The breadth of cloud cost management features has grown.
This guide has a list of every important cloud cost management feature, particularly for those who use AWS as their primary cloud provider, to help you identify the features you really need for your use case. We hope that you’ll be able to find the best provider for your use case, budget, and security requirements.
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In this post, we'll cover the following core features that are probably worth considering when evaluating cloud cost management solutions:
AWS Spot Management can get you between 40-80% in AWS EC2 cost savings after a simple 10-minute installation. Some providers have an orchestrator that runs in your environment and is ideal for applications that leverage AWS EC2, Autoscaling, ECS, EKS, or Kubernetes. Moments after installation, it begins migrating applications to AWS Spot to generate savings.
You should nearly always use a 3rd party Spot Management solution, because AWS's native spot tools can produce high failure rates. This is because AWS can reclaim a Spot instance at any time which limits the use of Spot to non-mission critical applications.
Spot Management from some 3rd parties offer intelligent failover between Spot and On-Demand. You also do not need pre-defined allocations of On-Demand vs. Spot. And, when the orchestrator detects an active Reserve Instance, it will avoid moving the instance to Spot for maximum savings overall.
Marginal cloud cost analysis allows you to map your cloud costs to products, features, teams and customers ideally without tagging. Measure how the activities that relate to the goods or services you provide impact your cloud costs and other metered services. You can finally figure out your true COGS on the cloud for better planning, decisions and scaling.
Know your real-time costs, up to the latest hour with providers that have a cost model can measure your real-time running costs. While your application and engineering team works around the clock, the AWS cost report has always had long delays. That's why having a real-time running cost feature that allows you to know your AWS spend in real-time before and between the bill can be useful.
Have you ever wondered what your AWS bill would look like on GCP or Azure and vice versa? It's incredibly difficult to compare costs between different cloud providers. Some providers can map your costs to other clouds to see what your cloud costs and take into account availability, quality of service and efficiency.
Get your analysis and insights directly integrated into your preferred dashboarding tools, like Grafana, or one that's vendor-provided, so you can quickly filter alerts, visualizations, and other types of data. Drill into your data how you want to by tags, service, region, container, etc. Ideally, you can look at your spend velocity in 1-hour to weekly intervals, and virtually any perspective on cost you should be available to you.
Integrating cloud cost management into your developer workflow is key, so you'll want to receive alerts and periodic reports in Email, Slack, and other tools for incidents.
For obvious reasons, Finance will ask your team to forecast cloud spend and keep cloud budgets under control. A vendor that can provide tightly-fitting forecasts is great to have. They should provide forecasts updated regularly for your next hour, day, week, month, quarter, or even year of AWS costs.
Root cause analysis ties in your deployment and business data effectively to find out if a spike was caused because of a bad deployment, increase in business/traffic, or a bug in your code. When things don't work, dollars keep burning while you find a fix. Why should you have to wrangle information from disparate teams, services and tools to get a timely answer? That's why vendors that make it super easy to tie your events from any deployment or CI/CD tool (e.g.: Jenkins, CloudFormation, Terraform, GitHub Actions) as well as business data to AWS cost anomalies are worth considering.
Accidents happen. Some vendors offer powerful anomaly detection without the complex setup and use machine learning to help detect anomalies in real-time so you can find mistakes and resolve them before they rack up your bill. In a complex environment with countless deploys every day, it's easy for anyone to push bad code. While it's easy to find out when your service is down, partly because of autoscaling, it's difficult to find out if you're accidentally overspending on resources. Some vendors use machine learning and collect state changes from CloudWatch to help detect anomalies in real-time. In these kinds of setups, you can usually find mistakes and resolve them before they rack up your bill.
The perfect mix of AWS Reserved Instances and Savings Plans is hard to achieve without a dedicated tool. A few cloud cost management vendors offer to instantly find the perfect blend of reserved, savings plans and on demand instances, by continuously monitoring your instance workloads. They can also monitor the instance marketplace to present arbitrage opportunities with cheaper instances on shorter commitments. This includes EC2, RDS, DynamoDB, Redshift, Fargate, and more. You'll free up engineering and finance resources calculating and coordinating what type of instances, when, and how much you need to buy.