source solutions can be smarter, less risk than being the
Speaker 2: only customer for something niche, potentially better quality from a
Speaker 2: wider community.
Speaker 1: And connecting to all. This is getub sponsors.
Speaker 2: Right, a direct way for companies, even individuals to financially
Speaker 2: support the maintainers of open source projects they depend.
Speaker 1: On giving back helping keep those projects sustainable. Okay, let's
Speaker 1: pivot to a core DevOps practice automation with GitHub actions.
Speaker 1: Big section on this.
Speaker 2: Yeah, this is where we really start talking about accelerating
Speaker 2: the delivery pipeline. The guide breaks down the basics. Workflows
Speaker 2: are your automated processes.
Speaker 1: Pipelines are the stages.
Speaker 2: Actions are the individual steps, and it introduces YAML, the
Speaker 2: language you use to define.
Speaker 1: All this YAML. That indentation can look a bit scary
Speaker 1: at first.
Speaker 2: You can, but the guide explains the basics pretty well, comments,
Speaker 2: data types, how lists and dictionaries work. It helps get
Speaker 2: you started. Then it moves into defining a workflow, giving
Speaker 2: it a name, setting up the triggers.
Speaker 1: The triggers the events that kick off the workflow.
Speaker 2: Exactly and they're super flexible. Run on a push to
Speaker 2: a specific branch like main or release branches, or when
Speaker 2: a pull request is opened, or as signed or labeled,
Speaker 2: even on a schedule. Lots of control over when things
Speaker 2: run automatically.
Speaker 1: Now automation, especially deployments, you need to handle secrets securely. Yeah,
Speaker 1: API keys.
Speaker 2: Path absolutely critical. The guide emphasizes this. GitHub provides secure
Speaker 2: storage for secrets at the repository level ORG level, even
Speaker 2: for specific deployment environments.
Speaker 1: Encrypted never shown in logs.
Speaker 2: Right at the org level, you can control which repos
Speaker 2: can access which secrets. For environment secrets, you can even
Speaker 2: require manual approval before a workflow uses them extra security.
Speaker 1: Layer, and you can manage secrets via the CLI too
Speaker 1: for scripting m HM.
Speaker 2: The guide mentions that, and it clearly shows how to
Speaker 2: use secrets in your workflow, using the secrets context, passing
Speaker 2: them as inputs to actions, or as environment variables.
Speaker 1: What about building your own actions, not just using ones
Speaker 1: from the marketplace.
Speaker 2: The guide covers that too. Walk through an example. Define
Speaker 2: an action dot AML file describing inputs, outputs, how it runs, and.
Speaker 1: An entry point dot S script with the actual commands exactly.
Speaker 2: You define what inputs your action needs, what outputs it produces.
Speaker 2: It's pretty powerful and.
Speaker 1: If you build something cool, you can share it on
Speaker 1: the marketplace.
Speaker 2: Yep, publish it, let others use it. Builds that whole
Speaker 2: ecosystem of reusable automation components.
Speaker 1: Okay, last bit on actions. Where do these workflows actually run?
Speaker 1: Hosted versus self hosted runners?
Speaker 2: Right? GitHub hosted runners are vms managed by GitHub, Linux, Windows, macohsts.
Speaker 2: Each job runs in a fresh, isolated environment.
Speaker 1: Isolation sounds good for security and you get admin privileges.
Speaker 2: That's surprising, it is, But the downside can be build times.
Speaker 2: If you need lots of tools installed each run and cost.
Speaker 1: How does cost work?
Speaker 2: Free for public repos Mostly private repos get an allocation
Speaker 2: of minutes and storage with your plan go over you might.
Speaker 1: Pay extra and self hosted.
Speaker 2: You provide the infrastructure. You manage. The machines might be
Speaker 2: necessary for specific network rules like ip alo lists. More control,
Speaker 2: but more management overhead.
Speaker 1: Okay. Automated builds are sorted. Now managing the packages. The
Speaker 1: dependencies getub packages.
