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Speaker 1: episode nineteen hundred and seventy eight. I'm Carl Franklin and
Speaker 1: am Richard Camp and Richard, you're a down under?
Speaker 2: I am?
Speaker 1: I am.
Speaker 2: This is the last week of the month long tour
Speaker 2: with the grand baby. And you know, the whole idea was,
Speaker 2: while she's not moving around too much, just a little package,
Speaker 2: it'll be a good time to take her and show
Speaker 2: her off to the extended family. Of course, in this
Speaker 2: time she's learned to crawl, so now she's a toddler
Speaker 2: and starting to get bumps and bruises. Just you know,
Speaker 2: remember that time your kids get all.
Speaker 1: Your baby get gets all banged up. That's happening. How
Speaker 1: cool is that? It's been really fun. The only thing
Speaker 1: she might regret is not being able to remember any
Speaker 1: of it's the best part.
Speaker 2: Right when she's twelve years old, like you've already been
Speaker 2: to Australia.
Speaker 1: Yeah, she won't remember the trauma of being dropped on
Speaker 1: her head on the plane, you know, nothing like that.
Speaker 2: Well, we've got a few more days left. I'm actually
Speaker 2: up near Brisbane.
Speaker 1: We're in the.
Speaker 2: Gold Coast, an area called kulan Gata, right by the beach.
Speaker 2: It's beautiful here. I love the Gold Coast boys.
Speaker 1: It hot holy man. Yeah, all right, So let's start
Speaker 1: right off with the year nineteen seventy eight, right, dude,
Speaker 1: what do you got? Well, some of the major events.
Speaker 1: Harvey Milk was elected the first openly gay person elected
Speaker 1: the public office in California, so you know, things are
Speaker 1: becoming a little more socially liberal. The Jonestown massacre on
Speaker 1: November eighteenth was terrible, crazy. We're nine hundred members of
Speaker 1: the People's Temple died in a mass suicide murder in Jonestown, Guyana,
Speaker 1: orchestrated by Jimmy Jones in the good News Camp David Accords.
Speaker 1: In September, President Jimmy Carter facilitated a peace agreement between
Speaker 1: Israel and Egypt. There were some air flight crashes Air
Speaker 1: India Flight eight fifty five Boeing seven forty seven coasts
Speaker 1: crashed off the coast of Bombay. Two hundred and thirteen
Speaker 1: people perished. The northeastern US blizzard of nineteen seventy eight.
Speaker 1: You weren't around for this, Richard, because I was on
Speaker 1: the West coast territory. Do you remember it? I do
Speaker 1: I remember it? So I would have been ten eleven, Yeah,
Speaker 1: And we had the day off from school and there
Speaker 1: was literally four and a half five feet of snow
Speaker 1: right packed up against the door, wow, and all over.
Speaker 1: And so my brother and our friend Todd, and I
Speaker 1: and Chris Conrandy from down the street, we set up
Speaker 1: out to make Skylab, which is what they called it.
Speaker 1: Just this huge edifice of snow with snowballs could roll
Speaker 1: down and around and everything. We just had a great time,
Speaker 1: all right.
Speaker 2: Yeah, sure, And this is right right when Skylab was
Speaker 2: going to about to re enter, right, they'd love it
Speaker 2: the next year, yep.
Speaker 1: So we were hip little kids even then. The FIFA
Speaker 1: World Cup nineteen seventy eight FIFA World Cup was held
Speaker 1: in Argentina, with the host nation winning the tournament. Garfield
Speaker 1: debuted in the comic strip World Jim Davis made its
Speaker 1: first appearance in nineteen seventy eight films Grease, National Lampoon's
Speaker 1: Animal House. Of course, those were great. In science, you
Speaker 1: can talk about these things. You'll probably talk about the
Speaker 1: first human cloning claims.
Speaker 2: Right, yeah, well I'm not going to talk a lot
Speaker 2: about it, but yes, that's when those experiments going on.
Speaker 1: Nobel Peace Prize was awarded to Anwar Sadat and monocom
Speaker 1: Big and for their efforts in the Camp David Accords.
Speaker 1: So what was happening in computing in space.
Speaker 2: Let's do the space stuff first. Last year and seventy seven,
Speaker 2: the Shuttle Enterprise was deployed and they were doing their
Speaker 2: first captive tests and landing tests. In seventy eight, they
Speaker 2: fly the Enterprise by seven forty seven to Alabama going
Speaker 2: to do vibration testing for launching. There was the intent
Speaker 2: to actually fly Enterprise into space at that time, although,
Speaker 2: as we'll find out a couple of years later further on,
Speaker 2: there's so many changes that happened from all these tests
Speaker 2: that it's too expensive to retrofit Enterprise to be a
Speaker 2: flable vehicle. And they'll take an earlier test Article STA
Speaker 2: zero nine to nine and that'll and refit in and
Speaker 2: it'll become challenger. Otherwise, in space, there was Venus missions
Speaker 2: in nineteen seventy eight, both American and so the Pioneer
Speaker 2: Venus project launched in May, arise in December. This is
Speaker 2: the orbiter, so it actually goes into orbit around Venus
Speaker 2: and actually operated until nineteen ninety two doing measurements and
Speaker 2: so forth. But there was a second part to it
Speaker 2: called the multi Probe, which actually launched later in August,
Speaker 2: but arrived earlier because it didn't need to go into orbit,
Speaker 2: so it used a higher energy trajectory to get there.
Speaker 1: What did we not know about Venus that we felt
Speaker 1: we needed to know by sending those probes.
Speaker 2: We I mean, we didn't have We didn't know the
Speaker 2: composition of the atmosphere. We didn't know it all the
Speaker 2: way down. That's why putting the landers down to measure
Speaker 2: as you went down, we were just trying to figure
Speaker 2: out what was going on there, Like even understanding how
Speaker 2: hot it was took time. You know, the the blanket
Speaker 2: effects of CO two weren't well known yet, so this
Speaker 2: was part of you know, the CO two absorbs in
Speaker 2: for red light and so that's why it'll concentrate heat.
Speaker 2: But also this is like it's down on the surface there,
Speaker 2: like what can we see? And so there was a
Speaker 2: whole series of missions. They kept going like this is
Speaker 2: even the end of it. So on the American side
Speaker 2: they put down this multiprobe actually had four probes on it,
Speaker 2: a big one that was about seven hundred pounds, called
Speaker 2: the Large Probe, cleverly named, and then three small probes
Speaker 2: that were all about two hundred pounds. The big one
Speaker 2: had a parachute, so it was more like the Venera landers.
