Whitepaper 'FinOps and cost management for Kubernetes'
Please consider giving OptScale a Star on GitHub, it is 100% open source. It would increase its visibility to others and expedite product development. Thank you!
Ebook 'From FinOps to proven cloud cost management & optimization strategies'
OptScale FinOps
OptScale — FinOps
FinOps overview
Cost optimization:
AWS
MS Azure
Google Cloud
Alibaba Cloud
Kubernetes
MLOps
OptScale — MLOps
ML/AI Profiling
ML/AI Optimization
Big Data Profiling
OPTSCALE PRICING
cloud migration
Acura — Cloud migration
Overview
Database replatforming
Migration to:
AWS
MS Azure
Google Cloud
Alibaba Cloud
VMWare
OpenStack
KVM
Public Cloud
Migration from:
On-premise
disaster recovery
Acura — DR & cloud backup
Overview
Migration to:
AWS
MS Azure
Google Cloud
Alibaba Cloud
VMWare
OpenStack
KVM

Mastering cloud budget management: ensuring your costs stay on track

mastering cloud budget management

Cloud budget overruns are not attributable to a single root cause but rather encompass a spectrum of diverse factors. These elements combine to create a complex challenge, like a vivid array of jelly bean flavors. Consequently, devising practical strategies to mitigate these overruns requires a thoughtful and nuanced approach that recognizes and addresses the unique characteristics of each contributing factor.

Unforeseen usage patterns

In this scenario, the organization faces the consequences of its cloud success. An increasing number of unanticipated cloud projects emerge, significantly deviating from the initial budget estimates for cloud resources. While these cloud initiatives undeniably bring substantial business value, declining them is often impractical, and even if central IT attempts to veto them, the costs typically find their way into a line-of-business budget. Nonetheless, this situation can generate considerable organizational stress, primarily because the central IT or sourcing teams failed to anticipate such expenditure.

Organizations should view this as a pivotal opportunity to recalibrate their budgeting processes for the digital age. Cloud chargeback mechanisms can foster transparent cost allocation and facilitate more informed decision-making for future endeavors.

Uncontrolled expenditures

The organization often struggles to track and understand its cloud spending beyond the monthly invoices, leading to a lack of clarity regarding where funds are being allocated.

Basic cost hygiene

Addressing unregulated costs requires implementing basic cost management practices.

Bill analysis

Organizations should conduct detailed research on their cloud bills to gain insights into expenditure patterns and areas for optimization.

Cost management tools

Utilizing cost management tools is essential to track and manage cloud expenses effectively.

Enhanced visibility

Implementing tagging or partitioning discipline enhances cost visibility, making allocating and controlling expenses across different cloud projects or departments easier.

Inefficient development and testing resource utilization

In this context, developers tend to allocate resources that are larger than necessary or err on the side of overestimating their requirements. Consequently, numerous abandoned resources remain idle, and infrastructure dedicated to development and testing, which is not utilized during non-business hours, is left running without suspension. To address this issue effectively, cloud cost management tools prove invaluable by pinpointing instances of evident resource wastage. This enables organizations to take action by either shutting down or suspending these unused resources, ideally implementing automation for efficiency.

Free cloud cost optimization & enhanced ML/AI resource management for a lifetime

Lack of commitment

The organization can secure cost-saving advantages through public discounting mechanisms, such as AWS savings plans and Azure reserved instances, and through entering into contractual agreements to negotiate discounts. However, the organization has chosen not to make any commitments due to uncertainty regarding its future usage and an inability to predict its current utilization accurately. This approach inadvertently leads to excessive expenditure, universally regarded as an ill-advised strategy. For organizations beyond the initial pilot stage with established long-term production applications and some level of usage predictability, committing to resources that are certain to remain in use is advisable.

Misalignment in production resource allocation

Production environments often suffer from overprovisioning, resulting in unnecessary and excessive costs. This is particularly prevalent in on-premises setups, where resource utilization levels can be as low as 30%.

