AWS SNS Outage: Effects On The Unreliable Town Clock

It took a while, but the Unreliable Town Clock finally lived up to its name. Surprisingly, the fault was not mine, but Amazon’s. - Countdown Timer Microservice Built On Amazon API Gateway and AWS Lambda

deceptively simple web service with super powers is a fully functional, fully scalable microservice built on the just-released Amazon API Gateway and increasingly popular AWS Lambda platforms. is a public web service that maintains a practically unlimited number of countdown timers with one second resolution and no practical limit to the number of seconds each timer can run.

New timers can be created on a whim and each timer can be reset at any time to any number of seconds desired, whether it is still running or has already expired.


Let’s begin with an example to demonstrate the elegant simplicity of the interface.

1. Set timer - Any request of the following URL sets a timer named “YOURTIMERNAME” to start counting down immediately from 60 seconds:

You may click on that link now, or hit a URL of the same format with your own timer name and your chosen number of seconds. You may use a browser, a command like curl, or your favorite programming language.

2. Poll timer - The following URL requests the status of the above timer. Note that the only difference in the URL is that we have dropped the seconds count.

If the named timer is still running, will return HTTP Status code 200 OK, along with a JSON structure containing information like how many seconds are left.

If the timer has expired, will return an HTTP status code 504 Timeout.

That’s it!

No, really. That’s the entire API.

Simple New Web Service: Testers Requested

Interested in adding scheduled job monitoring (dead man’s switch) to the existing monitoring and alerting framework you are already using (Nagios, Sensu, Zenoss, Zabbix, Monit, Pingdom, Montastic, Ruxit, and the like)?

Last month I wrote about how I use to monitor scheduled events with an example using an SNS Topic and AWS Lambda.

This week I spent a few hours building a simple web service that enables any polling-based monitor software or service to automatically support alerting when a target event has not occurred in a desired timeframe.

The new web service is built on infrastructure technologies that are reliably maintained and scaled by Amazon:

lambdash: AWS Lambda Shell Hack: New And Improved!

easier, simpler, faster, better

Seven months ago I published the lambdash AWS Lambda Shell Hack that lets you run shell commands to explore the environment in which AWS Lambda functions are executed.

I also posted samples of command output that show fascinating properties of the AWS Lambda runtime environment.

In the last seven months, Amazon has released new features and enhancements that have made a completely new version of lambdash possible, with many benefits including:

Monitor an SNS Topic with AWS Lambda and

get alerted when an expected event does NOT happen

Last week I announced the availability of a public SNS Topic that may be used to run AWS Lambda functions on a recurring schedule. To encourage folks to realize the implications of a free community service maintained by an individual, I named it the “Unreliable Town Clock”.

Even with this understanding, some folks in the AWS community have (again) placed their faith in me and are already starting to depend on the Unreliable Town Clock public SNS Topic to drive their own AWS Lambda functions and SQS queues, and I want to make sure this service is as reliable as I can reasonably make it.

Here are some of the steps I have taken to increase the reliability of the Unreliable Town Clock:

Schedule Recurring AWS Lambda Invocations With The Unreliable Town Clock (UTC)

public SNS Topic with a trigger event every quarter hour

Update 2015-10-08: Amazon has released AWS Lambda Scheduled Functions. I recommend using that feature to schedule AWS Lambda functions. In fact, the Unreliable Town Clock switched to use this feature behind the scenes, the day it was announced.

Scheduled executions of AWS Lambda functions on an hourly/daily/etc basis is a frequently requested feature, ever since the day Amazon introduced the service at AWS re:Invent 2014.

Until Amazon releases a reliable, premium cron feature for AWS Lambda, I’m offering a community-built alternative which may be useful for some non-critical applications.






Beyond its event-driven convenience, the primary attraction of AWS Lambda is eliminating the need to maintain infrastructure to run and scale code. The AWS Lambda function code is simply uploaded to AWS and Amazon takes care of providing systems to run on, keeping it available, scaling to meet demand, recovering from infrastructure failures, monitoring, logging, and more.

The available methods to trigger AWS Lambda functions already include some powerful and convenient events like S3 object creation, DynamoDB changes, Kinesis stream processing, and my favorite: the all-purpose SNS Topic subscription.

Even so, there is a glaring need for code that wants to run at regular intervals: time-triggered, recurring, scheduled event support for AWS Lambda. Attempts to to do this yourself generally ends up with having to maintain your own supporting infrastructure, when your original goal was to eliminate the infrastructure worries.

Unreliable Town Clock (UTC)

The Unreliable Town Clock (UTC) is a new, free, public SNS Topic (Amazon Simple Notification Service) that broadcasts a “chime” message every quarter hour to all subscribers. It can send the chimes to AWS Lambda functions, SQS queues, and email addresses.

Debugging AWS Lambda Invocations With An Echo Function

As I create architectures that include AWS Lambda functions, I find there are situations where I just want to know that the AWS Lambda function is getting invoked and to review the exact event data structure that is being passed in to it.

I found that a simple “echo” function can be dropped in to copy the AWS Lambda event to the console log (CloudWatch Logs). It’s easy to review this output to make sure the function is getting invoked at the right times and with the right data. Site Redesign

The web site has been redesigned. The old design was going on 8 years old. The new design is:

Ok, so I still have a little improvement remaining in the fast dimension, but at least the site is static now and served through a CDN.

Since fellow geeks care, here are the technologies currently employed:

Subscribing AWS Lambda Function To SNS Topic With aws-cli

The aws-cli documentation and command line help text have not been updated yet to include the syntax for subscribing an AWS Lambda function to an SNS topic, but it does work!

