Maximizing Your Azure Investment: Tips and Best Practices
Maximizing Your Azure Investment: Strategies for Getting the Most Out of Your Cloud Spend
6 min read
Table of contents
- Leverage free training resources.
- Automate deployments with templates and scripts
- Understand what you are getting for your money.
- Design for performance and availability
- Leverage fault domains for cloud resiliency
- Deploy your application to multiple regions within an Azure region group
- Monitor resource utilization and costs in detail, including tags.
- Use auto-scaling to scale out or in based on application demand
- Take advantage of Azure's per-minute billing granularity to reduce costs during off hours.
- Shut down dev/test environments to save money during off hours.
Most businesses are looking to optimize their Azure investment but don't know where to start. This article will walk you through tips and best practices to help your business save money on Azure.
Leverage free training resources.
Azure has a lot of free training resources. It also has a lot of free resources for your test environment and development projects, including the following:
Azure credits to get you started with your first application in minutes
Free SQL Database Developer subscriptions that provide 1 TB of storage and up to 1 million rows per table
Free managed services such as Cosmos DB, Log Analytics, and Application Insights
Automate deployments with templates and scripts
Templates can be an excellent way to automate deployments if you have many instances to manage or deploy similar applications across different environments. You can use them to deploy one or more samples (or groups) of the same application. Templates also allow you to specify specific settings for each deployed model using the template.
If you want to save yourself time and effort by automating your deployment process as much as possible, consider creating templates that represent different types of servers within your environment — for example, web servers or database servers — and use these in conjunction with scripts that perform manual tasks such as assigning DNS names and configuring server roles. This allows for greater flexibility when scaling up an application's infrastructure over time because it eliminates many manual processes; however, it may require more technical knowledge than other methods discussed previously.
Understand what you are getting for your money.
For example, if you want to host a website on Azure, you can choose from several SKUs that provide varying computing, memory, and storage capabilities. If your website is not very popular or does not generate a lot of traffic, then using the free tier will be sufficient to get it up and running. But if your site attracts millions of visitors daily, you'll need to consider upgrading your subscription plan before things break down due to increased load.
Understanding what each Azure SKU provides is essential because it helps determine whether or not the package fits within your budget while ensuring that the infrastructure has enough resources available for whatever workloads need to be hosted there.
Design for performance and availability
For example, suppose a system has multiple nodes that are required 24/7 (such as an e-commerce website). In that case, the design should protect against failures of individual nodes by using replicas or replication so that there is always one copy available. This can increase costs because more resources are being used and might also limit performance due to I/O contention on read replicas or other bottlenecks in the system. By contrast, if an application doesn't need high availability but does require breakneck speeds (for example, video streaming), then replicating data across multiple regions might be more expensive than just buying a machine with more RAM or CPU cores in each area where most of your customers live; however this may result in better overall user experience since users won't see any lag when accessing content from any location where they live (even though some replicas may not be used).
For designers to make these decisions correctly (and ultimately drive down costs), they must first understand their applications' requirements to make informed choices about how best to implement them efficiently while still meeting those needs.
Leverage fault domains for cloud resiliency
Fault domains are a way to isolate failures. If an entire fault domain goes down, you can continue operating in another, so your application or service will remain available despite hardware failure. You can use fault domains for various purposes: for instance, you can group virtual machines into multiple fault domains based on their physical location (such as in different availability zones). This strategy helps protect against hardware failures by isolating individual failure scenarios by holding limited resources (VM instances) within each fault domain.
Deploy your application to multiple regions within an Azure region group
To maximize your Azure investment, you can deploy your application to various areas within an Azure region group. You can use this capability for disaster recovery, high availability, and business continuity.
Monitor resource utilization and costs in detail, including tags.
When using Azure, monitoring resource utilization and costs in detail is essential. Price, performance, and availability monitoring should be done in real-time across all resources and regions. Here are some tips:
Use tags to track what you spend your money on. Tags are available for the services: App Services (web apps & mobile apps), virtual machines (VM), storage accounts, databases & SQL Databases, Cosmos DB & Geode databases. You can add up to 50 tags per resource type; each tag has a maximum length of 512 characters.
Use tag expressions when assigning multiple values from another field to a single tag value to see how much each resource costs across different teams or business units within an organization.
Use auto-scaling to scale out or in based on application demand
Autoscaling can be used to scale out or in based on application demand. For example, you can use autoscaling to reduce costs by stopping and starting virtual machines (VMs) based on your application's usage patterns. This is especially useful at night when there is less activity.
In addition, autoscaling allows you to automatically add more VMs when your application requires additional capacity. For example, if all the VMs are busy processing incoming requests, then Azure will automatically deploy new instances of VMs as the load requires.
Take advantage of Azure's per-minute billing granularity to reduce costs during off hours.
You can reduce your Azure bill by taking advantage of per-minute billing granularity. Per-minute billing allows you to define and specify the amount of time that should be billed for each virtual machine instance that runs on Azure models, which means you only pay for what gets used.
For example, if the VM is running, but you have no users connected to it and no website for some time (at night or on weekends), those costs will be zeroed out and won't even appear in your monthly invoice. This can save significant money if applied correctly, especially when combined with other cost optimization techniques like spot pricing discounts or reserved instances, as described above!
Shut down dev/test environments to save money during off hours.
You may be surprised to learn that shutting down dev/test environments during off hours can save money. Dev/test environments are often used for development and testing, not production. They are typically unnecessary 24 hours a day, seven days a week, so it makes sense to shut them down when they're not in use. This can help lower your Azure bill by as much as 80%.
Shutting down dev/test environments is easy. All you need to do is create an automation rule that shuts them off every night at midnight local time and then turns them back on again at 6 am local time each morning of the following day (and repeat). If you work for another business during the day, this might mean adding an extra hour or two so your rules don't turn on the environment too early or late in the morning—but it's still relatively simple!
Most companies start their journey with Azure by leveraging free resources and learning. Once you've built a solid foundation, you can look at templates, scripts, and other automation tools to help improve your deployment process. We also recommend automating as much monitoring as possible to ensure the high availability and performance of your applications running in Azure.