Capital expenditure (CapEx) vs. ongoing cloud costs

Underutilized resources are considered CapEx in traditional setups and can go unnoticed as long as they are within budget. However, these excess resources in cloud computing translate into ongoing monthly expenses, which demand continuous cost evaluation.

Complexity of rightsizing

While rightsizing resources in the cloud sounds simple, the practical implementation is challenging. Applications that scale vertically often cannot be easily adjusted to match their usage.

Technical and operational challenges

Implementing rightsizing can be difficult due to the complexity of application installations, the fragility of mission-critical applications, and the risk of causing downtime during maintenance.

Resource knowledge and priorities

The teams managing these applications are typically busy with other priorities, making allocating time and resources to rightsizing efforts challenging.

Frustration in cloud cost management

Organizations facing these challenges may become frustrated when they see the waste in resource allocation. Managing cloud costs in such scenarios becomes a source of frustration and helplessness.

Complex cross-functional effort

Addressing resource inefficiencies requires a complex, cross-functional effort that involves negotiation and coordination among various stakeholders.

Questioning the value of optimization

In some cases, stakeholders may ask whether the intricate process of resource optimization is worth the effort compared to simply continuing to pay a higher bill.

Excessive production resource allocation

Application teams have encountered issues related to resource allocation in production environments. Specifically, they have either failed to implement autoscaling for applications capable of horizontal scaling or overestimated the amount of headroom required for applications with variable usage patterns. This may lead to allocating excessive compute units or an overly aggressive approach to autoscaling.

Addressing this issue entails the implementation of autoscaling with careful consideration of parameter settings. Furthermore, it prompts the need for a broader discussion about the trade-offs between the costs and benefits associated with consistently higher application performance. This conversation should align with the organization’s business objectives and priorities.

Inefficient design and implementation

In cloud solutions, architects often overlook cost considerations in their designs. This oversight can lead to suboptimal design choices, and changes in application features and behavior over time may unexpectedly result in increased costs stemming from these design decisions. Furthermore, developers may inadvertently write code that performs poorly, consume excessive infrastructure resources, or generate numerous and costly calls to cloud services. In such cases, relying solely on cloud cost management tools may not effectively identify these issues.

Addressing these challenges requires a proactive approach to performance engineering, focusing on assessing the business value associated with the time, effort, and financial investment needed to rectify these issues. For many organizations, this may entail seeking expertise from a third-party specialist who can diagnose the problems and provide recommendations.

It is worth noting that the challenges connected with cloud budget overruns are often more intricate and multifaceted than they may initially appear. So then, the proper solution to these issues is inextricably linked to implementing a cloud cost management tool like OptScale that allows the maintenance of complete cloud budget transparency for each resource used in the cloud.

✔️ Hystax OptScale, a FinOps & MLOps open source platform that helps you optimize cloud costs, bring more cloud usage transparency, and unlock more significant potential in your Machine Learning capabilities, is fully available under Apache 2.0 on GitHub → https://github.com/hystax/optscale.

Enter your email to be notified about new and relevant content.

Thank you for joining us!

We hope you'll find it usefull

You can unsubscribe from these communications at any time. Privacy Policy

News & Reports

FinOps and MLOps

A full description of OptScale as a FinOps and MLOps open source platform to optimize cloud workload performance and infrastructure cost. Cloud cost optimization, VM rightsizing, PaaS instrumentation, S3 duplicate finder, RI/SP usage, anomaly detection, + AI developer tools for optimal cloud utilization.

FinOps, cloud cost optimization and security

Discover our best practices: 

  • How to release Elastic IPs on Amazon EC2
  • Detect incorrectly stopped MS Azure VMs
  • Reduce your AWS bill by eliminating orphaned and unused disk snapshots
  • And much more deep insights

Optimize RI/SP usage for ML/AI teams with OptScale

Find out how to:

  • see RI/SP coverage
  • get recommendations for optimal RI/SP usage
  • enhance RI/SP utilization by ML/AI teams with OptScale