4 posts tagged with "finops"

Cloud computing has revolutionized the way we build and scale applications. But with great flexibility comes the challenge of cost control. Without governance, costs can spiral due to idle resources, over-provisioned instances, unnecessary data transfers, or underutilized services.

This guide outlines key principles, actionable steps, and proven strategies for optimizing cloud costs—whether you're on AWS, Azure, or GCP.

Why Cloud Cost Optimization Matters#

• Avoid unexpected bills — Many teams only detect cost spikes after billing alarms go off.
• Improve ROI — Optimize usage to get more value from your investment.
• Enable FinOps — Align finance, engineering, and ops through shared accountability.
• Sustainable operations — Efficiency often translates to lower energy usage and better sustainability.

Learn more from FinOps Foundation

Step-by-Step Approach to Cloud Cost Optimization#

1. Gain Visibility Into Your Spending#

Before you optimize, measure and monitor:

• AWS: Cost Explorer, Budgets, and Cost & Usage Reports
• Azure: Cost Management + Billing
• GCP: Billing Reports and Cost Tables

Pro Tip: Set alerts with CloudWatch, Azure Monitor, or GCP Monitoring for anomaly detection.

Explore the site to start with AWS Cost Explorer and visualize your cloud usage trends.

2. Right-Size Your Resources#

Over-provisioning is expensive:

• Use Auto Scaling for EC2/VMs
• Monitor CPU, memory, disk usage
• Use recommendations:
  • aws compute-optimizer
  • Azure Advisor
  • GCP Recommender

Automation Tip: Enforce policies with Terraform or remediation scripts.

Explore the site to get insights from AWS Compute Optimizer and reduce over-provisioned instances.

3. Use Reserved Instances & Savings Plans#

Instead of on-demand:

• AWS: Savings Plans, Reserved Instances
• Azure: Reserved VM Instances
• GCP: Committed Use Discounts

Save 30–72% by committing for 1–3 years.

4. Eliminate Idle and Zombie Resources#

Common culprits:

• Unattached EBS volumes (AWS)
• Idle IPs (AWS, GCP)
• Stopped VMs with persistent disks (Azure, GCP)
• Forgotten load balancers
• Old snapshots/backups

Tools: aws-nuke, gcloud cleanup, Azure CLI scripts

5. Optimize Storage and Data Transfer#

Storage and egress can sneak up on you:

• Use CDNs: CloudFront, Azure CDN, GCP CDN
• Tiered storage: S3 Glacier, Azure Archive, Nearline Storage
• Set lifecycle policies for auto-delete/archive

For step-by-step examples, check AWS’s official guide on S3 Lifecycle Docs Configuration.

6. Consolidate & Modernize Architectures#

• Use serverless: Lambda, Azure Functions, Cloud Functions
• Containerize: ECS, EKS, AKS, GKE
• Migrate to managed DBs: RDS, CosmosDB, Cloud SQL

Bonus Tools:

• KubeCost (Kubernetes costs)
• Infracost (Terraform cost insights)

Explore the site to understand Kubernetes cost monitoring with KubeCost and allocate expenses by workload.

7. Implement Cost Governance Policies#

• Enforce tags by team, env, project
• Set team-level budgets
• Use chargeback/showback models
• Auto-schedule non-prod environments:
  • AWS Instance Scheduler
  • Azure Logic Apps
  • GCP Cloud Scheduler

Deep Dive: CloudWatch Cost Breakdown#

🔧 Optimization Tips:

• Delete unused dashboards
• Reduce custom metrics
• Use embedded metrics format
• Aggregate metrics (1-min or 5-min intervals)

Conclusion#

Cloud cost optimization is a continuous process. With visibility, automation, and governance, you can:

• Reduce cloud spend
• Boost operational efficiency
• Build a cost-conscious engineering culture

Start small, iterate fast, and let your infrastructure pay off—without paying more.

Enterprises needing advanced automation can rely on Nife.io’s PlatUS platform to simplify multi-cloud storage orchestration and seamlessly integrate with AWS-native tools.

Nife.io delivers advanced orchestration capabilities for enterprises managing multi-cloud environments, enhancing and extending the power of AWS-native tools.

Cloud bills can feel like magic tricks—one minute, you're paying peanuts, and the next, poof!—your CloudWatch bill hits $258 for what seems like just logs and a few metrics. If this sounds familiar, don’t worry—you're not alone.

Let’s break down why this happens and walk through some practical, no-BS steps to optimize costs—whether you're on AWS, Azure, or GCP.

Why Is CloudWatch So Expensive?#

CloudWatch is incredibly useful for monitoring, but costs can spiral if you’re not careful. In one real-world case:

• $258 in just three weeks
• $46+ from just API requests (those sneaky APN*-CW:Requests charges)

And that’s before accounting for logs, custom metrics, and dashboards! If you're unsure how AWS calculates these costs, check the AWS CloudWatch Pricing page for a detailed breakdown.

