Several years ago, a lot of enterprises moved some of the heavy lifting of managing their business critical applications from data centers to software-as-a-service (SaaS) solutions, such as Salesforce and Microsoft 365. These applications are hosted in massive cloud environments and enterprises pay for subscriptions essentially by headcount.

Salesforce and Office 365 specifically require a pretty complex application architecture that runs with various components that would be a nightmare to manage locally in a data center by any of today’s IT standards. Another disrupter is ServiceNow, a SaaS solution that has displaced on-prem IT ticketing systems for many organizations. In general with modernization, the idea of a SaaS solution that reduces the IT footprint of capital expenditures (CapEx) to operating expenses (OpEx) is very appealing to most enterprises.  

SaaS vs On-Prem

In many cases, IT departments turned to SaaS because the on-premises solution required hardware, installation, and maintenance. Typically, for an enterprise application you would have some sort of “engine” that was the main application, and then you would have to install one or more database servers, a web server, load balancing, or high availability with redundancy.  

To add to the complexity, you had to do the upgrades yourself and, depending on the solution, you could have licensing and third-party applications with separate licensing of its own. It was no joke..

With a SaaS alternative, all of that goes away. The updates and maintenance often is left up to the service provider. Although you don’t have control of the environment, many of these SaaS providers simply provide a service level agreement (SLA) that mitigates any fear of downtime. With on-prem, you got the classic “war room” of finger pointing for why something did not go right with an upgrade or your database exceeds capacity without warning. With SaaS, however, you can rely on (or blame) someone else.

A Hosted VM—The Best of Both Worlds

For the purpose of this comparison, we’re considering a hosted VM as a solution that includes all of the complexity of the application in a single virtualized appliance. In this case, you do not have to configure or install the different components on separate operating systems. Rather, you provision a designated VM with the capacity to run the virtual appliance as a single unit. You can even provision the VM in a private or public cloud environment that you are paying for as a service. In this case, you pay for part of the running environment as an operating expense and the rest is paid for based on the cost of the appliance.

If the vendor of the appliance software can bill you on a subscription basis, then Voila! You have the best of both worlds. You’ll be spending on an as-needed basis only when you’re running the solution and paying for a subscription based on the value you receive. There’s no heavy lifting of configuring a complex application environment and you control where you host the solution. Instead of being subject to the SaaS provider’s ability to be secure and guarantee service levels, you control all of it with a hosted VM. You can even customize your environment a lot easier than you can with most SaaS applications.

Are there drawbacks? It’s hard to think of much, other than the fact that you have to provision and install the VM somewhere. If your solution is an enterprise hybrid cloud platform like CloudBolt, the users and administrators are very comfortable with installing what is called an open virtual appliance (OVA) that includes all the files necessary to run the application. Other vendors might suggest that it’s easier to provide a free subscription with a SaaS solution.

Calculating the return on investment (ROI) for any digital enterprise initiative is tricky. There are so many factors to consider, most of which involve a decision to invest in new digital resources vs sticking with current approaches. The analysis is typically informed by asking, “What business value will be advanced by a new approach?”

By using an either/or approach, you might consider the cost of deploying your infrastructure in a public cloud vs the equivalent of those resources on premises. Hybrid cloud means choosing the right-fit environment for the workload, so this is a good start.

When making the ROI calculation, consider the cost for the resources as well as the time to deploy them in the cloud or on-premises. Your goal is to identify quantifiable savings. However, don’t dismiss that some of your choices might take less time and cost less while not achieving the innovation that you’re really looking to get. Make sure that in addition to time and cost factors, elements like the experience of the users in your environment or the future benefits from adopting a system might cost more in the beginning but have a better long-term benefit.

Getting a lower cost and shorter time-to-value is important but it’s far from the whole picture. Let’s look at the following summary of key analysis factors as you consider possible outcomes for hybrid cloud ROI.  

Public Cloud vs Public Cloud

Shopping for a public cloud provider for your hybrid cloud strategy is not going to be easy. Recently, all three major public cloud providers have claimed “all-in” to hybrid cloud. Microsoft Azure boosts its Azure Stack for data center development for enterprises. Google recently released Google Kubernetes Engine (GKE) On Prem to help enterprises manage Kubernetes clusters anywhere. Amazon Web Services (AWS) at their recent re:Invent 2018 conference released AWS Outpost, for providing their cloud experience on-prem.