Speaker 2: This is about managing dependencies in a structured way. The
Speaker 2: guide mentions popular register NPM for JavaScript, Docker for containers,
Speaker 2: nugit for dot net, and.
Speaker 1: You can integrate these with GitHub actions roamlessly.
Speaker 2: You can automate the whole release process. Build succeeds dot
Speaker 2: BA back publish to the registry.
Speaker 1: And using semantic versioning major minor patches. Yeah.
Speaker 2: The guide stresses using simber and automating the versioning with actions.
Speaker 2: Trigger a workflow on a new GitHub release. It automatically
Speaker 2: bumps the version using tools like NPM version or git version,
Speaker 2: then publishes the package. Streamlines everything fewer errors.
Speaker 1: For container images, it mentions the git ub container registry,
Speaker 1: GHCR dot io.
Speaker 2: Right images can be owned by ords or users, fine
Speaker 2: grained access.
Speaker 1: Control, and again automate it with actions.
Speaker 2: Build the docker image, log in securely using the jit
Speaker 2: hub token, push the image. It makes sharing code as
Speaker 2: containers or versioned packages much much smoother solves a lot
Speaker 2: of release headaches.
Speaker 1: Okay, codes packaged now, deployment infrastructure as code iac and automation.
Speaker 2: There super fundamental and modern DevOps IC means managing your
Speaker 2: infrastructure servers, networks, databases using code, not manual clicks. The
Speaker 2: guide lists the big tools Terraform, polumy, Ancable, chef Puppet.
Speaker 1: It makes a point though, just because a tool supports
Speaker 1: multiple clouds doesn't mean your exact config works everywhere without changes.
Speaker 1: Right correct.
Speaker 2: You'll still need some cloud specific bits, but the core
Speaker 2: benefit is consistency, repeatability in managing infrastructure.
Speaker 1: How do team structure deployment responsibility?
Speaker 2: The guide mentions a few models centralized where an OPS
Speaker 2: team handles everything, Decentralized where feature teams deploy their own services,
Speaker 2: more and template.
Speaker 1: It, where a central team provides templates.
Speaker 2: Exactly feature teams use and customize them. Good balance between
Speaker 2: consistency and flexibility.
Speaker 1: And reusable workflows and actions help here too.
Speaker 2: Definitely enhance consistency, efficiency, and.
Speaker 1: Deployment and measuring success. Back to the four keys.
Speaker 2: Yep, the Dora metrics deployment frequency, lead time for changes,
Speaker 2: meantime to restore or change fail rate if you're auto deploying.
Speaker 2: The guide says, move beyond surveys track these real world metrics.
Speaker 1: Okay, shifting gears, managing feature rollouts, feature flags or toggles.
Speaker 2: Super powerful technique. Deploy new code to production, but keep
Speaker 2: the feature turned.
Speaker 1: Off initially, then rolled out gradually.
Speaker 2: Yeah. The guide outlines a typical life cycle ideation, internal testing, alpha,
Speaker 2: beta with small external groups, then maybe a preview release
Speaker 2: eventually default for everyone.
Speaker 1: Advantages seem clear. Merge code more often, zero downtime deployments
Speaker 1: by hiding unfinished stuff.
Speaker 2: Much more control over the rollout. But beware feature flag.
Speaker 1: Hell ah, yes, too many flags. Nobody knows what they.
Speaker 2: Do exactly, so best practices track metrics on flag usage,
Speaker 2: have central management with clear ownership, document dependencies between flags,
Speaker 2: keep it tidy.
Speaker 1: And flags aren't just for releases, but for experiments too.
Speaker 1: Ab testing.
Speaker 2: Absolutely formulate a hypothesis this new feature will improve conversion
Speaker 2: by x percent. Use a flag to show it to
Speaker 2: say ten percent of users compare their behavior to the
Speaker 2: control group ninety percent.
Speaker 1: Gather data, validate or invalidate your idea objective measurement exactly.
Speaker 2: The guide even has an example with a simplified registration
Speaker 2: dialogue Test.