Speaker 2: It transmitted information for an hour as it was descending
Speaker 2: through the atmosphere, but as soon as it impacted the
Speaker 2: surface it stopped transmitting. The three small probes were just
Speaker 2: arrow shells. They had no parachutes or anything, so they
Speaker 2: were free falling granted through a very thick atmosphere. And
Speaker 2: one of them, the one they called Day because it
Speaker 2: landed on the Day side, Venus continued to function. It
Speaker 2: survived the landing and transmitted for over an hour from
Speaker 2: the surface.
Speaker 1: So that means there was some kind of solid surface and.
Speaker 2: Without it there is right, it's mostly old volcanic flows.
Speaker 2: The Venia missions this were eleven and twelve. So the
Speaker 2: Soviets flew to Venus many, many times, and they will continue.
Speaker 2: They'll be a thirteen oh fourteen. And so both of
Speaker 2: an air missions went off flawlessly. They both landed on
Speaker 2: Venus cleanly. Eleven transmitted for ninety five minutes, twelve transmitted
Speaker 2: for one hundred and ten. And I'd like to point
Speaker 2: out it's not that they only lasted that long. It's
Speaker 2: that their transmitters are only so strong, and so the
Speaker 2: orbiter has to relay the data back to Earth.
Speaker 1: Oh wow, and it goes.
Speaker 2: Out of range after about an hour and a half,
Speaker 2: I see, and then nothing can pick it up anyway,
Speaker 2: although generally speaking within it within twenty four hours or
Speaker 2: so forth, things are broken from the pressure of the
Speaker 2: heat and the amount of sulfuric acid in the atmosphere.
Speaker 1: Yeah, there is that little detail, little detail.
Speaker 2: This is also the year that Sharon, the moon of Pluto,
Speaker 2: is identified by some astronomers just looking at it with telescopes.
Speaker 2: It's the moon is massive, of course, it's about almost
Speaker 2: an eighth the size of Pluto itself, so really really big,
Speaker 2: and of course not great resolutions. We wouldn't get a
Speaker 2: good picture of Sharon until the new Horizon spacecraft gets
Speaker 2: there in twenty fifteen. Science wise, the RSA algorithms that's RIVS,
Speaker 2: Shamir and Aldeman is publicly described in nineteen seventy eight.
Speaker 2: So that's craz I think we still depend on.
Speaker 1: To this day. Still is it to this day? Yeah?
Speaker 2: And speaking of computing, this is a crazy year for computing.
Speaker 2: So this is the introduction of Microsoft's Altair Basic.
Speaker 1: Yeah.
Speaker 2: Right, nineteen seventy seven was when the Altar came out,
Speaker 2: but it's now it's fully released.
Speaker 1: Bill Gates through OUTE that right, Yeah, that's right.
Speaker 2: The Apple two distrive, the five and a quarter drive
Speaker 2: gets released for the Apple two and they start making
Speaker 2: the twoe. The Intel eighty eighty.
Speaker 3: Six processor kind of an important one, yeah, kind of important.
Speaker 3: The sixteenth and sixteenth definitive sixteen bit processor. Yeah, here's
Speaker 3: when you don't know the Intel twenty eight to sixteen.
Speaker 3: Twenty eight sixteen the first electronically reirasable and reprogrammable ROM.
Speaker 1: Wow.
Speaker 2: So up until then when you when we finally made ROM,
Speaker 2: they had to be erased by UV light, so you
Speaker 2: would take the chip out of the computer, you would
Speaker 2: shine a bright UV light on it to erase it,
Speaker 2: and then you'd reprogram it and put it back in
Speaker 2: the machine. This was an electronically reprogrammable one E PROM Yeah.
Speaker 2: The first e proms. Carter also brought the first computer
Speaker 2: into the White House, was in HB three thousand, the
Speaker 2: introduction of laser disc Oh yeah, I remember those, remember the.
Speaker 1: Big laser discs. Yeah, and you know what its original
Speaker 1: name was.
Speaker 2: You're gonna love this because it is nineteen seventy eight
Speaker 2: disco vision.
Speaker 1: Oh no, no, And the first and the first disc
Speaker 1: released is Jaws. Yeah, that makes sense.
Speaker 2: Yeah, I want to talk the word Star for CPM. Okay,
Speaker 2: that's what it comes out, and it doesn't become super popular,
Speaker 2: then it'll become super popular in nineteen eighty one because
Speaker 2: word Star cuts a deal with the Osbourne people to
Speaker 2: bundle it with the Osbourne one bundling even back then,
Speaker 2: Wow and the deck vacks eleven seven eighty And I
Speaker 2: wouldn't normally talk who a lot about an individual computer,
Speaker 2: but there's so much of the architecture of this machine,
Speaker 2: even though it was a mini computer, that sort of
Speaker 2: describes how PCs will be built going forward, because it
Speaker 2: was really they really worked hard on the instruction set
Speaker 2: to maintain backward compatibility so that newer models could build
Speaker 2: on the same instruction set pretty much indefinitely. And much
Speaker 2: as that machine didn't survive long term, although it was
Speaker 2: a phenomenal machine in its era, it really sort of
Speaker 2: outlined the ideas of maintaining backward compatibility for better or worse. Yeah,
Speaker 2: one last item. This is when Vince Surf and his
Speaker 2: team define and test TCPIP.
Speaker 1: Yeah.
Speaker 2: Wow, the stuff we're using right now as we make
Speaker 2: this show nineteen seventy eight.
Speaker 1: The TCPIP stack. That's it's the holy grail of computing
Speaker 1: communication back then.
Speaker 2: Yeah, and UDP as well. It was all part of
Speaker 2: the definition. UNIP is part of the stack. Yeah, and
Speaker 2: that's we're using UDP now obviously. Yeah, we do what
Speaker 2: we're doing wicked fast.
Speaker 1: All right, Well, uh, what's next? I think we do better?
Speaker 1: No framework, right, let's do it. Let's do it. Roll
Speaker 1: the music all right, man, what do you go? You're
Speaker 1: in Australia right now. I am Our friend Simon Crop
Speaker 1: is from Australia and he's up to something else. Now
Speaker 1: it's often is yeah, this is uh, he just posts
Speaker 1: in our Slack channel. Hey, I wrote a source generator.
Speaker 1: Oh cool, of course you did, said, that was my reply. Yeah.
Speaker 1: So this is called project files source generator. It's a
Speaker 1: C sharp source generator that provides strongly typed compile time
Speaker 1: access to project files marked with copied output directory in
Speaker 1: the CS projectile. Wow. So a type safe API for
Speaker 1: accessing files that are copied to the project's output directory,
Speaker 1: eliminating magic strings, and providing intelligence and support for filepaths. Cool.