Here’s the format:

aws sns subscribe \
  --topic-arn arn:aws:sns:REGION:ACCOUNT:SNSTOPIC \
  --protocol lambda \
  --notification-endpoint arn:aws:lambda:REGION:ACCOUNT:function:LAMBDAFUNCTION

where REGION, ACCOUNT, SNSTOPIC, and LAMBDAFUNCTION are substituted with appropriate values for your account.

For example:

AWS Lambda Event-Driven Architecture With Amazon SNS

Today, Amazon announced that AWS Lambda functions can be subscribed to Amazon SNS topics.

This means that any message posted to an SNS topic can trigger the execution of custom code you have written, but you don’t have to maintain any infrastructure to keep that code available to listen for those events and you don’t have to pay for any infrastructure when the code is not being run.

This is, in my opinion, the first time that Amazon can truly say that AWS Lambda is event-driven, as we now have a central, independent, event management system (SNS) where any authorized entity can trigger the event (post a message to a topic) and any authorized AWS Lambda function can listen for the event, and neither has to know about the other.

Making this instantly useful is the fact that there already are a number of AWS services and events that can post messages to Amazon SNS. This means there are a lot of application ideas that are ready to be implemented with nothing but a few commands to set up the SNS topic, and some snippets of nodejs code to upload as an AWS Lambda function.


Persistence Of The AWS Lambda Environment Between Function Invocations

AWS Lambda functions are run inside of an Amazon Linux environment (presumably a container of some sort). Sequential calls to the same Lambda function could hit the same or different instantiations of the environment.

If you hit the same copy (I don’t want to say “instance”) of the Lambda function, then stuff you left in the environment from a previous run might still be available.

This could be useful (think caching) or hurtful (if your code incorrectly expects a fresh start every run).

Here’s an example using lambdash, a hack I wrote that sends shell commands to a Lambda function to be run in the AWS Lambda environment, with stdout/stderr being sent back through S3 and displayed locally.

Before You Buy Amazon EC2 (New) Reserved Instances

understand the commitment you are making to pay for the entire 1-3 years

Amazon just announced a change in the way that Reserved Instances are sold. Instead of selling the old Reserved Instance types:

  • Light Utilization
  • Medium Utilization
  • Heavy Utilization

EC2 is now selling these new Reserved Instance types:

  • No Upfront
  • Partial Upfront
  • All Upfront

Despite the fact that they are still called “Reserved Instances” and that there are three plans which sound like increasing commitment, the are not equivalent and do not map 1-1 old to new. In fact the new Reserved Instances are not even increasing commitment.

You should forget what you knew about Reserved Instances and read all the fine print before making any further Reserved Instance purchases.

One of the big differences between the old and the new is that you are always committing to spend the entire 1-3 years of cost even if you are not running a matching instance during part of that time. This text is buried in the fine print in a “**” footnote towards the bottom of the pricing page:

S3 Bucket Notification to SQS/SNS on Object Creation

A fantastic new and oft-requested AWS feature was released during AWS re:Invent, but has gotten lost in all the hype about AWS Lambda functions being triggered when objects are added to S3 buckets. AWS Lambda is currently in limited Preview mode and you have to request access, but this related feature is already available and ready to use.

I’m talking about automatic S3 bucket notifications to SNS topics and SQS queues when new S3 objects are added.

Unlike AWS Lambda, with S3 bucket notifications you do need to maintain the infrastructure to run your code, but you’re already running EC2 instances for application servers and job processing, so this will fit right in.

To detect and respond to S3 object creation in the past, you needed to either have every process that uploaded to S3 subsequently trigger your back end code in some way, or you needed to poll the S3 bucket to see if new objects had been added. The former adds code complexity and tight coupling dependencies. The latter can be costly in performance and latency, especially as the number of objects in the bucket grows.

With the new S3 bucket notification configuration options, the addition of an object to a bucket can send a message to an SNS topic or to an SQS queue, triggering your code quickly and effortlessly.

Here’s a working example of how to set up and use S3 bucket notification configurations to send messages to SNS on object creation and update.

AWS Lambda: Pay The Same Price For Faster Execution

multiply the speed of compute-intensive Lambda functions without (much) increase in cost


  • AWS Lambda duration charges are proportional to the requested memory.

  • The CPU power, network, and disk are proportional to the requested memory.

One could conclude that the charges are proportional to the CPU power available to the Lambda function. If the function completion time is inversely proportional to the CPU power allocated (not entirely true), then the cost remains roughly fixed as you dial up power to make it faster.

If your Lambda function is primarily CPU bound and takes at least several hundred ms to execute, then you may find that you can simply allocate more CPU by allocating more memory, and get the same functionality completed in a shorter time period for about the same cost.

Exploring The AWS Lambda Runtime Environment

In the AWS Lambda Shell Hack article, I present a crude hack that lets me run shell commands in the AWS Lambda environment to explore what might be available to Lambda functions running there.

I’ve added a wrapper that lets me type commands on my laptop and see the output of the command run in the Lambda function. This is not production quality software, but you can take a look at it in the alestic/lambdash GitHub repo.

For the curious, here are some results. Please note that this is running on a preview and is in no way a guaranteed part of the environment of a Lambda function. Amazon could change any of it at any time, so don’t build production code using this information.

The version of Amazon Linux:

$ lambdash cat /etc/issue
Amazon Linux AMI release 2014.03
Kernel \r on an \m

The kernel version:

$ lambdash uname -a
Linux ip-10-0-168-157 3.14.19-17.43.amzn1.x86_64 #1 SMP Wed Sep 17 22:14:52 UTC 2014 x86_64 x86_64 x86_64 GNU/Linux

The working directory of the Lambda function: