What is your digital waste footprint?

How many times have you walked into your garage and took stock of all the things you haven’t used in years? Those bikes that you bought for you and your partner that you haven’t used since the summer of ‘09, the fishing rods, the mitre saw, the boat (if you’re lucky) and the list goes on and on. Imagine if you didn’t have to pay for them all up front – and better yet, imagine if you could stop paying for them the moment you stopped using them!

Amazingly, that is the world we live in with the public cloud. If you’re not using something, then you shouldn’t be paying for it – and if you are, then you need to ask yourself some hard questions. The problem we’re seeing in customer-land is twofold:

  1. Technical staff are too far removed from whoever pays the bills, and
  2. It’s easier than ever to start new resources that cost money

Technical staff don’t care about the bill

Many technical staff that provision resources and use services on AWS have no idea what they cost and have never seen an invoice or the billing dashboard. They don’t pay the bills, so why would they worry about what it costs?

Working with technical staff and raising awareness around the consequences of their choices in the public cloud goes a long way to arresting the free-fall into an unmanageable hosting bill. By bringing the technical staff along on the optimisation journey, you’re enabling them to align themselves with business goals and feel the choices they make are contributing in a positive way.

It’s so easy to create new resources

One of the biggest strengths of the public cloud is how easy it is to provision resources or enable services, however this appears to be one of its weaknesses as well. It’s because of this ease of use that time and time again we see serious account sprawl: unused, underutilised and over-sized resources litter the landscape, nobody knows how much Project A costs compared to Project B and there isn’t a clear plan to remediate the wastage and disarray.

Getting a handle on your hosting costs is an important step to take early on and implementing a solid strategy to a) avoid common cost related mistakes and b) be able to identify and report on project costs is crucial to being successful in your cloud journey.

Success stories

Consegna has recently engaged two medium-to-large sized customers and challenged them to review the usage of their existing AWS services and resources with a view to decreasing their monthly cloud hosting fees. By working with Consegna as an AWS partner and focusing on the following areas, one customer decreased their annual bill by NZD$500,000 and the other by NZD$100,000. By carefully analysing the following areas of your cloud footprint, you should also be able to significantly reduce your digital waste footprint.

Right-sizing and right-typing

Right-sizing your resources is generally the first step you’ll take in your optimisation strategy. This is because you can make other optimisation decisions that are directly related to the size of your existing resources, and if they aren’t the right size to begin with then those decisions will be made in error.

Right-typing can also help reduce costs if you’re relying on capacity in one area of your existing resource type that can be found in a more suitable resource type. It’s important to have a good idea of what each workload does in the cloud, and to make your decisions based on this instead of having a one-size-fits all approach.


Right-sizing compute can be challenging if you don’t have appropriate monitoring in place. When making right-sizing decisions there are a few key metrics to consider, but the main two are CPU and RAM. Because of the shared responsibility model that AWS adheres to, it doesn’t have access to RAM metrics on your instances out-of-the-box so to get a view on this you need to use third party software.

Consegna has developed a cross-platform custom RAM metric collector that ships to CloudWatch and has configured a third-party integration to allow CloudCheckr to consume the metrics to provide utilisation recommendations. Leveraging the two key metrics, CPU and RAM, allows for very accurate recommendations and deep savings.


Storage is an area that gets overlooked regularly which can be a costly mistake. It’s important to analyse the type of data you’re storing, how and how often you’re accessing it, where it’s being stored and how important it is to you. AWS provides a myriad of storage options and without careful consideration of each, you can miss out on substantial decreases of your bill.


Right-sizing your database is just as important as right-sizing your compute – for the same reasons there are plenty of savings to be had here as well.

Right-typing your database can also be an interesting option to look at as well. Traditional relational databases appear to be becoming less and less popular with new serverless technologies like DynamoDB – but it’s important to define your use case and provision resources appropriately.

It’s also worth noting that AWS have recently introduced serverless technologies to their RDS offering which is an exciting new prospect for optimisation aficionados.

Instance run schedules

Taking advantage of not paying for resources when they’re not running can make a huge difference to how much your bill is, especially if you have production workloads that don’t need to be running 24/7. Implementing a day / night schedule can reduce your bill by 50% for your dev / test workloads.

Consenga takes this concept to the next level by deploying a portal for non-technical users to control when the instances they deal with day-to-day are running or stopped. By pushing this responsibility out to the end users, instances that would have been running 12 hours a day based on a rigid schedule now only run for as long as they’re needed – an hour, or two usually – supercharging the savings.

Identify and terminate unused and idle resources

If you’re not using something then you should ask yourself if you really need it running, or whether or not you could convert it to an on-demand type model.

This seems like an obvious one, but the challenge can actually be around identification – there are plenty of places resources can hide in AWS so being vigilant and using the help of third party software can be key to aid you in this process.

Review object storage policies

Because object storage in AWS (S3) is so affordable, it’s easy to just ignore it and assume there aren’t many optimisations to be made in this area. This can be a costly oversight as not only the type of storage you’re using is important, but how frequently you need to access the data as well.

Lifecycle policies on your object storage is a great way to automate rolling infrequently used data into cold storage and can be a key low-hanging fruit that you can nab early on in your optimisation journey.

Right-type pricing tiers

AWS offers a robust range of pricing tiers for a number of their services and by identifying and leveraging the correct tiers for your usage patterns, you can make some substantial savings. In particular you should be considering Reserved Instances for your production resources that you know are going to be around forever, and potentially Spot Instances for your dev / test workloads that you don’t care so much about.

Of course, there are other pricing tiers in other services that are worth considering.

Going Cloud Native

AWS offers many platform-as-a-service offerings which take care of a lot of the day to day operational management that is so time consuming. Using these offerings as a default instead of managing your own infrastructure can provide some not so tangible optimisation benefits.

Your operations staff won’t be bogged down with patching and keeping the lights on – they’ll be freed up to innovate and explore the new and exciting technologies that AWS are constantly developing and releasing to the public for consumption.

Consegna consistently works with its technology and business partners to bake this optimisation process into all cloud activities. By thinking of ways to optimise and be efficient first, both hosting related savings and operational savings are achieved proactively as opposed to reactively.