AWS EC2 Cloudwatch monitoring - amazon-web-services

Firstly, Appreciate your patience in reading and thinking through this problem I have mentioned here.
I had unique problem on one of my AWS EC2 instances(Ubuntu 14.04), where the instance just goes unreachable through either http or ping. It also locked me out of ssh access. I had to log in to aws console everytime, and reboot the instance manually. As a solution, I have configured cloudwatch monitoring to reboot the instance automatically and send a notification email to me, on any occasion where the system check has failed.
So far, so good.
Now, what I really want is the root cause / reason for instance going unreachable. I assuming that to be a memory issue. I have gone through the get-system-logs, which helped a bit. But, is there anyway, I can configure cloudwatch to send me the fail logs or something similar when it sends me the alert email. Or is there any way, I can alert myself with sufficient log info like - example : memory usage being 80%, network not responding etc- when I instance goes unreachable. I have heard of swap tool, but I am looking for something more generic, just not limited to memory monitoring.
Anything? Anyone has any idea?

I would go old skool and use a script on the server to log to a file
Presumably ( you don't mention this detail in the above ) there is a particular program running on the system that is giving you this problem
Usually system programs store their PID in a file. Let's assume the file is /var/run/nginx.pid. You can work this out for your particular system
Write a script to read the PID and record the memory use, for example add this file as "/usr/local/bin/mymemory"
PID=`cat /var/run/crond.pid`
# the 3 fields are %mem, VSZ and RSS
DATA=`ps uhp $PID| awk '{print $4, $5, $6}'`
NOW=`date --rfc-3339=sec`
echo "$NOW $DATA" >> /var/log/memory.log
Add a line to crontab as root
* * * * * /usr/local/bin/mymemory.log
This will make an ever growing file for memory per minute. I suggest you login once a day and check it, download it if interesting and delete it.
(In a real production context log rotation could be used)
Every time there is a crash the file should contain memory use data

Related

Cloud composer tasks fail without reason or logs

I run Airflow in a managed Cloud-composer environment (version 1.9.0), whic runs on a Kubernetes 1.10.9-gke.5 cluster.
All my DAGs run daily at 3:00 AM or 4:00 AM. But sometime in the morning, I see a few Tasks failed without a reason during the night.
When checking the log using the UI - I see no log and I see no log either when I check the log folder in the GCS bucket
In the instance details, it reads "Dependencies Blocking Task From Getting Scheduled" but the dependency is the dagrun itself.
Although the DAG is set with 5 retries and an email message it does not look as if any retry took place and I haven't received an email about the failure.
I usually just clear the task instance and it run successfully on the first try.
Has anyone encountered a similar problem?
Empty logs often means the Airflow worker pod was evicted (i.e., it died before it could flush logs to GCS), which is usually due to an out of memory condition. If you go to your GKE cluster (the one under Composer's hood) you will probably see that there is indeed a evicted pod (GKE > Workloads > "airflow-worker").
You will probably see in "Tasks Instances" that said tasks have no Start Date nor Job Id or worker (Hostname) assigned, which, added to no logs, is a proof of the death of the pod.
Since this normally happens in highly parallelised DAGs, a way to avoid this is to reduce the worker concurrency or use a better machine.
EDIT: I filed this Feature Request on your behalf to get emails in case of failure, even if the pod was evicted.

