December 2024 - Cloudlytics

As cloud adoption grows, so do cloud costs. For businesses operating across multi-account setups, managing and optimizing cloud spend can become a daunting challenge. Visibility gaps, lack of accountability, and unoptimized resource utilization can lead to spiraling costs that threaten innovation and profitability. This is where FinOps (Cloud Financial Operations) steps in, helping organizations bring financial accountability to the variable spending model of the cloud.

If you’re looking to kickstart a FinOps practice in your organization, AWS Native Services provide a strong foundation. Coupled with SpendEffix by Cloudlytics, a comprehensive Cloud FinOps platform, you can establish a streamlined, scalable, and transparent FinOps strategy.

Why FinOps Matters in a Multi-Account AWS Setup

Operating in a multi-account AWS environment has its advantages—better resource isolation, improved security, and tailored access controls. However, it also introduces complexities in managing costs, such as:

Limited visibility into how resources are being consumed across accounts.
Difficulty in aligning spend ownership to respective business units or teams.
Challenges in optimizing resource utilization and curbing waste.

An effective FinOps practice addresses these challenges by enabling organizations to:

Gain granular visibility into cloud spend
Optimize costs through actionable insights.
Implement showback or chargeback models for financial accountability.

Cloud Cost Visibility vs. FinOps: What’s the Difference?

Aspect	Cost Visibility	FinOps Maturity
Goal	Understand current spend	Optimize cloud investments aligned to business goals
Tools	Cost Explorer, CUR reports, dashboards	Budget automation, anomaly detection, optimization workflows
Users	Cloud Ops, Finance	Cross-functional: Engineering, Product, Finance, Procurement
Insights	Reactive (what happened?)	Proactive (what should we do now?)
Scope	Cloud billing	Cloud usage, unit economics, team accountability
Maturity	Static reports	Continuous improvement loops (Inform → Optimize → Operate)

Cost visibility is foundational — but not sufficient to drive a FinOps culture. Companies need to move beyond visualizing spend and towards influencing how cloud is used.

AWS Native: Cloud Intelligence Dashboards

AWS offers an excellent first step with its Cloud Intelligence Dashboards (CID), powered by:

AWS Cost & Usage Reports (CUR)
Amazon Athena for querying usage data
Amazon QuickSight for dashboarding

These dashboards — including CUDOS, KPI, and Budgets — give Finance and CloudOps teams curated insights to:

Break down costs by service, account, or tags
Visualize usage trends and anomalies
Track RI/SP coverage and unused commitments

📌 Get started with AWS Cloud Intelligence Dashboards:
https://catalog.workshops.aws/awscid/en-US/dashboards
(Credit: AWS Well-Architected Labs)

How it works?

QuickSight Dashboard Sample

Why SpendEffix Kickstart is the Next Logical Step

As organizations scale their cloud footprint, cost visibility must expand to governance, automation, and accountability. This is where SpendEffix Kickstart becomes essential.

SpendEffix builds on the foundation of AWS native dashboards and delivers a SaaS layer purpose-built for mature FinOps practices.

A Cloud-Native + SaaS Powered FinOps Stack

Here’s what a modern cloud financial operations stack could look like:

AWS Native Layer (Foundation)
1. CUR → Athena → QuickSight
2. Cloud Intelligence Dashboards (CUDOS, KPI, Budgets)
SpendEffix Kickstart Layer (FinOps Accelerator)
1. Unified multi-cloud view
2. Pre-built dashboards for CFO, FinOps, and Engineering
3. Automation workflows for cost cleanup, commitment planning
4. Slack/MS Teams/ITSM integrations
Strategic FinOps Ops Layer
1. FinOps maturity scoring
2. Savings realization tracking
3. Forecasting, variance analysis, showback

Closing Thoughts

If you’re an organization starting your FinOps journey — start with AWS native dashboards. But if you’re seeking:

Deeper accountability across teams
Multi-cloud visibility
Tangible savings tracking
FinOps operations at scale

Then SpendEffix Kickstart offers a ready-to-use solution to bridge that gap.

You don’t need to build from scratch. You need to extend and accelerate.

Resources:

Interested in seeing how you can get better ROI on your Cloud Spend with SpendEffix?

Introduction

Modernization is key to staying ahead in the ever-evolving landscape of cloud security and compliance. At Cloudlytics, we continuously innovate to deliver a seamless customer experience. As part of this commitment, we recently embarked on a critical backend migration—upgrading from Java 8 to Java 17. This move was pivotal for improving performance, ensuring security, and future-proofing our platform. What initially seemed daunting was completed in record time, thanks to Amazon Q.

Why the Migration?

Enhanced Performance: Java 17’s modern features promise better runtime efficiency.
Security Updates: Java 8’s end of public updates posed a risk. Java 17 offered advanced security patches.
Long-Term Support: As an LTS release, Java 17 ensures stability for years to come.
Scalability: With new features like sealed classes and record types, Java 17 aligns with our vision of building a scalable platform.

However, the migration’s complexity was significant, involving 40+ backend modules, 100+ APIs, and a codebase exceeding 4 million lines of code.

Challenges We Faced

Complex Code Base: Transitioning a large, interconnected codebase required careful handling of dependencies and library upgrades.
Stringent Timelines: Initial estimates predicted a six-month effort, requiring significant resources.
Comprehensive Testing: With security and compliance at the core of our business, thorough testing was non-negotiable.
Resource Constraints: With a lean team, balancing the migration alongside ongoing operations was a challenge.

The Amazon Q Advantage

To address these challenges, we partnered with Amazon Q. These AI-powered tools streamlined the migration process by automating code analysis, refactoring, and testing.

How Amazon Q Helped:

Automated Refactoring: Amazon Q analyzed our Java 8 codebase, identified incompatible patterns, and suggested optimized replacements for Java 17.
Regression Testing: The tool provided comprehensive validation to ensure performance and stability post-migration.
Resource Optimization: With Amazon Q’s assistance, the project required only 2 developers and 1 QA engineer, compared to a larger team initially planned.

Results Delivered in Just 6 Weeks

With Amazon Q, we achieved remarkable results:

4x Faster Migration: Completed the project in 6 weeks, compared to an estimated 6 months.
Performance Gains: Applications now leverage Java 17’s modern features, resulting in better runtime efficiency.
Stronger Security: Deprecated APIs and vulnerabilities were addressed, enhancing the overall security posture.
Cost Efficiency: Reduced resource requirements and minimized operational costs while maintaining quality.

Business Impact

The migration positions Cloudlytics as a more robust, scalable, and secure platform. Our customers now benefit from improved performance and security, reinforcing our commitment to delivering cutting-edge cloud security and compliance solutions. This success also showcases the power of combining human expertise with automation tools to tackle large-scale modernization projects efficiently.

Conclusion

Migrating from Java 8 to Java 17 was not just a technical upgrade; it was a step toward redefining how we deliver value to our customers. With the support of Amazon Q, we turned a complex, resource-intensive project into a streamlined success story.

As we continue to innovate, this migration is a testament to our dedication to providing our customers with a modern, secure, and future-ready platform. Stay tuned for more updates as we evolve and enhance Cloudlytics to meet the demands of tomorrow.

Month: December 2024

Why FinOps Matters in a Multi-Account AWS Setup

Cloud Cost Visibility vs. FinOps: What’s the Difference?