Discover Teevity Cloud Costs Analytics
Last updated - 2022/06/19
Part 1 - Teevity multi-users dashboards
Part 2 - Reporting by combinaison of Tags
Part 3 - Tags cleaning and normalization
Part 3 - Teevity Reports and Widgets
Part 4 - Reserved Capacity recommendations (AWS RIs, GCP CUD, Azure RIs)
Part 5 - Resource Usage Level analytics (detect over-sized deployments or unused resources)
Part 6 - Advanced/custom charge back
Part 7 - Programmatic Configuration
Part 7 - Teevity API - https://api.teevity.com
Part 8 - Teevity Incognito (AWS Marketplace AMI + CloudFormation); coming later this year
Part 2 - Reporting by Tags and combinaison of tags + Creation of VirtualTag when tags are missing
Instead of reporting by AWS Accounts (or Google Cloud Projects or Azure Subscriptions), you can choose to report by Tags.
You can even report by a combination of Tags.
Here are a few examples of the kind of Tag based reporting your can set up:
BusinessUnit / Application / Component
BusinessUnit / Application / Component / Environment
CostCenter / Component
This helps you configure Teevity dashboard that let every user in your company have a dashboard fully customized to their needs and focused on what matters to them.
Part 3 - Teevity Reports and Widgets
Teevity Reports are like saved queries created in the Teevity Dynamic Cost Explorer. Basically, Teevity Reports help you make cost and usage requests results very easily accessible. To create a Teevity Report you just need to press Save Report from the Teevity Dynamic Cost Explorer.
And you can then access the reports from your dashboard. You can share reports with other Teevity users from your company (if you share the reports with some that doesn't have a Teevity account, it will send an invite to them). Just click on the Share icon.
You can also chose to display the result of these reports as a widget on your Teevity dashboard, with your own custom layout (size and position of widgets)
Part 4 - AWS RI Optimization reports
This chart shows you how many instance of which types would need RI relocations or additional RI purchases to optimize spending. It also show you which RIs are unused.
You can filter this view to show only selected instance types, selected Tags or selected AWS Region/Zones.
A synthetic financial summary shows how much you would save by buying the recommended RIs or make the recommended RI moves (you can configure which type of RIs your want the recommendations to be made for).
The report only contains "smart" RI recommendations since Teevity lets you define for which Tags it makes sense to buy RIs. So the report will only show recommendations that makes sense for you (for instance, if you have told Teevity that you don't want to buy RIs for certain development environment, the recommendations will never show RIs for these instances).
and for each RI which is recommended for purchase, you get the details of which instance groups are going to use it (instances are identified per tags). When RIs are shared between instances with different tags, you get the indication of which percentage of the RIs are going to be used by "each instance groups".
Part 5 - Resource Usage Level analytics
Resource Usage Level analytics helps users detect over-sized deployments or unused resources.
At the core of this report is a graphical representation of your Cloud environment, split by tags.
Thanks to it, you can easily navigate inside the various resources running on your Cloud accounts.
Each circle represents a "group of resources" defined by tags (the size of the circle depends on the cost of the resources).
Teevity supports nested resource groups ("Prod / ApplicationA / Component1", "Prod / ApplicationA / Component2" for instance).
You can dynamically zoom inside each level to drill down into the details of the analysis, down to the AWS service level (EC2, RDS, EBS, ...).
Regarding the "resource usage analytics" itself:
The color of each circle is based on the level of optimization of the associated resources (we call it "optimization score")
The "optimization score" defines how optimized these resources are (CPU-wise, RAM-wise, ...) with configurable rules (cf next point)
The "optimization scoring logic" for each resource group can be customized (ie you chose which logic to use to compute the scores, which parameters, ...)
Scoring logic example 1 : give a "good score to instances whose CPU or RAM is above 75% usage"
Scoring logic example 2 : give a "good score to instances whose CPU and RAM is above 75% usage"
You chose the scoring logic based on the nature of each system (ie a backend service will not require the same scoring logic as a frontend service for instance)
You can quickly access the history of the "optimization score" of each resource groups by simply hovering on it.
And you also get a justification for the score.
Learn more about the Resource Usage Analytics.
Understanding resources optimization levels, over long period of times (at an hourly granularity)
Optimizing cloud resources is hard!
We are not talking about "unattached volumes" or "VMs who are consistently using below 5% of their resources". These are the "low hanging fruits" and we do help you find them (but they are not the hard part).
The hard part is identifying which resources require optimization, when these resources belong to system of different natures (web frontend, batch jobs, isolated VMs vs VMs part of autoscaling groups, ...) which all require different criteria to understand if they are well optimized or not, and which optimization to apply (configuration change, architectural change, ...)
To make this task easier, Teevity provides a view showing Optimization Scores per resources over several months, at an hourly granularity which is the level required to enable optimization analysis. And "Teevity Optimization Scores" help capture the complexity needed to go beyond "raw metrics" analysis.
FinOps teams can leverage this tooling to investigate:
Resources which are the easiest to optimize (because they consistently have a poor optimization score)
Resources for which a discussion with Application teams is required in order to identify optimization actions
And Resources for which an architectural change is likely the best option in order to optimize (for instance because they are mostly showing poor optimization scores but are also briefly highly optimized)
Part 6 - Advanced charge-back and refactoring rules
Teevity also has support for advanced/custom charge back and cost refactoring rules. Get in touch with us if you want to know more about that by sending a email to firstname.lastname@example.org
Part 8 - Teevity Incognito (AWS Marketplace AMI + CloudFormation)
Teevity will also soon be available to run on your AWS account, through an AWS Marketplace AMI and a CloudFormation.
We call this version of Teevity Incognito because it lets you use our service without having to share cost with us.