Consider that choosing one over the other might also be influenced by a strategic position of your organization or the public cloud providers. If you’re a big retail customer, for example, you might not want to invest in AWS because of its obvious connection to Amazon’s online shopping business. In another case, your staff might be partial to a Microsoft Windows environment and would lose out on the expertise that might get underutilized in another public cloud environment.  

Public Cloud vs Data Center

For a new business, IT at your fingertips in the cloud that scales on demand will probably be your best bet. In this case, you would then do the analysis in the previous section and pit the public clouds against each other. On the other hand, most large enterprises that have been in business for a decade or so will have a more complicated analysis. Most of their IT departments would concede that they have over 50% of their infrastructure on premises in one or more data centers across the globe.

Adopting an incremental or trial and error approach seems to be what most organizations are doing with such a heavy on-prem footprint. Several of our customers have reported that they’ve moved infrastructure to the cloud only to move in back on-prem due to unexpected costs. They encounter security, control, or even a competitive factor like the one previously mentioned about a retailer not going with AWS. The ROI calculation would first start by comparing the cost to run services in a public cloud versus those same services on premises.

Hybrid Cloud Delivery

Here’s where it gets more complicated—the way that enterprise users consume resources to achieve digital business objectives. Enterprises with a deep bench in the IT department might have systems in place in which delivering cloud resources are tied to IT service requests. This is typically done through ticketing systems while provisioning is done by IT operations.

In a DevOps environment, the public cloud resources might be available as self-service within each cloud environment—responsibility and control are more distributed. A cloud delivery platform that connects to hybrid cloud resources for the entire enterprise can enable Self-Service IT and User Empowerment that can have an incredibly positive effect on ROI.   

Other factors to consider in the time-to-value consideration of ROI, include complexity versus ease of use for any system in place. as well as Extensibility to Future and Legacy Technology.

CloudBolt provides a single platform for hybrid cloud delivery that enables significant ROI for faster time-to-value and the ability to empower end users to innovate without being tied up in the complexity of configuration in multiple clouds.

The likelihood of dealing with enterprise IT gremlins1 is heightened during certain times of the year for any DevOps team. My brother, who works in IT Disaster Recovery for a healthcare agency, reminded me of this during our most recent Thanksgiving gathering. He had to address four hours of downtime right before the holiday, as something DevOps related pushed a change to the production system instead of in a test environment. Sound familiar?

Whether it’s a holiday, close of the quarter, or “go live” day, any number of factors can put a little extra stress on IT staff with more of a chance for network gremlins to plague any enterprise. Although not as mischievous as mythical gremlins, sloppiness causes trouble, difficulties, or unexpected failures—threatening security as well as contributing to downtime and poor performance.

Self-Service Resources and IT Automation

Keeping gremlins at bay can be achieved with a solid plan for self-service options and IT automation. End users need to have access to hardened resources and processes when others who have the keys to these resources are on PTO or swamped by other high priority projects.

Leaving users in the dust while waiting for resources or an update can make them turn to workarounds or short cuts. The idea is that you don’t want anyone in your organization going rogue during the stressful times. The more that enterprise IT and DevOps teams have self-service IT enabled, the less likely the chance for folks to fend for themselves.

Making any DevOps practice or IT process bulletproof for occasional mishaps is nearly impossible, but reducing the likelihood is worth the effort needed by using the following approaches:

A centrally managed platform like CloudBolt can get any IT organization on the right path to avoiding the “gremlin” effect, especially as we approach another holiday season and schedules and priorities will undoubtedly be different for many enterprises.

1—Gremlins are unexplained problems or faults (↑BACK↑)

Over time computing has gone from mainframes to bare metal servers to on-premises virtualization to cloud server instances and containerization to serverless computing.  What’s next, codeless computing? Probably not, but luckily we’re not talking about something as bizarre as that with serverless computing. The server element for executing code is essentially abstracted away from its developers, and it’s new enough that we’re in the Wild West.

Serverless Computing Explained

Serverless computing is a fancy way of saying that you don’t have to worry about the servers when you want to execute code—often referred to as a Function-as-a-Service (FaaS). Major cloud providers have compute capacity ready for anyone to reserve and run virtual machines (VMs) and containerization of microservices.

