Luyện nói tiếng Anh bằng Shadowing qua video: FullStack Interview Questions (Junior & Mid)
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So first question of today's interview, what is an SQL injection attack?
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An SQL injection attack.
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Can I share my screen?
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Yeah, sure.
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Go ahead.
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If that helps.
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Okay.
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So SQL injection, it's basically when we have a webpage, right?
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And we have an input field on that webpage.
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Let's imagine it that way.
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And basically the attacker, so this is our application.
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We have a backend and the attacker is capable of writing SQL code over here.
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So they do write some SQL.
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Oh my God, I'm super zooming.
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So they write some SQL over here
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and that SQL gets actually executed because we failed to sanitize that input into our database.
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And they could do certain things like they could probably, for example, change the privileges of their own user.
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They can read our database.
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They can drop the database.
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And this was a very common attack, I think back in the early 2000s.
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So basically what they would do is I would write here some SQL, like select all from but they need to engineer their queries very well
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so for example what they would do is they would add they'll try different things
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and you would start this statement with maybe a semicolon
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and what that would do is that in the back
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if in the back end the way the back end developers
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go their queries was like this like let's say they had
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a select all from users where user username it's equal to and you would normally do string interpolation
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with the input that comes from the front end.
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So you'd put directly the input here.
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The attacker could actually put this query that they put in into here.
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And so you'd end up running SQL on the database.
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And the way to avoid this is to just use, first of all, sanitize all the input.
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And second of all, use SQL parameters.
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Basically, they look something like this.
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But what SQL will do when you send this query over and you provide this dollar sign argument separately, it will not run this as SQL.
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It was really like the query, the executable part of the query is this one and then provide this as an input and then it won't work.
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If they provide some SQL here, it's just going to, they will get no results, but it's not going to execute that on our database.
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Cool.
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Now we're going to move on with the second question.
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Can you explain HTTP caching?
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Right.
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And also go into advantages and let me know if you ever used it in the past later.
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Awesome.
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Sure.
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So HTTP caching, it's one of my favorites because it's very easy to set up these days.
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And basically, well, it's always, it's an HTTP mechanism.
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So it happens between a client and a server.
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And imagine we have here a CSS file or any other file, an image, a heavy file.
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We definitely want the users, we could actually make the webpage load faster
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if users could reuse this resource in the future and not have to download it every time they go to their website.
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So what happens normally is, let's imagine this is our server.
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And they will be our client.
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Yes.
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And they'll make a first request of an asset.
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It can be even a REST resource, an HTML file.
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And so what they would receive in the HTTP headers would be a header called cache control.
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And there's different values for this header.
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but one of the most common is to basically specify this is the header that specifies
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how the client should cache this
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so basically here they would have something like let me make this bigger perfect
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so we'll have something like public and a max age property
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so max age and this would be milliseconds
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and what this means is the client can reuse that resource as long as the age
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of the asset so there's an age which starts at zero
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when we just got it as long as the age it's
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smaller than max age the client doesn't need to get
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that resource uh basically the web browser would store
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that on the computer and get the resource from there get the css file from there um
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and that's so that's basically the the basics behind it what would happen what what's happening
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when the age goes higher than this uh then then whatever the max age was is that the
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client will make a request but it's not a request for the resource
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but it's rather to check
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if it's this is what we call caching validation is the resource still fresh is the resource still fresh
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and basically they will do that nowadays with the e-tag
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so you probably have an extra tag which was it's the tag
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and basically it's a unique hash that was computed for this version of the css file
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and so they will send that to the server
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and check was this modified
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and the server can answer with in two ways they can either say no it wasn't modify keep
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that version or yes it was modified make a request get a new version over
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and back to your question on
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if i ever used it this is basically uh most of
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times comes out of the box with any cdn you're using
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so if you're deploying your application
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and you put a cdn in front of it like a
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content delivery network basically they already apply this to all your
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static assets they add etags they add the cache control
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and the age and we can even go in
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and look at the live example
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if you want yeah let's pick something like maybe github
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or any like popular developer website okay let me see if i can share my screen again Now,
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one thing I want you to do to go over is this public parameter.