Speaker 1: Now you might think that this is oh yeah, that's
Speaker 1: kind of a neat feature. But you know, the more
Speaker 1: I dug into the documentation here, the more you know
Speaker 1: he highlights these features, and you're like, oh, how could
Speaker 1: I have you know, lived without these strongly typed access
Speaker 1: to project files. Right? That means you know this dot
Speaker 1: dot dot file name compile time safety, so typos and
Speaker 1: filepass become compilation errors. I love it. Intel Sense support
Speaker 1: so you can discover available files through ID autocomplete. Automatic
Speaker 1: synchronization regenerates when project files change, which is a great
Speaker 1: feature of a cogenerator. Hierarchical structure that mirrors the project's
Speaker 1: directory structure. Support for the glob pattern including star star,
Speaker 1: recursive patterns. Smart naming converts file directory names to valid
Speaker 1: see sharp identifiers, so you know, file names with a
Speaker 1: space in the middle, that kind of stuff get converted
Speaker 1: to a dash or whatever you say. Just really smart
Speaker 1: thinking about source generation. Yeah, so there you go. Hats
Speaker 1: off to Simon as usual.
Speaker 2: And you know, I've been calling LM's lately source generators too,
Speaker 2: just re entrant.
Speaker 1: Ones, yeah, and nondeterminist there.
Speaker 2: Yeah, but it's interesting to see a proper source generator,
Speaker 2: you know, in this day and age as well.
Speaker 1: Yeah, it's good on ya, Simon. Yeah, cool stuff.
Speaker 2: Who's talking to us today? Richard and I grab a
Speaker 2: comment top of show nineteen seventy four. That's one we
Speaker 2: did with Den Delamarski or we talked about kid hubspec
Speaker 2: Kid because you know, all the AI.
Speaker 1: I realized there's so much we didn't talk to Dan
Speaker 1: about that we could have. We could have gone on
Speaker 1: for another hour at least.
Speaker 2: Easily, and it probably you know, and we're likely going
Speaker 2: to maybe not with Den, but you know, one of
Speaker 2: the things I've been doing on this tour talking to
Speaker 2: a lot of different developers about how their development workflows
Speaker 2: are changing using these new tools and just thinking large scale.
Speaker 2: This comment comes from Brad who said during the episode
Speaker 2: of the State of the developers will become shepherds of AI.
Speaker 1: Love the term. My question is that these.
Speaker 2: Companies don't hire younger developers to learn who will shepherd
Speaker 2: the AI when the current developers retire or leave. And
Speaker 2: I think Rad's referring to this idea that we don't
Speaker 2: need junior developers anymore because the llms are going to
Speaker 2: do it, which I think is passed for how long.
Speaker 2: I think it's patently false. Yeah, right, Like it's just
Speaker 2: not the case. I think what junior developers need to
Speaker 2: know and what every developer needs to know is starting
Speaker 2: to change with these tools, and arguably the junior developers
Speaker 2: will be more responsive to this because you know, in
Speaker 2: the end, our job wasn't the right code. It was
Speaker 2: to provide solutions to customers. And we've been teaching junior developers, well,
Speaker 2: that's you do that by writing code, and I think
Speaker 2: we're just gonna be teaching them something different, you know,
Speaker 2: as these new tools start to merge. It's it's pretty
Speaker 2: raw stuff, but it's a great shocking point about what
Speaker 2: the life cycle a developer looks like with these tools. Yeah,
Speaker 2: involved as well, right, and and who you know what
Speaker 2: it really means to shepherd AI going forward and just
Speaker 2: want to talk about here. I'll leave it for the show.
Speaker 1: Brad.
Speaker 2: Thank you so much for your comment, and a copy
Speaker 2: of Music go By is on its way to you.
Speaker 2: If you'd like a copy of Music go Buy, write
Speaker 2: a comment on the website at dot NetRocks dot com
Speaker 2: or on the facebooks. We publish every show there and
Speaker 2: if you comment there and a read on the show,
Speaker 2: we'll send you copy Music go By.
Speaker 1: I told you that I've been working on the next
Speaker 1: version of Music to code By, the next track, right,
Speaker 1: mm hmm. Yeah, so it's pretty good. I think I
Speaker 1: sent you a little sample. I think you have and
Speaker 1: I don't know that I've had a chance to open it.
Speaker 1: Traveling hither and you're on right now? Yeah, yeah, okay, Yeah,
Speaker 1: it's pretty cool. It's different, you know, And that's the
Speaker 1: that's the thing. I try to make every track a
Speaker 1: little bit different because well, you know, you're a bit older,
Speaker 1: you want to switch it up. I think you're you know,
Speaker 1: you've been doing this for a while, Fred, so I
Speaker 1: mentioned things have changed, you know, yeah, and waiting your
Speaker 1: approach sure, I'll give it a listen music to co
Speaker 1: by dot net if you want to get those tracks,
Speaker 1: twenty three of them to be exact in waveflak or
Speaker 1: in MP three format. Okay, so let's bring back Tom Karkov.
Speaker 1: He's been on the show several times. Tom's a senior
Speaker 1: software engineer at Microsoft working on the data plane for
Speaker 1: Azure API Management, helping customers successfully scale their API landscapes.
Speaker 1: He has been working in the cloud native space for
Speaker 1: more than seven years. As of now, auto scaling is
Speaker 1: in his DNA and is an alumni maintainer of Kubernet's
Speaker 1: Event Driven Auto Scaling or KEDA kDa. Then that's a
Speaker 1: CNCF graduation project that makes application auto scaling on Kubernetes
Speaker 1: dead simple. Prior to joining Microsoft, Tom was recognized as
Speaker 1: a Microsoft Azure MVP an advisor from twenty fourteen to
Speaker 1: twenty twenty one, a CNCF Ambassador from twenty twenty to
Speaker 1: twenty twenty three, and was one of the first gid
Speaker 1: up stars. He is famous for turning coffee into scalable
Speaker 1: and secure cloud systems and writes about his adventures on
Speaker 1: blog dot Tom Karkov be and That's k e r
Speaker 1: K h O V E. Welcome back, Tom, Thank you
Speaker 1: very much for having me. You bet good to have
Speaker 1: you back.
Speaker 4: Friend, always fun.
Speaker 1: Any comments on anything you've heard so far.
Speaker 4: Yeah, AI definitely is changing things. It's also making it
Speaker 4: easier to learn and to explore. And also I had
Speaker 4: a small accident a half a year ago, so it
Speaker 4: was not really able to type with one hand.
Speaker 1: Oh no, But it was.
Speaker 4: Interesting to see how you can use AI or good
Speaker 4: old speech to text and how powerful it is nowadays
Speaker 4: to help you mind blowing.
Speaker 1: Are you all recovered?
Speaker 4: Semi?
Speaker 1: So?
Speaker 4: I can move almost my finger a bit, but not
Speaker 4: fully so pressing control is a bit hard, but there's
Speaker 4: more things in life.
Speaker 1: Do you play an instrument?
Speaker 4: Thankfully?
Speaker 1: Not thankfully, but you could always play the kazoo.
Speaker 4: My wife does not approve, but.