For public cloud providers, why not take it one step further and isolate running code on demand as a way to make more money? This is great for developers who need to continuously add services and features to their application stack but don’t want to fuss with managing the infrastructure.

Major cloud providers offer these serverless computing options with an emphasis on the payment model:

As great as these services are, though, we still have to contend with The Good, The Bad, & The Ugly

The Good

The good is the on-demand nature of this computing strategy at low cost. Suppose an application developer wants to give their aging application architecture a quick lift with a small feature that checks an Internet of Things (IoT) sensor in a smart home, like air quality to automatically suggest or order a new air filter. Instead of adding the compute power of infrastructure needed for many thousands of subscribers to the application, they can develop this on-demand function that only needs to run occasionally.

The Bad

The bad is that these functions can get complicated and hard to manage, especially if they must run for more than five minutes at a time in an application process. They must also be accessed by a private API gateway and will require the dependencies from common libraries to be packaged into them. This can be terribly inefficient compared to containerization. The more complicated the coding required the less likely a serverless function is going to suit the application architecture well. For more information, see What is Serverless Architecture? What are its Pros and Cons?

The Ugly

The ugly is that there is currently no standardization of serverless computing across the different public providers. Vendor lock-in will be at risk when these enticing functions as code—with low prices—become addicting to some developers and enterprises. They cannot be easily ported around like in the same was as containers can.

As Rick Kilcoyne, VP Solutions Architecture at CloudBolt stated in a recent article:

“…tantalizing as serverless computing is, one must be fully aware that moving code between serverless platforms is extremely difficult and only made more so by cloud vendor specific libraries, paradigms, and IAM. Serverless computing is the technological equivalent of a snare trap as there’s virtually no way to easily migrate from one platform to another once committed.”

Roundup

Serverless computing should definitely be a part of any enterprise hybrid cloud strategy. Just as a hybrid cloud application has a mix of public and private clouds, it can also have a mix of infrastructure technologies such as virtualization, containerization, and serverless computing with functions. Our CloudBolt hybrid cloud management platform helps you manage it all from one place.  

To see how CloudBolt makes serverless computing easier, check out a demo.

Most IT leaders can agree that agility and speed are the main focus for any enterprise DevOps team, meaning that responding quickly to digital business needs is essential. There’s an implied bargain in this—we can get these results faster if we have more control of our working environments. Alongside that, there’s the risk that the DevOps teams will spend a lot more time and money than necessary without a good strategy in place.

DevOps promises to shorten the time-to-value (TTV) by merging aspects of application development and IT operations. DevOps teams need to be empowered to configure, code, and run mission-critical digital services for the enterprise without too many handoffs between different departments.

DevOps Challenges

DevOps teams either play a role in or are responsible for IT resource provisioning, automation, and orchestration followed by development, testing, and delivering applications, services, and workloads. Most of them follow a framework of continuous integration and delivery (CI/CD). But you guessed it—that’s a tall order for most enterprises—particularly because they have become entrenched in so much complexity and have a strong footprint in datacenter legacy technologies. There is a lot of digital value running in these legacy enterprise workloads.

A startup company can just run with all the new and shiny stuff, architecting their solutions from scratch. Obviously, this is not the case for most large enterprises.  

There are many tradeoffs to consider in an enterprise-level DevOps process. For example, provisioning new IT resources could be unbridled and very generous. You could give the teams whatever they want by allowing them to self-provision in whatever environment they need with the hopes that they’ll be prudent in making decisions.  But how will you know that they do not end up spending more than the value that is achieved by using those resources? Keep in mind that the advantage of being more generous is the ability to get moving on any initiative without being too concerned with the cost of compute resources.

On the other hand, IT resources might not be as easily attainable. Public cloud providers would love for DevOps teams to just order as many resources as they wanted from an open account. But there might be more hurdles to address with regards to governance and approval processes that can slow everything down, leading to TTV taking a hit. By balancing all of these competing factors, DevOps teams need to take into account utilizing legacy value, the speed needed to get started, and their spending budgets.  

Achieving Cost Management Nirvana

When DevOps teams have the ability to do self-provisioning unhampered by inefficient hurdles and have the ability to right-size and manage costs throughout the process, they get closer to an ideal state-of-being for delivering value.  

