4 April, 2025
Our client is a digital energy management specialist, providing services to retailers across Australia and New Zealand. A scale up, focused on providing multi-utility services across electricity and water networks for residential, commercial utilities, embedded networks and solar.
With scale came the increasing use of AWS cloud technologies to power their data platform. This increased adoption of the AWS ecosystem made it more important to accurately measure value and cost of the growth.
It’s a quintessential challenge for a scale up, how do we leverage the cloud to scale while simultaneously optimising cloud usage and spend?
Midnyte City worked with the client on a DevOps initiative when the question of cost trajectory was raised. To optimise the operational AWS costs, a small team was co-sourced from both organisations. This model allowed the client to continue focusing on delivering and managing their platform, while also enabling the internal team to improve and optimise cost across the platform. Also, boost cloud cost literacy across the teams.
To summarise, the aims included:
Assess the current platform and AWS infrastructure costs
Identify any opportunities to reduce spend or eliminate waste
Identify any opportunities to reduce spend or eliminate waste
Midnyte City worked with this client to begin defining a roadmap for how the teams could measure and visualise cost. Including investigation into tooling that will help to enable easy reporting for non-technical folk and other team members to gain an easy glance at overall cost and trends across the platform. The client’s team had done some previous investigation into the use of the AWS Cloud Intelligence Dashboards Framework. After some further investigation within the co-sourced team, the decision was made to begin utilising the CUDOS Dashboard.
This would make for a baseline of how the initial visualisations are built and implemented and enable evolution and iteration from there. The team implemented and utilised the dashboarding to better understand the operational costs within their data platform environment.
Almost immediately, after enabling the ability to visualise and round up these platform costs, savings of over 40% of the current monthly spend within the platform were identified. This was achieved by removing under and non-utilised infrastructure from the platform.
Figure 1. A simplified view of the tooling used to measure and visualise the client’s cloud spend via the CUDOS Dashboard
The advantage of this approach meant the team could keep things simple and bootstrap a usable solution within less than a week and then continue to iterate as needed.
The implementation meets the immediate needs of the team by supplying the appropriate visibility of cloud cost, but also allows for flexibility to augment visualisations, or even iterate away from the existing visualisations as needed.
Enhanced Ability to Understand and Measure Cost
The client and Midnyte team were able to help implement the right tooling to ensure the cloud cost model was measurable and coherent.
By enabling the visibility across multiple accounts, the team were able to rapidly identify and optimise for cost across multiple workloads and multiple environments across the entire platform.
Reduction in Operational Cloud Cost
With the ability to measure and understand the operational AWS costs, the client and Midnyte team was able to implement a range of cost management outcomes, such as the removal of waste via deletion of old, unused solutions and infrastructure instances. Some of which had been deprecated a long time ago, but due to the lack of visibility the team were unaware they were causing waste.
As a result, the client’s data platform monthly AWS bill was reduced by over 40%, representing thousands of dollars in savings.
If you would like to speak to someone about similar challenges in your team or organisation, reach out below to schedule a time.