Hi, I am getting this below error after configure the application as you have mentioned in the video. "No adapter for endpoint " I have updated few of the dependency to support java 11 Please help me to resolve the issue
@eugenicko11 күн бұрын
How to do graceful shutdown for spring boot with kafka streams?
@prasadpardeshi58715 күн бұрын
pls create video using open ai
@londonuk64816 күн бұрын
The intro video is so shitty and unnecessary!
@adokshajbhandarkar549217 күн бұрын
Why did you not show Conflicts? It would have been so helpful.
@amit2197kumar19 күн бұрын
Thanks for the explanation :) Note for self: In system design, particularly in the context of performance measurement and analysis, *P90*, *P99*, and other similar notations refer to *percentiles*. Percentiles are statistical measures that indicate the relative standing of a value within a dataset. They are often used to understand the distribution and variability of metrics like response times, latencies, or other performance indicators. # Understanding Percentiles A percentile is a value below which a given percentage of observations in a dataset fall. For example: - P90 (90th percentile): 90% of the data points are below this value. In system performance terms, it means that 90% of the requests or transactions complete within this time. - P99 (99th percentile): 99% of the data points are below this value, indicating that 99% of the requests complete within this time. - P50 (50th percentile, also known as the median): 50% of the data points are below this value. Percentiles are particularly useful for understanding the performance experienced by the majority of users and identifying outliers or rare occurrences that might indicate problems. # Common Percentiles in System Design - P50 (Median): Indicates the middle value of the dataset, where half the observations are faster and half are slower. It's a useful measure of central tendency. - P90: Often used to represent the performance experienced by the majority of users. If the 90th percentile latency is 200ms, it means 90% of users experience response times faster than 200ms. - P95: This percentile indicates the point below which 95% of the observations fall. It's useful for identifying the tail latency, where a small fraction of requests may experience slower performance. - P99: Focuses on the "worst" 1% of the performance spectrum. It's critical for understanding the behavior of the system under peak load or during rare, high-latency situations. - P99.9 (Three Nines): Provides even more granular insight into the worst-case scenarios, highlighting extreme outliers. Let's consider an example of a web service's response times to illustrate P90 and P99 percentiles. # Scenario Imagine we have recorded the response times (in milliseconds) for 1,000 requests made to a web service. The response times are as follows (in sorted order for simplicity): [10, 12, 14, 15, 16, ..., 195, 200, 210, ..., 400, 450, 500, 550, 600] # Calculating Percentiles To calculate the P90 and P99 percentiles, we find the values below which 90% and 99% of the response times fall, respectively. 1. P90 (90th Percentile): - Position: To find the 90th percentile, we calculate (0.90 times 1000 = 900). So, we look at the 900th value in the sorted list of response times. - Value: Let's say the 900th value in the sorted list is 200ms. This means that 90% of the requests were completed in 200ms or less. 2. P99 (99th Percentile): - Position: For the 99th percentile, we calculate (0.99 times 1000 = 990). So, we find the 990th value in the sorted list. - Value: Suppose the 990th value is 500ms. This indicates that 99% of the requests were completed in 500ms or less. # Interpretation - P90 = 200ms: 90% of the requests were processed within 200ms. This gives an idea of the typical response time experienced by most users. - P99 = 500ms: 99% of the requests were completed within 500ms. This indicates that 1% of the requests took longer than 500ms, highlighting potential issues or outliers in performance. These percentiles provide valuable insights into the service's performance, particularly in understanding both the common experience and the rare, worst-case scenarios. They help identify whether there are significant delays affecting a small portion of users, even if the average response time is satisfactory.
@s8x.22 күн бұрын
isnt rabbitmq more suitable for high throughput stuff since it can prioritize messages?
@dew_reddit25 күн бұрын
Is there an expiry on access key?
@user-qq8em4bn5g25 күн бұрын
can you tell me how you make grafana dashboard in linkerd-viz dashboard
@user-qr4pi4ow7b27 күн бұрын
Great job explaining it !
@alwayskrishnaconsciousness5636Ай бұрын
Very nicely explained
@YoEnigmaАй бұрын
Which chrome extension you are using that show Highlighter options on screen ?
@TechPrimersАй бұрын
no extensions buddy, it was a video element added manually during editing
@Dizzy_DizzАй бұрын
Great, I appreciate a lot, but I could not see authorization in this code but I can applaud for authentication, kindly reply, Thank you
@Dizzy_DizzАй бұрын
kindly explain the flow where it is starting and where it is ending
@Dizzy_DizzАй бұрын
Exception "jwt missing is ok " but when tokem is tampared then message is coming as "token is incorrect but here if (jwtUser == null) { throw new RuntimeException("JWT Token is incorrect"); } but Jwtuser is not null, kindly clarify
@katushyaАй бұрын
It's hard to find quality content about advanced topics like this. Well explained 👍
@TechPrimersАй бұрын
Glad it was helpful!