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You know, what does public mean in that request?
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Okay, so let's see how this looks like in Stack Overflow, for example.
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Yeah, so I'm going to go over why I did that and what does that mean, but I just reloaded a page right now.
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And as you see here, it says 200 from the disk cache.
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So this was not, this is not coming from the server.
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This is coming from my personal computer.
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And the reason for that is that you see I'm not sure how big this is, but the age parameter here, the age, it's this minimum milliseconds.
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And if we look at the cache control, it's a public mass max age 315, 360.
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So basically what this is saying is, Hey, you, you can keep the asset for a bit longer.
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Yes.
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As long as this age goes over, they will rely on the e-tag.
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So there's this e-tag header that should be somewhere.
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Now, because there's no e-tag, because I probably did not, give me a second, accept.
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Okay, it didn't really find the e-tag.
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I think they might be relying on the last modified.
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Last modified, it's an alternative and expires.
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There are alternatives to eTags, but because it's so hard in programming to compare dates and you need to always bring them back to a time zone,
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it's just a lot easier to use the eTags.
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And so the modern way is to use eTags.
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Maybe if we look at another asset, like a CSS asset, they probably use...
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I could see the eTag there.
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There you go.
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It has an eTag.
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but again um the cache control on this resource is no cache
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so okay even
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if we have it's not really being used that's what i was looking for this one that's a better example
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but again there's no there's no e-tag on this one
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so it very much depends on how they um perfect it's
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pretty much i feel like they're using an older um setup because they're using expire and last modify all the time
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The other thing is, as you see here, if we enable Disable Cache, what we will be doing, and this is something really cool that Google Chrome does for us, is that whenever we get a resource,
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on the request headers, we are setting a cache control ourselves to no cache as the client.
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We're saying, hey, there won't be any caching happening.
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Bypass the cache, right?
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Yes, you could say that.
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We're actually using the headers to specify there is no cache.
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and because we do that, you see cache control, no cache, then it doesn't really matter what the server implements.
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So just going back to the drawing, this is how HTTP caching works, I'd say at top view.
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Awesome, Bogdan.
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Now let's move on with the next question.
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So imagine you have a huge SQL database.
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We want to scale that.
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So what are the different ways we can scale that huge SQL database?
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Okie dokie so we have one of those um i'm going to go back to my board just
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because it's a lot easier to show than tell um yeah
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as a quick question do we know anything about the traffic
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on this database in terms of reads versus writes for example do we read a lot
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or do we write a lot what is it let's let's assume we read a lot more than we write
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but as we scale we will also um face a writing problem down the road.
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Okay, I mean most web applications you will read a lot more than you write
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if you take the example of Instagram and so on
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or any social media people watch and consume stuff much more than they publish on average.
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Yeah that's a good news feed based application like a social media that's a good example so you can use that yes.
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Okay so if that's the case and we get a lot of incoming traffic here
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and we figure out that the queries are getting slower the memory on this component memory
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and cpu usage uh it's blown up what we can do is to basically apply a replication strategy
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that will basically rather than having one database we will have one database
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that handles the reading
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and then we're going to have a bunch of let me copy this a bunch of read-only replicas so
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they used to be called master
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and slave although right now we can just call it the the main database
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and then uh and basically what happens is we write to the main database
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and whenever we write that it gets replicated to the child to the to the read-only replicas
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but whenever we read from the database we go to this cluster of read-only replicas
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and so we can offload a lot of reading pressure to these replicas
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and they are quite performant and
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that will be one of the easiest way to scale the
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database by by having read-only let me write it down here
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read-only replicas you can do this in aws i've done this with rds it's very straightforward
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and it's one of the easiest way now to follow up
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on what you mentioned as a second case imagine we do need to write a lot so
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um we are getting to this point where this database right is getting bigger
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and bigger we have too much pressure on the hardware
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and we either add more hardware which is usually a bad strategy or what we can try to implement it's sharding
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so basically what we do is
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that we try to split um into different databases based on a property
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that we hash so for example we have a bunch of records here
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and then we take their let's say the id
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and then we somehow hash it
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and you can think of this as a almost a load balancer it's not really a load balancer
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but based on the id we can actually push the record here or here or here
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and whenever we need to read based on the id whenever we want to fetch
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that then they will redirect
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and read from the right database getting into the distributed systems
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part right yes this is a bit more complex to implement again um
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because you don't want to do this with you don't write
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any application code you don't we don't want to couple the storage with our code
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so this becomes a bit more complex to implement um you need to know about consistent hashing
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and the hard thing about this is when you have joins
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or when you want to query um you want to query records
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that are distributed over distribution it's always um a huge limitation
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but if you're on a scale there's There's no way around it.