Speaker 1: Okay, different topic. Managing code branches trunk based development, faster velocity.
Speaker 2: That's the claim The core idea very few long lived branches.
Speaker 2: Ideally age is one main trunk feature branches, keep them
Speaker 2: super short lived, merge back daily.
Speaker 1: Ideally it's more model than a strict workflow.
Speaker 2: Right adopted by many high performing teams. The guide talks
Speaker 2: about GitHub flow and variations like myflow as examples.
Speaker 1: What's the issue with pure GitHub flow? Sometimes deploying every
Speaker 1: pr straight.
Speaker 2: To prod can become a bottleneck, So a pragmatic adaptation
Speaker 2: validate prs in a test environment but only deploy to
Speaker 2: prod after merging to the trunk makes sense.
Speaker 1: And with short branches frequent merges, code integration is key, urging, rebasing.
Speaker 2: Dealing with conflicts. The guide covers techniques also handling hot
Speaker 2: fixes for old releases using cherry pick.
Speaker 1: It even has that cool get alias example amstart.
Speaker 2: Yeah in their miflow strategy automates creating a branch, committing changes, pushing,
Speaker 2: creating a draft pr nice little workflow helper.
Speaker 1: Now ensuring quality in this fast pace. Yeah, shift left
Speaker 1: testing testing earlier.
Speaker 2: Crucial, The guide argues, manual testing just doesn't scale anymore.
Speaker 2: You need robust, automated tests, owned and maintained by the
Speaker 2: dev team itself.
Speaker 1: Why own by devs?
Speaker 2: If developers test their own code, they tend to write
Speaker 2: more testable code to begin with.
Speaker 1: Uh makes sense, So shift left principles.
Speaker 2: Test at the lowest level possible. Unit tests first, right
Speaker 2: tests once run everywhere. Treat test code like production code.
Speaker 2: Keep it clean and the core you code it, you
Speaker 2: test it. Develop a responsibility.
Speaker 1: It mentions a testing manifesto QA roll evolving.
Speaker 2: Yeah, QA isn't just finding bugs at the end. It's
Speaker 2: about building quality in throughout the process. And then it
Speaker 2: dives in to TDD test driven development.
Speaker 1: Write the test before the code right the.
Speaker 2: Red green refactor cycle. Write a failing test, read write
Speaker 2: the minimum code to make it past green, then clean
Speaker 2: up the code. Refactor leads to better design, less debugging later.
Speaker 1: Then manage the whole test portfolio, unit integration end to end.
Speaker 2: Know the difference, use them appropriately The guide lays out
Speaker 2: their characteristics and.
Speaker 1: Then things like fault injection, chaos engineering, proactively breaking stuff.
Speaker 2: Sounds scary, but it's about testing resilience. Introduce failures in
Speaker 2: production controlled to see how a system handles it. Verify
Speaker 2: your safeguard's work builds really.
Speaker 1: Robust systems igh stakes, and finally, test management in GitHub
Speaker 1: tools for tracking results.
Speaker 2: Yeah, integrating test results into the workflow.
Speaker 1: Okay. Another shift left security devsekops. Integrating security throughout not
Speaker 1: an afterthought.
Speaker 2: Starts with the assumer reach mindset and zero trust principles.
Speaker 2: Don't assume your internal network is safe, assume a breach
Speaker 2: could happen anywhere. Focus shifts to detection, response.
Speaker 1: Recovery, and prepping for that with attack simulations Red Team,
Speaker 1: Blue Tank.
Speaker 2: Exactly, Red Team attacks simulated, ethical, Blue Team defends, identify weaknesses,
Speaker 2: raise awareness, train response teams. The guide has ground rules
Speaker 2: for doing this safely and productively.
Speaker 1: Common attacks to watch for.
Speaker 2: Phishing, unprotected resources left open, exploiting compromised machines, spear phishing too.
Speaker 2: The targeted kind and.
Speaker 1: Gidthub code spaces is a more secure dev environment.
Speaker 2: Yeah, hosting the whole workspace in the cloud reduces the
Speaker 2: attack surface on local machines.
