Businesses often face difficulties whenever it comes to managing operational expenditures, but with the rise of cloud-based IT infrastructure, it has become easy for them by scaling usages as per business resources-based demands. Cloud-based platforms are considered to be the best platform benefiting businesses that often get frequent variations in customer demands. In order to meet such variable demands, businesses need to continuously observe cloud services utilization, performance efficiency, and billing scales.
Well, there are various cloud platforms available, such as AWS, Microsoft Azure, Alibaba cloud platform, and many others, but in this article, we’ll dive into Google Cloud Platform services and their approaches to measure service costs.
Brief About Google Cloud Platform (GCP):
Google Cloud Platform is a type of public cloud infrastructure, also known as G-suite of cloud services such as data storage, computing, data analytics, and machine learning, that runs on the same infrastructure where Google is running its other end-user products.
Even though Google Cloud provides support and guidelines to customers for managing their cloud operations expenses, but there are some areas where most people tend to miss. So, in this article, we’ll uncover the common mistakes and some tricks to optimize resources and performance to get the best cloud service outputs at predicted costs.
Before, we start listing the best practices for cost optimization of GCP. Let’s first understand the measures for billing.
How Does Pricing Model Work in GCP?
In order to get started with GCP services, at first, you need to set up a billing account and link it with your project. GCP also allows you to link your billing account with various GCP projects so that your financial and development teams can get complete visibility over resource billing processes.
If you don’t link your GCP project with a billing account, it will still allow you to use its free services. Those services, however, have some computation-related limitations, which need some connections to make the most out of scalable services. Once it is made, Google will automatically send invoices to you as per your cloud service utilization on a monthly basis. Moreover, it provides separate invoices per project by creating sub billing accounts.
5 Best Practices For GCP Cost Management:
Understand The GCP Cost Management Tools:
Cloud utilization should be monitored closely because of its on-demand and variable nature, which can cross the predicted cost limits. To understand the cost structure and manage its utilization, Google Cloud Platform provides a set of cost management tools that can give visibility and insights to your cloud deployments.
The following steps will help to understand the working of cost management tools:
- Identify the projects, which can cost the most.
- Make a cost structure as per your business needs.
- Collect the billing reports per service in order to understand the cost structure.
- Identify the cost utilization per team.
- Design your custom dashboards to get more precise cost spending entries.
- Also, use tables, financial plans, and notifications to closely observe your spending and make some assumptions about them in particular time durations.
Pay According to Your Compute Needs:
Now that you have a better understanding of your cloud spend, so let’s identify the compute resources that suit your project(s).
- The easiest way to control your Google Cloud Platform billing is by excluding unnecessary resources. There are many cases where some businesses forget to delete deprioritized instances or projects, and that carelessness often results in larger bills. Thus, you must take the help of experts continuously analyzing and identifying deprioritized resources and optimizing them. Similarly, Google’s Ideal VM recommender helps you identify inactive VMs and active disks according to your usage metrics.
- Well, there are possibilities for some inactive VMs to become helpful in future, so delete them by considering all possible scenarios. Always keep a habit of taking a picture/screenshot of instances before deleting. Alternatively, you can also stop the VM, which will only terminate the instance than disks or IP addresses resources.
- Always schedule VMs for auto-start and auto-stop, as it can help you reduce costs by around 70% from Monday to Friday (If set to run for 10 hours a day).
- Choose custom VMs with required CPU and RAM configurations to save extra billing expenditures.
- Leverage preemptible VMs running 24 hours (or live up to), which are 80% cheaper than normal instances. They can also manage workloads like big data, media transcoding, genomics, financial simulation and modelling.
Optimize Cloud Storage Performance and Costs:
When you run services in your own data centres, it becomes difficult to do cost management because it does not have proper constraints for utilized resources and computations. In the cloud, however, both storage usages and orchestration are analyzed before billing to set cost-effectiveness. Each workload has different storage requirements; hence, you should choose the storage class by measuring computation demands from previous usage reports.
The following shows the best way to optimize storage costs and performance:
- Google Cloud Platform offers various storage classes, including Standard, Nearline, Archival, and Coldline, and each comes with its own best-fit use cases and different costs. The companies who want their computation faster with high volume workloads can choose the Standard class. But companies planning to save money can benefit the most from archival class than other classes.
- Such cost saving can be automated by enabling a lifecycle policy that chooses the class as per the workloads.
- To make a high impact on cost optimization, you also need to reduce the data duplication by using object versioning, setting the object versioning policy to automate the identifying process, and setting the bucket lock feature to avoid deletion of important duplicated data.
Optimizing Costs for BigQuery Operations:
Many organizations are considering BigQuery as a modern approach for data analytics, but they often miss the point of it being more expensive than others. Apparently, there are some ways to lower some of its computation costs. Let’s check the BigQuery environment for setting up some guardrails to manage utilization.
- Enforce the use of the Maximum bytes billed setting to limit the query costs.
- Minimize the query operational costs by partitioning and clustering your table according to entry date, timestamp, or number range column. Also, enable required partition filter to partition column whenever WHERE clause comes. With this method, you can reduce the BigQuery processing costs by 50% for each partition.
- Use streaming insert to unlock two options for loading BigQuery, either by adding jobs in batches or live streaming.
- Use flex shots:
- By default, it follows on-demand pricing according to bytes utilized by BigQuery operations.
- For high-volume, it provides requirement-related pricing.
- Recently, Google had launched Flex Slots, a combination of on-demand and flat-rate pricing, which allows buying BigQuery slots for the required duration as short as 60 seconds with monthly and annual billing options. It enables to respond quickly to queries and is cost-effective as per varying analytic demands.
Identifying Network Spending:
Continuously monitoring and reporting activities are at the core of network and security activities. But the process of identifying the network usages in an environment that is leveraging both cloud and on-premise environments can be a tough job. Although, the google cloud platform provides many tools providing clear visibility into your network usages and costs.
The following point contains some configuration changes to lower the network costs:
- Use tools like Cloud Platform SKUs and Network Topology to get comprehensive visibility on your overall GCP deployment and help in optimizing network egress cost at the regional and international level.
- If you want excellent network performance, you can choose Premium Network Service Tier. But if your requirement is just to have low-cost performance than expecting high-level performance, Standard Network Service Tier is the best option for you.
Optimize Your Google Cloud Platform Today:
When you are working on Google Cloud Platform, cost optimization and performance management are extremely crucial aspects. Most organizations want to maintain lower costs, which they can only achieve by following best practices for GCP cost management.
Want to set up your Google Cloud Platform with better cost optimization approaches? Contact us now with your requirements and get the best GCP cost optimization plan and solution in India.