Top 5 AWS Lambda Anti Patterns
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- เผยแพร่เมื่อ 1 ส.ค. 2024
- In this video, learn about my Top 5 AWS Lambda Anti Patterns. These are based on my personal experiences and are pitfalls that developers fall into the most often.
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Can you chain lambdas if you don't expect a response?
I'd like to add a note about lambda batch processing: in some cases, message can fail over and over again. This can create an endless loop, so always use a dead letter queue with maxReceiveCount parameter.
Great tip!
I am new to lambdas and I was going to design my lambda with the very first anti pattern, thanks for saving me haha
You're very welcome!
Thanks a ton, Daniel!! I've learnt lot of AWS components from your channel. Especially lot of stuff around Lambda like this.
Your playlists are super helpful & i've kept a target to watch at least one playlist of yours per week to complete 343 videos that you uploaded till date
Thanks so much Srinivas! The 343 videos may take a while haha :D
Would love to see episode on this lambda logging
Thank you for making this video.. I learnt a lot from your AWS videos
hello. recently started working at the same place as you and finding it particularly helpful on your videos and its funny i could tell you worked at this place before i even checked due to the strong and obvious values presented. Thanks for the vids
Thanks Djaniel. Glad this resonated with you and you find it helpful :)
your video content is AWS some! keep it up bro
Thanks for bringing up metrics from Lambda - I may need that soon!
Happy to help Paul!
very good, thanks
great video I'm guilty of putting runtime exceptions and 5XX errors into the metric API, I'll look into creating a metricfilter to catch them for the alarms.
Great video. Thanks!
You're welcome!
BABD, you run an amazing channel. Thanks!
Very helpful content.
Glad it helped!
Good ones!
Excellent.
Many thanks!
Please please make some videos on real time projects, you have a huge experience on the serverless. Project will help us to grow fast
4:43 Are log streams really independent of the Lambda functions? In my experience, log streams are created, one for each lambda function.
Do you have any solution video on Pitfall2. emitting line to cloud-watch and creating metric filter out of it. Would really appreciate it.
Wow!
For emitting metrics it’s much easier to use Embedded Metrics Format
I've heard about this from peers but never tried it myself. Is it easy to set up and use?
I was planning to say the same thing. Yes it is trivial to do, and Lamdba Powertools provides some extra features on top like cold start metrics
Thanks, I didn't know about this. This is so great!
@@BeABetterDev Would love a video on this!
*what what are you doing step-function?*
For the last pitfall, another caveat would be: If your lambda function takes a lot of time in processing each SQS message, then it may take some time for the rest of your messages to be processed since it would be sequential iteration.
Ex:
Scenario 1: Each lambda processes 1 message each, so 5 messages and 5 lambda instances processing them in parallel. Each message take 10mins to run so everything done in 10-12mins (including invocation time).
Scenario2: Each lambda processes 5 messages in a batch and then iterate over them processing them together. The whole flow will end up in 50-52mins so the last message will get processed in way more time here.
Any alternative for such uses?
But in second case lambda will fail because max timeout is 15 minutes. Maybe you should use something else if you need process large chunks of data that take a long time. How about glue etl jobs?
What will be solution for Pitfall 3? If we have lambda synchronously tied up? What is the better approach to this?
Persist the state to database and do a call back.
Why is it better to process batch instead of single lambda processing?. The only downfall I think might be the amount of invoked lambdas, but I think it keep the process more clean
One of the downside is scalability. In each region you can have only X lambdas running concurrently. If all of a sudden you have a huge influx of message you might hit the concurrency limit. You can keep the process clean when handling a batch of messages by splitting the handler function (which receives the messages) from the actual business logic processor.
Basically what Cristian said is spot on. The other major factor is cost.
@@cristiannechita2032 thanks for the response!. But if you use sqs you will hit the concurrency limit, but no new event will be process from the queu right?. So when a lambda finish a new lambda will be triggered, so no message will be “lost”. Either way I get the point 👌.
Also if you use batch, what if you have 1 event alone for a “long time”? it will not be process until you have the X amount of events?
About pricing, is it really a factor?, if a lambda takes 2secs to process a message. What will be cheaper 5 parallel lambdas with 2sec each or 1 with 10 seconds? (The first scenario will be faster because of paralellism, but am not sure really).
Thanks again for explaining me out the pitfall 🙌
Batch processing in some cases is more preferable, for example, when you need to process a bunch of URLs. So doing multiple requests in parallel such as axios.all is much efficient than doing single requests, such as axios.post or axios.get.