Speaker 1: Welcome to the deep dive. We take complex source material,
Speaker 1: you know, dense stuff, and really pull out the actionable
Speaker 1: insights you need.
Speaker 2: That's right.
Speaker 1: Today we're digging into the role of the modern solutions architect.
Speaker 1: The essay. We've got some key excerpts here from the
Speaker 1: Solutions Architect's Handbook, which is pretty much a go to
Speaker 1: text in this space.
Speaker 2: Yeah, it really is, and our mission today it's about synthesis.
Speaker 2: Really the solutions architect role. It's super dynamic. It's evolved
Speaker 2: quite a bit from the older application or it architect roles.
Speaker 1: Deem change fast they do.
Speaker 2: And if you're interested in this career path, maybe especially
Speaker 2: the cloud solutions architect, which is probably the most common
Speaker 2: type these days, well, we're aiming to give you the
Speaker 2: core principles pretty quickly, the things that really drive strategic
Speaker 2: decisions in modern tech.
Speaker 1: That's the word strategy. We're not just like listing tasks
Speaker 1: from a job description. We're trying to get to the
Speaker 1: principles as is used to connect those big business goals
Speaker 1: you know, speed, cost with the actual tech choices and
Speaker 1: system design. It's about understanding the trade offs they manage
Speaker 1: all the time. Okay, so let's let's unpack this, say,
Speaker 1: roll a bit. The source material points out it's complex
Speaker 1: partly because those old lines between it jobs developer, DBA
Speaker 1: Security guide they're getting really blurry.
Speaker 2: Now, very blurry. And the essay there are the ones
Speaker 2: with that end to end ownership, right from the initial
Speaker 2: idea through to deployment.
Speaker 1: End to end. That's a lot of responsibility. It is.
Speaker 2: They're fundamentally bridge builders. It often starts with translating what
Speaker 2: users actually need into requirements you can measure. We talk
Speaker 2: about functional requirements with the system does honestly the big
Speaker 2: architectural choices, they're usually driven by the non functional.
Speaker 1: Requirements ah right, things like how fast it needs to be,
Speaker 1: or how secure or how many users it needs to.
Speaker 2: Support exactly latency, security scale. Those characteristics really dictate the design.
Speaker 2: You know, if the system has to handle say a
Speaker 2: million users at once, that's a non functional requirement. That
Speaker 2: single need. It pretty much defines your database choice, your
Speaker 2: network set up, your whole cloud strategy.
Speaker 1: Wow, okay.
Speaker 2: And beyond just requirements, the essays constantly juggling constraints, often
Speaker 2: high stakes ones. They have to make these really critical
Speaker 2: technology selections, you know, often getting into that big debate
Speaker 2: do we build this ourselves or do we buy a
Speaker 2: third party tool?
Speaker 1: The classic build versus.
Speaker 2: Buy right and that choice It isn't purely technical, it's
Speaker 2: kind of a fundamental bet. Really, you're betting on future
Speaker 2: flexibility versus maybe immediate cost savings or speed.
Speaker 1: It sounds like what sounds like they could easily get
Speaker 1: pulled in too many directions. Yeah, if they're talking to stakeholders,
Speaker 1: defining requirements, making these huge bill by calls, handling constraints,
Speaker 1: are they basically doing three jobs?
Speaker 2: It can feel like that sometimes, I bet, but it's
Speaker 2: all sort of unified by one goal managing risk, Okay,
Speaker 2: which is why a really key part of their jobs
Speaker 2: is discovering risks early. They'll often build a proof of concept,
Speaker 2: a pose or maybe a proto type quite early on.
Speaker 1: So not just coding for fun.
Speaker 2: Definitely not. It's about proving that the tech stack you've
Speaker 2: picked can actually handle the trickiest requirements before you commit
Speaker 2: huge amounts of resources. It's de risking the whole project.
Speaker 1: What's really interesting, and the source mentioned this, is that
Speaker 1: the first draft of the architecture often happens incredibly early,
Speaker 1: like sometimes even during pre sales, when they're just putting
Speaker 1: together an RFP.
