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By Anodot
Upcoming specific new AWS regulations will significantly impact how businesses handle their AWS operations. Starting from January 15, 2024, AWS will no longer permit the resale of discounted Reserved Instances (RIs) bought from the Amazon EC2 Reserved Instance Marketplace. This update aligns with AWS’s service terms, particularly Section 5.5, which explicitly prohibits the resale of discounted RIs.
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By Anodot
Our solution (Anodot) and CloudZero are popular choices regarding third-party solutions for businesses managing cloud costs, adapting a FinOps approach to make their cloud operations more efficient. That’s why a platform that can effectively support a FinOps model has become necessary for optimizing cloud functionality. Let’s analyze and dive deeper into who offers the best solutions, technology, and support to take your FinOps culture in the cloud to the next level.
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By David Drai
Understanding your AWS S3 billing is crucial to effectively manage and reduce your costs. Charges in AWS S3 are primarily based on three factors: the amount of data you store, the number of requests you make, and data transfer fees. Storage costs are calculated per gigabyte (GB) stored, which are tiered depending on the total size of your data. Requests costs are incurred with each put, get, or list operation on your objects, with prices varying based on the type of request.
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By David Drai
Effective Google Cloud Platform (GCP) cost management is an essential aspect of cloud administration, ensuring that resources are used optimally without overspending. Utilizing BigQuery for GCP cost analysis offers a comprehensive solution to understand and control your cloud expenses. The integration of GCP billing data into BigQuery allows for real-time analysis and detailed insights into your cloud spend.
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By Anodot
Embarking on the journey of understanding your cloud bill can initially seem daunting, but grasping a few essential concepts and familiarizing yourself with common terminology can significantly demystify the process. At its core, cloud billing is the method by which cloud service providers charge for the resources and services that your business consumes.
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By Anodot
Kubernetes or K8s is an open-source production-grade container orchestration system for automating, scaling, and managing containerized applications. A container is a lightweight, standalone, executable ready-to-run software package that contains everything needed to run an application. It includes the runtime, code, libraries, systems tools, and default values for any essential settings.
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By Anodot
In our first blog post, we introduced the concept of cloud unit economics—a system to measure cost and usage metrics. It helps maximize cloud value for better outcomes per dollar spent. We reviewed what cloud unit economics is, why it’s crucial to FinOps success, and how it enables organizations to unlock the full business value potential of cloud computing.
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By Anodot
The cloud’s elasticity—the ability to scale resources up and down in response to changes in demand—as well as variable cost structures offer significant advantages, enabling enterprises to move from rigid capex models to elastic opex models where they pay for what they provision, with engineers in control and focused on innovation, becoming true business accelerators.
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By Anodot
Want to hear a sad but true fact? 70% of companies overshoot their cloud budgets. Why is that? Although the cloud is a mighty tool for speed, scalability, and innovation, the inability to see costs can lead companies to limit cloud usage, which hampers innovation and puts them at a disadvantage against the competition. Rather than limiting cloud usage, adopting the FinOps approach provides the insights you need to feel confident about your cloud costs.
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By Anodot
Amazon RDS or Relational Database Service is a collection of managed services offered by Amazon Web Services that simplify the processing of setting up, operating, and scaling relational databases on the AWS cloud. It is a fully managed service that provides highly scalable, cost-effective, and efficient database deployment.
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By Anodot
Watch this on-demand webinar to discover how to turn manual cost control into automated, data-driven insights for optimizing client experiences in the cloud. #cloudcost #aws #cloudoptimization #cloudmanagement #finops #anodot.
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By Anodot
The Cloud is dynamic, and your costs can change any moment. The trick to cost control? It might just be catching anomalies. Learn more and get more insights from our 2023 State of Cloud report.
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By Anodot
Introducing CostGPT: Anodot’s New AI Tool gives instant insights into cloud cost structure. Get actionable cloud cost insights by simply asking a question!
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By Anodot
Anodot's FinOps specialist shares the top 5 strategies to optimize cloud costs and reduce waste.
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By Anodot
Effective management of cloud costs is critical for digital-first organizations, especially during times of market volatility. But, it can be very challenging to effectively drive organizational alignment around FinOps. Join CyberArk and Anodot as we explore tactics for delivering successful ongoing FinOps in your organization.
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By Anodot
Take a quick tour of the Calculated Metrics page, where you can view both composite metrics and output metrics created from alerts.
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By Anodot
In this webinar, led by Ira Cohen and Jeff Haines, you will hear how you can foresee the evolution of your cloud spend by harnessing the power of AI.
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By Anodot
In this webinar, led by Nir Shtein from Komodor and Jeff Haines from Anodot, you will learn how to empower your team to own reliability and FinOps for Kubernetes.
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By Anodot
Anodot's cloud cost management solution enables you to visualize costs in a single screen — across AWS, Azure, GCP and Kubernetes. Anodot leverages proprietary ML-based algorithms to offer root-cause analysis and recommended remediation. With continuous monitoring and deep visibility, you gain the power to align FinOps, DevOps, and Finance teams and cut your cloud bill.
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By Anodot
This introduction to next-generation analytics includes a step-by-step comparison between legacy BI and Autonomous Analytics, from data integration to anomaly detection and forecasting.
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By Anodot
Learn now anomaly detection can remedy urgent problems faster and capture opportunities sooner.
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By Anodot
Learn how leading adtechs like Rubicon Project, Uprise, and NetSeer are leveraging the power of machine learning - discovering outliers in time series data and turning them into valuable business insights.
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By Anodot
Immediately address data quality problems and save weeks of dealing with inaccurately reported data.
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By Anodot
This white paper presents unique insights into the costs, benefits, and complexities associated with anomaly detection systems, including whether it makes more sense for your company to build or to buy, and which will give the best and fastest return on investment.
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By Anodot
An introduction to design principles of creating a machine learning based anomaly detection system.
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Anodot applies AI to deliver autonomous analytics in real-time, across all data types, at enterprise scale. Unlike the manual limitations of traditional Business Intelligence, we provide analysts mastery over their business with a self-service AI platform that runs continuously to eliminate blind spots, alert incidents, and investigate root causes.
Autonomous Analytics uses machine learning to understand behavioral patterns within time series data, to identify anomalies and to continuously forecast future values. Our alerts operate in real time and offer you context - correlating each incident to similar anomalies, relevant factors and the potential root cause. Detect and diagnose high-impact problems faster than is humanly possible.
Why Autonomous Analytics?
- Track Every Business Parameter: Anodot uses its patented technology to learn the normal behavior of all your business metrics and constantly monitor their every move. All without configuring a thing.
- See The Anomalies That Matter: Not all anomalies are created equal. Anodot scores every business abnormality by degree of deviation so you can prioritize and act based on what’s most important to you.
- Models Automatically Trained For Accuracy: Our solution uses deep learning to automatically optimize forecasts. It selects a model that’s uniquely suited to your metrics from a library of predictive analytics algorithms. Data feedback is used to train your model for the highest possible accuracy.
- Continuous Forecasting For Operational Agility: Autonomous Forecast is always running. It works on data streams in real time to provide forecasts in the moment. With these capabilities, businesses can anticipate changing conditions and optimize their operations in advance, to improve customer satisfaction and seize opportunities.
The only alerts you need. Just when you need them.