Our web application has 5 pages (Signin, Dashboard, Map, Devices, Notification)
We have done the load test for this application, and load test script does the following:
Signin and go to Dashboard page
Click Map
Click Devices
Click Notification
We have a basic free plan in AWS.
While performing load test, till about 100 users, we didn’t get any error. please see the below image. We could see NetworkIn, CPUUtilization seems to be normal. But the NetworkOut showed 846K.
But when reach around 114 users, we started getting error in the map page (highlighted in red). During that time, it seems only NetworkOut is high. Please see the below image.
We want to know what is the optimal score for the NetworkOut, If this number is high, is there any way to reduce this number?
Please let me know if you need more information. Thanks in advance for your help.
You are using a t2.micro instance.
This instance type has limitations on CPU that means it is good for bursty workloads, but sustained loads will consume all the available CPU credits. Thus, it might perform poorly under sustained loads over long periods.
The instance also has limited network bandwidth that might impact the throughput of the server. While all Amazon EC2 instances have limited allocations of bandwidth, the t2.micro and t2.nano have particularly low bandwidth allocations. You can see this when copying data to/from the instance and it might be impacting your workloads during testing.
The t2 family, especially at the low-end, is not a good choice for production workloads. It is great for workloads that are sometimes high, but not consistently high. It is also particularly low-cost, but please realise that there are trade-offs for such a low cost.
See:
Amazon EC2 T2 Instances – Amazon Web Services (AWS)
CPU Credits and Baseline Performance for Burstable Performance Instances - Amazon Elastic Compute Cloud
Unlimited Mode for Burstable Performance Instances - Amazon Elastic Compute Cloud
That said, the network throughput showing on the graphs is a result of your application. While the t2 might be limiting the throughput, it is not responsible for the spike on the graph. For that, you will need to investigate the resources being used by the application(s) themselves.
NetworkOut simply refers to volume of outgoing traffic from the instance. You reduce the requests you are sending from this instance to reduce the NetworkOut .So you may need to see which one of click Map, Click Devices and Click Notification is sending traffic outside of the instances. It may not necessarily related only to the number of users but a combination of number of users and application module.
Related
I deployed the Machine Learning classification model in AWS EC2 (UBUNTU)instance successfully. I am able to access the instance "http://ec2-18-191-31-0.us-east-2.compute.amazonaws.com" and predictions are working fine only for few minutes. After that I or my colleagues are not able to access this. Getting an error "cannot connected to the server".
Security group that I crated as attached.
t2.micro instances are not suitable for any long running calculations. They are burstable. This means that their performance can be sustained only for short periods of time, e.g., sudden, short lived spikes in CPU usage. On top of that they have only 1 GB of RAM which limits its usefulness in machine learning.
For calculations, you could consider Compute optimized or Memory optimized instances. Obviously, these instance types are not free, but they are suited for calculations.
You can change instance type if you want and test with other, more power types. What you are describing indicates that your t2.micro exhausts all its RAM and/or CPU burst credits after few minutes and it freezes.
You can use CloudWatch Metrics for EC2 to monitor your instances and observer its CPU utilization and other metrics which can help you determine what exactly is causing the backlog. You can also monitor RAM and disc usage but this requires CloudWatch Agent setup on the instance.
We have 2 Elastic VMs (Linux) (Currently DS2V2) behind an Azure Load Balancer. We are doing HTTP Posts from our local lan into the Load Balancer, but we seem to be getting throttled. We have tried: Changing the size of the VMs, no difference; adding additional premium SSDs, again no difference; running multiple threads on our end, again no differenece.
What we did do though, was to having the Elastic Engine suck in all of the log files from the Linux boxes and the index rate jump pretty high while it was ingesting them. So we are assuming that it's not really the Linux Elastic boxes that are throttling us.
We do have Kibana installed on the boxes, and as a base line, we're just using the "Cluster Indexing Rate" for both our local posts to the box, and the local ingestion of the log files.
We do understand that yes, there is going to be some latency and overhead since we are now involving the internet, but not the rates we are currently getting. (We have a 1G pipe to the internet, it's nowhere near capacity, so we can rule out at least getting out of our company).
The question is, where else can we look to determine where we might be getting throttled?
For the performance "MUCH slower", it is a bit subjective question and hard to identify. I just provide some information that may impact it.
Azure Compute requests may be throttled at a subscription and on a per-region basis. If you have an API throttling error, you could refer to this document to troubleshoot throttling issues, and best practices to avoid being throttled.
Some factors CPU and storage limits that differ on Azure VM sizes may impact the Azure VM to process incoming data. You may change the size to a higher CPU and premium SSD disk. You could also change Azure resources to another region which is close to your location. You could refer to this article.
Given What is difference between Lightsail and EC2? and my own testing, I am convinced that LightSail Instances are burstable performance instances.
Are LightSail database instances subject to this kind of burstable performance too? I'm interested in both I/O burst and CPU burst.
If so, is there a way to view the remaining CPU or IO burst credits? Unlike EC2, the web console for LightSail doesn't seem to offer these numbers.