@arunabraham9382Ай бұрын
Why didnt these companies not moving to linux?
@TechPrimersАй бұрын
Most of the client systems are still on Windows. eg, machines in hospitals, airlines checkin. In addition to that, servers where databases (eg SQL Server) could be running on Windows Servers.
@arunabraham9382Ай бұрын
@@TechPrimers Microsoft support SQL Server in linux right?
@JaNaMSoNiАй бұрын
We are still recovering 😂
@TechPrimersАй бұрын
ah! thats unfortunate. Is the workaround fixing these issues? I know they need to be done manually! Phew! Wish AI Agents could fix these!
@JaNaMSoNiАй бұрын
@@TechPrimers ya just 10% remains
@funcreations4864Ай бұрын
How we can share same session with other application and this could be the good use case of spring session data redis , what fo you say ?
@TechPrimersАй бұрын
Yes that’s the usecase when redis stores the session and can be shared across apps
@Shreenidhi110Ай бұрын
clear explination, thanks
@chinmoydey3283Ай бұрын
How to remove this "data:" from the final output?
@AlphaKaijuАй бұрын
Great video! I am implementing this in my CI/CD for everything it can cover.
@ezhilarasikrishnan5408Ай бұрын
❤❤💯.. this is what I was searching,, Thanks bro.❤
@TechPrimersАй бұрын
Glad it’s helpful
@ammarhassan4571Ай бұрын
openAPI was nothing but...
@sakethmanupatiАй бұрын
Does this not work with localstack instead of actual kinesis? I could not find a way to configure this with localstack
@rajatsamseriyafitness3265Ай бұрын
Hi, I am creating automation rule in JSM but when rule trigger its showing the jira automation in heading of mail by default but i want to change to my project name. please let me know how to configure this implementation
@ravideviceregunta5794Ай бұрын
The Best RAG architecture video ever seen…. Lot of people are complicate the concept a lot… Could you do another video with the how prompt is compared with embeddings and measured accurate results…
@TechPrimersАй бұрын
Sure ravi. Will do
@rajkumaradduАй бұрын
thank you Ajay. you made my day.. one query, is it possible to upload a resume file and get the required details like, name, contact, skills etc..
@TechPrimersАй бұрын
I haven’t tried that yet Raj. Will try it out. Thank you
@rajkumaradduАй бұрын
@@TechPrimers thank you so much.. I too trying the same.. Please let us know if you done with it. Thank you
@idreesahmed2051Ай бұрын
simple thing also you keep on repeating you could have reduce the video size and make it simple way
@gabrielfono844Ай бұрын
Thanks a lot.
@shivprakashyАй бұрын
open-webui appears to be a better alternative
@TechPrimersАй бұрын
Oh. Sure let me try
@user-uy2ct3vg1bАй бұрын
Wisjxdb;🗺️[Arkgw 'bl]!
@shanksdixitАй бұрын
Great example. Your videos are always useful.
@TechPrimersАй бұрын
Glad you like them!
@user-uo2yo2wk9i2 ай бұрын
I thought you would be showing a demo on how to monitor.
@MadhusudanBhosale2 ай бұрын
Good demo to get started with Thanks Ajay
@gixer9122 ай бұрын
Calling a library in 5 lines of code
@himanshuvaidya31932 ай бұрын
yes very helpful content with open source library for chatbot . But I think streamlit works similar way.
@sakchigupta88582 ай бұрын
perfect
@AbhishekKumar-ub8co2 ай бұрын
Login part that you are explaining is I guess OIDC because OAuth alone is just meant for Authorization, it is basically OIDC that enforces login and hence the Authentication
@thinker52702 ай бұрын
Thanks for the video. this is very helpful
@MadhusudanBhosale2 ай бұрын
We are enjoying this series <3
@TechPrimers2 ай бұрын
Glad its helpful Madhu
@rishiraj25482 ай бұрын
🙂👍
@JaNaMSoNi2 ай бұрын
AI Primer❤
@TechPrimers2 ай бұрын
yo!
@Dizzy_Dizz2 ай бұрын
Hi, Kindly make a video of event source implementation. Thank you
@RajP-py4fu2 ай бұрын
Great job
@rajeshbongurala84912 ай бұрын
Gr8 info buddy for beginners. I want to use microsoft azure openai with custom data and rag too. Also need a custom chatbotot (own). Can you help me with desing? How to build my app in python, call 3rd party api, how to use RAG, how to expose API to custom chatbot etc ?