Speaker 1: I appreciate that you started.
Speaker 2: You'd use this as an opportunity experiment with the voice interfaces,
Speaker 2: so you're writing code by voice.
Speaker 4: So I used to use a speech to text to
Speaker 4: write my emails and it didn't make any mistakes, so
Speaker 4: that was very interesting. I tried to use Copilot and
Speaker 4: Visual Studio back then, but there was no voice option,
Speaker 4: but VIAS code had it back in the day, so
Speaker 4: I just gave it prompts to a voice. And it
Speaker 4: also made me realize how important it is to think
Speaker 4: about these kind of features so that everybody can use
Speaker 4: these tools.
Speaker 2: Yeah, you're going to be an accessibility advocate now I
Speaker 2: think you've had You've now had the pain.
Speaker 1: Yes, yes, that's really interesting.
Speaker 4: Now I know how it is to be able to
Speaker 4: do it. So that was interesting.
Speaker 2: Yeah, we we. I think we three value our hands
Speaker 2: just about more than anything. Yes, like you think about
Speaker 2: what we do all day. My god, I need my
Speaker 2: hands exactly totally.
Speaker 1: Yeah.
Speaker 2: But even been the API guy for forever, right, and
Speaker 2: I only see that as getting more Importantase. I can't
Speaker 2: tell you how many times we have this conversation about
Speaker 2: if you're not using as your API management, you're making
Speaker 2: a mistake, like you expose that API to the world.
Speaker 2: There's all kinds of punishing things that are going to
Speaker 2: happen to you unless you have a tool you know
Speaker 2: meant for that problem.
Speaker 4: Yes, clearly I'm biased, but before I joined Microsoft, I
Speaker 4: was a consultant and it was kind of one of
Speaker 4: the default tools in my tool chain because sometimes people think, oh,
Speaker 4: I don't need this, but later on they would notice that,
Speaker 4: oh I could have used it, but now it's not
Speaker 4: in place, so now it's a problem to shove it in.
Speaker 4: Is it challenging to retrofit and theory? No, but like
Speaker 4: you need to talk to different endpoints. If you don't
Speaker 4: have DNS properly set up, that's kind of breaking change
Speaker 4: for your customers, et cetera, et cetera. So if you
Speaker 4: don't think about those things upfront, that can be problematic.
Speaker 4: But yeah, I agree. It helps you govern all your
Speaker 4: APIs and to secure them and keep things under control,
Speaker 4: which is usually a problem if you're growing like fast
Speaker 4: as a company.
Speaker 1: Yeah, for sure. Some things people don't think of when
Speaker 1: they expose an API layer is denial of service attacks
Speaker 1: against your API. Yes, you know, because if you have
Speaker 1: an endpoint out there that's answering the door no matter
Speaker 1: who comes to the door, and an army shows up,
Speaker 1: you've got a problem.
Speaker 4: Yeaheah, it's fine until it isn't. Yeah, then go figure
Speaker 4: out how to solve it. If you don't have a
Speaker 4: solution like this.
Speaker 1: Even when that DDoS attack is an over diligent developer
Speaker 1: who's written some bad software.
Speaker 4: Oh well, I've seen things before I joined, Like people
Speaker 4: get to know what a health endpoint is, so they
Speaker 4: eagerly start adopting it and then they create their own
Speaker 4: videos attack and they cannot turn it off, so they
Speaker 4: need to figure out which machinef to shut down to
Speaker 4: avoid bringing their customers down.
Speaker 2: That's an interesting one and that's one of the things
Speaker 2: that as your API is really good for is that
Speaker 2: you can hey, take that one out. You know, in fact,
Speaker 2: you can set you set a policy places it's over there,
Speaker 2: just shut that one off and let me know.
Speaker 1: Yeah.
Speaker 4: Ballacies are a great way to rate limit at a
Speaker 4: validation of the payloads at security logging, KPI tracking, et cetera.
Speaker 4: And the second thing we have is like API analytics.
Speaker 4: So if you were to have one customer that's very
Speaker 4: aggressive and you need to figure out like who is it,
Speaker 4: that report would basically tell you, oh, it's Richard or Carl,
Speaker 4: we need to reach out or probably make access.
Speaker 1: Yeah.
Speaker 4: So and now we have as of built I think
Speaker 4: last year, we have an AI gateway and that one
Speaker 4: is getting a lot of traction. So you can also
Speaker 4: put it in front of your AI models and workloads.
Speaker 1: You mean, if you have exposed an ll M via
Speaker 1: an endpoint. Why would you do that?
Speaker 4: Yeah? For example, if you have asure open AI, but
Speaker 4: you need to kind of rate limit the tokens for
Speaker 4: that service or balance across accounts, you can now do
Speaker 4: that through our gateway as well.
Speaker 1: So there's still security there.
Speaker 4: Yes, there's security. There's rate limiting, monitoring, et cetera. So
Speaker 4: that's growing a lot as well. So, like I can imagine,
Speaker 4: we keep joking we used to be an API gateway,
Speaker 4: but now the piece between brackets because we're also in
Speaker 4: AI gateway Now.
Speaker 2: Yeah, I mean it's just a subsection in the documentation
Speaker 2: for the Azure API management but it's I bet it's
Speaker 2: got a lot of demand on it right now. Lots
Speaker 2: of people are trying to figure out what the product
Speaker 2: is here.
Speaker 4: Yeah, it's it's been fun lately. I wouldn't say quiet,
Speaker 4: but interesting.
Speaker 1: Interesting, we've been busy.
Speaker 2: What I mean, what makes the is the the tricky
Speaker 2: part of the AI gateway. Now you're measuring tokens like that,
Speaker 2: that's the issue. I want to rate limit on tokens?
Speaker 4: Yes, correct, Yeah, so measuring tokens uh to rate limit
Speaker 4: but also kind of have metrics. Who's using how many
Speaker 4: tokens were to have those insights, Yeah.
Speaker 2: All the same things I want when with my a
Speaker 2: PI utilization it's like, you know, this person is making
Speaker 2: x many calls per second, or yes, they're doing the
Speaker 2: most expensive calls like that, that kind of thing, just
Speaker 2: sort of having that shape of what the utilization looks
Speaker 2: like per customer exactly. Yea, yeah, all right, because yeah,
Speaker 2: if you're if you're if those tokens roll uphill and
Speaker 2: you're paying for them and then you know, flat rating
Speaker 2: to the customer, this is a good way to bankrupt
Speaker 2: your company a big old hurry exactly.
Speaker 4: So that's that's why we try to help protect yourself
Speaker 4: from running out of money.
Speaker 2: Yeah, finding out all of a sudden you yeah, I
Speaker 2: don't think. I think, yeah, I suddenly get a big
Speaker 2: bill at the end of the month. It's like, guess
Speaker 2: what your customers did.