Speaker 2: Response, yeah, request for proposal or RFI request for information.
Speaker 1: Right, so they're already scoping the tech solution, figuring out
Speaker 1: the parts, estimating complexity and resources before the contract's even signed.
Speaker 2: Absolutely, they're making informed technical bets essentially to help win
Speaker 2: the business in the first place. And those early bets, well,
Speaker 2: they need to be built on something solid, right, which
Speaker 2: brings us neatly to these foundational design attributes or pillars
Speaker 2: that really define a good solution. Every decision and essay
Speaker 2: makes it kind of needs to map back to these pillars,
Speaker 2: especially now with cloud computing completely changing the game.
Speaker 1: Yeah, the cloud changed there. Yeah, Okay, let's start with growth, scalability,
Speaker 1: the system's ability to handle more work. Why did the
Speaker 1: cloud make this so much well easier.
Speaker 2: Basically because of elasticity. Think about the old days traditional it.
Speaker 2: If you needed more capacity, you had to order hardware
Speaker 2: that could take what four to six months?
Speaker 1: Yeah, easily, And if you got.
Speaker 2: It wrong exactly under provision and your system falls over
Speaker 2: during peak times over provision, and you've got expensive servers
Speaker 2: just sitting there doing nothing.
Speaker 1: Just burning money, a constant guessing game.
Speaker 2: Right, Cloud elasticity means we can grow and shrink capacity
Speaker 2: almost instantly on demand, and the strategic way says usually
Speaker 2: achieve this is through horizontal scaling, adding more machines, not
Speaker 2: just making one bigger. Okay, scale out, not up precisely.
Speaker 2: And a really key technical decision to enable that is
Speaker 2: decoupling user sessions from the actual application server. Instance.
Speaker 1: Ah, so you don't store the user shopping cart on
Speaker 1: the web server.
Speaker 2: They happen to hit exactly. You store that session state
Speaker 2: somewhere else, an independent layer that's highly available, like a
Speaker 2: no SQL database maybe yeah, Amazon DynamoDB or Mango dB
Speaker 2: something like that.
Speaker 1: Gotcha.
Speaker 2: The insight there is by making the application server stateless,
Speaker 2: you can suddenly add or remove hundreds of them instantly
Speaker 2: without anyone losing their work, and no SQL databases, with
Speaker 2: their speed and flexible schemas, are often perfect for that.
Speaker 1: Okay, moving on too, reliability. The sources talk a lot
Speaker 1: about resiliency. Specifically, this idea of self healing systems that
Speaker 1: recover from problems without a human stepping in sounds a
Speaker 1: bit like sci fi still.
Speaker 2: Eh, maybe a few years ago, but it's pretty standard
Speaker 2: engineering now. It's almost mandatory. Think about a load balancer.
Speaker 2: It's not just directing traffic. It's constantly checking the health
Speaker 2: of the servers behind it. Bick a health check exactly
Speaker 2: If it, season instance, isn't responding right, boom, it pulls
Speaker 2: it out of rotation immediately, and then usually through an
Speaker 2: auto scaling group, it tells the system to spin up
Speaker 2: a brand new, healthy replacement. The end user they probably
Speaker 2: never even notice itself.
Speaker 1: Okay, that handles small, localized failures. But what about you know,
Speaker 1: the big stuff, real disasters, right.
Speaker 2: That's where disaster recovery, dr and business continuity planning come in.
Speaker 2: The strategic thinking here is all about geography and redundancy,
Speaker 2: threading things out way out. For a critical global business,
Speaker 2: like say a payment processor, the essay has to plan
Speaker 2: for enough it resources in a completely different region, maybe
Speaker 2: even a different continent. The goal is simple, really. If
Speaker 2: the main data center gets wiped out flood, earthquake, major
Speaker 2: power outage, the business has to keep running globally. Often
Speaker 2: that means failing over completely to the other regions, sometimes
Speaker 2: within minutes. Okay, security, this is huge. It's not just
Speaker 2: a feature you add at the end. It has to
Speaker 2: be baked into the design from day one. An architectural mindset.