Is there an AWS / Pagerduty service that will alert me if it's NOT notified

We've got a little java scheduler running on AWS ECS. It's doing what cron used to do on our old monolith. it fires up (fargate) tasks in docker containers. We've got a task that runs every hour and it's quite important to us. I want to know if it crashes or fails to run for any reason (eg the java scheduler fails, or someone turns the task off).
I'm looking for a service that will alert me if it's not notified. I want to call the notification system every time the script runs successfully. Then if the alert system doesn't get the "OK" notification as expected, it shoots off an alert.
I figure this kind of service must exist, and I don't want to re-invent the wheel trying to build it myself. I guess my question is, what's it called? And where can I go to get that kind of thing? (we're using AWS obviously and we've got a pagerDuty account).
We use this approach for these types of problems. First, the task has to write a timestamp to a file in S3 or EFS. This file is the external evidence that the task ran to completion. Then you need an http based service that will read that file and calculate if the time stamp is valid ie has been updated in the last hour. This could be a simple php or nodejs script. This process is exposed to the public web eg https://example.com/heartbeat.php. This script returns a http response code of 200 if the timestamp file is present and valid, or a 500 if not. Then we use StatusCake to monitor the url, and notify us via its Pager Duty integration if there is an incident. We usually include a message in the response so a human can see the nature of the error.
This may seem tedious, but it is foolproof. Any failure anywhere along the line will be immediately notified. StatusCake has a great free service level. This approach can be used to monitor any critical task in same way. We've learned the hard way that critical cron type tasks and processes can fail for any number of reasons, and you want to know before it becomes customer critical. 24x7x365 monitoring of these types of tasks is necessary, and helps us sleep better at night.
Note: We always have a daily system test event that triggers a Pager Duty notification at 9am each day. For the truly paranoid, this assures that pager duty itself has not failed in some way eg misconfiguratiion etc. Our support team knows if they don't get a test alert each day, there is a problem in the notification system itself. The tech on duty has to awknowlege the incident as per SOP. If they do not awknowlege, then it escalates to the next tier, and we know we have to have a talk about response times. It keeps people on their toes. This is the final piece to insure you have robust monitoring infrastructure.
OpsGene has a heartbeat service which is basically a watch dog timer. You can configure it to call you if you don't ping them in x number of minutes.
Unfortunately I would not recommend them. I have been using them for 4 years and they have changed their account system twice and left my paid account orphaned silently. I have to find a new vendor as soon as I have some free time.

Forwarding journald to Cloudwatch Logs

I'm a newbie to CentOS and wanted to know the best way to parse journal logs to CloudWatch Logs.
My thought processes so far are:
Use FIFO to parse the journal logs and ingest this to Cloudwatch Logs, - It looks like this could come with draw backs where logs could be dropped if we hit buffering limits.
Forward journal logs to syslog and send syslogs to Cloudwatch Logs --
The idea is essentially to have everything logging to journald as JSON and then forward this across to CloudWatch Logs.
What is the best way to do this? How have others solved this problem?
Take a look at https://github.com/advantageous/systemd-cloud-watch
We had problems with journald-cloudwatch-logs. It just did not work for us at all.
It does not limit the size of the message or commandLine that it sends to CloudWatch and the CloudWatch sends back an error that journald-cloudwatch-logs cannot handle which makes it out of sync.
systemd-cloud-watch is stateless and it asks CloudWatch where it left off.
systemd-cloud-watch also creates the log-group if missing.
systemd-cloud-watch also uses the name tag and the private ip address so that you can easily find the log you are looking for.
We also include a packer file to show you how to build and configure a systemd-cloud-watch image with EC2/Centos/Systemd. There is no question about how to configure systemd because we have a working example.
Take a look at https://github.com/saymedia/journald-cloudwatch-logs by Matin Atkins.
This open source project creates a binary that does exactly what you want - ship your (systemd) journald logs to AWS CloudWatch Logs.
The project depends on libsystemd to forward directly to CloudWatch. It does not rely on forwarding to syslog. This is a good thing.
The project appears to use golang's concurrent channels to read the logs and batches writes.
Vector can be used to ship logs from journald to AWS CloudWatch Logs.
journald can be used as a source and AWS Cloudwatch Logs as a sink.
I'm working on integrating this with an existing deployment of about 6 EC2 instances that generate about 30 GB of logs daily. I'll update this answer with any caveats or gotchas after we've used Vector in production for a few weeks.
EDIT 8/17/2020
A few things to be aware of. The match batch size for the PutLogEvents is 1MB and there is a max of 5 requests per second per stream. See the limits here..
To help with that, in my set up each journald unit has it's own log stream. Also, there are a lot of fields that the Vector journald sink includes, I used a vector transform to remove all the ones I didn't need. However, I'm still running into rate limits.
EDIT 10/6/2020
I have this running in production now. I had to update the version of vector I was using from 0.8.1 to 0.10.0 to take care an issue with vector not respecting the max bytes per batch requirement for AWS CloudWatch logs. As far as the rate limit issues I was experiencing, it turns out I wasn't having any issues. I was getting this message in the vector logs tower_limit::rate::service: rate limit exceeded, disabling service. What that actually means is that vector is pausing send logs temporarily to respect the rate limit of the sink. Also, each Cloudwatch Log Stream can consume up to 18 GB per hour which is fine for my 30 GB per day requirement for over 30 different services on 6 VMs.
One issue I did run into was causing the CPU to spike on our main API service. I had a source for each service unit to tail the journald logs. I believe this somehow blocked our API from not being able to write to journald (not 100% though). What I did was have one source and specified multiple units to follow so there was only one command tailing the logs and I increased the batch size since each service generates a lot of logs. I then used vector's template syntax to split the Log Group and Log Stream based on the service name. Below is an example configuration:
[sources.journald_logs]
type = "journald"
units = ["api", "sshd", "vector", "review", "other-service"]
batch_size = 100
[sinks.cloud_watch_logs]
type = "aws_cloudwatch_logs"
inputs = ["journald_logs"]
group_name = "/production/{{host}}/{{_SYSTEMD_UNIT}}"
healthcheck = true
region = "${region}"
stream_name = "{{_SYSTEMD_UNIT}}"
encoding = "json"
I have one final issue I need to iron out, but it's not related to this question. I'm using a file source for nginx since it writes to an access log file. Vector is consuming 80% of the CPU on that machine getting the logs and sending them to AWS CloudWatch. Filebeat also runs on the same box sending the logs to Logstash, but it's never caused any issues. Once we get vector working reliably we'll retire the Elastic Stack, but for now we have them running side by side.

