14: Distributed Logging & Metrics Framework | Systems Design Interview Questions With Ex-Google SWE

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Jordan has no life

Күн бұрын

Пікірлер: 71

@martinwindsor4424 8 ай бұрын

Jordan might not be a pregnant, but he never fails to deliver.

@jordanhasnolife5163 8 ай бұрын

I might be pregnant

@jhonsen9842 3 ай бұрын

Jordan is pregnant, and he Delivers in All sys design.

@siddharth-gandhi 8 ай бұрын

Bro's single handedly making me question studying ml over systems. Bravo on these videos!

@knightbird00 13 күн бұрын

Talking points Can intro about push (low latency, needs app changes (better data), version skew) vs pull (highly scalable, no app changes(generic data), service discovery) 2:07 High volume, time series, structured vs unstructured, text logs, data sink 4:26 Data aggregation (tumbling vs hopping) 6:30 Time series db (hyper table, chunks, partition (label, timestamp)) 10:40 Text logs (elasticsearch) 12:40 Structured data (better encoding, protobuf, avro, schema registry) 16:05 unstructured data (post processing to structured data, flink -> file -> ETL using spark) 17:40 Analytics data sink (column but not tsdb, more like OLAP), use parquet files for loading (S3 vs HDFS). 23:45 Stream enrichment 25:15 Diagram

@JapanoiseBreakfast 24 күн бұрын

How to build distributed logging and metrics in 3 easy steps: 1) Join Google. 2) Run blaze build //analog:all //monarch:all. 3) Profit. Congratulations, you have now built distributed logging and metrics. Thank you for coming to my ted talk.

@jordanhasnolife5163 22 күн бұрын

This guy Googles

@chadcn 8 ай бұрын

Congrats on 200 videos mate! Keep up the great work 🚀🚀

@jordanhasnolife5163 8 ай бұрын

Thanks man!! I guess I actually enjoy doing this 😄

@doobie91 8 ай бұрын

Thanks a lot for your videos. Currently looking for a new job, brushing up/learning a lot about system design, watched lots of your videos recently. Appreciate your work. Keep it up!

@jordanhasnolife5163 8 ай бұрын

Thanks Andrii, good luck!

@DavidWoodMusic 8 ай бұрын

My interview is in 9 hours I hear your voice in my sleep I have filled a notebook with diagrams and concepts And I am taking a poopy at this very second We just prevail

@jordanhasnolife5163 8 ай бұрын

Just imagine me doing ASMR as I tell you about my day in a life

@bezimienny5 6 ай бұрын

Yo how did it go? Are you in your dream team? I sure hope so

@DavidWoodMusic 6 ай бұрын

@@bezimienny5 thanks friend. Offer was made but I turned it down. Turned out to be a really poor fit.

@bezimienny5 6 ай бұрын

@@DavidWoodMusic oh damn. That's a Shame. I'm kinda struggling with a similar decision right now. I passed all the interview stages but even at the offer stage I'm still learning new key pieces of info about the position that no one told me about before.... But hey, you beat the systems design interview! That's an amazing win and now you know you can do it 😉

@VijayInani 3 ай бұрын

Why are you so underrated!!! You should have been famous until now (more than your current famous index!).

@jordanhasnolife5163 3 ай бұрын

I'm famous in the right circles (OF feet creators)

@prasenjitsutradhar3368 8 ай бұрын

Great content!....pls make a video on code deployment!

@OmprakashYadav-nq8uj Ай бұрын

Great system design content. One think i noticed voice is not sync with real video.

@JapanoiseBreakfast 21 күн бұрын

Missed opportunity for a coughka pun.

@guitarMartial Ай бұрын

Jordan can TSDB's run in multi leader configuration as there are perpetually no write conflicts per se? And is that a typical pattern where a company might run multiple Prometheus leaders which just replicate data amongst themselves to get an eventually consistent view? Or is single leader replication still preferred? Thinking multi leader helps with write ingestion. Thanks!

@jordanhasnolife5163 Ай бұрын

There are many time series databases, so you'd have to look it up. But at the end of the day I think what you're looking for is better solved by just sharding per data source. That should help with ingestion speeds. If you're not really writing to the same key on multiple nodes, I'm hesitant to call it multi leader replication.

@chaitanyatanwar8151 6 күн бұрын

Thank you!

@SunilKumar-qh2ln 8 ай бұрын

Very informative video as always. Was just thinking how the metric is pulled by prometheus (which will eventually store in the DB). How the different clients responsibility is assigned to the aggregator pods so that metric is pulled exactly once from each client pods.

@jordanhasnolife5163 8 ай бұрын

I'm not too familiar with prometheus personally, feel free to expand on what you're mentioning here!

@georgekousouris4900 Ай бұрын

In this video you are using the push method, by having hosts connect to Kafka directly. This could be deemed too perturbing to the millions of hosts, so instead they can expose a /metrics endpoint that a consumer can use to fetch their current data. To answer the question above, we need to do some sort of consistent hashing to assign the millions of hosts to consumer instances and then put the data in Kafka (can create multiple messages, one for each metric). In the push method, we are putting the data directly to Kafka from each EC2 host where it is buffered before being consumed by our Spark Streaming instance that updates our DBs.

