I am looking for idea how to approach this problem, basically measuring EC2 instance activity.
Is there a way I can know that via AWS? If not, how can I measure activity on e.g. Ubuntu instance. Taking into account that I will have some processes running and looking into their activity?
I'm not sure how you are defining "instance activity" but you can monitor your Amazon EC2 instance with Amazon CloudWatch and then query on the CPUUtilization metric to get information about how much CPU your instance is using (see Amazon Elastic Compute Cloud Dimensions and Metrics for details).
It's better to measure by 2 metrics and compare, Network traffic and CPU utilization
Ref: https://www.trendmicro.com/cloudoneconformity/knowledge-base/aws/EC2/idle-instance.html#:~:text=Using%20AWS%20Console-,01%20Sign%20in%20to%20the%20AWS%20Management%20Console.,to%20identify%20the%20right%20resource).
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I am running an R ShinyApp on Fargate ECS. It is roughly used once per week by the customer. It is running constantly and therefore we are paying for a substantial amount of idle time.
Is there a way it could be launched when there is an incoming connection and then stopped when this connection ends?
Does anyone have any suggestions for this?
Many thanks
You need a serverless style of application hosting, e.g. as suggested by a commentor with API Gateway backed by Lambda. If your request count is low, you may actually not pay much due to Free tier for these services. There is an R Runtime for Lambda here:
[1] Serverless execution of R code on AWS Lambda - https://github.com/bakdata/aws-lambda-r-runtime
I am experiencing an issue with my EC2 instance. I am scraping different websites using R programming and it works fine but after some hours, my EC2 instance is freezing.
After raising a ticket to AWS support, they noticed that this was caused by the rise of the "VolumeQueueLength" which then was decreasing the BurstBalance credits from 100 to 0.
See below when I tried around June 19th:
Would you know what is causing this VolumeQueueLength to go up?
Thanks a ton!
From I/O Characteristics and Monitoring - Amazon Elastic Compute Cloud:
If your I/O latency is higher than you require, check VolumeQueueLength to make sure your application is not trying to drive more IOPS than you have provisioned. If your application requires a greater number of IOPS than your volume can provide, you should consider using a larger gp2 volume with a higher base performance level or an io1 volume with more provisioned IOPS to achieve faster latencies.
For more information about Amazon EBS I/O characteristics, see the Amazon EBS: Designing for Performance re:Invent presentation on this topic.
This is basically saying that the IO allocated to an Amazon EBS 'General Purpose' volume is proportional to its size, so a larger volume might solve your IO problems. Alternatively, you could consider moving to a Provisioned IOPS volume (which is faster, but more expensive).
Your application seems to be using more IO than has been allocated for the volume.
This is a very simple question for those with the knowledge, but I'm a newbie.
In essence, I just need to know if it would be considered okay to run a small, approx. 700 visitors/day bitnami wordpress blog on just one t2.medium EC2 instance (without any auto-scaling, beanstalk).
Am at risk of it crashing? What stats should I monitor or be aware of to be aware of potential dangers? Sorry for the basic nature of these questions, but this is new.
tl;dr: It might be "okay", but it's not ideal.
If your question is because of:
Initial setup time - Load-balancing and auto-scaling will be less expensive (more time-efficient) over time.
Cost - Auto-scaling spins down instances that aren't being used to reduce cost.
Minimal setup for a great user experience - The goal of a great AWS setup is to ensure that capacity matches demand
Am at risk of it crashing?
Possibly, yes. If you average 700 visitors, then the risk is traffic spikes if all visitors hit at the same. It also depends on what your maximum visitors are, which could vary widely from the average (or not)
What stats should I monitor or be aware of to be aware of potential dangers?
Monitor the usage on high traffic days (ie. public holiday sales)
Setup billing alerts
Setup the right metrics:
See John Rotenstein's SO answer:
CPU Utilization is not always the right measure to use -- your
application might only be able to handle a limited number of
connections, it might be squeezed on RAM and the types of requests
might vary too.
You can use normal monitoring tools, or you can write something that
pushes metrics to Amazon CloudWatch, so that you go beyond the basic
CPU and Network metrics that CloudWatch normally provides. You could
even use the Load Balancer's Latency metric to trigger scaling when
the application slows down (custom code required).
I'd start with:
Two or more instances - to deal with instance redundancy (an instance going down)
Several t2.small rather than one t2.medium can work out to be more cost-efficient, and more cost efficient than EC in some use cases.
Add auto-scaling - automatically spin up or down instances based on minimum and maximum counts
Load balancing - to re-route users from unhealthy to healthy instances. And also to keep all of the spun up instances all working as evenly as possible (rather than a single instance handling 80% of the workload while the others bludge).
You can always reduce your instances after time with monitoring.