Why You Should Care About Cloud Cost Optimization#

The cloud is flexible, but that flexibility can lead to:

• Overprovisioned resources (paying for stuff you don’t need)
• Ghost resources (old logs, unused dashboards, forgotten alarms)
• Silent budget killers (high-frequency metrics, unnecessary storage)

The good news? You can fix this.

Step-by-Step: How to Audit & Slash Your Cloud Costs#

Step 1: Get Visibility (Where’s the Money Going?)#

First, figure out what’s costing you.

For AWS Users:#

• Cost Explorer (GUI-friendly)
• AWS CLI (for the terminal lovers):
  aws ce get-cost-and-usage \

  --time-period Start=2025-04-01,End=$(date +%F) \

  --granularity MONTHLY \

  --metrics "UnblendedCost" \

  --filter '{"Dimensions":{"Key":"SERVICE","Values":["AmazonCloudWatch"]}}' \

  --group-by '[{"Type":"DIMENSION","Key":"USAGE_TYPE"}]'

  Copy
  This breaks down CloudWatch costs by usage type. For more CLI tricks, refer to the AWS Cost Explorer Docs.

For Azure/GCP:#

• Azure Cost Analysis or Google Cloud Cost Insights
• Check for unused resources, high storage costs, and unnecessary logging.

Step 2: Find the Biggest Cost Culprits#

In CloudWatch, the usual suspects are:
✅ Log ingestion & storage (keeping logs too long?)
✅ Custom metrics ($0.30 per metric/month adds up!)
✅ Dashboards (each widget costs money)
✅ High-frequency metrics (do you really need data every second?)
✅ API requests (those APN*-CW:Requests charges)

Step 3: Cut the Waste#

Now, start trimming the fat.

1. Delete Old Logs & Reduce Retention#

For a deeper dive into log management best practices, check out our guide on Optimizing AWS Log Storage.

2. Kill Unused Alarms & Dashboards#

• Unused alarms? Delete them.
• Dashboards no one checks? Gone.

3. Optimize Metrics#

• Aggregate metrics instead of sending every tiny data point.
• Avoid 1-second granularity unless absolutely necessary.
• Use Metric Streams to send data to cheaper storage (S3, Prometheus).

For a more advanced approach to log management, AWS offers a great solution for Cost-Optimized Log Aggregation and Archival in Amazon S3 using S3TAR.

Step 4: Set Budgets & Alerts (So You Don’t Get Surprised Again)#

Use AWS Budgets to:

• Set monthly spending limits
• Get alerts when CloudWatch (or any service) goes over budget

Step 5: Automate Cleanup (Because Manual Work Sucks)#

Tools like Cloud Custodian can:

• Delete old logs automatically
• Notify you about high-cost resources
• Schedule resources to shut down after hours

Bonus: Cost-Saving Tips for Any Cloud#

AWS#

🔹 Use Savings Plans for EC2 (up to 72% off)
🔹 Enable S3 Intelligent-Tiering (auto-moves cold data to cheaper storage)
🔹 Check Trusted Advisor for free cost-saving tips

Azure#

🔹 Use Azure Advisor for personalized recommendations
🔹 Reserved Instances & Spot VMs = big savings
🔹 Cost Analysis in Azure Portal = easy tracking

Google Cloud#

🔹 Committed Use Discounts = long-term savings
🔹 Object Lifecycle Management in Cloud Storage = auto-delete old files
🔹 Recommender API = AI-powered cost tips

Final Thoughts: Spend Smart, Not More#

Cloud cost optimization isn't about cutting corners—it's about working smarter. By regularly auditing your CloudWatch usage, setting retention policies, and eliminating waste, you can maintain robust monitoring while keeping costs predictable. Remember: small changes like adjusting log retention from 30 days to 7 days or consolidating metrics can lead to significant savings over time—without sacrificing visibility.

For cluster management solutions that simplify this process, explore Nife's Managed Clusters platform - your all-in-one solution for optimized cloud operations.

Looking for enterprise-grade cloud management solutions? Explore how Nife simplifies cloud operations with its cutting-edge platform.

Stay smart, stay optimized, and keep those cloud bills in check! 🚀

DevOps in finance is one of the most innovative development practices in the financial sector.

Moving quickly in response to market developments is essential if you want your firm to remain relevant in the current digital world. This is especially true for the financial services sector. In the financial sector, sustaining services while meeting client expectations is more important than ever.

And, DevOps technologies, methods, & concepts have developed as the mechanism to drive this change from pattern recognition to the discovery of new income streams. It covers governance, risk, security, and compliance methods and enhances the quality of application releases. In this article, we will discuss some best practices and case studies for implementing DevOps for finance services.

