Real-time and predictive analytics for storage and compute
Predictive Analytics and Machine Learning for Enterprise Cloud
Tintri Analytics helps you make the right decision. With cloud-based predictive analytics powered by Elasticsearch, you can get visibility into every application right now, so you can troubleshoot in seconds. Plus, machine learning algorithms model every storage and compute need for up to 18 months into the future, based on your applications’ behavior.
Figure1: Tintri Analytics Dashboard
Ensure your applications always have access to sufficient compute and storage resources, by modeling scenarios and making precise predictions. Only Tintri Analytics—built on Tintri’s CONNECT architecture—ensures you always have the information you need to make the right decisions based on the historical compute and storage usage patterns of all your applications. That’s because of the Tintri’s ability to gather data about individual virtual machines and containers at a granular level from both compute and storage. That provides an all-round picture of an application in an instant.
Tintri Analytics is a cloud-based SaaS offering that provides organizations the ability to model both capacity and performance requirements. Tintri Analytics uses data lake of up to three years or more of real-time VM- and container-level data, including historical and current performance and resource usage statistics on every application in your environment. All this is collected natively by Tintri CONNECT.
Powered by Apache Spark and Elasticsearch and machine learning, Tintri Analytics then uses these data points to enable powerful predictive analytics and planning capabilities. It uses your application’s historical performance, capacity and working set data to precisely predict your organization’s future needs for capacity and performance for storage and compute. You can even model “what-if” scenarios to assess the impact of changes before they are implemented.
Tintri Analytics leverages machine learning to find hidden insights, without needing explicit programming. In any machine learning model, the quality, quantity and depth of available data, combined with the quality of the model, directly impact the accuracy and usefulness of the predictions. Tintri collects data at the right level of abstraction – the virtualized or cloud application – with up to three years of historical data. The very high quality of these inputs, combined with the power of Tintri’s machine learning algorithms, provide powerful insights and future trend analysis.
Solve a latency problem in seconds
What happens if an end user's application is running slowly? Easy: just open the Tintri storage analytics UI, scroll over the application, and see the source of latency across host, network and storage. Problem solved.
Model your resource needs
Deploying a workload or two? Powered by Elasticsearch, Apache Spark and Amazon Machine Learning, Tintri Analytics leverages your historical metadata to predict your capacity, performance, working set and compute. Provision exactly what you need, only when you need it.
What-if application planning
Your DevOps team has asked to add another 10 SQL servers to your Tintri footprint. Can you accommodate? Tintri storage analytics can break down the behavior of SQL servers already residing on your arrays, then help you complete what-if analysis on this request, so you can provide a precise yes / no answer.
Compute and Storage Planning and Forecasting
Tintri Analytics ensures organizations stay on top of their changing needs. It can:
- Predicts your needs for storage capacity and performance, as well as compute CPU and memory as far as 18 months into the future.
- Profile application types and then model how changes in application number or behavior impact your compute and storage footprint.
- Model your capacity, performance and throughput to account for organic growth and new projects in your enterprise cloud.
- Establish application profiles—for desktops, SQL servers, databases, custom virtual applications, etc.
- Conduct what-if analysis to understand the consequences of changes to your enterprise cloud for next 18 months in advance.
Planning next quarter’s and next year’s needs won’t take a crystal ball—just a few minutes with Tintri Analytics.
Figure2: Compute and Storage Usage Trends and Projections
Figure3: Do what-if analysis with Planner
With Tintri Analytics you can develop application profiles based on compute and storage with just a few clicks. That will help you understand the storage and compute requirements of all your virtual desktops, SQL servers, Oracle databases or other profiles. You can drill into a profile to see which specific applications are outliers: well below or above average. Now, when you get your next request to add applications, you don’t have to guess or deploy and hope; instead, model the exact impact and make a decision about whether or not you can accommodate the request with complete confidence.
Tintri Analytics significantly reduces the effort and time spent for resource management and planning to a few simple clicks.
You’ll be able to quickly and confidently answer the following questions for compute and storage planning and analysis:
How is my current resource utilization trending?
Look at the dashboard to see the current consumption of storage capacity, storage performance, CPU and memory to get an overall picture of your compute and storage resources.
How is my environment growth trending?
Explore trends and project when you will run out of resources — understand which resources are your bottlenecks.
What resources are my applications consuming?
Are there any outliers?
Create application profiles and see resource utilization across different applications. Drill into a specific profile to identify exactly which applications are outliers and may need special attention.
We are hiring 500 additional employees over the next two quarters. What additional resources are required?
Use the what-if planner to simulate the load of 500 additional VDI seats. See the impact on compute and storage and know in an instant what you’ll need to support this new project.
Download the Tintri Analytics Datasheet (PDF).