Azure cloud cost optimization
According to Flexera’s “State of the Cloud 2023” report, for the first time in a decade for over 80% of companies, managing cloud spend has become a greater challenge than security.
The Microsoft Azure platform offers organizations, regardless of industry or business challenge, endless opportunities to scale their IT environment and cost savings. However, to effectively leverage these opportunities and reduce expenses, it is worthwhile to reach for 10 proven and effective practices.
10 best practices for optimizing Azure cloud costs
- Accurate Size and Performance Analysis of Virtual Machines
Before you throw yourself into the Azure cloud, consider what kind of computing power and instance size you really need. Avoid excessive computing power choices, which can lead to unnecessary costs.
- Use of SPOT and B Series Virtual Machines
SPOT and “b-series” virtual machines may be a good alternative to traditional services. The difference between standard virtual machines and b-series ones is that in case of the latter computing power is adapted to the current needs of the application, which allows for cost savings. SPOT, on the other hand, is a Microsoft Azure cloud service that allows you to run virtual machines in “spot instance” mode, i.e. only when free resources are available in the cloud. This allows you to save on expenditures because the prices for using VMs in “spot instance” mode are lower than for running VMs in a standard way.
- Monitoring and Disabling Unused Resources
An extremely important part of cost optimization is to regularly monitor the use of resources in the Azure cloud and consistently shut down unused elements, such as virtual machines, databases, or data stores. This operation can be performed manually but can also be automated using tools such as Azure Automation or Azure Logic Apps.
- Database Instance Optimization
Database instances in the Azure cloud can be costly, especially if they are used suboptimally. To minimize costs, consider using elastic database pools that allow you to automatically scale up and down as needed. You can also consider using the Azure SQL Database Managed Instance service, which offers lower costs compared to traditional database instances.
- Advanced Use of the Autoscaling Function
Advanced use of the autoscaling feature in the Azure cloud allows resources to be automatically sized according to the workload of an application or service, minimizing unnecessary costs. Combining this feature with SPOT and B-series VMs will contribute to additional cost reductions. Advanced autoscaling options, such as scheduling or application metrics, enable precise optimization of resource utilization and effective cost management.
- Application of Reserved Instances
The use of proprietary installations allows the purchase of a predetermined resource for a long period of time. This provides significant savings compared to paying for resources on a pay-as-you-go basis. Proprietary instances are particularly advantageous for stable and predictable workloads.
- Effective Cleaning of Backup Copies and Computing Instances
Managing backups and computing instances on a regular basis will allow you to avoid accumulating unnecessary costs. Set policies for storing backups, delete those that are no longer needed, and control the number of active computing instances to maintain an optimal balance between availability and cost.
- Full Control and Costs Visibility
Keeping costs under control and planning wisely should come at the beginning of your cloud adventure. Give yourself full control and visibility over costs by using the monitoring and reporting tools available in the Azure cloud. Regularly analyze your cost reports, identify areas where you can make savings, and adjust your strategy based on the information you gain to avoid hidden cloud computing costs that affect your bills.
- Effective Monitoring of Data Transfer
Control and analyze data transfer between different services and regions. Implement strategies to minimize unnecessary data transfer by using local copies or CDN (Content Delivery Network). Optimizing data transfer can significantly contribute to reducing costs associated with cloud services.
- Prioritizing Testing and Optimization of Application Code
The practice involves conducting regular performance tests and optimizing application code before moving it to the Azure cloud. Improving code efficiency can significantly impact resource consumption, which translates into lower operating costs. Reliable testing and optimization before migrating to the cloud avoids unnecessary expenses related to sub-optimal use of resources.