Integrating Optimization into Your Cloud Journey
Last week, I had the privilege of presenting live to an audience of AWS re:Invent attendees, as well as those who watched the broadcast across the event hotels in Las Vegas. This was the largest crowd I ever presented to, so I was a bit nervous, but then felt the amazing impact in no time.
Watch the video below or read on for my recap:
The cloud does not offer a one-size-fits-all model. Instead, it is highly configurable, with many services and configuration options. Therefore, using the cloud without optimization could bring more harm than good to companies in terms of money, service disruption, and reputation. This article will focus on the cloud-native journey and discuss optimization at each stage to achieve more while becoming a cloud-native company.
In this recap you will learn how to:
- Understand your cloud journey pyramid position
- Evaluate your current “Sweet Spot”
- Integrate automated optimization
- Save costs and improve application performance
Maslow in a Cloud-Native World: DevOps Hierarchy of Needs
Maslow’s hierarchy of needs helps us understand human needs by delving into the motivations for human behavior.
Using this approach, it is possible to draw a pyramid with five essential stages to explain DevOps requirements:
- Physiological needs are related to survival in the cloud, such as setting the infrastructure and making some applications run in the cloud.
- Safety and performance security ensure that companies feel safe in the cloud as their applications run smoothly with complete functionality.
- Love and belonging is when the cloud is adopted within the company, and a secure relationship is achieved. In this stage, both horizontal and vertical scaling is seen. More applications are transferred to the cloud, while those already running in the cloud receive more traffic and scale up.
- Self-esteem is where people and teams build affection and respect for the technology and processes as these bring more reliability. It is the stage where most organizations integrate their quality management and cost optimization into cloud operations.
- Self-actualization, at the top of the pyramid, is where companies know their requirements, understand their potential, and reach it with the help of cloud technologies. Automation ensures that the massive scale-up is managed well, while continuous optimization makes the whole software stack work efficiently.
The critical part of this stage is the automation and continuous improvement that is not offered in most of the monitoring platforms in the market. Granulate ensures that companies reach and stay at the top of the DevOps pyramid of needs. With real-time continuous optimization, it solves the growing performance optimization challenge and enables self-actualization for companies.
When the companies reach the top of the pyramid, they become cloud-native regarding their software development mindset, processes, technology, and automation. However, the cloud is not free and could be highly pricey if it is not managed well.
Finding Your Cloud Sweet Spot
The hierarchy of needs is highly related to your cloud bill. The very first applications running in the cloud will not be costly. However, if applications are scaled up and managed poorly, cloud costs will rise fast. Let’s integrate cost with the pyramid of needs:
In the chart, the x-axis represents cloud adoption in terms of a hierarchy of needs. And the y-axis shows the size of the infrastructure, namely the cost of the cloud. Self-actualization and optimization stages ensure that the sweet spot is achieved where you gain the most from cloud services while paying the optimal amount of money.
However, drawing a single chart and defining a single “sweet spot” is not meaningful since every organization is different in terms of organizational needs, cloud adoption, and budget:
In addition, the optimal point is open to variations in dynamic environments, such as software updates, upgrades, or seasonal usage changes. Therefore, automation and optimization in the cloud are more than a single-time task; they constitute a continuous process.
Optimization Process: Methodology and Practices
Optimization in the cloud can be divided into four main phases with different focuses.
This is the first phase, where cloud costs and applications are tracked and monitored. From the cost side, tracking overhead cloud costs to specific applications and teams is essential. From the monitoring side, application performance monitoring (APM) tools ensure that performance is tracked for potential enhancements.
The second phase, awareness, is where organizations realize that cloud costs can be hefty. This perception leads to discovering savings plans, reserved instances, and spot instances; these are cost-reduction methods based on selecting cheaper ways of implementing cloud services.
This third phase is when FinOps comes to the table, and teams share the responsibility of cloud costs. In this stage, cheaper machine types are selected, and rightsizing methods are implemented. Rightsizing ensures that the instance types of machines are chosen according to their workload performance and capacity requirements.
Finally, in the optimization phase, more and more applications move to the cloud, and configuration options are exhaustively tuned. In addition, contract negotiations with cloud providers are undertaken to gain from economies of scale.
Cloud cost optimization is a complex process that includes some critical challenges, such as resource exhaustion and diminishing returns. However, in the end, organizations reach a new and better “sweet spot” with less cost, improved performance, and efficient usage of cloud services. However, in order to combat the challenges and achieve the desired goal, new solutions and technologies are required.
Integrating Granulate into Your Cloud Journey
Granulate is a cloud-native performance monitoring and enhancement platform capable of learning, optimizing, and reducing costs. The critical feature of Granulate is its quick and easy deployment with minimum R&D efforts required. It enables comprehensive optimization that reaches 63% in terms of application performance and cost cuts.
Granulate implements a four-stage circular process to incrementally enhance overall efficiency:
- Automatic analysis to learn application resource usage and data flows
- Continuous optimization to tailor OS-level scheduling and prioritization decisions such as CPU, network, and memory
- Performance improvement to reduce response time and increase the throughput of the whole application stack
- Cost reduction with leveraged performance and reduced cluster size, as well as downsized resources
With its innovative approach and continuous optimization, Granulate unlocks further opportunities for you to achieve a new optimum sweet spot.
Get started now, and start your cloud-native optimization journey with Granulate!