Category Archives: Amazon Simple Queue Service (SQS)

AWS SNS Retry Policy – New Feature – Push Based Messaging Instead of SQS Polling

The good guys at Amazon Web Services just announced a new feature in Simple Notifications Service (SNS) which allows settings a retry policy for SNS notifications.

Up until now SNS had an unknown publish retry policy (and maybe non existing). I always suspected it had some logic for different subscription types (Email, HTTP, Text, SQS) but it was never mentioned anywhere.

by Ed Russel

The new retry policy feature allows you to define the number of retries and the wait period between them (even if its a linear or exponential wait!) as well as set a throttling policy so that if your server is currently down it won’t get flooded with notifications once its back up.

This allows for some very interesting patterns. Most notably is push based messaging mechanism in which instead of writing a dedicated process to poll an SQS queue you can use SNS as sort of an ad-hoc push queue that will post the messages to an HTTP/S URL. Setting a reasonable retry policy and throttling policy will also ensure that if your server is down, messages won’t get lost.

I posted a while back a suggestion for a hack which utilized SNS as a notification mechanism to start polling SQS, however now that SNS has a retry policy its a good candidate for allowing you to handle your async tasks using your regular HTTP servers with all the goodies of logging, multi-threading, debugging, etc.

Before you run to start implementing a push based messaging (or re-implement Google AppEngine’s TaskQueue Push Queue API), there are certain things which are yet unknown and/or require further consideration:

  • SQS has a 15 days storage policy, so you have up to 15 days to fix a bug or setup a system that will empty a queue. In the new SNS retry policy you may reach a similar long period of time however, the maximum values to set in the policy are not yet known and may pose a limit.
  • I am no aware and couldn’t find any documentation which related to the HTTP status code of a message pushed to an HTTP/S subscriber (other than answering the subscription request). How can you tell SNS that if a message was pushed to an HTTP subscriber, the subscriber failed due to an HTTP error? In that case will SNS consider a non HTTP Status 200 request a failed request and will do the retry policy?
  • What happens if a message pushed to an HTTP/S subscriber takes a long time to process due to load or any other reason? When will SNS decide if the request failed due to timeout?
I hope some of these questions will get cleared up and SNS can become a viable push based messaging mechanism.
I previously recommended to always push via SNS (even if its just to an SNS queue) just to get the added benefits of easier debugging (subscribe to an SQS queue AND send email or HTTP request to debug, etc). The new features only proves that its becoming a very interesting building block to use inside and/or outside of AWS.



The cool example of SaaS for developers by @mza and @jeffbarr

In a recent post on the AWS blog, Jeff Barr and Matt Wood, showed the architecture and code they wrote which lists the most interesting AWS related jobs from the Amazon Jobs site.

It serves as a rather good example of how service components such as the ones AWS provides (SNS, SQS, S3 to name a few that are AWS agnostic) a great set of building blocks that can easily help you focus on writing the code you really need to write.

I found the auto scaling policy for spinning up & down machines just to tweet a bit of an over kill at first (and Jeff could have easily added the code on the same instance running the cron), however thinking about it  a bit more and considering the various pricing strategies it actually makes a lot sense.

The cloud is more than just the hardware – its also about services!

When talking about the cloud, most people talk about running the servers on the cloud. They talk about the fact that they can start or stop virtual servers with a simple API call.

Cloud Services Toolbox
taken by keepthebyte

A lot of Cloud Providers do provide you with virtual servers, virtual load balancer and infinite (and/or scalable) storage, but these are all building block of servers. You still need to do the heavy lifting of taking a bunch of servers and making it do the work for you. You need to install the software (not just the one you wrote), mange, handling disaster recovery, backups, logging, etc.

What makes Amazon’s cloud unique on top of the servers and storage they provide is the fact that it provides a set of cloud services that can be used as black boxes for your application/service reducing the code you need to write/maintain as well as the number of servers you need to administer. These services are also available for use outside of Amazon’s cloud but there are benefits of using them within your EC2 instances.

The Amazon non-hardware cloud services offering is split into two categories:

  • Off the shelf services – These are preconfigured services that Amazon takes most of the hassle off of managing it. Such services are
    • Amazon Relational Database Services (RDS) – Hosted MySQL which Amazon manage, patches and helps you backup and restore as well as deploy in a smart way across multiple availability zones.
    • Amazon ElastiCache – Hosted Memcached which Amazon manages, allows to resize (add or remove servers) as well as patch with the latest software.
  • Development Building Blocks (Black Boxes) – Web services that provides functionality which you can mix and match to create you service, removing the need for you to handle the load, machines and configuration of these services. Such services are:
    • Amazon SimpleDB – an Amazon written key/value datastore that is hosted and operated by Amazon. Scalable and simple. It just works
    • Amazon Simple Queue Service (SQS) – A reliable, scalable, persistent queue service. Great for talking with distributed async components.
    • Amazon Simple Email Service (SES) – A scalable Email service which allows you to send Email (for humans and machines)
    • Amazon Simple Notification Service (SNS) –  A web service to send notifications to people/machines/service/etc. It allows to send the notification out as an Email or as an HTTP request as well as post it to an SQS queue

What I love the most about Amazon Web Services is the fact that when they do provide a certain Development Building Block such as Simple Email Service (SES), they do so without killing or harming the competition. There is still enough value and features in other Email services such as mailgun, SendGrid and MailChimp for them to co-exist with SES.

