Did you miss our latest roundtable on AI-driven FinOps? Don’t worry, we got you!

In this recap, we’ll review what our FinOps experts discussed and the key takeaways from the roundtable discussion.

• The challenges of delivering successful FinOps
• Managing DevOps teams and cloud billing in government environments.
• The future of FinOps 
• The role of automation, predictive analytics, and AI

Not much of a reader? Watch it on demand!

Who’s in our roundtable?

Sean Donaldson, CTO of Protera: Sean is an experienced technology professional who has served as the CTO for Proterra for 25 years. With a focus on AWS and Azure, Sean excels in handling critical workloads and ensuring efficient cost management. 

Corné van der Vaart, Technical Cloud Project Manager of A.C.A. Group: A.C.A. primarily focuses on software development for public and private sector companies. They also work with various cloud environments, following the MSP approach. Recently, they made significant investments in our Finops offering to meet market demand.

Nir Raz, Cloud FinOps Director of Nice: Nir is a cloud FinOps director with a diverse background in the field and has played a key role in growing the Cloud FinOps Group. While working across various business units with complex workloads, Neil has worked on-prem and cloud-native solutions on platforms like AWS and Azure. His expertise lies in financial aspects, such as predicting cloud costs and budgeting, while developing internal BI tools and advanced KPI dashboards. 

Inbal Tadeski, a Data Scientist at Anodot: Inbal leads a team responsible for building sophisticated analysis tools to extract valuable insights from cost data. Her work includes anomaly detection, forecasting, and smart recommendations to help users reduce costs. Oh, and not to brag, but she was our innovative project CostGPT, which lets users explore cost data using natural language effortlessly. 

Ran Blumenfeld, FinOps & Customer Success at TeraSky: An experienced leader in FinOps for over two decades, excelling in the public Cloud industry with a strong background in customer success and product management.

Melissa Abecasis, Presenter and Customer Success Director at Anodot: Melissa has expertly managed cloud costs for eight years, preserving trust while taming expenses. Melissa helps MSPs scale using Anodot and is an amazing roundtable host!

The challenges of delivering successful Finops

In this section, we explored the traditional practices of businesses before transitioning to the cloud and the challenges of adopting this new model.

The past

Organizations invested heavily and expected long-lasting results, disregarding dynamic cost management in IT resources. Budget planning sessions were the norm. However, the shift to public cloud platforms like AWS or Azure is changing the game.

Today’s challenges

Setting up a server in AWS or Azure may seem simple, but the real challenge lies in architecting it right.

This includes severe complexities like

• Proper security
• Seamless compliance
• Governance
• Backups
• Discover recovery 

Anomaly detection on cloud costs

Spike on cloud costs – anomaly detection

Challenges in Dealing with DevOps Teams 

We asked our expert, Nir, who has successfully set up a FinOps team at his company, about the main challenges when dealing with DevOps teams.

It’s a roller coaster ride

Defining waste reduction approaches, modernization, and architectural improvements is easy. The challenge lies in ensuring the availability of development and DevOps teams when needed.

The problem with being dependent on the availability and coordination of the teams

To avoid big cost setbacks in the cloud, it’s crucial to spot anomalies in time.

As Nir mentioned, a single query that generates too many logs can seriously mess up operations.

Manual FinOps falls short in today’s world. A cost management solution can address this issue through automation, identifying key factors for quantifiable action.

Anodot’s cloud cost management tool

Cloud Billing in Government Environments

Corné’s company, A.C.A. Group, serves a primarily government consumer base and mentions that many of them find cloud billing challenging, and many don’t want to embrace FinOps.

“We regularly meet with clients to discuss their cloud bills and any potential spikes. However, where we are based in Belgium, Finops is not widely recognized by many companies or governmental departments. It’s challenging to explain how improvements can lead to cost reductions or alternative options.”

-Corné van der Vaart

True cost optimization requires architectural changes

One major issue that Corné sees in this sector is that cost optimization isn’t a priority. It often gets overlooked until problems start popping up. So, their customers assume that the architectural design already considers financial optimization when they renew the project. 

🚨 Alarming stat🚨: Corné says about 90% of clients are skeptical of making changes for cost savings alone.

The future of Finops

Now that the challenges have been discussed, let’s dive into how modern FinOps can help control and optimize costs in the cloud.

Leveraging  AI-driven methods and machine learning

As we’ve seen, manual methods don’t do the trick when dealing with real-time anomalies.

As our Data Scientist, Inbal relayed: “We need to alert users correctly, avoiding false positives while ensuring important events are not missed. We aim to automatically alert and help users explore anomalies, identifying the root cause.”

Machine learning solutions

To speed up cloud operations with a FinOps perspective, machine learning, and generative AI will have a major role in comprehending data clearly and insightfully.

Hint: Our Cost GPT tool allows customers to explore data using natural language. It’s simple, intuitive, and all in one place. 

Inbal discussed how predictive analytics and forecasting can amp up your FinOps game.

“Forecasting helps with planning and budgeting, giving you confidence in your decisions. We are also working on focused-based recommendations, such as suggesting saving plans based on your current usage.”

-Inbal Tadeski

By leveraging AI and machine learning, proactive analytics can provide alerts and advance warnings about exceeding budgets and guidance on saving money. This combination of intelligent capabilities can deliver significant value to customers.

Upcoming Anodot’s goals

The perk of having Anodot’s chief scientist on the roundtable is getting an inside look at what the company prioritizes for the future!

This includes:

Utilizing predictive analytics: cost-saving suggestions can be made, including recommending a more suitable savings plan and anticipating potential cost reductions.

Advance alerts budget overruns: We aim to bring great value to customers by using AI and machine learning to manage costs proactively.

AI predictive models and the role of the FinOps engineer 

With all the exciting advancements that AI and automation bring, we can expect great efficiency in cloud costs. But what about the human role in these operations? 

Inbal acknowledges the power of these tools, but full automation will take time.

“This process should be a learnable loop. We’re not currently trying to perform actions on your behalf. In the future, we might let customers add resolutions and actions they’re sure of in certain cases.”

-Inbal Tadeski

Balancing human knowledge with AI 

Our experts believe that AI will improve by making recommendations and predictions. This will allow us to focus more on reducing cloud waste and finding ways to modernize and plan commitments.

Balancing human knowledge with AI 

Cloud architects are hesitant to adopt new tools or use advanced AI, thinking they can handle it themselves. But having them figure out costs is a waste of resources. Your cloud architect or the FinOps engineer should not be trying to determine how much their GP three costs. 

The FinOps engineer and the AI rely on each other. AI assists the FinOps role, but customization and supervision require a human touch.

Sean mentions the importance of keeping analytics and AI in constant interaction.

“FinOps analysts play a crucial role at the intersection of artificial intelligence (AI) and human intelligence. While AI enhances their effectiveness, human involvement remains essential.”