@timavilov8712 8 ай бұрын

U forgot to mention the tradeoff between polling and pushing for event producers

@timavilov8712 8 ай бұрын

Great video tho !

@jordanhasnolife5163 8 ай бұрын

I'm assuming you mean event consumers not producers. Yeah this is one of those things where it's kinda built into the stream processing consumer that you use, so under the hood I assume we'll be using long polling. I don't know that I see the case made here for web sockets since we don't need bidirectional communication. Server sent events may also be not great because we'll try to re-establish connections automatically, which may not be what we want if we rebalance our kafka partitions.

@jordiesteve8693 4 ай бұрын

thanks for your work!

@beecal4279 2 ай бұрын

thanks for the video in 22:00 when we say Parquet files are partitioned by time, do we mean partitioned by the file creation time?

@jordanhasnolife5163 2 ай бұрын

I mean time of the incoming data/message, however that's probably similar

@shibhamalik1274 7 ай бұрын

Hey jordan what is the data source in the last diagram here ? Is it the VM pushing logs / serialised Java objects etc to kafka ?? U mean the application when it logs a statement that statement makes a push to kafka ? Then what should be the partition key of this kafka cluster ? Should it be server id or a combination of server id + app name or how should be we structure this partition key ?

@jordanhasnolife5163 7 ай бұрын

Yes the application is pushing to Kafka. I think that you should probably use the app/microservice name as the Kafka topic, and then within that partition by server ID in kafka

@deepitapai2269 4 ай бұрын

Great video as always! Why do you store the files on S3 as well as a data warehouse? Why not just store on the data warehouse directly from Parquet files? Is it that we need a Spark consumer to transform the S3 files before putting the data into the data warehouse?

@jordanhasnolife5163 4 ай бұрын

Depends on the format of the S3 data. If it's unstructured, then we'd likely need some additional ETL job to format it and load it into a data warehouse.

@hoyinli7462 8 ай бұрын

great job!

@mukundkrishnatrey3308 5 ай бұрын

Hi Jordan, Regarding the post processing of unstructured data, can we do the batch processing in Flink itself, as it does support that, or it's not suitable for large scale of data? What could be the size of data which can dealt by flink itself, after which we might need to use HDFS/ Spark? PS :- Thanks for the amazing content, you're the best resource I've found till date for system design content :)

@jordanhasnolife5163 5 ай бұрын

Flink isn't bounded in the amount of data it can handle, you can always add more nodes. The difference is that flink is for stream processing. Feel free to watch the flink concepts video, it may give you a better sense of what I mean here.

@mukundkrishnatrey3308 5 ай бұрын

@@jordanhasnolife5163 Okay, got it now, thanks a lot again!

@nithinsastrytellapuri291 7 ай бұрын

Hi Jordan, I am trying to cover infrastructure-based system design questions like this one first. Can you please clarify if I need to watch video 11, 12, 13 to understand this? Any prerequistes ?( I have covered concepts 2.0). Is it same for 17, 18, 19 videos as well?

@jordanhasnolife5163 7 ай бұрын

Watch them in any order you prefer :)

@Dozer456123 2 ай бұрын

Is it true that s3 files would still have to get loaded over the network for something like AWS Athena? That seems to be a data warehousing strategy that relies on native s3 and not loading all of it across network

@jordanhasnolife5163 2 ай бұрын

Unfortunately I can't claim to know very much about Athena, I'll have to look into it for a subsequent video.

@Dozer456123 2 ай бұрын

@@jordanhasnolife5163 Sorry, didn't mean to use you like Google :P. I researched it after I asked, and it's quite cool. Basically a serverless query engine that's direct-lined into S3

@shibhamalik1274 7 ай бұрын

Hey Jordan do u have a video on pull vs push based models of consumption ? I blv kafka is pull based but I want to understand who uses push based

@jordanhasnolife5163 7 ай бұрын

Nothing regarding which message brokers do push based messages, feel free to Google it and report back

@shibhamalik1274 7 ай бұрын

Ok @jordan. I think kafka is push based not pull based . Pull based could be custom implemented I think …

@helperclass8710 7 ай бұрын

Great video man. Thanks.

@31737 6 ай бұрын

hey Jordan great video, does this require any sort of API design? given that we need to read through the data metrics does it makes sense to also describe the API structure, let me know your thoughts, thanks.

@jordanhasnolife5163 6 ай бұрын

Sure. You need an endpoint to read your metrics by time range, and it probably returns paginated results. (Perhaps taking in a list of servers) Anything else you're looking for?

@31737 6 ай бұрын

@@jordanhasnolife5163 right also for elastic search result you gonna need an API unless you wanna combine it with metrics which I don't think it's a good idea

@31737 6 ай бұрын

Also a request for making a video for tracking autonomous cars + collecting other metrics sensors/etc, thanks man your work is gold and I love the depth them