Here’s just a short summary of ways to improve cost management for DevOps teams:

Nirvana with CloudBolt

CloudBolt’s enterprise hybrid cloud management platform provides a perfect fit to empower DevOps teams with resources from on-premises legacy infrastructure to every major private and public cloud provider. The platform also provides robust cost management to satisfy the dilemma of balancing speed and agility with spending.

For more information about avoiding slow-car scenarios in your enterprise IT environment, check out our solutions overview

Hybrid Cloud and Hypervisor Management

It’s no secret that most enterprises have a mix of cloud technologies to meet their IT needs. They set up IT environments in both private and public clouds that are used to develop mission-critical applications and run additional services as well as subscribe to software-as-a-service (SaaS) applications to support other business needs.

New cloud initiatives can help enterprise IT achieve:

When these initiatives get out of control, cloud usage can end up giving you unexpected results and catch you off guard—in many ways, it’s like being caught in a rainstorm without an umbrella. Having the visibility of what is running in complex environments is key, just as watching clouds overhead can help you plan for the upcoming downpour. You want to keep an eye out for any storms that can come your way.

Visibility and Control

As your IT department manages the complexity of a hybrid cloud environment, you must consider the following:

User Management

Enterprise user management requires the administration of connections to so many different environments such as IT systems, networks, and SaaS applications. Most enterprises implement role-based access control (RBAC) so that each resource can be accessed based on a level of security and control.

The management of users and passwords can easily get out of hand, especially in large enterprises. This, obviously, hinders overall productivity. One way to mitigate the maintenance of the credentials used across an enterprise is to configure Single Sign-On (SSO) so that everyone in the organization can use just one username and password to access the many IT resources they need. As more complexity enters IT control, maintaining SSO access can become more difficult without a plan in place.

Subscriptions and Metered Usage

SaaS applications, as well as platform-as-a-service (PaaS) and infrastructure-as-a-service (IaaS), each have specific accounts to set up and manage. Some of these accounts might have been initially acquired by other departments, but they are now part of central IT.

SaaS applications typically have billing associated with the number of users or access levels of users. This can be easier for setting and maintaining a budget but some of them are using consumption-based pricing so that can be a little more difficult to anticipate. Other “as-a-service” resources can be billed based solely on usage. Their costs can surge during peak times unexpectedly or the resources can be running and racking up expenses with no oversight.

Cloud Resource and On-Premises Inventory

As private, public, and on-premises resources are running together, IT departments will benefit from the ability to discover and maintain an inventory of every environment. In some cases, they can do this with all of the native consoles for a particular environment. For example, they can log in and manage their on-premises inventory for virtual machines (VMs) using tools like VMware vCenter. For other public providers, such as MS Azure, Amazon Web Services (AWS), and Google Cloud Compute (GCP), they can achieve a view of a similar inventory of resources and usage within the clouds themselves.

As most enterprises are adopting a range of cloud resources to meet the growing needs of their users, the ability to maintain a view of the inventory and usage can get overwhelming quickly. For that reason, they seek ways to consolidate views and make it easier to manage whenever they can. Having a robust hybrid cloud management platform that provides this visibility to you in one place will greatly reduce this struggle.

Provisioning and Orchestration

Having the ability to provision and orchestrate which resources are provided for which users has a significant impact on the overall productivity of an enterprise. IT needs to oversee how resources are created, modified and deleted across their on-premises, private, and public cloud environments. Most enterprises now have resources from at least two of the three major cloud providers, AWS, Azure, or GCP.

For large enterprises, this process can be taken care of by IT service management solutions that are designed to help users and IT work together to initiate, track, and respond to any need. A lot of the backend configuration and resource presentation comes from central IT.

What can go wrong?

With all of this complexity, there is also a lot that can go wrong. There can be a lack of visibility into one or more of the environments that provide compute power to the organization leading to a bad understanding of what is being used and how much is providing value. When you couple that with tracking multiple users and what they are doing in each environment, IT departments can end up with that storm that catches them by surprise and never ends.

CloudBolt Helps to Weather the Storm

With the right central platform, your IT department can connect to any 3rd-party resource, gather the inventory, and provision new resources to be used by anyone inside the organization. With this capability in place, you can:

No matter how you approach this challenge, having a holistic view of your hybrid cloud environment, coupled with the ability to know costs and which functions within your organization are consuming resources, is going to keep you ahead of the game.