Speaker 2: The sources really hammer this defense in depth.
Speaker 1: IDEA defence in depth sounds like a layers it is.
Speaker 2: It's necessary paranoia. Basically, you have to assume your outer
Speaker 2: defenses will be brooched at some point. So security can't
Speaker 2: just be at the edge. It needs to be applied
Speaker 2: at every single layer, So not.
Speaker 1: Just the main firewall at the network edge, but also
Speaker 1: controls on the load balancer in the network segments, in
Speaker 1: the application code itself, the database, everywhere, everywhere.
Speaker 2: Absolutely. A classic example of how an essay thinks defensively
Speaker 2: is designing against common web attacks like cross site scripting
Speaker 2: XSS or SQL enrection as a nasty totally, so the
Speaker 2: essay will mandate using something like a web application firewall
Speaker 2: a wave. It sits in front and blocks known malicious
Speaker 2: patterns in traffic before it even gets near your actual application.
Speaker 1: Makes sense, and for some industries compliance is an optional.
Speaker 1: It actually dictates the architecture from the start right.
Speaker 2: Oh. Absolutely, compliance is a massive design constraint. If you're
Speaker 2: in finance, for instance, dealing with payments regulations like PCIDSS,
Speaker 2: they demand comprehensive logging and auditing.
Speaker 1: You track everything everything.
Speaker 2: The essays design must ensure that there's a clear, unchangeable
Speaker 2: log trail for every single transaction, every access attempt. If
Speaker 2: you mess that up, it's not just a technical problem,
Speaker 2: it's finds maybe losing your license to operate serious business.
Speaker 1: Okay, so we've got this solid blueprint. The architecture looks robust, scalable, secure, great,
Speaker 1: But a great design is useless if you can't actually
Speaker 1: build and deploy it quickly and.
Speaker 2: Reliably exactly, which shifts us from those static design principles
Speaker 2: to thinking about speed and efficiency and execution getting it
Speaker 2: out the door. And this is where the essay really
Speaker 2: needs that Agile mindset. They have to embrace continuous feedback,
Speaker 2: rapid delivery. The big contrast the sources draw is with
Speaker 2: the old waterfall.
Speaker 1: Method right waterfall, where you plan everything up front, build
Speaker 1: it all, and then show the customer at.
Speaker 2: The very end yeah, and often find out it's not
Speaker 2: quite what they wanted. Agile, with its short sprints, means
Speaker 2: frequent checkpoints. You're focused on delivering small working pieces constantly.
Speaker 1: The main benefit there isn't just speed, right, It's also
Speaker 1: about catching mistakes, reducing the cost of making changes.
Speaker 2: Precisely inspect and adapt. And what really enables that speed
Speaker 2: and crucially reliability, it's automation. The sources are pretty clear
Speaker 2: automation is the best way to kill human error, boost productivity,
Speaker 2: and ultimately cut costs in the long run.
Speaker 1: Okay, So if automation is non negotiable, where does the
Speaker 1: say need to focus those efforts. What gets automated?
Speaker 2: Well, pretty much everything you can Application testing is obvious,
Speaker 2: But just as critical, maybe even more so, is automating
Speaker 2: the environment itself, the infrastructure.
Speaker 1: How do you automate the infrastructure?
Speaker 2: That's where infrastructure as code comes in IAC tools like
Speaker 2: antsable or Terraform, maybe cloud formation if you're in Awska.
Speaker 2: The huge strategic win with IIC is reproducibility. You define
Speaker 2: your entire environment servers, networks, databases and code. That means
Speaker 2: you can stamp out identical environments repeatedly no more. It
Speaker 2: worked in test problems because test is identical to production.
Speaker 2: It kills configuration drifts. Ah nice, And then you automate
Speaker 2: the whole release pipeline too, Continuous integration, continuous deployment CICD
Speaker 2: pipelines that and shows every change goes through the same
Speaker 2: automated build, test, and deploy process consistency and velocity. And finally,
Speaker 2: related to all this, we need to talk about how
Speaker 2: the system itself is organized, which brings us to this
Speaker 2: really important design principle loose coupling. Loose coupling, Okay, fundamentally,
Speaker 2: it's about minimizing the error radiuses how far things break
Speaker 2: when something goes wrong.