Not stepping (too much) on web services developers toes is not something to dismiss and I would love to see the innovation that comes out of Cloud based web services in the future.

Go cloud services! 🙂

Recommendation: Consider Submitting Messages to Amazon’s Simple Queue Service (SQS) via Simple Notification Service (SNS)

Thinking a bit more about my last post, I’d come to the conclusion that unless there is a really good excuse, one should always submit items to Amazon’s Simple Queue Service (SQS) via publishing to a topic in Simple Notification Service (SNS).

In the simplest case, you’ll publish to a topic and that topic will have a single subscriber that will post the message to the queue.

However, since SNS allows multiple subscribers you can get a couple of features free of charge without changing a single line of code. For example you can:

  • Add a temporarily an Email address to get messages going to the queue via Email for easy debugging (you can easily and quickly unsubscribe via the link at the end of the Email)
  • Add additional logging by adding an HTTP/S subscriber, getting the message and perform some logging on it
  • Notify other monitoring systems that a certain process has started
I know that from now on I’ll try to think really hard if I really need to publish directly to a queue instead of using SNS.

Using Amazon’s Simple Notification Service (SNS) & Simple Queue Service (SQS) For a Reliable Push Based Processing of Messages

I’ve recently encountered a use case where I need to reliably send a message to a worker process that should handle the following requirements:

  • Message should persist until the action it specified is done.
  • Message should be processed (or wait to be processed) when the worker processes have a bug or are down
  • Message processing should be as fast as possible – process the message ASAP.

Using Amazon’s Simple Queue Service (SQS)

SQS can provide the persistency needed. The message will be available until it is deleted (at least up to ~3 days) even if the worker processes are down or have a bug.

The problem with using SQS is that it requires polling which introduces a certain delay between the time a message is published and until it is processed. That delay can be small, a couple of seconds, but can easily be up to 30 seconds and more (depending on the limitations of SQS polling and the polling interval used).

Using Amazon’s Simple Notification Service (SNS)

SNS can provide a push mechanism to notify in near-real-time to a subscriber that a message has been published.
However, SNS can only guarantee a single delivery to each subscriber of a given topic. This means that if there was a bug or a problem processing the message and there was no specific code to save it somewhere, the message is lost.

The Solution

SQS and SNS can be combined to produce a PUSH mechanism to reliably handle messages.
The general configuration steps are:
  • Create a topic
  • Subscribe an SQS queue to that topic
  • Subscribe a worker process that work via HTTP/S to that topic (for increased reliability this can be an Elastic Load Balancer (ELB) that hides a set of machines)
Then the flow goes like this:
  • Submit a message to the topic
  • SNS will publish the message to the SQS queue
  • SNS will then notify via HTTP/S POST to the handler to start processing the message
When the worker process gets the HTTP/S POST from SNS it will start polling the queue until it has no items in the queue and finish the HTTP request.
To handle failures when the worker process has a bug or is down or did not get the SNS message, a regular worker process can run and poll the queue in regular, longer, intervals to make sure all messages are processed and no one gets behind.

This solution covers the original 3 requirements of message reliability, handling cases where workers are down or have bugs and handling messages as soon as they are sent.

Monitor Your Amazon Web Services Simple Queue Service (SQS) Queue Length in Amazon CloudWatch

UPDATE (2011-07-16): I just got a newsletter Email from Amazon stating that they have added SQS and SNS to CloudWatch which allows monitor SQS queues not just for the length of the queue, but for others metrics as well, so there is no real need in my script. Unless you really really want to use it 🙂

All you have to do is select SQS in the metrics type drop down and you will see a set of metrics to select from for all of your existing queues.



Amazon’s CloudWatch is a great tool for monitor various aspects of your service. Last May Amazon introduced custom metrics to CloudWatch which allows sending any metrics data you wish to CloudWatch. You can then store it, plot it and also create CloudWatch Alerts based on it.

One of the things missing from CloudWatch is Simple Queue Service (SQS) monitoring, so I’ve written a small script to update a queue’s count in a CloudWatch custom metric.
Having the queue’s count in CloudWatch allows adding alerts and actions based on the queue’s length.

For example, if the queue’s length is above a certain amount of a certain period of time, one of 2 things happened:

  1. There is a bug in the code causing the worker processes that process the queue’s message to fail
  2. There is a higher than usual load on the system causing the queue fill up and get more and more messages while there aren’t enough worker processes to process these messages in reasonable time

If the load is higher than usual you can easily tell via a CloudWatch alert to add an additional machine instance running more worker processes or simply send an Email alert saying there is something wrong.

The script is very easy to use and can be run from a cron job. I’m running it as a cron job in 1 minute intervals and have set up various CloudWatch alerts to better monitor my queue.

Grab the script on Github at:   SQS Cloud Watch Queue Count.