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Yeah, you mentioned scaling it via hardware, right?
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Let's say vertical scaling.
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This is an example of horizontal scaling.
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Why not scaling our database vertically?
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Why distribute in the first place?
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Very good question.
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The problem with vertical scaling is that it's going to become exponentially more expensive.
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The more hardware...
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So the difference between a machine that has, let's say 16 gigabytes to 32 in terms of price, it's very high.
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And the other problem is you will most likely not need
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so much capacity all the time you probably have peak hours
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and so the problem once you scale vertically is that it's not
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so easy to go back you need to shut down the server
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and then relocate to a bigger machine or even
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if you do it in the cloud it's usually very expensive it has downtime
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and you still have a unique point of failure that's another problem that can appear.
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So distribution not only improves scalability, but also improves availability of the resource.
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Okay, now we're going to go and talk about deployment.
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Could you explain the different deployment types?
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And as you explain them, feel free to dive deep into pros and cons, advantages, disadvantages.
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Yeah, different deployment types you've been exposed as a senior backend engineer.
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Okay, so I'm going to start with the simplest one.
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I used to do this, we used to do this at pretty much every startup you work for.
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That would be the in-place deployment.
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And this basically means that in one way or the other, we have our server, whatever that is, a Linux server, let's say.
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And we have a code that's, let's say, so let me make this green.
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Let me make my code blue.
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And basically, we just kind of somehow replace the code with a new version.
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I'm going to put that green.
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right so we somehow push a new version
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and then we restart the server i've done a lot of
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those especially at the beginning of my of my career it's
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very robust it's very easy to set up you just need to know a bit of server administration
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but you do have downtime so whenever you are restarting the application there might be downtime
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and it's extremely hard to roll back sometimes
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so rollback can be a problem uh you and
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because you don't have a good rollback mechanism downtime can another problem um
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and also well it depends how you have it set up
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but usually it's very very manual but this is like the good old-fashioned deployment um
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and you need to stay awake until
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2 p.m when you have no users right down downtime yeah i mean it depends on your traffic
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but i had to i did a bunch of all nighters doing those
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so um not funny cool not at all not at all um then Then there's the rolling deployment, which is more or less the same,
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but the only difference here is that, and this is when it gets complicated, because you, let's say, have a fleet of instances, because we are horizontally scaling our service, let's say.
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In Amazon, in AWS, they call this auto-scaling groups, but it doesn't really matter.
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You have a fleet of instances, and so what you do is you gradually deploy the new version of the software, right?
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So this becomes green all of a sudden, and then this too.
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And then ideally, there's no issues, and then it can continue um this is again it's kind
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of complex uh the disadvantage is some people will access version two
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and some other will action version version one
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so you can have problems there especially if you have databases involved
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because you need to also deploy migrations if you have a skill databases
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so again it's not great but it is the only way you can deploy to a fleet of instances
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the advantage here it's if there's any problem with these two you still have the other two alive
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so you can maybe just shut this down really quickly
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and then instantiate a bunch of those really fast
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so downtime it's a bit less
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but it's also again it's complex um you pay a lot of costs
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because you're distributing everything how do you distribute the traffic in this case
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um so in this case you have a load balancer component
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that sits here
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and the load balancer it's responsible for kind of distributing traffic either with a round robin algorithm
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or whatever load balancing algorithm you choose
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but again the load balancer doesn't really know which version is it
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so some users will go over there some users will go over there that's kind of the problem
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let's go into prosynchrons
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so um i what i understand is there is no downtime
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you just might get different different users might get different versions right
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but here we avoid the downtime right
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because we have this rolling strategy um yes
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and no you can still have users that experience bad experiences because if there's a mistake here, it's going to affect them.