In my opinion, with 700 visitors a day, the safer option would be to run a load balanced/auto-scaling environment on Elastic Beanstalk with at least 2 instances. The problem with running just one instance is that yes you are at a great risk of crashing in case you get an increase in traffic or when the instance goes down and with just one running you will not have a fallback. You can easily set up CloudWatch monitoring on NetworkIn, NetworkOut to get a sense of the number of requests your site is receiving and serving, and setup CPU Usage monitoring as well. The trade-off with running a load balanced environment over a single instance environment is that the cost might significantly increase as you introduce other things into your environment such as a load balancer. Also if you introduce a load balancer consider reducing the instance size to maybe a t2.small, could aid in reducing the cost.
It actually depends. This question range is wide. You have multiple options here.
You can use only ec2 instance for that much amount of visitors or even more if your application allows. You can also consider caching if your app need it.
You may add instance in an autoscaling group. So that if by any chance you need more resources you can increase them horizontally.
You can add load balancers lateron also. You just need to add user data in your launch configuration attached to autoscaling group. So when your instance get up it should automatically register itself in your load balancer.
For monitoring, you can check for the request metrics in cloudwarch for ELB. You have to keep an eye on your CPU and trigger the scale out policy once it reaches a particular threshold.
Currently I am using one availability zone in my ec2 launch config. It is important that I don't get network partitions in my app, as rabbitmq does not handle network partitions well when clustering and HA is used (which I am using).
I am very fuzzy on the concept of network partitions. Would it be safe for me to use two availability zones?
The different Amazon EC2 Availability Zones are in different physical locations. While the connections between availability zones are quite good, it is still a WAN connection.
From the RabbitMQ docs
RabbitMQ clusters do not tolerate network partitions well. If you are thinking of clustering across a WAN, don't. You should use federation or the shovel instead
(emphasis mine)
https://www.rabbitmq.com/partitions.html
In short, a 1 minute or so interruption in connectivity will cause a network partition to be created. While this would be an unusual event for EC2, it can and sometimes will happen.
In the DynamoDB documentation and in many places around the internet I've seen that single digit ms response times are typical, but I cannot seem to achieve that even with the simplest setup. I have configured a t2.micro ec2 instance and a DynamoDB table, both in us-west-2, and when running the command below from the aws cli on the ec2 instance I get responses averaging about 250 ms. The same command run from my local machine (Denver) averages about 700 ms.
aws dynamodb get-item --table-name my-table --key file://key.json
When looking at the CloudWatch metrics in the AWS console it says the average get latency is 12 ms though. If anyone could tell me what I'm doing wrong or point me in the direction of information where I can solve this on my own I would really appreciate it. Thanks in advance.
The response times you are seeing are largely do to the cold start times of the aws cli. When running your get-item command the cli has to get loaded into memory, fetch temporary credentials (if using an ec2 iam role when running on your t2.micro instance), and establish a secure connection to the DynamoDB service. After all that is completed then it executes the get-item request and finally prints the results to stdout. Your command is also introducing a need to read the key.json file off the filesystem, which adds additional overhead.
My experience running on a t2.micro instance is the aws cli has around 200ms of overhead when it starts, which seems inline with what you are seeing.
This will not be an issue with long running programs, as they only pay a similar overhead price at start time. I run a number of web services on t2.micro instances which work with DynamoDB and the DynamoDB response times are consistently sub 20ms.
There are a lot of factors that go into the latency you will see when making a REST API call. DynamoDB can provide latencies in the single digit milliseconds but there are some caveats and things you can do to minimize the latency.
The first thing to consider is distance and speed of light. Expect to get the best latency when accessing DynamoDB when you are using an EC2 instance located in the same region. It is normal to see higher latencies when accessing DynamoDB from your laptop or another data center. Note that each region also has multiple data centers.
There are also performance costs from the client side based on the hardware, network connection, and programming language that you are using. When you are talking millisecond latencies the processing time on your machine can make a difference.
Another likely source of the latency will be the TLS handshake. Establishing an encrypted connection requires multiple round trips and computation on both sides to get the encrypted channel established. However, as long as you are using a Keep Alive for the connection you will only pay this overheard for the first query. Successive queries will be substantially faster since they do not incur this initial penalty. Unfortunately the AWS CLI isn't going to keep the connection alive between requests, but the AWS SDKs for most languages will manage this for you automatically.
Another important consideration is that the latency that DynamoDB reports in the web console is the average. While DynamoDB does provide reliable average low double digit latency, the maximum latency will regularly be in the hundreds of milliseconds or even higher. This is visible by viewing the maximum latency in CloudWatch.
They recently announced DAX (Preview).
Amazon DynamoDB Accelerator (DAX) is a fully managed, highly available, in-memory cache for DynamoDB that delivers up to a 10x performance improvement – from milliseconds to microseconds – even at millions of requests per second. For more information, see In-Memory Acceleration with DAX (Preview).