swaranga's comments

Amazon may be big but even then resources are limited. Individual teams owning the roadmap for services are still small. And there are always competing priorities. Do you prioritize these security and availability improvements or do you pickup some operational improvements to make our engineers oncall easier? Oh there is also this long line of customer features you need to deliver. And re:Invent is also approaching.

When you look at it like this, not very surprising that initiatives like cost savings optimizations may take a back seat for periods of time.

For me it is the little things. Like switching windows. Mac feels half a second slower then Linux and that delay make it feel less responsive. Opening up the terminal can iterm2 is another one. For me these things just adds up. I want my OS to get out of my way when I want to get work done.

I have turned off the genie effect and perhaps other animations, but my Ubuntu on my Lenovo still feels faster than the Mac.

Sure, it works for a narrow use-case like a pure function that just queries and returns data. What about stored procedures/triggers that mutate data on insert/delete etc?

With one-box, you can assign a specific set of customers/canaries to be served by the new 1-box and validate your results. If there is a problem you rollback and only your canary data was affected. It is just not very simple IMO.

Not a security engineer so can’t comment on the threat model. But an insider threat like a rogue employee can do as much damage with a managed laptop vs an unmanaged one IMO.

I am loving the Netflix model. You can ask for a MacBook or a thinkpad. If you opt for the thinkpad, you can also install whatever Linux you want and all tools will still work.

In fact you can bring your own laptop and without reimaging use that for development. All interval tools (of which there aren’t too many are written in Go so are cross platform). I ordered a framework laptop and will expense it once it is here.

Onebox deployment typically deploys the new revision of the application code to a single host/box and leaves the rest of the fleet in the older revision and then you run your tests against the new revision running in that single box. You also might monitor the metrics from that single box and attempt to find regressions from the rest of the fleet.

If the code is deployed to the database (version controlled or not) all application servers will start using the new code immediately which is not what we would want from a onebox deployment first strategy. Usually all the servers will share the same database and thus the code in the code in database model. What am I missing.

How would you do one-box deployments with code in the database? Everything else could be solved with perhaps some or a lot of pain.

I have no background in AI or neural networks. And I barely understand machine learning in general. My only chat bot experience is ordering pizza at a Dominos website, I must say even though it is stringing words together to form a coherent response using some statistical model, the engineering behind this seems staggering. I am super impressed that it has come this far.

I have been pretty happy with BofA. The mobile app is modern and wires and ACH can all be done online. I gripe though is that you cannot do either of those from the mobile app. You need to login to the website via a computer.

There are some edge cases because of which this had to be done, I think. For example calling static methods via the instance variables, the actual method called would be the static type of the variable at compile time and not the actual type at runtime:

    public static void main(String[] args) {
        Parent instance = new Child();

        if (instance instanceof Child p) {
            instance.print(); // prints Parent
            p.print(); // prints Child
        }
    }

    static class Parent {
        static void print() {
            System.out.println("Parent");
        }
    }

    static class Child extends Parent {
        static void print() {
            System.out.println("Child");
        }
    }

Hence, with flow typing, existing code could break in subtle ways.

Have you considered an HP Elitebook? I am using an Elitebook 850 G7 given by my company. I have been daily driving it for a year now with Ubuntu 20.04 (previously an 840 G3 I think) and have no complaints.

I use it with triple monitor setup, all 32 inch 2K (I find 2K better for programming) and use it with the Hp 120W dock.

I even upgraded its memory to 64GB myself from Amazon for much improved quality of life (I give Intellij 24G alone; have at it!)

I have long searched for a configuration (Linux laptop + docking station) that can drive a triple monitor setup. Ideally all three at 4K@60 Hz but I might settle for one of them being QHD (2560 x 1440). Why isn't there any confirmed options? Or is that the limitations of Thunderbolt?

For me, the Roku's killer features is its app that lets me instantly stream the audio to my phone/airpods so i do not disturb anyone else while still watching tv. All others require me to pair my headphones with the tv or some other painful process.

What would you say are some examples where you look back what the state was 15 years ago vs the progress we made till the present and the jump would seem just as profound. Just curious.

I felt the same way - it seemed like the early 20th century made so much progress with those visionaries compared what what is being made now. Obviously I am not well informed because that is likely not the case.

I have been using the HP Elitebooks provided by my company and works well with Ubuntu. No complaints. I even upgraded my RAM to 64 GB.

You are thinking of SQS, the preview version of which was the first to be introduced. S3 was the first non-preview service made generally available.

I built a system in my previous team where clients can register "filters" described in Fusion. My system, which was a source of a lot of different notifications, would then run these filters and only send those notifications that passed the filters. It became very popular very quickly because of the easy on-boarding and the fact that clients not get only a fraction of the messages they were interested in. I just checked the Java implementation, it seems to be still active and get commits.

Seriously? I bought in-car navigation for my car instead of opting for CarPlay/AndroidAuto for this exact reason. When I start a trip, my phone (always used Google Maps) can never figure out which way I am facing and will keep rotating around and recalculating directions until I gather some speed on the road. With my in-car navigation, the compass works flawlessly even in parking garages and basements. I though the holy grail would be a UX where Google Maps would use its maps, traffic and navigation data while using the car's GPS.

For me I usually forget the generic stuff. If I wrote something that was a bit different or if I put some extra effort or thought into it I find I can recall those implementation notes may be ever after a year.

My take on such “rules” is that these are not really rules but guidelines you can take hints from to make code easier to read and understand. I rarely try to force these rules to my code whether I am writing new code or changing existing code. Sometimes breaking these rules will make it better, and sometimes enforcing the rule will make it easier to read.

My process is to write the code, take my hands off the keyboard and just read it. Take a break and come back and read it again. Then upload a code review request but before you “publish” it for review read it in the browser again and makes changes as you see fit. This applies to design patterns as well. To me it is always circumstantial and should not feel forced. Sometimes the inherent nature of the logic requires me to keep all the conditionals together in a tight method with good documentation to make it easier to read it a year later. Sometimes it just “feels” cleaner to split it out. It always depends.