Speaker 1: Exactly. That's what probably also a good place to log
Speaker 1: the prompts, right, Yes, so you can do that. You
Speaker 1: could say, hey, we ran out of token, so let
Speaker 1: me see what everybody's sending, and then they're like, you know,
Speaker 1: what's the nearest burger king or whatever, Hey, you don't
Speaker 1: use it for that.
Speaker 4: Or how often do people say thank you?
Speaker 1: Yeah? Right. There was a whole article about how much
Speaker 1: thank you was costing in tokens.
Speaker 4: Yes, it's burning a lot of compute just to process
Speaker 4: thank you, which is being polite in case the robots
Speaker 4: start to wake up.
Speaker 1: But I don't know money. I think it helps us
Speaker 1: when we're polite to the models.
Speaker 2: Yes, I got it. I got to tell you. I've
Speaker 2: read some prompt chains for coding where it's like, dude,
Speaker 2: if this wasn't software, this is an HR violation. Why
Speaker 2: are you communicating to this tool so obnoxiously?
Speaker 1: Yeah? Right, I told you that. My My wife's favorite
Speaker 1: thing to tell she who starts with a you know,
Speaker 1: the echo, but is shut up, not stop. She just
Speaker 1: says shut up and it and it works makes her
Speaker 1: feel good. I guess.
Speaker 4: I don't know.
Speaker 1: Google.
Speaker 4: Google responds interesting. So once was an in traffic jam
Speaker 4: and then Google asked me how can I help you?
Speaker 4: And I said, oh, go away, like not so politely,
Speaker 4: and it said, oh, I know I'm not a human,
Speaker 4: but you still need.
Speaker 1: To be polite, but be nice.
Speaker 4: It's like there was like, okay, interesting, good point.
Speaker 1: Yeah do I do? I? Well, like I said, I
Speaker 1: think it makes us humans feel better about ourselves when
Speaker 1: we're just polite as a habit. I agree. Yeah, No,
Speaker 1: I think that, you know, negativity is contagious, Yes, you know, ye,
Speaker 1: and so I think think it's a thing.
Speaker 4: I guess it comes. It will also improve you, Like,
Speaker 4: these agents work better the more context you give it,
Speaker 4: and if you're more polite, you will naturally give more
Speaker 4: context and explain more rather than being rude. That's not
Speaker 4: going to be useful anyway.
Speaker 2: Yeah, route tends to be terse where politeness tends to
Speaker 2: be more or moose, and that additional information should get
Speaker 2: better results exactly. Yeah, that's an interesting point on that
Speaker 2: as well. It's just like, hey, it makes the room nicer. Sure,
Speaker 2: I'm just thinking about a bullpen of developers, you know,
Speaker 2: a dozen people working together and they're all cursing at
Speaker 2: software at the same time.
Speaker 1: What kind of room is that. I don't know if
Speaker 1: I want that room, I want a better room than that.
Speaker 4: That's why they invented the term war room.
Speaker 5: Yeah, yeah, well there is, there are real war rooms,
Speaker 5: you know, and I think I think we just borrow
Speaker 5: that in software from the military.
Speaker 1: We had a warm room at a place that I
Speaker 1: worked in California in the nineties. It was before Carl
Speaker 1: and Gary's went up. So, but it was my idea.
Speaker 1: It was this is a really weird experience. I basically said, hey,
Speaker 1: let's make this extra office that nobody's using the warm room,
Speaker 1: and if somebody has a problem, you go in there
Speaker 1: and try to solve it with them, and you know,
Speaker 1: shut the door, and then when you come out, you
Speaker 1: don't come out until you have a solution. So one
Speaker 1: developer said, Okay, Carl, let's go into the warm room.
Speaker 1: I have a problem. I said, what, And he goes,
Speaker 1: do you have an agenda? Like what? Oh? Man, that's weird.
Speaker 1: Be careful what you ask for. Yeah, I know.
Speaker 2: And nothing's free, man, it comes to consequences the case.
Speaker 1: Yeah, why don't we take a break? Yeah, that's good idea.
Speaker 1: So we'll be right back after these very important messages.
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Speaker 1: Rocks Amateur Campbell. It's called Franklin.
Speaker 2: Hey, talking to our friend Tom, who spends part of
Speaker 2: his life in API management. But now you're more focused
Speaker 2: on sustainability. But I guess API managements about sustainability as well, right.
Speaker 4: Yeah, So we've been spending some time on this because,
Speaker 4: like we just mentioned, like we front all these APIs
Speaker 4: and now these AI models as well, and we kind
Speaker 4: of have a good position to help customers who want
Speaker 4: to reduce their emissions. Interesting, like, we're at the heart
Speaker 4: of these platforms and we know where the traffic is
Speaker 4: going to route, so we have a very good opportunity
Speaker 4: to make sure that the traffic that gets routed to
Speaker 4: the back end can for example, be routing to a
Speaker 4: region where it is daytime versus night, which means right,
Speaker 4: if they're more solar. If we map them to the
Speaker 4: Azure data centers, for example, we know what the regular
Speaker 4: emission is in those regions, so we can say, oh,
Speaker 4: this one now runs dirty energy. Let's shift the traffic
Speaker 4: to another region where we know it's screen energy. And
Speaker 4: that gives you the benefit of if they use auto
Speaker 4: scaling on these back ends, they can really shift their
Speaker 4: whole traffic there so they can scale in and reduce
Speaker 4: their emissions.
Speaker 2: And it's an interesting truth that data centers have more
Speaker 2: energy available during the day, presumably largely due to solar
Speaker 2: so arguably could even be cheaper. You know, we could
Speaker 2: be chasing the lowest cost workloads around as well. I've
Speaker 2: always thought that API management was a great point for
Speaker 2: measuring like cost of transaction, but you're also talking about
Speaker 2: emissions per transaction as well. Is Microsoft, We've seen a
Speaker 2: lot of work being done and Carl you've been a
Speaker 2: part of that with the new version of Polly where
Speaker 2: they're re engineering software A to scale enormously, so just
Speaker 2: to be more aware of what that utilization looks like
Speaker 2: at scale, because they're looking at millions billions of utilizations
Speaker 2: possibly per second, and that does every cycle costs money,
Speaker 2: every cycle lost money. Man, So yeah, intriated, all these
Speaker 2: things work together.
Speaker 1: Stein of Energy, Richard, do you want to give us
Speaker 1: a little what am I trying to say a little
Speaker 1: preview of the end of year energy geek out? Anything
Speaker 1: that you'd like to talk about in terms of energy
Speaker 1: methods or generating energy from you know, to power these
Speaker 1: AI data centers. That might be a good idea. Well,
Speaker 1: I'm there's a whole section.