Speaker 1: Give me a picture that air radius.
Speaker 2: Okay, Think of like a giant solid statue versus maybe
Speaker 2: a set of Lego blocks in a tightly coupled system,
Speaker 2: a monolith. If one critical part breaks, say one big
Speaker 2: application server fails, everything connected to it instantly feels the pain.
Speaker 2: Maybe all the web servers start getting errors. The whole
Speaker 2: system can start to wabble. The blast radius is.
Speaker 1: Huge, right, One thing takes down.
Speaker 2: Everything pretty much, but with a loosely coupled system, more
Speaker 2: like the Lego blocks. If one component one's service fails,
Speaker 2: there's usually something in between, like that load balance that
Speaker 2: we talked about, or a message queue. It spots the
Speaker 2: failure and instantly routes traffic away from the broken bit
Speaker 2: to the.
Speaker 1: Healthy ones, So the damage is contained exactly.
Speaker 2: Only that single failed component is impacted the blast radius
Speaker 2: is tiny, much more resilient, and.
Speaker 1: That idea limiting the air radius. That's kind of led
Speaker 1: to the modern architectures we see everywhere.
Speaker 2: Now, absolutely service oriented architecture SOA and its more modern
Speaker 2: evolution micro services. That's how we achieve loose coupling today.
Speaker 2: You break the application down into these small independent services.
Speaker 2: Each does one thing well and they talk to each
Speaker 2: other over standard lightweight ways. Often you know RESTful APIs using.
Speaker 3: Jason lightweight language independence yep, and the big win teams
Speaker 3: can develop, deploy, and scale their individual services independently, which
Speaker 3: leads to huge gains in both development speed and overall
Speaker 3: system stability.
Speaker 2: It's a powerful pattern hashtag tag outro. So when you
Speaker 2: pull it all together, looking back at the sources, the
Speaker 2: solution's architect prole Wow, it's intensely multidisciplinary, isn't it. Definitely
Speaker 2: you need deep technical chops across well, pretty much everything.
Speaker 2: But just being a tech wizard isn't enough. That skill
Speaker 2: has to be grounded in those crucial soft skills leadership,
Speaker 2: being able to think big strategically but still sweat the details,
Speaker 2: and being flexible enough to adapt when business needs inevitably change. Yeah,
Speaker 2: and continuous learning. It's just table stakes, reading blogs, trying
Speaker 2: new tech. You have to stay current. It's non negotiable
Speaker 2: for an essay, and I.
Speaker 1: Think one thing they should really stand out for you
Speaker 1: the listener is this central tension. The essay constantly manages
Speaker 1: the fact that performance optimization always always comes with the cost.
Speaker 3: Good point.
Speaker 1: You know an application doing high speed stock trading, it
Speaker 1: might need sub mill second response times. Achieving that requires
Speaker 1: really expensive complex architecture, specialized hardware, maybe custom network protocols.
Speaker 1: You have to spend big to get that level of performance.
Speaker 2: If your application is just say an intro fnel timesheet
Speaker 2: system for one hundred employees, spending all that money to
Speaker 2: get submillisecond latency, it's completely unjustified. There's no real business
Speaker 2: value there. Every single choice, from the database you pick
Speaker 2: to the cloud reagion you deploy in, it's always a
Speaker 2: trade off technical perfection versus budget reality.
Speaker 1: Which leads us right into our final thought for you
Speaker 1: to think about for your next project or maybe when
Speaker 1: you're working on right now, how do you figure out
Speaker 1: that acceptable trade off the balance between pushing for the
Speaker 1: absolute best performance, lowest latency, highest throughput and keeping the
Speaker 1: costs both upfront capital and ongoing operational costs under control.
Speaker 2: Where exactly would you draw that line for your business
Speaker 2: needs