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How Best to Collect Unstructured Data from Hybrid IT

How Best to Collect Unstructured Data from Hybrid IT

Auto-Discovery Provides a Simple, Scalable, Automated Approach

By Bishnu Nayak

We live in a world that is massively distributed, disparate and diverse.

There are a lot of different people speaking various languages, and different cultures. If you can interact with these individuals in their language, you can learn a lot. And the broader knowledge and insights can significantly benefit people as well as businesses across the world.

Enterprise networks are worlds of their own. And in some ways, they mirror this larger disparate world.

Enterprise hybrid IT data centers contain lots of entities across network, compute, and storage supplied by different technology vendors. The vendors that supply these technologies have their own cultures, their own syntax and languages on how they manage and interact with other entities in the IT environment.

But if you can interact with these distributed entities in a normalized way and understand how they relate to one another, you can derive a deeper understanding into the end-to-end environment. That understanding helps enterprises manage their IT environments optimally and profitably.

My point is that we live in a diverse world. And when we collect information about different entities across the world from different sources, we gain greater understanding. That can help improve human lives. I mention this because FixStream AIOps platform helps business to improve their IT operations by understanding their application and IT infrastructure resources.

FixStream AIOps technology can

  • collect data from disparate IT entities and siloed systems
  • correlate and analyze the flood of data from different sources
  • and present that information in a way that makes it quick and easy for businesses to understand and gain value from it.

Sameer Padhye has blogged about the data correlation and visualization aspects of FixStream’s AIOps solution. (I should note here that AIOps stands for Artificial Intelligence platform for IT Operations.)

But  before data is correlated and visualized, it needs to be collected from millions of disparate datasources. And FixStream uses its smart auto-discovery solution for optimal data collection.

So, I’m going hit the rewind button with this blog and address the first step in the process.

Auto-discovery in this context describes the process of automatically fetching lots of data from many disparate sources. FixStream can do that because it knows how to communicate with the various infrastructure and application entities. Data is collected by FixStream data collectors from all kinds of entities –switches, routers, load balancers, firewalls, servers, storage devices, hypervisors, VMs, application entities – both physical, virtual as well as logical.

FixStream is vendor agnostic. So, it doesn’t matter if the entity comes from Cisco, HP, IBM, Nutanix, Juniper, VMware, or some other supplier.

FixStream knows how to normalize and make sense of the massive amount of data it collects using a semantic model. And it can do that regardless of the physical location of those entities across hybrid enterprise network.

That’s really useful, especially considering that complex IT environments typically lack a real-time inventory of assets. FixStream addresses that gap. Our hybrid cloud discovery capability provides a reliable and up-to-date inventory of enterprise compute, network, storage, and application environments.

Here’s how it works. Data collectors scan IP addresses in network subnets or user input boundaries to learn about infrastructure. FixStream can then identify the make and model of an and uses the vendor-specific command library to learn how it’s configured, and other topology-related data such as dynamic table, interfaces, MAC addresses, routing information, and VLANs, etc.

That allows FixStream to provide a topology map that illustrates the relationships among all IT entities. FixStream also does automatic and dynamic discovery and mapping of applications and their infrastructure dependencies.

The contextual maps are then correlated with alerts, faults, log events, and tickets ingested from different sources via the FixStream Open API ingestion layer.

This discovery, correlation and mapping delivers tremendous operational and business value to our customers. For example, if you’re doing maintenance on a device, you can see what else is connected to it. If you are doing a migration, you can easily understand the dependent systems that can be impacted. This end- to-end correlated view allows enterprises to do faster root cause analysis, lowers business risk, and eases migration challenges.

Many of our competitors lack such capabilities. Some have them, but their approaches to auto-discovery are less than optimal. To be frank, they tend to be quite basic.

By comparison, FixStream auto-discovery allows for a very rich data experience. Our approach is extremely granular with derivation and analysis of relationship data such as hierarchies, links, and relationships across all the IT entities.

For example, the platform derives the parent-child relationships between hypervisors and all VMs hosted in it. That shows the links between the VM to hypervisor to the TOR switch they are connected with. And the FixStream AIOps solution derives all available network paths between all compute, storage, and network entities and correlates them to application flows (Flow2Path analytics). That helps IT teams with troubleshooting, maintenance, and to make more effective use of their resources.

You don’t know what you don’t know. So FixStream auto-discovery solution helps you to know the unknowns.

Some FixStream customers have uncovered assets they didn’t even realize they had. It was a nice surprise. But the fact that some businesses lose track of their IT assets isn’t particularly surprising. It’s easy to do.

FixStream discovery process enriches the value of ITSM systems by feeding the discovered data to CMDBs of ITSM systems. Traditional CMDB discovery and update process lacks the knowledge of relationships between compute, storage, network and application layer and FixStream provides rich relationship data across all layers to CMDB, further enhancing the ITSM processes such as incident, change, config and asset management.

FixStream cloud discovery makes it just as easy to identify the underutilized resources and repurposes them for business services that need additional capacity. As a result, businesses don’t have infrastructure assets sitting idle. And they can use their limited budgets on things they really need.

Knowing what’s in your network is also important from a compliance and security standpoint. If you don’t know what’s in your network, you can’t keep tabs on what’s happening with it.

It’s also important to note that FixStream’s auto-discovery approach is agentless, so it’s not intrusive.

With agentless auto-discovery there’s no need to deploy agents on the devices from which data is collected. That means businesses don’t have to install agents on thousands or tens of thousands of devices. And they don’t have to worry about implementing different agent versions to address various vendor solutions.

All of the above illustrates how FixStream makes data collection simple and scalable. Even in hybrid cloud, multi-cloud, multi-domain, and multi-vendor environments.

Not only that, but we make sure you’re collecting the right kind of data. Once we do that, FixStream uses AIOps to aggregate, correlate, analyze, and visualize your data. All that adds up to new value for your business.

FixStream continues to add value to AIOps ecosystem through its data collector and open API architecture. Our open architecture means new collectors can be built in a one to three months release cycle. And third parties can now build collectors based on the FixStream open architecture too.

(In my next blog, I’ll talk more about the importance of APIs and open data ingestion.)

But for now, let me leave you with this quote from author and speaker Deepak Chopra.

“Success comes when people act together. Failure tends to happen alone.”

The same could be said of data in the IT operations management, planning, and troubleshooting realm.

IT environments today are made up of many different and disparate entities. The cloud and virtualized technologies like containers, microservices, virtual machines, and network functions have added to the chaos.

Businesses, which are increasingly reliant on connected applications, need to get a handle on all this. They can do that by correlating, analyzing, visualizing, and acting on an array of data.

That’s the only way organizations can avoid failure, optimize networks, and ensure application – and business – success. And auto-discovery is the first step in that process.

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