Speaker 2: You know, I work off my notes for the end
Speaker 2: of year geek outs for months, so I have a
Speaker 2: whole section about what all the tech companies are doing
Speaker 2: to deal with the power requirements for AID data centers.
Speaker 2: It's extraordinary. And you know, we've talked about this before
Speaker 2: and I don't want to get too far into it now,
Speaker 2: but power companies are all sure conservatives. They don't tend
Speaker 2: to build new technologies. That's not what power companies do.
Speaker 2: They're in the reliability business. Tech companies like building new things.
Speaker 2: So an interesting debate here about whether it makes sense
Speaker 2: for tech companies to actually mature power technologies, mostly because
Speaker 2: the three spending money on them that'll be available to
Speaker 2: the greater public in the long term. So yeah, stay tuned.
Speaker 1: We have a nuclear power station in my town. I'm
Speaker 1: at the north end of the town. It's at the
Speaker 1: south of the southern tip, right on the water. And
Speaker 1: this we heard rumors floating that somebody wanted to op
Speaker 1: I think it might even be Microsoft might have wanted
Speaker 1: to open a data center or build a data center
Speaker 1: right next to the power nuclear power plan. Sure interesting,
Speaker 1: you know, and that's really thinking ahead because if you're
Speaker 1: going to use wads and wads of energy, you might
Speaker 1: as well be as close to the source as possible.
Speaker 2: And it reminds us that data centers in many ways
Speaker 2: are the new heavy dust street. You know, it's super
Speaker 2: normal to build an aluminum smelter or a steel plant
Speaker 2: beside the power generation source because you use so much
Speaker 2: of it. So you know, this new heavy energy building
Speaker 2: it alongside its power makes a lot of sense. But
Speaker 2: that's another show, and.
Speaker 1: Another show I don't want to do rail Us and
Speaker 1: another show that's coming up soon. Yes, yes, the end
Speaker 1: of the year is upon us.
Speaker 4: So it's interesting though how much progress they've made on
Speaker 4: the data center side to be more efficient. Like, I'm
Speaker 4: not an expert on that, but like we now have
Speaker 4: AI data centers they announce that ignite it are fully
Speaker 4: closed water systems where they pour in like households of
Speaker 4: water that they consume usually in the closed system, and
Speaker 4: it stays in there for years. Right, because it's closed loop,
Speaker 4: you're not like losing any water.
Speaker 2: Yeah, they're reusing water over over again, she was more complicated, doue.
Speaker 4: Yeah, they're getting rid of concrete by kind of reinventing
Speaker 4: types of wood to make it more sustainable. It's really interesting,
Speaker 4: mind blowing, Yeah, if you dive into that area.
Speaker 1: Yeah.
Speaker 2: And the advantage here, of course, is that tech is
Speaker 2: not a low margin business, so you can afford to
Speaker 2: spend more money knowing you're going to earn out over
Speaker 2: time with these data centers. But I think this all
Speaker 2: starts with being able to measure utilization. Yes, it's crazy
Speaker 2: to think about this in context of an API, but
Speaker 2: it makes perfect sense.
Speaker 1: It is the logical unit of measure.
Speaker 4: Yeah, so we don't expose the kind of the carbon
Speaker 4: emission directly, but if you want to measure things in
Speaker 4: azure there's a service called Azure Carbon Optimization which shows
Speaker 4: you the emission by Azure compute workload and it gives
Speaker 4: you kind of a recommendation and it says, for example,
Speaker 4: it's also good for cost saving. Oh, you're using this
Speaker 4: vmsas instance, with this vmskew, this is your emission for
Speaker 4: this service, but you're utilizing only like twenty percent. We
Speaker 4: recommend you using this skew or that skew or all
Speaker 4: these kind of things. So that is good for the
Speaker 4: kind of reporting side. Interesting, where are we over provisioned?
Speaker 4: And then what we're trying to help with is to
Speaker 4: kind of route your requests to the regions where it's
Speaker 4: more efficient. But there's also a second aspect, like we
Speaker 4: have all these policies that you can run kind of
Speaker 4: this logic on your gateway before going to the back end.
Speaker 4: So we've introduced capability that in your policies you can check, oh,
Speaker 4: the emission is high. So let me not log all
Speaker 4: these big payloads which require more compute on the gateway
Speaker 4: or puts pressure on service bus or event hubs in
Speaker 4: that region. Let's just skip this section and reduce the
Speaker 4: kind of the overhead in this region. If it's not
Speaker 4: required so that the gateways can also scale in.
Speaker 2: So it's just a recognizing there are optional workloads that
Speaker 2: could be time shifted, the location shifted, yes, to change that.
Speaker 4: Like auditing metrics. These kind of things are not always
Speaker 4: mission critical. So I always compare it with what teams
Speaker 4: did during COVID right, they were overloaded, they did not
Speaker 4: have the CPUs, so we did it small things like
Speaker 4: remove the Thomas typing indication, which costed a lot of CPU.
Speaker 4: And there's a blog from I think Mark Rosinovich that
Speaker 4: explains the impact from disabling that feature on the compute
Speaker 4: that required. Wow, it's kind of our flavor of this
Speaker 4: for your APIs Yeah.
Speaker 2: Yeah, No, I think it's interesting to think in terms
Speaker 2: of you've got a company with a green initiative like this,
Speaker 2: and you can start working through your software to say
Speaker 2: where can we make an optimization. There's a case study
Speaker 2: begging here to say, well, which which of these has
Speaker 2: the largest impact?
Speaker 1: Where do you even start? But I think the number one,
Speaker 1: of course is measure is once you measure, the obvious
Speaker 1: ones will fall out. Yeah.
Speaker 4: Measure and adopt auto scaling would be another one. I
Speaker 4: would say, like a lot of people are over provisioned
Speaker 4: or maybe like you don't need to be over provisioned
Speaker 4: all the time. Like most cases, customers can just start
Speaker 4: scaling out during the business week, but in the weekend
Speaker 4: they can scale in because nobody's in it.
Speaker 2: Yeah, if you still got the old reflexes, which I'd
Speaker 2: have to admit I still do. Like we always when
Speaker 2: we're building out our own infrastructure, you provision for peak,
Speaker 2: which is to say, you over provision for everything else, Yes,
Speaker 2: so that you can get through you know where we're
Speaker 2: recording this right around the time Black Friday is coming,
Speaker 2: so talk about peak, right, and so they you know
Speaker 2: the idea that really elasticity works both ways, not just
Speaker 2: scaling up but scaling down. Yes, but autoscale is not
Speaker 2: a product per se, right, Like there's a lot are
Speaker 2: things that go into auto scale.
Speaker 4: Yes, that is true. There's more things you can do though,
Speaker 4: Like it doesn't always have to be like this intense.
