Data Protection & Getting Started (Trial Walkthrough)

Post 6 — the finale of my Everpure Cloud series. If you’re just joining, Post 1 has the full roadmap and the “why” behind all of this.

We’ve covered what Everpure Cloud is, the architecture underneath it, the workloads it supports, and the cost model. This last post covers the part that matters most when something actually goes wrong: data protection. Then we’ll walk through how to actually get your hands on it.

Immutable snapshots and fast recovery

Data protection in Everpure Cloud centers on immutable snapshots paired with fast recovery. A few reasons that combination matters more than it might sound like at first glance:

• Immutability means a snapshot can’t be altered or deleted within its retention window — including by a compromised account or a ransomware event trying to wipe your recovery points along with your primary data. This has become table stakes in any serious data protection conversation, not a nice-to-have.
• Fast recovery is the other half of the equation that often gets less attention than it deserves. A protection strategy is only as good as your actual recovery time — and if restoring from a snapshot takes hours you don’t have during an incident, the protection existed on paper more than in practice.

Because this all runs on the unified data plane we covered in Post 3, protection behavior is consistent whether your data is sitting on-prem or in the cloud — which closes a gap that trips up a lot of hybrid environments, where DR runbooks quietly assume on-prem-only behavior and fall apart the moment part of the environment moves.

Governance across environments

The other piece worth calling out: centralized data management with unified control and governance, spanning wherever your data actually lives. If you’ve ever had to answer an audit question about where a specific dataset is protected and how, and the honest answer involved three different consoles, you already understand why this matters.

This is also showing up in newer platform details, not just the big architectural story. On the AWS side, for example, a recent update changed Everpure Cloud Dedicated so that associated Lambda functions run inside your own VPC by default instead of outside it — a small-sounding change, but exactly the kind of network-isolation detail that governance and compliance teams actually check. It’s a good example of how the “unified governance” pitch is meant to hold up down at the implementation level, not just at the marketing-slide level.

Getting started: the trial walkthrough

Here’s the practical part. Two paths, depending on which deployment model from Post 2 fits your situation:

Everpure Cloud Azure Native

• Fully self-service: a 30-day free trial is available directly through the Azure Marketplace
• No sales call required to start — you can be testing this inside your own Azure environment same-day
• Best path if you’re Azure-only and want to move fast

Everpure Cloud Dedicated

• Purchased directly through an Everpure partner, or via the AWS and Azure Marketplaces
• Free trial options are available, but expect the process to run through a partner conversation rather than pure self-service
• Best path if you’re multi-cloud or need the customer-managed control model

My honest advice: don’t evaluate this in a vacuum. Go back to Post 4, pick the use case that actually matches a workload you run today, and structure your trial around proving (or disproving) the claims for that specific workload — not a generic “kick the tires” exercise. You’ll get a far more useful answer in 30 days that way.

Wrapping up the series

When I started this series back in Post 1, I said I didn’t know exactly where I’d land by the end. Here’s where I actually landed: the interesting thing about Everpure Cloud isn’t any single feature — it’s that the cost predictability, the protection model, and the use case flexibility all trace back to the same architectural decision (the unified data plane) instead of being three separate bolted-on capabilities. That’s the kind of design choice that tends to age well.

If you’ve been following along:

1. Why Everpure Cloud?
2. Azure Native vs. Dedicated
3. The Unified Data Plane
4. Real-World Use Cases
5. The Cost Angle
6. Data Protection & Getting Started — you’re here

Thanks for sticking with the series. If you found it useful, I’d genuinely love to hear from you — drop a comment, or find me on LinkedIn. And if you’re not subscribed yet, now’s the time — I’ve got more of these vendor deep-dives planned, and I’d rather you hear about them from me than stumble across them six months late.

The Cost Angle: FinOps, Predictable Pricing & Data Efficiency

Post 5 in my Everpure Cloud series. If you’re catching up, Post 1 has the full roadmap.

I’ve sat on both sides of the table on this one — as a customer defending an infrastructure budget, and now as a vendor-side person who has to explain why something is worth what it costs. So this post is the one I’m probably most opinionated about.

The problem with cloud storage costs

Anyone who’s owned a cloud bill knows the pattern: the estimate looks great in the sales deck, and then egress fees, unpredictable scaling, and a dozen line items you didn’t know existed show up three months in. It’s not usually dishonesty — it’s that consumption-based pricing is inherently harder to forecast than a fixed spend, and most teams don’t have the tooling or the discipline to track it closely until it’s already a problem.

This is exactly the gap FinOps as a discipline exists to close, and it’s exactly the gap Everpure Cloud is aiming at with its pricing model.

Predictable, subscription-based pricing

Everpure Cloud is built around a subscription pricing model designed to align with how organizations actually consume cloud services, rather than the raw pay-as-you-go model that makes forecasting so painful. For anyone who’s had to walk into a budget review and explain a surprise variance, “predictable” isn’t a nice-to-have — it’s the difference between infrastructure spend being a solved problem or a recurring fire drill.