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So you have less downtime, but you can have problems.
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And this is what the next, like the blue-green deployment kind of solves.
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Blue-green.
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So in here, we basically duplicate the whole thing.
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So rather than, imagine this is our old version, right?
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It's receiving traffic right now.
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yes and what we do is we totally deploy
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and provision in a total copy of this with a new application so let me just make this green
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okie dokie and so that
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because we have two of them we can actually make all our checks
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and then start redirecting traffic here and
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if there's any problem you keep alive this distribution and and shut it down as soon as you see there's a problem.
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So this has basically, literally, it shouldn't have no downtime.
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Like literally this has no downtime.
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No downtime.
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And the rollback, it's very fast because you keep this alive.
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And if there's any problem, you can shut it down.
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The disadvantage is you're going to pay a lot in your infrastructure costs.
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This can cost you a lot because you are duplicating this infrastructure and you need to keep it alive for a while.
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You also need to have a lot of complex tooling to be able to manage these load balancer components, to spin infrastructure really fast, so something like Infrastructure as Code can help you.
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But again, this is very complex.
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If you're using tools like Kubernetes and containers, you can set it up fairly quick.
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Is there any more type of deployments that you would like to mention?
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There's Canary deployment, and it's pretty much the same as Blue Green, but there's a big difference,
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which is that you usually only redirect part of the traffic to our new instance.
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So you go ahead and you say, let me have 2% of the traffic over here or 10%, or let me have the traffic from a specific geography.
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I worked with that a lot.
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And the other thing, the reason it's called canary is because you have a canary.
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remember the
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uh back in the days the miners had a canary
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that they would send over to see if if there's any gas leak
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and the canary
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if it comes back then then it's all good um the
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canary it's usually an entrance test that's running all the time
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and you run it against the new instance and so
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if the canary it's okay then you start um radiating more traffic again you need a canary that's number one
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and complex load balancing setup because you want to redirect you want to slice your traffic somehow
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and number five i do not consider this a type of deployment i know some people do
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but that would be the feature toggles where you you're really not you deploy the whole version
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but you have some code logic that can switch a feature on
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and off um i do not consider this a type of
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deployment for me it's almost like a feature in the software but some people do and it has several advantages
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which is that you decouple your deployment from your code deployment, like the deployment of the feature from the code deployment, but at the same time having a lot of feature toggles
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really increments the amount of testing you need to do to your software.
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So I'm not gonna add it as an extra deployment.
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Next question, how does the internet works?
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And I want you to explain that, you know, since the moment you type something into your browser, until the page is shown,
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but until the page is rendered to the users to yeah
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to the final user okay that's actually a very fun exercise
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um how does internet work well let's say it all starts as you mentioned with
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a web browser where we type something let's say we type the senior dev
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um so we type this in our web browser
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and the first thing the web browser will do it will
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make a query to look up the dns like the ip
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address of this of the server that's hosting this website
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and they will make
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that to the dns server like the domain name system the servers are basically like tables
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so you just kind of think of a table hosted somewhere
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that says you know what the senior dev uh let me see has
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so this senior dev whatever it has this ip address
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so whatever okay that's not the real ip address
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that i'm adding there but you get the idea so
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and they have a bunch of them
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and then the browser knows okay that's the ip address
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and of course this is the internet protocol and
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so over the ip network we will start sending we can now start sending ip packages um
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these ip packages are containing tcp packages and tcp packages are put together in an http request so basically
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when you type this address you end up making a 200
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get a get request to uh to this path to our domain
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and i would assume the the browser will send some headers to like what does it accept
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and most of times it would be something like accept text slash html
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so it's basically requesting an html file that we have here um
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so that would be the request and then it will be a response.
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So the server will connect, will open up a TCP connection with this and probably reply with, ideally, if I think it's successful, a 200 OK.
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And there will be some headers, but basically the headers will tell you what's the content type of our response,
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which would be text slash HTML.
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And then there's an empty line, and then you have your HTML document.