Call Sentinel failover from Python

I have a simple Redis configuration running with 3 Servers and 3 Sentinels (different instances though). This configuration is running almost flawlessly, eventually, my Master fails (common Redis problem where it couldn't finish background saving).
My problem is when that happens whenever I try to save (or delete) something, I get the error:
ResponseError: MISCONF Redis is configured to save RDB snapshots, but
is currently not able to persist on disk. Commands that may modify the
data set are disabled. Please check Redis logs for details about the error.
Is there any way for me to ask Sentinel to call "failover" force electing a new master? By redis-cli is quite easy, but I couldn't find a way of doing it from my Python(2.7) program (using redis.py).
Any ideas?
First you are probably running out of disk space, which would cause that error. So address that and it will stop needing to be failed over.
That said, to do it in Python I think you need to use "execute_command" and pass it the sentinel command and the args. So something like:
myclient.execute_command("SENTINEL failover", podname)
where myclient is your connection object and poundage is the name you use for the pod in Sentinel, should do it.

Hello World PipeLine with ShelCommandlActivity

I'm trying to create a simple dataFlow pipeline with a single Activity of ShellCommandActivity type. I've attached the configuration of the activity and ec2 resource.
When I execute this the Ec2Resource sits in the WAITING_ON_DEPENDENCIES state then after sometime changes to TIMEDOUT. The ShellCommandActivity is always in the CANCELED state. I see the instance launch and very quicky changes to the terminated stated.
I've specified a s3 log file url, but that never gets updated.
Can anyone give me any pointers? Also is there any guidance out there on debugging this?
Thanks!!
You are currently forcing your instance to shut down after 1 minute which gives the TIMEOUT status if it can't execute in that time. Try increasing it to 50 minutes.
Also make sure you are using an AMI that runs Amazon Linux and that you are using full absolute paths in your scripts.
S3 log files are written as:
s3://bucket/folder/