Speaker 1: Makes sense now. Securing the code itself, getub features.
Speaker 2: For this DependaBot is huge automatically checks dependencies for vulnerabilities,
Speaker 2: creates prs with updates, supports tons of ecosystems, set it daily, weekly, monthly,
Speaker 2: keeps things patched.
Speaker 1: Huge timesaver prevents known vulns creeping in and secret scanning.
Speaker 2: YEP scans public, repos and private if you have advanced
Speaker 2: security for accidentally committed secrets, API keys, tokens, oops.
Speaker 1: And code QL for deeper static analysis.
Speaker 2: Right set it up in actions scans code for security issues,
Speaker 2: quality problems without running it. Results show up right in
Speaker 2: the pull request.
Speaker 1: That PR integration is gold, catch issues before merging.
Speaker 2: Totally, and you can write custom co QL queries for
Speaker 2: specific patterns you care about.
Speaker 1: Okay, beyond the code securing deployments, container scanning, infrastructure scanning,
Speaker 1: you need to check those two.
Speaker 2: The guide mentions tools like anchor Claire for containers have
Speaker 2: infrastructure policies. Audit configus regularly.
Speaker 1: And automated infrachanges with ic managed via.
Speaker 2: PRS provides that audit trail control. The guide brings up
Speaker 2: the solar winds attack as a reminder.
Speaker 1: Supply chain security critical.
Speaker 2: Which leads to things like s BOM software bill of materials,
Speaker 2: what's in your software?
Speaker 1: Commit signing, verifying the author code.
Speaker 2: Signing, verifying the release integrity? All important pieces.
Speaker 1: What about active testing?
Speaker 2: Dynamic application security testing? Test the running application? O wasp
Speaker 2: z app is a popular open source.
Speaker 1: Tool for this and generally harden the whole release pipeline,
Speaker 1: secure runners, lease privilege monitoring.
Speaker 2: The whole nine yards. Security needs to be baked in everywhere, and.
Speaker 1: The guide circles back to E shaped team members.
Speaker 2: Yeah, people with broad experience, deep expertise, curiosity for exploration
Speaker 2: and strong execution skills need that mix for high collaboration
Speaker 2: across all these areas.
Speaker 1: So how do we measure if all this is working?
Speaker 1: Metrics that matter engineering velocity, developer productivity.
Speaker 2: The guide starts with the why why accelerate companies life
Speaker 2: spans are shrinking. Digital capabilities are crucial for survival. IT
Speaker 2: mentions the McKinsey Developer Velocity Index.
Speaker 1: DVII HIDVII companies outperform significantly.
Speaker 2: Yes, So how to measure back to the four keys
Speaker 2: deployment frequency, lead time for changes, MTTR, change fail rate,
Speaker 2: use surveys initially if you have to, but aim for
Speaker 2: direct measure.
Speaker 1: But productivity is broader than just those four, much broader.
Speaker 2: The guide introduces the space framework satisfaction and well being, performance, activity,
Speaker 2: communication and collaboration, efficiency and flow, need a balanced view.
Speaker 1: And OKRs objectives and key.
Speaker 2: Results to align engineering work with business goals, track progress,
Speaker 2: prioritize effectively.
Speaker 1: The guide then quickly revisits some earlier topics in light
Speaker 1: of metrics.
Speaker 2: Right planning and tracking with visual boards, WIP limits, reducing context.
Speaker 1: Switching, prioritization, swim lanes.
Speaker 2: Trunk based development, myflow, automation, streamlining things, force push considerations.
Speaker 1: Shift left testings impact on velocity, the evolving QA role.
Speaker 2: Shift left, security again, red blue teams as learning opportunities,
Speaker 2: code spaces for secure.
Speaker 1: Dev and linking metrics back to business goals. Developer satisfaction
Speaker 1: is key to absolutely happy.
Speaker 2: Effective engineers are productive engineers.
Speaker 1: Now making sure we're building the right things, lean product development, lean.