What is DevOps?#

DevOps is the combination of the words "development" and "operations." It is a software development methodology that emphasizes collaboration and communication between development and operations teams. It aims to improve software development, deployment speed, quality, and efficiency. In the financial industry, DevOps can be especially valuable for improving the performance and scalability of financial systems and reducing the risk of errors and outages.

Best Practices for DevOps in Finance#

1. Increase in Collaboration and Communication between Teams

One of the key best practices for implementing DevOps in finance is to focus on collaboration and communication between development and operations teams. This can be achieved by creating cross-functional teams that include development and operations members and implementing tools and processes that facilitate communication and collaboration. For example, an issue-tracking system like Jira or GitHub can help development and operations teams stay on top of bugs and feature requests. In contrast, a chat tool like Slack or Microsoft Teams can help teams stay in touch and share information quickly.

2. Automation Process

Another best practice for implementing DevOps in finance is to focus on automation. Automation can reduce the risk of errors and outages and improve software development and deployment speed and efficiency. Automation tools such as Jenkins, Ansible, and Puppet can help automate repetitive tasks and reduce manual errors. Automation can also help with testing and deployment by automating the testing process and deploying code to production quickly and efficiently.

3. Continuous Integration and Continuous Delivery (CI/CD)

Continuous integration and continuous delivery (CI/CD) are also important practices for DevOps in finance. CI/CD is a methodology that emphasizes the continuous integration of code changes and delivery of new features to production. This can be achieved by implementing a continuous integration server like Jenkins or Travis CI and automating the testing and deployment process.

4. Infrastructure as Code (IaC)

Infrastructure as code is another important practice for DevOps in finance. Infrastructure as code is a methodology that enables the management of infrastructure as code rather than as manual configurations. This can be achieved using tools like Terraform and Ansible, which enable the provisioning and management of infrastructure as code. This can help reduce the risk of errors and outages and improve the scalability and performance of financial systems.

5. Monitoring and Logging

Monitoring and logging are also important practices for DevOps in finance. Monitoring and logging help to ensure that financial systems are working properly and that any issues are identified and addressed quickly. Monitoring tools such as Prometheus and Grafana can help monitor system performance and resources. In contrast, logging tools such as Elasticsearch and Kibana can help analyze log data.

Various Case Studies about DevOps#

1. JPMorgan Chase:

JPMorgan Chase is one of the largest financial institutions in the world and has implemented DevOps for financial services to improve the speed, quality, and efficiency of software development and deployment. They have implemented a continuous integration and delivery pipeline, automated testing, and deployment. They have also implemented infrastructure as code and have a dedicated team for monitoring and logging. This has helped them to reduce the risk of errors and outages, as well as improve the scalability and performance of their financial systems.

2. Barclays DevOps Adoption

In 2015, Barclays announced that DevOps was being used as part of its digital transformation strategy. At the moment, Barclays is in charge of managing payments, which make up over 30% of the UK's GDP. The leadership team credited DevOps at Barclays with significantly reducing the complexity of their programs, which allowed them to lower delivery risk and, in turn, improve the quality of their services. Developer satisfaction and code quality increased as a consequence.

3. Capital One:

Capital One is a financial services company that has implemented DevOps for financial services improvements such as performance and scalability. They have implemented a continuous integration and delivery pipeline, automated testing, and deployment. They have also implemented infrastructure as code and have a dedicated team for monitoring and logging. This has helped them to reduce the risk of errors and outages, as well as improve the scalability and performance of their financial systems.

4. DevOps the Lunar Way

An experience that shows Kubernetes doesn't require a large organization to be used. The large monolithic application was divided into more manageable microservices as the first step in their cloud-native DevOps journey. Ansible, Terraform, and Jenkins were used to spin up these microservices and deploy them as a single unit.

They then suddenly began encountering some of the microservices' scaling problems. They thus did not gain in any way from microservices.

They thus began seeking solutions to this complexity by reorienting their attention from machine-oriented to application-oriented design. They didn't care where the containers were operating and instead picked Kubernetes and AWS as the abstraction layer, which allowed them to manage microservices and unleash their velocity. Additionally, they chose Kubernetes for its security features and to describe how the apps should function. With the help of Kubernetes, they currently manage over 80 microservices in production.

Conclusion#

Companies in the financial services industry are under a lot of pressure to embrace sophisticated and demanding software development methodologies that satisfy stringent corporate and regulatory standards. With DevOps, the financial sector can deploy software faster than ever to keep up with demand and outperform the competition they face.

FinOps tools help cloud-based organizations allocate resources and achieve their business goals effectively. Read the full article to get an understanding of FinOps.

All About FinOps from a DevOps Perspective#

Modern-day businesses always try to integrate new practices to make their businesses more efficient, cost-effective, and consumer-friendly. Ever wonder as DevOps what happens when someone forgets to shut down a sizable project on the cloud? The goal of FinOps is to prevent any kind of financial disaster by improving the cloud infrastructure by monitoring everything.