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HTML, which is obviously, it's just text, right?
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It's just a bunch of text.
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And then the browser will take this and see, okay, this is text HTML.
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So I'm going to get all the body of the request here and applies basically what we call the critical rendering path.
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So basically it will take our markdown.
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It will try to build the HTML tree.
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It will request any links to CSS assets
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or javascript assets it will interpret those
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and then it will try to stream to incrementally build the
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ui as it reads down the html very good overview um
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we're not gonna go deep into the critical rendering pad um because that belongs more to the front-end engineering
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interview but that's definitely a topic that um that's pretty interesting talking about
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painting final the final website to the user well bugdon uh
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this is it for uh today very well done now uh for the people watching us um you know
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if there's any specific back-end question you want bar the night
347
to dive deep uh just drop it in the comments
348
and we will add it to our next video that's number
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one um number two we are putting together a community for javascript software engineers
350
that are looking to get to the senior level with quality
351
resources accountability we have monthly calls where you can directly interact with bargain
352
and i um you know we help you with interview technical
353
interview resources any kind of resources you need to make
354
that jump towards a senior and beyond um
355
if you want to check it out uh just check the link in comments you can apply
356
and we will um you know we we have a bunch of people waiting to get in
357
so we will review your application just give us time
358
and get you in if there's a fit and finally
359
if you would like to work personally with barton
360
and i in a you know one-on-one group mentoring um coaching
361
program right this is what software mastery is designed for we are helping developers fill up the tinkle gaps
362
and become that confident competent senior engineer um
363
but we cannot work with any kind of developer
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so uh this is a premium service if you think you know
365
that would be something you'd be interested in just click on
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the link in the comments also you'll find a link to
367
apply for a small chat with me where we will see hey can we help you is this a fit
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and see if we can talk fighter uh whether you want to join us
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or not with that being said thank you so much very great answers
370
and we will see you folks in the next one
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15 từ khó nhất trong video, kèm phiên âm và nghĩa:
| Từ | Phiên âm | Nghĩa |
|---|---|---|
| cache danh từ | /kæʃ/ | bộ nhớ đệm, vùng nhớ đệm |
| canary danh từ | /kəˈnɛəɹi/ | chim tước, chim bạch yến |
| hash danh từ | /ˈhæʃ/ | thịt băm, thịt bằm |
| disadvantage danh từ | /ˌdɪsədˈvæntɪd͡ʒ/ | sự bất lợi |
| injection danh từ | /ɪnˈd͡ʒɛk.ʃən/ | sự tiêm |
| millisecond danh từ | /ˈmɪlɪˌsɛkənd/ | một phần nghìn giây |
| expire động từ | /ɪkˈspaɪə(ɹ)/ | hết hạn |
| duplicate động từ | /ˈd(j)uː.plɪˌkeɪt/ | nhân bản, sao chép |
| algorithm danh từ | /ˈælɡəɹɪðm̩/ | thuật toán |
| interpolation danh từ | /ɪnˌtɜː.pəˈleɪʃən/ | nội suy |
| miner danh từ | /ˈmaɪnə(ɹ)/ | thợ mỏ |
| fetch động từ | /fɛt͡ʃ/ | tìm |
| interpret động từ | /ɪnˈtɜː.pɹɪt/ | diễn giải |
| consume động từ | /kənˈsum/ | dùng, tiêu thụ |
| horizontal tính từ | /ˌhoɹəˈzɑn.təl/ | ngang |
Cụm động từ bạn sẽ nghe
| Từ | Phiên âm | Nghĩa |
|---|---|---|
| blow up động từ | nổ | |
| come back động từ | trở lại, trở về | |
| go back động từ | trở lại | |
| look up động từ | /ˌlʊk ˈʌp/ | ngước |
| open up động từ | mở | |
| shut down động từ | tắt nguồn |
Những câu đáng luyện lại
Các câu ngắn, trọn ý trong video mà bạn có thể dùng lại khi giao tiếp hằng ngày:
- Can I share my screen?
- Let's imagine it that way.
- You know, what does public mean in that request?
- Why not scaling our database vertically?
- Could you explain the different deployment types?