Speaker 4: Let's say, like architecture platforms like this, because of course,
Speaker 4: if you shift traffic, the kind of the new region
Speaker 4: where all the traffic is going needs to be able
Speaker 4: to handle it, because otherwise you're going to create your
Speaker 4: own outage. So that's why if not a single back
Speaker 4: end is kind of healthy, we'll just keep routing it
Speaker 4: there anyway. But as a developer, what's one of the
Speaker 4: most common thing that happens. I check in my code,
Speaker 4: I have a CI trigger, etc. In a lot of cases,
Speaker 4: people have a lot of pipelines starting out, but nobody
Speaker 4: looks at them. Right, that's a lot of compute as
Speaker 4: a company or burn So maybe revised. If you really
Speaker 4: need all of those CI pipelines, or make them on the.
Speaker 1: Nd maybe you only activate the pipeline on Friday or
Speaker 1: something exactly.
Speaker 4: So if it's not like that urgent, maybe don't do it.
Speaker 2: Yeah, you guys are countering like a decade. Now I'll
Speaker 2: go faster, go faster, Go faster, go faster. Right, it
Speaker 2: depends if you're using these pipelines. Fine, but I've seen
Speaker 2: a lot of people that once create a pipeline, then
Speaker 2: never look at it anymore.
Speaker 1: Question right, Well, I kind of think that was the
Speaker 1: lore of doing that. It's like, yeah, automate as much
Speaker 1: of that work as possible so that you don't have
Speaker 1: to worry about it. But now we're worrying about it
Speaker 1: because it's costing a lot of cycles and money that
Speaker 1: you know comes down to money.
Speaker 4: It is a trade of like is it useful or
Speaker 4: is it something that we actually don't really need anymore
Speaker 4: or run less often?
Speaker 1: Maybe remember we used to have build Friday's Richard, yep,
Speaker 1: you know, back when we thought a build master was
Speaker 1: a good idea. Oh yeah, build server. We had to
Speaker 1: build server. Yeah, but you know we're happy with just
Speaker 1: checking in code and everybody's synced up and all that stuff.
Speaker 1: And when we want to have a release, you just
Speaker 1: publish it and it's yeah, we can get that down
Speaker 1: to just one command now right.
Speaker 2: Yes, well so, but to Tom's point, you also get
Speaker 2: to the situation where everybody's pushing builds constantly and then
Speaker 2: somebody's deciding to actually put it out, and so in between,
Speaker 2: all those in between builds were kind of unnecessary. So
Speaker 2: you know, the advantage of automation is that it's also
Speaker 2: then tunable. So it would be that hard to go
Speaker 2: back in there from a macro perspective and say, how
Speaker 2: many of these builds actually get used?
Speaker 1: Can we delay? You know, when does it make sense
Speaker 1: actually push? And then with the consequence of that, I.
Speaker 4: Think CI is one aspect. There's also the situation where
Speaker 4: you have scheduled pipelines where the tests every hour or
Speaker 4: every two hours, but how often do you really look
Speaker 4: at these tests? Like maybe daily is enough?
Speaker 1: Right? How important do you see agency in DevOps be
Speaker 1: becoming a partner so that you could give it a
Speaker 1: set of rules that it could monitor and make its
Speaker 1: own decisions as to when to build based on those rules.
Speaker 1: Because that's really what you're doing when you when you're
Speaker 1: figuring out strategies and and doing it yourself. So I
Speaker 1: mean when you see that.
Speaker 4: I think that that's something that will come as a
Speaker 4: next step. Maybe not as the next step, but eventually
Speaker 4: one Like we push all these cis how many devs
Speaker 4: actually check if it regresses the tests, then everything accumulates
Speaker 4: and then you have x failing tests. Now go figure
Speaker 4: out what what what's the problem or who to figure out?
Speaker 4: Who to solve this problem? I think that's where agents
Speaker 4: will become a theme where they kind of auto three
Speaker 4: IG identified the issue. Yeah, picking the people alto rovert
Speaker 4: or whatever. That's going to help a lot.
Speaker 2: On run as I just put out a show on
Speaker 2: the Azure software Reliability Engineering agents, which that's literally what
Speaker 2: their job is is to pick up events in it
Speaker 2: that occur and a deployed piece of software and analyze
Speaker 2: them even to the point of making co change recommendations.
Speaker 1: This is all in the back end in Azure. It's
Speaker 1: all in Azure. Yeah.
Speaker 2: Yeah, these agents, I mean, it's the still miles to go.
Speaker 2: These are early versions, but it does speak to I
Speaker 2: think exactly what you're describing to them that you will
Speaker 2: have from you know, you know, as a guy who
Speaker 2: spent time on a Saturday trying to keep an e
Speaker 2: commerce side alive. The fact that you can have an
Speaker 2: error and these tools will at least do the initial
Speaker 2: homework right that by the time you're looking at it,
Speaker 2: it's already done. The pull of this was the state
Speaker 2: of the machine, This was the current load levels. Like
Speaker 2: all of the infos, we at least have a shape
Speaker 2: of what was this problem.
Speaker 1: Yeah, and at least they could recommend a few courses
Speaker 1: of it and you didn't even have it to it.
Speaker 1: But you're making decision and that's yeah, that's where we
Speaker 1: are today. I like that. I like being the decider.
Speaker 1: I'm the decider.
Speaker 4: So you're talking about it as youre s a reagent.
Speaker 4: I presume that's right. Yes, that is a very that's
Speaker 4: something we're onboarding as well. Like a lot of times
Speaker 4: it just reboot a machine and monitor its progress or whatever.
Speaker 4: It's perfect for all these kind of things.
Speaker 1: Yeah, for sure.
Speaker 4: Reducing all that toil, it's really great.
Speaker 2: Yeah, if the answer was just reboot the machine and
Speaker 2: the problem will go away. The fact that you can
Speaker 2: have a tool that can get to that chain and
Speaker 2: do it for you, yes, and so by the time
Speaker 2: you know about it, it's already happened and recovered itself.
Speaker 4: Yeah, and then it will start aggregating all these symptoms
Speaker 4: and kind of unfold the bigger problem. It's like, why
Speaker 4: do we need to reboot all these machines. Then it
Speaker 4: will kind of summarize all the symptoms and say, probably
Speaker 4: your problem lies there, now go fix it.
Speaker 2: Yeah, memorily here, or do dispaced there, that kind of thing.
Speaker 1: You know, It's always funny when the software acts and
Speaker 1: then notifies you.
Speaker 2: Like back in the old SQL server hot failover days,
Speaker 2: like you would just get a notification databases failed over,
Speaker 2: and it was chilling because it's like, well, why did
Speaker 2: you fail over?