FinOps is not only cost-effective but it tends to make the dev team work smarter to deliver quality work. FinOps practices also lead the way to a better customer experience. Read the full article to understand everything about FinOps from a DevOps perspective.

What is FinOps?#

FinOps (Financial Operations) is a practice adapted for cloud models to optimize the cost of business. All of the FinOps operations happen in a collaborative manner to effectively reduce expenditures while maintaining the same quality. FinOps does the same thing to financials as DevOps does to development.

FinOps is a very effective cost management practice and its implementation is dependent on tools of the cloud and an understanding of operations. It provides extensive information about spending, where the money is used, why it is used, and who is responsible.

Phases of FinOps Implementation#

FinOps distributes its work in phases like DevOps. All of these phases are repeated until the set goal is achieved. Following are the phases of FinOps.

Inform:#

In this phase, all the necessary information about the operations of different teams and departments is gathered. This information includes operation size, cost, and forecast. This phase helps estimate the total expenditures and all the other information like where they are coming from and where they will be used. This phase of gaining knowledge and controlling resources gives stakeholders a clear view of everything going on.

Detailed information helps the FinOps team to keep an eye on every small and big expenditure and optimize all unnecessary expenditures. It also helps them estimate the business value.

Optimize:#

After the necessary information is collected, the optimization phase begins. In this phase, a deep analysis of the gathered information is conducted. This analysis helps the FinOps team to separate liabilities. Once all unnecessary expenditures are identified, these expenses are cut down by using different methods. Some unnecessary projects are shut down to invest in good projects.

The FinOps team also optimizes team size and tools used to optimize the cost of a project rather than shutting the whole project down. These optimizations help these teams achieve their goals smartly.

Operate:#

In this phase, the FinOps team monitors all the cloud utilization to ensure the achievement of a set goal. The FinOps team also helps teams overcome their problems to ensure they reach their goals. All the information regarding the progress of teams is also shared with stakeholders to show them business progress.

What are FinOps Tools?#

Various tools are needed to track the billing, invoices, expenditures, and track progress. Different enterprises use different FinOps tools to help the FinOps team go over the above-explained three phases. These tools are used to track the progress of different departments and teams in an organization, estimate expenditures, track cloud usage, and create detailed reports.

These tools provide all the necessary information needed to optimize and operate. Team sizes, cost, and cloud usage are all decided based on the data provided by these tools. Moreover, projects are shut down based on the information provided by FinOps tools.

Features of FinOps Tools#

Here are some of the amazing features of FinOps tools that help FinOps teams Inform, Optimize, and Operate the cloud effectively.

Tags#

Tags allow FinOps teams to allocate tags and arrange them. These tags can then be used for efficient budgeting, tracking performances and purchases, etc. Apart from that, different cloud resources can be labeled for use accordingly.

Detailed Reports#

Each FinOps team member is responsible for a part of the cloud resource. To understand complex billing and cloud resources, FinOps teams use detailed reports on resources. These reports help these engineers understand the flow of money. On the basis of these reports, FinOps members make important decisions.

Performance Reporting#

FinOps tools also offer a performance reporting feature. This feature works by applying different metrics to all the employees of the organization. Based on the pre-defined metrics, a rating number is assigned to every department in the organization. This rating determines their performance.

This performance reporting helps FinOps members identify strong and weak departments. This data is then used to cut costs and help weak departments reach their goals.

Easy Budgeting#

FinOps tools evaluate different factors to set up cloud budgets and forecast. These tools help the team analyze the area where costs can be cut down. Moreover, these budgeting tools also provide data that helps assign reasonable budgets to different departments.

Benefits of FinOps#

The rise of cloud computing has undoubtedly brought agility and many other benefits. As more and more organizations are transforming to cloud-based systems, it is becoming more and more difficult for them to control their spending and achieve their goals. Over 70% of organizations that have transformed to hybrid and multi-cloud offerings are short on their goals.

FinOps is the best practice that, with collaboration with DevOps, can not only help these organizations achieve their set goals but also help these organizations cut their expenditures to become cost-effective.

FinOps provides a framework that lets DevOps perform their tasks with agility and speed. Hence, building trust across departments.

Conclusion#

The complex cloud structure can be a difficult cost management system for organizations. Many factors have to be taken into account and carefully examined to make any decision in that environment. This not only makes the business harder but also slows down the growth of an organization. Therefore, FinOps is a practical cost management solution for cloud-based businesses.

FinOps handles these complicated cloud businesses by dividing the work into different phases. These phases are repeated until the set goal is achieved. Different FinOps tools are used to collect information and allocate resources. This framework is very beneficial for businesses to take full control.