Cloud technology usage has been witnessing a spike ever since the pandemic hit and the way the world works shifted. It is considered a more secure and flexible option versus traditional on-premise computing. With large portions of the workforce functioning remotely over the past few years, businesses adopted cloud technology at a faster clip than they may have otherwise.
While Amazon Web Services (AWS) and Microsoft’s Azure were early entrants to the cloud infrastructure market and remain market leaders, Alphabet’s Google Cloud Platform (GCP) has already made a significant dent and for good reason.
Some of the benefits of GCP are:
- It’s viewed as being more flexible and affordable in terms of pricing.
- GCP is known for its reliability and minimum downtime. The company has committed to providing 99.99% uptime for users under its Compute Engine Service Level Agreement.
- It is considered user friendly, with a simplified onboarding process.
- GCP is backed by the tech giant’s security prowess, which also attracts users.
There are several other advantages of using GCP too, which have contributed to its market success despite being a late entrant when compared with AWS and Azure. Those include its network presence, continuous expansion of network, and its large customer support base.
The biggest advantage of cloud computing, of course, is users’ ability to scale up or down quickly and pay only for whatever resources they have used. However, if businesses are not using cloud infrastructures efficiently and monitoring usage, they can end up with significantly higher-than-expected bills.
If your business uses GCP, then it’s important for you to have robust GCP optimization strategies in place to make the most out of the platform while keeping costs at a minimum. In the rest of this article, we examine seven key GCP optimization strategies you can implement to reduce GCP costs.
- Cloud cost optimization and management tools
To ensure efficient GCP usage across the board, it’s good practice to consider using cloud cost optimization and management tools. Another advantage is that GCP comes with its own set of such in-built tools and features that you can make the most out of to reduce GCP costs. Here are a few such features you should consider using to target efficient GCP usage:
- Google Cloud console – This is the exclusive interface for managing GCP resources. It allows you to manage and get insights into everything connected to your cloud application; helps deploy, scale, and manage production issues; find resources; and handle DevOps workflows on the go. While the console is used across overall cloud platform management, what makes it a good GCP cost optimization strategy is that it allows you to view detailed breakdowns of your bills and set spending budgets so cloud costs don’t suddenly creep up on you.
- Cloud Quotas – This feature allows users to set a quota, which Google defines as specifying “the amount of a countable, shared resource that you can use.” Through Cloud Quotas, you can monitor usage, create and change quota alerts, and request limit adjustments for quotas.
- Billing reports, trends, and budgeting – The Google Cloud console, as mentioned, can be used to take an in-depth look at costs. Cloud Billing Reports, which can be generated from the Billing section of the console, allow you to discover and analyse trends. You can also use Cloud Billing budgets to manage your costs, maximize cost efficiency, and reduce GCP spending. While setting budgets, you can also enable alerts so you are informed when that limit is exceeded.
- Billing export tools – To aid in GCP cost optimization, the platform also allows users to export billing data to BigQuery, its data warehouse solution. Using Looker Studio to do this, users can also visualize costs for better understanding and more efficient GCP usage.
- Build your own custom dashboards – Google suggests using labels to better trace costs back to teams and departments, and building custom dashboards “for more granular cost views.”
While these are all features that are built into the GCP interface, there are many other cloud cost optimization tools in the market. iValue, for example, also provides cloud cost optimization services.
- Right-sizing and auto-scaling resources
The advantage of cloud computing is in being able to pay only for what you need and use. However, if you are not actively monitoring it, you may end up with unnecessary or redundant resources adding to your costs. This is where efficient GCP usage depends heavily on effective resource management.
One method of doing this is by using GCP’s Compute Engine for rightsizing recommendations. This feature allows you to customize virtual machine (VM) utilization and makes suggestions that do not just enhance performance, but also reduce GCP costs by ensuring your resource allocation is optimized and not overallocated. Auto-scaling, or adjusting resources to demand, is another GCP cost optimization strategy to consider. GCP allows users to set resource scaling based on certain metrics. You can also use the platform to auto start and stop VMs, thereby reducing GCP costs.
- Preemptible VMs
Preemptible VMs are more affordable versions that can be used for non-critical usage, which can withstand disruptions. GCP’s Spot VMs are a good option for applications that can tolerate interruptions because they can reduce Compute Engine costs by up to 91%, according to Google.
- Retiring or releasing obsolete resources
Another aspect of resource management is staying on top of resources that are no longer serving any purpose, and having a plan of action to deal with them. As a first step, you should be able to identify which resources are idle, or which ones have been deprioritized, or those that have now gathered the proverbial dust and are never going to be used again. Here, too, there are tools and features built into GCP or third-party options to consider. Finding and efficiently handling these idle resources is a key GCP cost optimization strategy.
- Cloud storage cost optimization
While it is crucial to focus on compute resource optimization, it is just as necessary to implement cloud storage optimization strategies. As with compute resources, your cloud storage needs are also dynamic and will keep evolving with time. Ensuring you are cognizant of these changing needs and paying attention to storage utilization can help in reducing GCP costs. GCP offers different storage classes — standard, nearline, coldline, and archival — at various costs. Although you choose a class when you first set your environment, you do not need to stick to it. GCP gives you the option of changing it and automating the process too.
- Monitoring, logging, and data warehousing
Often, enterprises have both cloud and on-premise environments to manage. While this makes monitoring and logging even more important to ensure efficient management, it can also pose challenges in terms of volume and visibility. GCP comes with its own set of features and tools to tackle this, including Cloud Platform SKUs, Network Topology, and cloud logging.
The advantages of using BigQuery are many. It is a useful data warehouse and analytics platform but certain configurations may prove to be more expensive than others. The more data you query through it and the more data you store, the higher your costs can be. So, optimizing query and storage costs is key when it comes to using BigQuery.
- Commitment discounts
Finally, as with any cloud service provider, its good practice to be on the lookout for long term and spend-based commitment discounts to recue GCP costs and gain the most out of it. Long-term commitment discounts are those that incentivize users who sign up for a cloud platform on an extended basis. Spend-based commitment discounts, as the name suggests, are linked to an agreed amount in expenditure on cloud resources within a defined timeframe.
Cloud cost optimization is poised to continue gaining importance as more and more enterprises turn to cloud computing. Making the most out of any cloud platform, including GCP, requires implementing robust cost optimization strategies.
