Choosing analytics: built-in, on-premises, or cloud-based

With the announcement of Tintri Analytics, we delivered on our vision: providing comprehensive, application-centric real-time analytics (using fully integrated on-prem and cloud-based solutions) that provide predictive, actionable insights based on historical system data (of up to 3 years).

Customers can now automatically (or manually) group VMs based on applications to analyze application profiles, run what-if scenarios, and model workload growth in terms of performance, capacity and flash working sets.Analytics

When you consider a storage solution refresh, analytics probably tops your list of needed features. It simplifies IT’s job, makes IT more productive and helps organizations save time and money.

The question is, what type of analytics should an organization look to have—built-in, on-premises or cloud-based? If you are just getting started, any sort of analytics would be great! Most storage vendors have an on-premises and/or a cloud-based solution. But an ideal storage product should have all three, as each of them has its own irreplaceable use case. Let’s take a look at each one.

Built-in analytics for auto-tuning

Built-in analytics that the system uses for self-tuning are uncommon in the industry. Tintri’s unique auto-QoS capability is a great example that uses built-in analytics, available at a vDisk level, to logically divide up all the storage resources and allocate the right amount of shares of the right type of resource (flash, CPU, network buffers etc.) to each vDisk. By doing this, a Tintri VMstore ensures that each vDisk is isolated from the other, without noisy neighbors.

Operationally, this simplifies architecture, as the IT team doesn’t have to figure out the number of its LUNs/volumes, the size of its LUNs/volumes, which workloads would work well together and so on. It can focus on just adding VMs to a datastore/storage repository as long as it has capacity and performance headroom available (as shown by the Tintri dashboard).

On-premises real-time analytics

On-prem analytics are extracted from a storage system by a built-in or external application deployed within the environment. Admins can consult these real-time analytics to help troubleshoot a live problem or store them for historical information. Admins can further use these analytics to help their storage solution deliver a prescriptive approach to placing workloads, and provide short-term historical data for trending, reporting and chargeback.

Tintri VMstore takes advantage of its built-in analytics to deliver an on-prem solution for analytics through both the VMstore GUI and Tintri Global Center. Up to a month of history can be imported into software like vRealize Operations, Nagios, Solarwinds and more.

Of course, customers don’t have to wait before they can see these analytics—unlike with cloud-based analytics, they can monitor systems in real-time.

Cloud-based predictive analytics

Cloud-based analytics help customers with long-term trending, what-if scenarios, predictive and comparative analytics. But not all cloud-based analytics are created equal. Some just show the metrics, while others let you trend storage capacity and performance. But the majority of them can’t go application-granular across multiple hypervisors, especially in a virtual environment. They’re just statistical guesswork based on LUN/volume data.

And that’s where Tintri Analytics separate themselves from the pack. With a VM-Aware approach, we understand applications, group them automatically and provide great insights across customers data.

Your IT team wants to be proactive, working on solving business problems instead of doing day-to-day mundane tasks. That’s why each of these three categories of analytics are must-haves. With Tintri Analytics, Tintri’s committed to reducing the pressure on storage and system admins, and helping to grow, not stall, your organization.

Cheers..

@storarch

The industry is validating Tintri – Another one comes through

Last few weeks have been great in terms of industry recognition of how Tintri has been approaching the storage problem for virtualized workloads.

First, VVOLs go GA and validates the approach Tintri took 7 years back with VMstore in terms of removing the boundaries around LUNs and Volumes in virtualized environments and come out with a product that delivered VM centric Storage Platform around 4 years back. The result is 4 years of product maturity (and 4 years of lead) based on real world deployments.

Now we have Pure Storage announce an integration with VMTurbo that allows customers to use VMTurbo in combination with Pure Storage to automate the movement of VMs from one LUN to the other based on various conditions including performance and latency.

What does this tell us?

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