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If you have done any DevOps work on Amazon Web Services (AWS) then you should be familiar with Amazon CloudWatch, a service for tracking and viewing metrics (CPU, network in/out, etc.) about the various AWS services that you consume, or better still, custom metrics that you publish about your service.
On top of that, you can also set up alarms on any metrics and send out alerts via Amazon SNS, which is a pretty standard practice of monitoring your AWS-hosted application. There are of course many other paid services such as StackDriver and New Relic which offer you a host of value-added features, personally I was impressed with some of the predicative features from StackDriver.
The built-in Amazon management console for CloudWatch provides the rudimentary functionalities that lets you browse your metrics and view/overlap them on a graph, but it falls short once you have a decent number of metrics.
For starters, when trying to browse your metrics by namespace, you’re capped at 200 metrics so discovery is out of the question, you have to know what you’re looking for to be able to find it, which isn’t all that useful when you have hundreds of metrics to work with…
Also, there’s no way for you to filter metrics by the recorded datapoints, so to answer even simple questions such as
‘what other timespan metrics also spiked at mid-day when our service discovery latency spiked?’
you now have to manually go through all the relevant metrics (and of course you have to find them first!) and then visually check the graph to try and find any correlations.
After being frustrated by this manual process for one last time I decided to write some tooling myself to make my life (and hopefully others) a bit easier, and in comes Amazon.CloudWatch.Selector, a set of DSLs and CLI for querying against Amazon CloudWatch.
With this simple library you will get:
- an internal DSL which is intended to be used from F# but still usable from C# although syntactically not as intuitive
- an external DSL which can be embedded into a command line or web tool
Both DSLs support the same set of filters, e.g.
|NamespaceIs||Filters metrics by the specified namespace.|
|NamespaceLike||Filters metrics using a regex pattern against their namespaces.|
|NameIs||Filters metrics by the specified name.|
|NameLike||Filters metrics using a regex pattern against their names.|
|UnitIs||Filters metrics against the unit they’re recorded in, e.g. Count, Bytes, etc.|
|Average||Filters metrics by the recorded average data points, e.g. average > 300 looks for metrics whose average in the specified timeframe exceeded 300 at any time.|
|Min||Same as above but for the minimum data points.|
|Max||Same as above but for the maximum data points.|
|Sum||Same as above but for the sum data points.|
|SampleCount||Same as above but for the sample count data points.|
|DimensionContains||Filters metrics by the dimensions they’re recorded with, please refer to the CloudWatch docs on how this works.|
|DuringLast||Specifies the timeframe of the query to be the last X minutes/hours/days. Note: CloudWatch only keeps up to 14 days worth of data so there’s no point going any further back then that.|
|Since||Specifies the timeframe of the query to be since the specified timestamp till now.|
|Between||Specifies the timeframe of the query to be between the specified start and end timestamp.|
|IntervalOf||Specifies the ‘period’ in which the data points will be aggregated into, i.e. 5 minutes, 15 minutes, 1 hour, etc.|
Here’s some code snippet on how to use the DSLs:
In addition to the DSLs, you’ll also find a simple CLI tool as part of the project which you can start by setting the credentials in the start_cli.cmd script and running it up. It allows you to query CloudWatch metrics using the external DSL.
Here’s a quick demo of using the CLI to select some CPU metrics for ElasiCache and then plotting them on a graph.
As a side note, one of the reasons why we have so many metrics is because we have made it super easy for ourselves to record new metrics (see this recorded webinar for more information) to gives ourselves a very granular set of metrics so that any CPU-intensive or IO work is monitored as well as any top-level entry points to our services.
- Amazon.CloudWatch.Selector project page
- Amazon.CloudWatch.Selector Nuget package
- Demo video of the CLI
- Webinar – performance monitoring with AOP & AWS
- Slides for the webinar
Hi, I’m Yan. I’m an AWS Serverless Hero and I help companies go faster for less by adopting serverless technologies successfully.
Are you struggling with serverless or need guidance on best practices? Do you want someone to review your architecture and help you avoid costly mistakes down the line? Whatever the case, I’m here to help.
Skill up your serverless game with this hands-on workshop.
My 4-week Production-Ready Serverless online workshop is back!
This course takes you through building a production-ready serverless web application from testing, deployment, security, all the way through to observability. The motivation for this course is to give you hands-on experience building something with serverless technologies while giving you a broader view of the challenges you will face as the architecture matures and expands.
We will start at the basics and give you a firm introduction to Lambda and all the relevant concepts and service features (including the latest announcements in 2020). And then gradually ramping up and cover a wide array of topics such as API security, testing strategies, CI/CD, secret management, and operational best practices for monitoring and troubleshooting.
If you enrol now you can also get 15% OFF with the promo code “yanprs15”.
Check out my new podcast Real-World Serverless where I talk with engineers who are building amazing things with serverless technologies and discuss the real-world use cases and challenges they face. If you’re interested in what people are actually doing with serverless and what it’s really like to be working with serverless day-to-day, then this is the podcast for you.
Check out my new course, Learn you some Lambda best practice for great good! In this course, you will learn best practices for working with AWS Lambda in terms of performance, cost, security, scalability, resilience and observability. We will also cover latest features from re:Invent 2019 such as Provisioned Concurrency and Lambda Destinations. Enrol now and start learning!
Check out my video course, Complete Guide to AWS Step Functions. In this course, we’ll cover everything you need to know to use AWS Step Functions service effectively. There is something for everyone from beginners to more advanced users looking for design patterns and best practices. Enrol now and start learning!
Here is a complete list of all my posts on serverless and AWS Lambda. In the meantime, here are a few of my most popular blog posts.
- All you need to know about caching for serverless applications
- Lambda optimization tip – enable HTTP keep-alive
- You are wrong about serverless and vendor lock-in
- You are thinking about serverless costs all wrong
- Just how expensive is the full AWS SDK?
- Check-list for going live with API Gateway and Lambda
- How to choose the right API Gateway auth method
- CloudFormation protip: use !Sub instead of !Join
- AWS Lambda – should you have few monolithic functions or many single-purposed functions?
- Guys, we’re doing pagination wrong
- Top 10 Serverless framework best practices
- How to break the “senior engineer” career ceiling
- My advice to junior developers