Built-in data efficiency

The other half of the cost story is data efficiency — features designed to reduce the actual footprint of what you’re storing, which reduces what you’re paying for in the first place. This matters more than it sounds like on paper: efficiency gains compound. A modest reduction in stored footprint doesn’t just save you money this month, it changes your growth trajectory over the life of the subscription.

Questions to ask before you commit budget

If you’re the one who has to defend this line item to your CFO or your infra budget owner, here’s what I’d actually ask a vendor (or find out for yourself in a trial):

1. What’s actually included in the subscription, and what triggers additional cost? Predictable pricing only helps if you understand where the edges are.
2. How is data efficiency measured, and does it apply consistently across on-prem and cloud? This ties directly back to the unified data plane conversation from Post 3 — efficiency claims are only as good as the consistency of the platform delivering them.
3. What does scaling up actually look like operationally, not just financially? A predictable price is only half the story if scaling requires a project every time.
4. How does this compare to what you’re already paying today, apples to apples? Don’t compare a subscription quote to a rough estimate of your current spend — get your actual current numbers first.

Why this matters for the series as a whole

Cost conversations tend to get treated as a separate track from architecture conversations, but they’re not — they’re downstream of everything we’ve covered so far. The unified data plane (Post 3) is what makes consistent efficiency possible across environments. The use cases (Post 4) are what determine your actual consumption pattern. This post is really just where those threads get translated into a number your finance team will ask you about.

Coming up

Last stop in the series: Post 6 covers data protection — immutable snapshots, fast recovery — and walks through actually getting started with the trial. If you’ve read this far, that’s the practical payoff post.

Subscribe below so you get it the moment it’s live.

Real-World Use Cases: Azure VMs, AVS, EC2, EVS & SQL Server

Post 4 in my Everpure Cloud series. New here? Start with Post 1 for the full roadmap.

We’ve covered the “what” (Post 2) and the “how” (Post 3). Now let’s get into the “so what” — the actual workloads people are running on Everpure Cloud today. If you’re evaluating this for your own environment, this is probably the post you skipped ahead to, and that’s fair.

Azure Virtual Machines

This is the use case that’s moved the most recently, so it’s worth spending extra time here. Everpure Cloud Azure Native for Azure VMs — a fully managed offering jointly engineered by Everpure and Microsoft — reached general availability in 2026. It lets you provision enterprise-grade block storage volumes and attach them directly to Azure VMs, fully managed inside the Azure portal. No appliances to stand up, no separate storage stack to stitch together: volumes mount as standard Windows or Linux disks, with thin provisioning, deduplication, and compression built in, and capacity and IOPS scale independently of compute.

For teams standardizing on Azure, this is now the lowest-friction entry point into Everpure Cloud — and given how recently it hit GA, it’s worth checking the current release notes for supported regions and configurations before you plan a rollout.

Azure VMware Solution (AVS)

This one’s personal for me, given my VMware background. AVS lets you run a native VMware SDDC inside Azure, which is a great option for organizations that aren’t ready (or don’t want) to re-platform their applications to be cloud-native, but still want the operational and financial benefits of running in Azure.

The wrinkle with AVS has always been storage — VMware environments have specific expectations around how storage behaves, and translating that cleanly into a public cloud context isn’t trivial. Everpure Cloud’s support for AVS is worth a close look if you’re supporting VMware workloads in Azure and want storage that doesn’t require you to relearn how you think about capacity, snapshots, or performance.

Amazon EC2

On the AWS side, Everpure Cloud Dedicated extends the same storage-intensive workload support to EC2 instances. This is where the “Dedicated works on both clouds” point from Post 2 actually pays off — if you’re multi-cloud, you’re not learning a second operational model just because you crossed from Azure to AWS.

Worth flagging for security-conscious teams: a recent platform update now deploys all Lambda functions associated with Everpure Cloud Dedicated for AWS inside your own VPC by default, rather than outside it. If your org has network isolation or compliance requirements around where cloud components execute, this is the kind of detail that decides whether a deployment clears review — I’d recommend confirming the exact version/rollout status with your Everpure contact before you rely on it in a compliance conversation.

Amazon Elastic VMware Service (EVS)

The AWS equivalent of the AVS story: native VMware workloads running inside AWS. Same logic applies — if your team already knows how to think about VMware storage operations, EVS plus Everpure Cloud is aiming to preserve that mental model rather than force a rebuild.

SQL Server 2025 on Azure

This is a good one to slow down on, because database workloads are usually where storage performance and protection requirements get the most demanding. Running SQL Server on Azure with Everpure Cloud underneath is positioned around hybrid flexibility — the ability to run demanding, transaction-heavy workloads with consistent performance and data protection whether the primary instance sits on-prem or in Azure.