Just as a runaway train can cause havoc, so can uncontrolled IT spending. Over the last few years, IT departments have been sidetracked by DevOps teams and other IT initiatives, while many convinced themselves and the leaders in their organizations to innovate on the edges of traditional IT.  

If you wanted to experiment or get things done faster, you swiped a credit card and rapidly took advantage of IT services that were not offered by the in-house department. In many cases, you were lured into a free trial. giving powerful resources to almost anyone. That was a real eye-opener. Why did it take so long for traditional IT to give you the same resources?

Over time, some business units essentially ran their own IT services from cloud providers and didn’t even bother with central IT. This happened to many enterprises—and will continue to be the case—until the bills start getting noticed by leaders in C-level suites of the enterprise.

When the Chief Financial Officer (CFO) of an organization drills down on how the expenses are aligned to revenue, it’s no longer business as usual.

Runaway IT

A lot of resources are being provisioned in clouds or in various places within the enterprise without being accounted for, making it difficult to reign in unnecessary spending. it’s very easy to end up with resources that are dormant or running at a much higher capacity than necessary. As a result of the fast pace, some teams can provision things that no one else in the enterprise knows about or even how to use. As people move on from the organization, these resources go unattended.

Most enterprise IT leaders know how difficult it is to understand their spending without the proper enterprise-wide visibility and control of resources. There are so many departments and so many different ways to get things done digitally. The derogatory term “shadow IT” is now obsolete. In fact, one of our industry analysts refers to this distributed IT as just “shadowy” and not with the same disdain that used to be the norm.

I once worked at a company maintaining two collaboration tools for file sharing. One was a trickle-up enterprise account that occurred when we started using Dropbox for business instead of just for personal. A department lead purchased the enterprise version of Dropbox without central IT approval. At the same time, our central IT was moving to a massive Sharepoint initiative to help with collaboration. Both existed for a while. I’m sure since it was a large organization, there are possibly terabytes of files that no one knows about that are being counted in storage fees.

Last week, I heard a good tip that can be compared to getting control of a runaway train of IT resources. Put a Post-it on the employee fridge stating, “Please claim your stuff and date it or it will be thrown out by Friday”. Sounds simple, but it works for the lunch room. Something similar can definitely work for IT too.

Visibility and Control for the Hybrid Cloud

With so many cloud providers and so many resources sprawled out in so many places and user accounts, it’s a huge advantage to have central visibility of what is being consumed as well as by whom. Resource accounts might still be active when users associated with these accounts are no longer part of the company.

From a central platform, IT can connect to any 3rd-party resource, gather the inventory, and provision new resources to be used by anyone in the organization.

This helps in the following ways to:

To get a deeper look into how CloudBolt can help you reduce cost and manage VM sprawl, check out our Product Overview

Slow cars can annoy many of us—you see one chugging along in the fast lane and you have to slow down or pass them at your own inconvenience. Alternately, you might be the slow one angering those behind you. Whatever the reason, it’s inconvenient.

The same is true in IT – sometimes you have to go slower than expected because of a lack of resources and other times it takes longer than expected to get the resources you need. Whether it’s you or others around you slowing down work, it can be just as frustrating as a slow-paced vehicle. Productivity is stifled while you and others are essentially driving slow cars in what should be a fast race.

Problematic IT Provisioning

There are many factors that can slow down any IT environment, but here’s a short list of some potentially problematic conditions:

The desire to innovate gets impacted because of the potential ordeal in getting resources efficiently, leading to delays in whatever work is facilitated by the IT resources.

When some users don’t get the resources they want in time, they take risks to get the IT resources they need on-demand from public cloud providers – just one credit card swipe away.

If a well-meaning initiative provides digital innovation without the help of central IT, the hope is that leadership won’t mind.

What’s at risk?

Having all of these disjointed and slow resources for end users within an enterprise will eventually catch up with central IT. Both budget and efficiency will be challenged all the way up to the top. In the meantime, when users get resources they might not have the compute power they wanted, and the turnaround time to fix the issue might make everything even worse.

What happens if the person in charge of the technical aspects of garnering resources moves on to another company? Nothing good.

Self-Service, Centralized by IT

In a previous blog, Balancing Risk and Reward, we discussed a continuum of self-service IT that most enterprises have, ranging from service tickets to a fully managed hybrid cloud platform like CloudBolt.

Many IT leaders are now looking to centralized platforms of self-service provisioning that empower users with easy-to-get IT resources without a lot of back and forth among departments. This makes the central IT department staff the heroes they have always wanted to be.

