Anodot

Redwood City, CA, USA
2014
  |  By Anodot
Artificial intelligence (AI) is the next significant technological frontier, poised to revolutionize the tech sector, particularly through its massive impact on cloud infrastructures. By 2024, this transformation is expected to be as widespread as managed Kubernetes services, with an estimated 70% of organizations utilizing managed AI services in their cloud setups.
  |  By Anodot
MSPs can’t afford to use a Cloud Management Solution (CMS) that doesn’t follow their FinOps standards. Even with useful features, if a CMS hasn’t seen significant upgrades since its launch, it’s likely outdated and not meeting industry standards. If you can’t count on a CSM for the best FinOps recommendations, can you call them reliable partners? That’s just one of the major differentiators between us (Anodot) and Yotascale.
  |  By Perry Tapiero
It’s 2024, and businesses are projected to spend over $1 trillion on the cloud – and yet, where the costs go is still a mystery. Sure, people say that a cloud or hybrid environment is more budget-friendly than on-prem, but what factors increase or, more importantly, decrease your monthly bill? We’ll help demystify things with Microsoft Azure. Read on to learn how one of the largest cloud providers decides what to bill you each month.
  |  By Perry Tapiero
As of 2023, 94% of companies use cloud services. Migrating has many upsides. Scaling is more accessible; you can save money by leaving on-prem and have more control. There is one big con, though (navigating cloud migration difficulties aside): Managing a cloud environment is a full-time job. And that’s just one cloud environment! Suppose your company is working with a multicloud environment, optimizing usage and costs, and monitoring output/input while juggling security.
  |  By Perry Tapiero
Load balancer is a system that distributes network traffic across a group of servers. AWS’s load balancing service is called ELB (Elastic Load Balancing). It automatically distributes incoming traffic across multiple targets like EC2 instances, containers, and IP addresses. It essentially acts as a traffic cop for your application, ensuring high availability and scalability.
  |  By Perry Tapiero
We’re back with this year’s cloud cost report. This time around, we’re mixing things up a bit. Don’t worry. You’ll still get an in-depth look at cloud cost in the FinOps industry, but you’ll get more insights with our data-driven results from leading reports and Anodot’s customers. If you’re already reaching out to grab that report, you can find it here.
  |  By Perry Tapiero
Network Address Translation Gateway or NAT Gateway is a managed service provided by Amazon Web Services(AWS) that allows instances in a private Subnet within a Virtual Private Cloud(VPC) to connect services outside the VPC. NAT ensures that even though your instances can connect to the outside world, outside services can’t establish a direct connection with them. It’s a tool that secures the instances, simplifies network architecture, and reduces administrative overhead.
  |  By Perry Tapiero
As of 2023, 89% of companies rely on a multi-cloud approach. Operating in the cloud is no longer a plus but a competitive necessity. Migrating from a fully on-prem to a hybrid or fully cloud environment isn’t exactly easy though, especially given the impenetrability of cloud data. Cloud monitoring enables your company to be proactive about its cloud services, ensuring that availability, security, performance, and other aspects are all up to par before reaching the end-user.
  |  By Perry Tapiero
Our Cloud Cost platform just got some practical upgrades to help you manage cloud costs better and boost your operational efficiency. Curious about the new features? Let’s jump right in! Forecast in ChatGPT Interacting with cloud cost data just got easier and smarter. Ask any cost-related question using natural language, and let CostGPT do the rest. It instantly delivers insightful visualizations and forecasts of your cloud costs.
  |  By Perry Tapiero
As of 2023, 89% of companies are using a multi-cloud approach. The race to the cloud might feel truly like that – a race – but the finish line isn’t hybridization or even a full migration. Even after you’ve made it to the cloud, there’s still more work. Namely, determining cloud costs. Microservices, containers, Kubernetes made resource costs, associated costs and more are near-impossible to sort though.
  |  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.
  |  By Anodot
  |  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.
  |  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!
  |  By Anodot
Anodot's FinOps specialist shares the top 5 strategies to optimize cloud costs and reduce waste.
  |  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.
  |  By Anodot
Take a quick tour of the Calculated Metrics page, where you can view both composite metrics and output metrics created from alerts.
  |  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.
  |  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.
  |  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.
  |  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.
  |  By Anodot
Learn now anomaly detection can remedy urgent problems faster and capture opportunities sooner.
  |  By Anodot
Learn how different industries are using Machine Learning Powered Analytics.
  |  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.
  |  By Anodot
Immediately address data quality problems and save weeks of dealing with inaccurately reported data.
  |  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.
  |  By Anodot
An introduction to design principles of creating a machine learning based anomaly detection system.

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.