Speaker 2: Startup yes, using customer feedback, experimentation, build stuff people actually.
Speaker 1: Need and want the build measure, learn.
Speaker 2: Loop core concept, build an MVP, quickly, measure how users react,
Speaker 2: learn from it, iterate requires understanding your product, your market.
Speaker 1: Business acumen for engineers increasingly important.
Speaker 2: The guide suggests the business model Canvas as a tool
Speaker 2: for engineers to get better at product thinking.
Speaker 1: Understanding the product life cycle too, innovators, early adopters.
Speaker 2: Majority laggards. Knowing where your product fits helps guide strategy
Speaker 2: and experimentation.
Speaker 1: Again ab testing for continuous.
Speaker 2: Improvement, applying the scientific method, clear hypothesis, design and experiment,
Speaker 2: define independent, independent variables, use control groups, rigorous testing tools.
Speaker 2: For this mentions growth book Flagger as engineering focused options
Speaker 2: and again aligns with okr's experiments. Should help you learn
Speaker 2: and achieve your goals.
Speaker 1: Okay. Wrapping up with GitHub for bigger organizations, teams and enterprises.
Speaker 2: Covers the pricing tiers. Free Team Enterprise highlights enterprise security
Speaker 2: features like sam LSSO enterprise managed Users.
Speaker 1: EMU, organizing teams within.
Speaker 2: GitHub, horizontal vertical, nested teams, visible versus secret teams, managing
Speaker 2: access for outside collaborators too.
Speaker 1: What about migrating to GitHub?
Speaker 2: Discuss the strategies high fidelity, keep all history versus clean cutovers,
Speaker 2: start fresh mentions tools, GitHub Enterprise Importer, GEI Valet for
Speaker 2: azured DevOps, migration, branching, model changes might be needed if
Speaker 2: coming from something else.
Speaker 1: And finally, why do so many big transformations fail?
Speaker 2: Critical question? The guide points to lack of clear vision,
Speaker 2: not enough coaching, unsupportive culture, shares principles for success, ask forgiveness,
Speaker 2: You build it, you run it, fail early, embrace failure, collaborate,
Speaker 2: go fix, Treat servers like cattle. If it hurts, do
Speaker 2: it more often. Familiar classic DevOps wisdom, and be data driven,
Speaker 2: measure fine bottlenecks, focus improvements there, which brings.
Speaker 1: Us back to DevOps culture itself.
Speaker 2: The union of people, process products, built on learning, collaboration, ownership,
Speaker 2: that's the foundation.
Speaker 1: Wow, okay, we have covered a ton of ground here.
Speaker 2: We really have, from the nitty gritty of pull requests.
Speaker 1: And automation all the way up to security, integration, metrics,
Speaker 1: lean principles, culture.
Speaker 2: It's a comprehensive view.
Speaker 1: And if there's one thing to really stick in your mind,
Speaker 1: remember that stat about company lifespan shrinking.
Speaker 2: Yeah, that's a sobering one.
Speaker 1: It just hammers home that being able to adapt to
Speaker 1: accelerate software delivery it's not a nice to have anymore.
Speaker 1: It's survival, it really is.
Speaker 2: So we'd encourage you listening to dive deeper into whatever
Speaker 2: sparked your interests most today.
Speaker 1: Check out the GitHub docs for the tools, look up
Speaker 1: those open source.
Speaker 2: Projects, and think critically, how could these ideas apply to
Speaker 2: your team, your workflow. Maybe identify just one bottleneck, one
Speaker 2: small thing you could start improving.
Speaker 1: Start small, iterate. So final thought to leave you with go.
Speaker 1: Given this relentless pace of change, our total reliance on software,
Speaker 1: how will these principles collaboration, automation continues improvement. How will
Speaker 1: they change not just software development, but maybe the whole
Speaker 1: way organizations operate and deliver value in the future. Think
Speaker 1: bigger than just code and deployments. What are the broader implications?
Speaker 2: Hm hmm, something that chew on definitely.
Speaker 1: Thanks for joining us for this deep dive.