Speaker 1: You know you're going to fail again. Reminds me of
Speaker 1: the early days of Azure Web Services when you because
Speaker 1: they didn't understand how to deal with the memory leaks
Speaker 1: or things like that, there was no stuff built in
Speaker 1: on the server. The recommend mended course of action was
Speaker 1: to automatically restart the service on a schedule, just you know,
Speaker 1: and that was a way that you could out of sight,
Speaker 1: out of mind memory leaks or other problems. Yep, you know,
Speaker 1: turn it off, turn it back on. The universal fix.
Speaker 1: All right. How much is security in the back of
Speaker 1: your mind or the forefront of your mind is to
Speaker 1: work your way through these things APIs and AI in
Speaker 1: all of that.
Speaker 4: That's a good question, Carl. So in the past half
Speaker 4: a year we've seen the sprawl of MCP servers spinning
Speaker 4: up its very early days on the kind of the
Speaker 4: authentication specification for this. But that's actually one of the
Speaker 4: aspects that we can help with with Azure Api Management
Speaker 4: is you can expose your APIs as MCP servers, and
Speaker 4: we have Azure Api Center, which is basically your internal
Speaker 4: MCP catalog or API catalog that can help you keep
Speaker 4: track of all of these things. And the beauty is
Speaker 4: that because you expose them to Azure Api Management, you
Speaker 4: can reuse those policies and say I want to have authentication,
Speaker 4: I want to have weight limit, et cetera. So you
Speaker 4: still can use these MCP servers inside your organization, but
Speaker 4: you can still have kind of your enterprise policies on top. Yeah,
Speaker 4: that policies and control on top that you have as
Speaker 4: a standard in your company to make sure it doesn't
Speaker 4: become a liability.
Speaker 1: Yeah, and that's all good stuff. What I'm thinking about
Speaker 1: is giving an MCP server, which is really an agent, right,
Speaker 1: giving it agency to act on your behalf things that
Speaker 1: you know, maybe some people don't want it acting that
Speaker 1: way on your behalf. Maybe that could pose a problem,
Speaker 1: especially with over hyperactive, hyperactively helpful lms like you know,
Speaker 1: Claudes on It for example, loves to do things that
Speaker 1: you didn't ask it to, and if it had if
Speaker 1: it had the power to send emails or to read emails,
Speaker 1: it could infect a system with now where like, there's
Speaker 1: so many problems when you give an agent agency to
Speaker 1: do things that might seem very convenient for you but
Speaker 1: could open up security holes.
Speaker 4: I think authorization is a very important point here, Like
Speaker 4: even if it would still have access, is it still
Speaker 4: authorized to perform the action right, right, and as you
Speaker 4: expose those APIs, like one of the things we allow
Speaker 4: you to do is like maybe you have an API
Speaker 4: that says get an order, create an order, and cancel
Speaker 4: an order, and then the back office of your store.
Speaker 4: But when you expose the MCP server, you have the
Speaker 4: option to only expose get order, maybe create order, and
Speaker 4: the rest. It doesn't like, even if it would have
Speaker 4: access to it, we're not going to expose the API
Speaker 4: even so it's not able to haul it right. And
Speaker 4: I think that's the second aspect, is that we used
Speaker 4: to have all these open eyes spects with the operations.
Speaker 4: Now with this tooling, which is not a human person,
Speaker 4: we need to be more careful what are we even
Speaker 4: giving it access to.
Speaker 1: For example, giving a SEQL server MCP the ability to
Speaker 1: generate queries and run queries.
Speaker 4: That is very dangerous.
Speaker 1: Yikes. I mean, think about that, generate t sql and
Speaker 1: then execute it. Unless you say, the only thing you
Speaker 1: can the only command you can create is select.
Speaker 4: Is drop table.
Speaker 1: If you say select is the only thing you can
Speaker 1: do and you can't do anything that's going to act
Speaker 1: you know, drop table or delete or anything like that.
Speaker 1: You know, but you're still still untrustworthy, I think.
Speaker 4: Very dangerous, and also enough material for the LM to
Speaker 4: have trained on to learn what not to do, you
Speaker 4: would hope, So that is definitely yeah. I think that
Speaker 4: comes back to the point I was making, like, don't
Speaker 4: just expose everything. Think carefully, do reviews of what you're exposing.
Speaker 4: Because it's not a human anymore. It's something that you
Speaker 4: will ask And like you mentioned, some models are eager
Speaker 4: to help, but that means you, like, maybe they're going
Speaker 4: to do things you don't want.
Speaker 2: Anyway, I do appreciate that, you know, getting back to
Speaker 2: as your API management. It's like you have to go
Speaker 2: down the ENTRA pipeline to even use this, right down
Speaker 2: to sort of the B two C model where your
Speaker 2: customers have to have identities and so forth. You're forcing
Speaker 2: us into the pit of security success. You want to
Speaker 2: use these tools, you've got to follow zero trust rules.
Speaker 2: You've got to properly authenticate everybody. It's that authorization and
Speaker 2: policy in place, and it's a paint in the butt.
Speaker 2: It's part of the challenge of getting started with these things.
Speaker 2: It's also way beneficial when stuff goes wrong.
Speaker 4: Yes, and I was not part of the screw, so
Speaker 4: I cannot kind of get into the details. But and
Speaker 4: ignited last week when we're recording this, foundry was a
Speaker 4: big thing. And as part of Foundry or AI gateways integrated,
Speaker 4: which means every agent now hasn't dedicated entra id identity. Right,
Speaker 4: So we used to be humans who had like a
Speaker 4: personal email address with an identity. Now agents have the same.
Speaker 4: So that kind of gives you the next step of
Speaker 4: putting these guardrails around these agents to make sure they're not.
Speaker 2: And I hate to can't anthropomorphize on that because we've
Speaker 2: also been giving applications identities as well for exactly the
Speaker 2: same reason, yesh, right, But.
Speaker 4: For agents it was it was more it was harder
Speaker 4: to achieve this and it was not really like dedicated
Speaker 4: to the model model, like you had to kind of
Speaker 4: configure it that way. But in this case, it's like
Speaker 4: fully dedicated to this agent, let's say. But again I
Speaker 4: did not work on that, so I need to defer
Speaker 4: that to my colleagues. But I think that's a good
Speaker 4: step forward for security as well.
Speaker 1: Tom, is there anything that we missed, anything else you
Speaker 1: want to talk about before we wrap it up?
Speaker 4: No, So if somebody is interested. We have a blog
Speaker 4: post which we can maybe onto the show notes where
Speaker 4: you can sign up to use these sustainability capabilities. There's
Speaker 4: a ton of announcements from Mignite. We also shift some
Speaker 4: of the AI capabilities which you can find on the blogs.
Speaker 4: But if you have any questions, just reach out to
Speaker 4: me on LinkedIn. Happy to excellent answer.
Speaker 1: Your question, Tom. Thanks, It's always interesting when we talk
Speaker 1: and this was no different. Thanks very much.
Speaker 4: Thank you very much. Have a good day many all.
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