Cost Optimization for the Cloud Tech Stack
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This article was contributed and written by Intel.
Cloud technologies offer companies of all types and sizes the potential to scale rapidly with relative ease. They also have a democratizing effect: Cloud technologies make the same infrastructure and services available to everyone, not just large corporations with enormous IT budgets.
However, cloud technologies are not free, and can even become unaffordable when used without adequate consideration. Cloud users—regardless of the size of their enterprise—need to understand and optimize their cloud spending. Running applications in the cloud with lower associated costs enables businesses to scale up, reach more users, and generate more profit.
Cost optimization consists of multiple layers of analysis and action. To get started, teams need to determine where the costs are coming from and what changes will make the greatest impact. Adding visibility to costs through APM tools either from the cloud provider or third-party vendors will enable a team to understand how and where costs are increasing and focus their attention on specific challenges.
In many cases this starts with better cloud hygiene. Examples of this are eliminating idle resources, perhaps a dev environment that is not used at night, and rightsizing instances. This first step ensures that simple excess costs are eliminated with minimal impact on the workload of the team.
Additionally, more complex layers of optimization can be carried out by applying performance analysis and more granular observability to the application. By engaging with optimization at this more in-depth level teams are able to target more complex cost increases while gaining greater application performance and improved user experiences.
This article will discuss cost optimization best practices across the entire cloud tech stack. It will offer money-saving suggestions for every step of the cloud journey, broken down into five stages from cloud beginner to cloud native.
No organization becomes cloud native overnight. Instead, they go through a series of stages with changing levels of cloud integration. Let's take a look at each of these stages and best practices for cost optimization.
Nowadays, every company needs to go digital. There are a number of reasons for this, including the capacity to reach more users and the high costs of running in-house IT infrastructure. Most organizations start their cloud journey by migrating a couple of their applications to cloud providers. The organization's cloud journey begins in earnest when these applications run flawlessly in the cloud.
The cost of running applications in the cloud will eventually rise when the business experiences success and has an influx of new users. However, this cost increase is mitigated by the increased revenue generated by the new users. Applying some simple cloud-native best practices can further improve cost efficiency:
- Build a cloud-native team with a DevOps mindset to use cloud services more effectively and efficiently.
- Modernize applications to make them cloud native before deploying them to the cloud. The modernization process includes creating smaller microservices with low overheads and integrating them into the cloud services.
With company success comes the need to scale. One side effect of this is the rise in an application's cloud bills, which can become a significant line item in the company budget. This is an important time to check which applications are running up high bills in the cloud budget and why. The main task in this stage is to track the costs for teams, environments—production, development, staging—and applications, ensuring cost visibility and transparency over the entire organization. FinOps is the current industry practice that creates a shared responsibility for cloud costs. In this framework, finance, IT, and DevOps groups collaborate together, with minimizing cloud costs as their primary concern.
Cloud is a pay-as-you-go model, so applications that consume more resources will cost more while they are running in the cloud. Thus, the standard approach in this journey stage is to use cloud profilers or open-source environment agnostic profilers such as Granulate's code profiler to gather resource consumption such as CPU, memory, or bandwidth.
When the applications are in the cloud, and part of their costs have been traced back to their uneconomical users, the next stage is to continuously monitor cost-related concerns and take appropriate action. There are two key approaches to this stage:
- Cloud hygiene: Frequently check cost-related metrics to prevent overspending and keep your expenses healthy—a similar concept to frequently washing your hands to avoid diseases and stay healthy.
- Rightsizing: Find the right instance types for your workload performance. Rightsizing consists of three steps: analyzing performance metrics; finding bottlenecks and ensuring efficiency; and updating infrastructure resources by upgrading, downgrading, or terminating a specific cloud resource.
If Kubernetes is a part of your cloud landscape, cost management becomes even more complex because of the additional layer of abstraction that it brings. For this reason, Kubernetes-native tools for cost optimization are available to bring down expenses specifically related to Kubernetes. One such tool is Granulate's Capacity Optimizer, which can reduce Kubernetes costs by up to 60% with autonomous actions and rightsizing, eliminate overprovisioning, and ensure optimal performance while offering complete visibility into Kubernetes clusters.
The next step in the journey to cloud native is to make cloud optimization a continuous process. In modern cloud native and agile software development, applications regularly undergo updates and, as a result, transformations. This means that even if you trace an application's costs, optimize its performance, and pick rightsized instance types, frequent application updates will render past optimizations irrelevant and therefore ineffective. When cost optimizations become irrelevant, applications will consume an unanticipated amount of resources and potentially incur high costs due to waste yet again. Successful cloud cost optimization can only be achieved by treating optimization as a continuous process, rather than a one-off event.
Continuous cloud optimization is a serious but worthwhile task requiring technical knowledge and deep cloud expertise. Granulate can make the optimization process more straightforward thanks to its quick and easy deployment that removes the need for R&D efforts. Granulate is a cloud native autonomous and continuous workload optimization solution that can improve application performance and cut costs by up to 63% without any changes to the application's code.
The final stage in the cloud journey is becoming a cloud company. At this point, a business already understands that the cloud is an indispensable part of its infrastructure and business operations. Becoming a cloud company requires a unified, holistic approach to creating governance and KPIs beyond stability and availability.
At this stage, best practice is to keep all workloads in the cloud without any exceptions, and to use the cheaper machine types with spot and preemptive instances in order to benefit from all available cloud provider options.
When a company embarks on its cloud journey, it will quickly become apparent that becoming a cloud-native company requires significant effort, including in the realm of cost management. There are many tools on the market that can help with optimizing costs or creating budget suggestions—that is, on the surface level.
Getting serious about optimization has historically required manual engineering efforts, which, ironically, incur their own costs. Today, cost optimizations can be continuous and automated, maximizing their effectiveness and the company's efficiency.
Granulate leverages the benefits of automation and continuous cloud optimization, allowing you to keep up with the dynamic nature of the cloud. Join Granulate's weekly live demo or talk to an expert now, and explore how you can optimize your application's performance while reducing costs.