This issue hit me hard today, taking down my instances making them unable to serve any request
Just want to inform you that they include the bursts area into their metric now. But I dont see the way to get remaining credits
Also now the burstable "feature" is documented
I have a web service running on several EC2 boxes. Based on the Cloudwatch latency metric, I'd like to scale up additional boxes. But, given that it takes several minutes to spin up an EC2 from an AMI (with startup code to download the latest application JAR and apply OS patches), is there a way to have a "cold" server that could instantly be turned on/off?
Not by using AutoScaling. At least not, instant in the way you describe. You could make it much faster however, by making your own modified AMI image where you place the JAR and the latest OS patches. These AMI's can be generated as part of your build pipeline. In that case, your only real wait time is for the OS and services to start, similar to a "cold" server.
Packer is a tool commonly used for such use cases.
Alternatively, you can mange it yourself, by having servers switched off, and start them by writing some custom Lambda scripts that gets triggered by Cloudwatch alerts. But since stopped servers aren't exactly free either, i would recommend against that for cost reasons.
Before you venture into the journey of auto scaling your infrastructure and spending time/effort. Perhaps you should do a little bit of analysis on the traffic pattern day over day, week over week and month over month and see if it's even necessary? Try answering some of these questions.
What was the highest traffic ever your app handled, How did the servers fare given the traffic? How was the user response time?
When does your traffic ramp up or hit peak? Some apps get traffic during business hours while others in the evening.
What is your current throughput? For example, you can handle 1k requests/min and two EC2 hosts are averaging 20% CPU. if the requests triple to 3k requests/min are you able to see around 60% - 70% avg cpu? this is a good indication that your app usage is fairly predictable can scale linearly by adding more hosts. But if you've never seen traffic burst like that no point over provisioning.
Unless you have a Zynga like application where you can see large number traffic at once perhaps better understanding your traffic pattern and throwing in an additional host as insurance could be helpful. I'm making these assumptions as I don't know the nature of your business.
If you do want to auto scale anyway, one solution would be to containerize your application with Docker or create your own AMI like others have suggested. Still it will take few minutes to boot them up. Next option is the keep hosts on standby but and add those to your load balancers using scripts ( or lambda functions) that watches metrics you define (I'm assuming your app is running behind load balancers).
Good luck.
Currently i'm building a chat application base on NodeJs
So i considered choose which is the best instance type for our server?
Because AWS have a lot of choice: General purpose, compute optimize, memory optimize ....
Could you please give me advise :(
You can read this - https://aws.amazon.com/blogs/aws/choosing-the-right-ec2-instance-type-for-your-application/
Actually it doesn't matter what hosting you chose -AWS, MS Azure, Google Compute Engine etc...
If you want to get as much as you can from your servers and infrastructure, you need to solve your current task.
First of all decide how many active users at the same time you will get in closest 3-6 months.
If there will be less than 1000k active users (connections) per second - I think you can start from the smallest instance type. You should check how you can increase CPU/RAM/HDD(or SSD) of your instance.
SO when you get more users you will have a plan how to speed up your server.
And keep an eye on your server analytics - CPU/RAM/IO utilizations when you are getting more and more users.
The other questions if you need to pass some certifications related to security restrictions...
Since you are not quite sure where to start with, I would recommend to start with General Purpose EC2 instance for production from M category (M3 or M4). You can start with smaller instance type like m3.medium.
Note: If its an internal chat application with low traffic you can even consider T series EC2 instances.
The important part here is not to try to predict the capacity needs. Instead you can start small with general purpose EC2 instance and down the line looking at the resource consumption of EC2 instance you can do a proper capacity planning. Since you can both Scale the instances Horizontally and Vertically, it will require to trade of the instance type also considering Cost and timely load requirements before selecting the scaling unit of EC2 instance.
One of the approach I'm following is as follows
Start with General Purpose Instance (Unless I'm confident that there are special needs such as Networking, IO & etc.)
Do a load test(Without Autoscaling for a single EC2 instance) of the application by changing the number of users and find out the limits (How many users can a single EC2 instance can handle).
After analyzing the Memory, CPU & IO utilization, you can also consider shifting to a different EC2 category or stick with the same type. (Lets say CPU goes to its limit but memory is hardly used, you can consider using C series instances).
Scale the EC2 instance vertically by moving to the next size (e.g m3.medium to m3.large) and carry out the load tests to find out its limits.
After repeating step, 3 and 4 you can find an optimal balance between Cost and Performance.
Lets take 3 instance types with cost as X for the lowest selected (Since increasing the EC2 size in one unit, makes the cost doubles)
m3.medium - can serve 100 users, cost X
m3.large - can serve 220 users, cost 2X
m3.xlarge - can serve 300 users. cost 3X
Its an easy choice to select m3.large as the EC2 instance size since it can serve 110 per X cost.
However its not straight forward for some applications where you need to decide the instance type based on your average expected load.
Setup autoscaling and load balancing to horizontally scale the EC2 instances to handle load above average.
For more details, refer the Architecting for the Cloud: Best Practices whitepaper.
I would recommend starting with a T2.micro Linux instance. Watch the CPU usage in CloudWatch. Once the CPU usage starts to exceed 50% to 75%, or free memory gets low, or disk I/O gets saturated, switch to the next larger instance.
T2.micro Linux instances are (for the most part) free. Read the fine print. T2.micro instances are burstable which means that you can get good performance from a small instance.
Unless your chat application has a huge customer / transaction base, you (probably) won't need the other instance types.