The Benefits and Limitations of Google Cloud Recommender Service

While there are opportunities to cut costs in the cloud, it’s also easy for costs to spiral out of control, especially as cloud environments become more complex and span multiple platforms.

In fact, without cost optimization, research firm Gartner has found that organizations could be overspending by more than 70% in the cloud.

Google Cloud’s recommender service is an often under-utilized tool that can help optimize cloud resources—helping to cut costs, but also to improve performance, reliability, and other critical factors.

How Google Cloud Recommender works

There isn’t just one recommender; each recommender provides usage recommendations for different Google Cloud resources, specific to a single product and resource type. So, one product could have multiple recommenders. For example, there’s a BigQuery slot recommender for on-demand workloads and a BigQuery partitioning and clustering recommender.

You’ll find the Recommendations Hub on the Google Cloud Console, part of Google Cloud’s Active Assist portfolio. Each recommender will generate recommendations (via machine learning) to optimize cloud resources, along with insights to help you see patterns in resource usage.

These fully automated recommenders assess resources on Google Cloud and make recommendations on everything from workload costs, to performance, reliability, manageability, and security—including the steps required to take action and what benefits you’re expected to see. It does this through machine learning, based primarily on recent workload usage.

You can apply recommendations manually, or you can hit the ‘Apply’ button to automatically make the recommended changes to your workload. For example, you can hit ‘Apply’ to resize virtual machines to more efficiently use instance resources and potentially lower costs. 

However, before you hit ‘Apply,’ it’s important to do a proper assessment. A human reviewer should assess the impacts of the recommendations to your infrastructure and to the business to ensure there won’t be issues with system performance or loss of required permissions.

You can also export recommendations to BigQuery (since there could be literally hundreds or thousands of recommendations to sort through). From there, you can build dashboards to regularly analyze cost insights.

Limitations of Google Cloud Recommender

While this service provides useful guidance (especially when combined with BigQuery), you shouldn’t necessarily follow any recommendations blindly. Rather, combine them with other methods, including human expertise and judgment, to get a broader picture.

While Google Cloud Recommender can be a useful tool in your cloud FinOps toolbox for identifying possible optimizations that could save you money, keep in mind that recommendations don’t consider your cloud environment from a holistic standpoint, nor do they consider long-term trends.

So while they can help with specific workloads, they aren’t necessarily going to help optimize your entire cloud environment. And they won’t make recommendations that involve moving to different clouds or taking a multi-cloud approach.

Taking a more holistic approach

Using a powerful combination of advanced data analytics, AI/ML tools and deep human technical and business expertise, Pythian’s FinOps service delivers a unified, multi-cloud approach to cloud cost management across all major cloud providers, including Google Cloud, AWS, and Azure.

Our FinOps service can offer immediate, and often substantial, cost savings—in fact, it generates an average monthly cloud cost savings of 20 to 35%. We do this by identifying, interpreting, and enacting cloud savings opportunities and architectural efficiencies across your entire cloud ecosystem to maximize the business value of your cloud spend.

You’ll also have access to a dedicated Cloud Advisor, who will help you manage, report, and interpret your cost and usage data so savings are maximized and continuity of care is maintained, all while ensuring business goals are met.

Google Cloud Recommender is a useful FinOps tool, one that is often under-utilized. But it should be one tool in your FinOps toolbox, so you can take a more holistic approach to cloud cost optimization across your entire ecosystem.

Want to optimize your cloud costs in Google Cloud—or across your entire cloud ecosystem? Contact us info@pythian.com.