A centralized platform can help alleviate some of the slow-car scenarios with the following outcomes:

An enterprise hybrid cloud platform with pre-built connections to the most common on-premises, private, and public cloud providers, as well as extensibility to any resources, can help.  

For more information about avoiding slow-car scenarios in your enterprise IT environment, check out our solutions overview

Anything involving data processing requires the movement of information, and moving stuff is not fun. No amount of pizza or beer can entice friends and relatives to help you on a moving day – they conveniently have other plans but are happy to pitch in any other day.  

Enterprises have a similar, possibly dreadful proposition. There is a ton of data everywhere, which can be incredibly cumbersome to deal with when needed. Just like on moving day, where a basement full of unused exercise equipment or overstuffed closets of memorabilia that you just can’t let go of ends up going with you instead of being tossed, enterprises typically have huge data sets that can be anywhere in the data center or at a remote, physical site for archival data.

Maintaining all of this might be useful for an auditing requirement or a backup and restore scenario, while other data is stuck in random places because no one has time to figure out what to do with it and the effort’s not worth the expense.

Big Data for the Enterprise

But wait! Many enterprises are now upping their game for addressing the value of data because of how much easier it is to get and store. The ability to get data from just about anywhere and to do more comprehensive analysis can help with new digital initiatives. Although this data is no fun to move or maintain, it’s a lot cheaper than it used to be. Data scientists can now mine both real-time and historical data a lot easier than ever.

Insights from what is known as big data drive anything from improving booking rates for hotels to reducing errors in cancer diagnosis. Big data was first defined as the combination of data volume, velocity, and variety, and a fourth quality is now been introduced – veracity.

To put it simply, big data gives you the ability to get value from super-large data sets. The value can come from analyzing multiple data sets in parallel in order to find correlating factors, discover anomalies, and predict outcomes. Typically, this is done using machine learning algorithms that look for specific patterns that reveal which information is not necessarily evident from traditional statistics used to quantify minimums, maximums, and averages of data sets.

For example, a big data insight would be something like this: someone who typically buys rain gear during the summer months is more likely to book a vacation rental in a wilderness setting.  A travel site would then figure out how to target advertising for this more qualified potential customer.

More everyday companies using big data include Netflix, where big data helps to suggest what movie you should watch next, or Starbucks, which crunches numbers to determine where new stores should be located, in some cases placing them only blocks from each other. Most folks might have a hunch that having the same store in the same proximity would be a mistake but the big data insights tell a different story.

Key Components of Big Data

The key components of big data for enterprises require data sets and analytics from software designed to execute the necessary algorithms. Apache Spark and Hadoop clusters provide the processing environment for the large volume of data.

Big Data for Hybrid Cloud

A lot of enterprises that first started working with big data initiatives did so on-premises. Big data typically needs infrastructure that requires a lot of attention. You have to set up Hadoop clusters and have Apache Spark in a separate networked environment, and then IT has to maintain it. This can require petabytes of storage, a capital expenditure (CapEx) required for getting it all set up, and an operating expenditure (OpEx) for all the expertise needed just to manage the data flows regardless of any analysis.

Recently, enterprises have begun moving their big data processing entirely or partially to major public cloud providers such as AWS, MS Azure, and GCP. The advantage is that this eliminates the CapEx for the computing environment, giving them the ability to scale on demand. Specialized knowledge for maintaining the environment is no longer necessary.

Enterprises realize that their existing attempts on-premises, although had great intentions, do not provide the same value that big data processing can do all or in part in a public cloud. This also provides the perfect use case for a hybrid cloud strategy were some of the data sets can still remain on-premises, regardless of where the processing is taking place.

Enterprises have also considered moving all or part of their data sets to public clouds into what are called data lakes for big data processing where a combination of many kinds of data can be accessed easily allowing insights to deliver value in real time.

CloudBolt Helps with Big Data

IT leaders turn to CloudBolt for all things hybrid cloud, and big data is no exception. Big data initiatives can often span the hosting of the resources either on-premises or in a public cloud, and data can be accessed in any part of the enterprise ecosystem. Please refer to last week’s post about Hybrid Cloud and Enterprise Digital Ecosystems for more information.

To see exactly how CloudBolt helps you manage your big data, check out our simple Solutions Overview