Ngữ pháp trong video
Những cấu trúc người nói dùng nhiều nhất, kèm đúng cụm từ trong video:
| Cấu trúc | Trong video |
|---|---|
| “Used to” used to + động từ — thói quen hoặc tình trạng trong quá khứ nay không còn | used to be · used to do |
| Câu bị động be + quá khứ phân từ — nhấn vào việc xảy ra, không phải người làm | was computed · was modified · be called |
| Mệnh đề quan hệ who / which + mệnh đề — thêm thông tin về người hoặc vật | tag which was · hardware which is · deployment, which is |
| Thì hiện tại hoàn thành have/has + quá khứ phân từ — việc đã xảy ra nhưng còn liên quan đến hiện tại | i've done · you've been exposed |
Phát âm cần chú ý
Người nói dùng 51 dạng rút gọn, ví dụ I'm, you're, we're. Hãy nói theo dạng ngắn đúng như bạn nghe.
- Âm “sh” và “zh”: cache /kæʃ/, hash /ˈhæʃ/, injection /ɪnˈd͡ʒɛk.ʃən/, exponentially /ɛkspə(ʊ)ˈnɛnʃəli/, instantiate /ɪnˈstænʃieɪt/
- Từ dài — đặt trọng âm cho đúng: parameter /pəˈɹæm.ə.tɚ/, disadvantage /ˌdɪsədˈvæntɪd͡ʒ/, millisecond /ˈmɪlɪˌsɛkənd/, vertically /ˈvɝ.tɪ.kəli/, ideally /aɪˈdi.ə.li/
Những âm người Việt thường gặp khó:
- Cụm phụ âm cuối — đọc đủ từng âm, đừng nuốt âm cuối: deployment /dɪˈplɔɪmənt/, millisecond /ˈmɪlɪˌsɛkənd/, restart /ˈɹiːˌstɑɹt/, executable /ˈɛksəkjutəbl/, performant /pɚˈfɔɹmənt/
- Âm /tʃ/, /dʒ/ và /ʒ/ — tiếng Việt không có, đừng đọc thành “ch” hay “gi”: disadvantage /ˌdɪsədˈvæntɪd͡ʒ/, injection /ɪnˈd͡ʒɛk.ʃən/, fetch /fɛt͡ʃ/, geography /d͡ʒiˈɑɡɹəfi/
- Âm /æ/ — mở miệng rộng hơn âm “e”: cache /kæʃ/, balancer /ˈbæ.lən.sɚ/, hash /ˈhæʃ/, parameter /pəˈɹæm.ə.tɚ/, attacker /əˈtækɚ/
Cách luyện với video này
- Nghe hết video một lần, chưa cần nói, và ghi lại những từ bạn chưa biết.
- Bắt đầu ở tốc độ 0,75×, nói đuổi từng câu, rồi quay lại tốc độ bình thường khi đã quen.
- Ghi âm giọng mình rồi so với bản gốc, chú ý các từ như cache, canary, hash.
Phương Pháp Shadowing Là Gì?
Shadowing là kỹ thuật học ngôn ngữ có cơ sở khoa học, ban đầu được phát triển cho chương trình đào tạo phiên dịch viên chuyên nghiệp và được phổ biến rộng rãi bởi nhà đa ngôn ngữ học Dr. Alexander Arguelles. Nguyên lý cốt lõi đơn giản nhưng cực kỳ hiệu quả: bạn nghe tiếng Anh của người bản xứ và lặp lại to ngay lập tức — như một "cái bóng" (shadow) đuổi theo người nói với độ trễ chỉ 1–2 giây. Khác với luyện ngữ pháp hay học từ vựng bị động, Shadowing buộc não bộ và cơ miệng phải đồng thời xử lý và tái tạo ngôn ngữ thực tế. Các nghiên cứu khoa học xác nhận phương pháp này cải thiện đáng kể phát âm, ngữ điệu, nhịp điệu, nối âm, kỹ năng nghe và độ lưu loát khi nói — đặc biệt hiệu quả cho người luyện IELTS Speaking và muốn giao tiếp tiếng Anh tự nhiên như người bản ngữ.