If you’ve ever had to explain to a DBA why the cloud version of “the same database” performs differently than on-prem, you know why this use case gets its own line item instead of getting lumped in with “general VM storage.”

Which use case should you dig into first?

If I had to prioritize for a reader trying to figure out where to start:

• Already all-in on Azure, standard VM workloads? → Azure VMs is your on-ramp
• Running VMware and don’t want to re-platform? → AVS or EVS depending on your cloud
• Multi-cloud shop? → EC2 + AVS/EVS combo, via Dedicated
• Performance-sensitive databases? → The SQL Server on Azure story is worth a dedicated conversation with your DBA team before you commit to an architecture

Coming up

We’ve talked architecture and use cases — now let’s talk money. Post 5 digs into the FinOps side: predictable pricing, built-in data efficiency, and the questions you should be asking before you sign anything.

Subscribe below to catch it when it drops.

Architecture Deep Dive: The Unified Data Plane

Part 3 in my Everpure Cloud series. Catch up on Part 1 and Part 2 if you’re just joining.

Every vendor in this space has a phrase like “unified data plane” or “single control plane” somewhere in their deck. It’s easy to gloss over as marketing-speak. But since this concept is the actual foundation everything else in the Everpure Cloud series builds on — cost predictability, data mobility, consistent protection — it’s worth slowing down and actually understanding what’s happening under the hood.

What “unified data plane” actually means

At a basic level, a data plane is the layer responsible for actually moving and storing your data — as opposed to the control plane, which handles the management and orchestration decisions about that data. When a vendor says “unified data plane,” they’re claiming that no matter where your data physically lives — on-prem, in Azure, in AWS — it’s being handled by the same underlying operating environment, not three different systems duct-taped together with APIs.

Why does that distinction matter in practice? Because most hybrid cloud pain doesn’t come from any single environment being hard to manage. It comes from the seams — the translation layer between how your on-prem SAN team thinks about snapshots and how your cloud team thinks about them, or the migration project that turns into a six-month slog because the source and destination don’t speak the same operational language.

How this plays out for admins

If you’ve spent any time in the VMware world (and if you’re reading this blog, odds are you have), think about it this way: part of what made vSphere powerful wasn’t any single feature — it was that once you learned the operational model, it was consistent whether you were managing five hosts or five hundred. A unified data plane is trying to deliver that same consistency, but stretched across on-prem and multiple public clouds instead of just across your own data center.

Practically, that shows up as:

• Consistent management — the same operational patterns and tooling whether you’re touching an on-prem array or a cloud-native deployment
• Data mobility without refactoring — moving data between environments without having to redesign how applications talk to storage
• Unified governance — visibility and control that doesn’t stop at the edge of whichever cloud you happen to be looking at that day

The migration angle

The “without refactoring” part is worth sitting with for a second, because it’s usually where hybrid cloud projects go sideways. A lot of storage migrations aren’t hard because moving bytes is hard — they’re hard because the target environment doesn’t behave like the source, so something downstream breaks: a backup job, a DR runbook, an application assumption nobody documented. A genuinely unified data plane is supposed to remove that class of problem entirely, because the operational behavior doesn’t change based on geography.

I’ll be testing that claim more directly in Post 4, where we get into real workload types — including a use case that’ll be familiar to anyone running Azure VMware Solution.

Where this connects to cost and protection

This architecture isn’t just a technical nicety — it’s the reason the two topics coming up later in this series (cost efficiency and data protection) are even possible to deliver consistently. You can’t have predictable pricing across environments if the underlying platform behaves differently in each one. You can’t have consistent immutable snapshots and recovery if protection is bolted on differently per cloud. The unified data plane is the foundation the rest of the pitch stands on — which is exactly why it deserved its own post instead of a bullet point.

Coming up

Part 4 gets concrete: Azure VMs, Azure VMware Solution (AVS), EC2, Amazon Elastic VMware Service (EVS), and a SQL Server on Azure workload example. If you run any of these today, that’s the post to bookmark.

Subscribe below so you don’t miss it.

Why Everpure Cloud?

If you’ve been reading Spooky Solutions for a while, you know my pattern by now. I get curious about a technology, I go down a rabbit hole, and eventually that rabbit hole turns into a blog series. This time, the rabbit hole is Everpure Cloud.

Here’s how I got here. Between customer conversations, VMUG chats, and my own timeline, one theme kept surfacing over and over this year: teams that are done treating “cloud strategy” and “storage strategy” as two separate conversations. Everyone’s running some mix of on-prem, Azure, and AWS, and the pain isn’t the workloads themselves — it’s the seams between environments. Different tools, different cost models, different ways of thinking about data protection depending on where the bits happen to live that week.

That’s the problem Everpure Cloud is built around, and it’s why I wanted to spend some real time with it instead of just skimming a press release and moving on.

Quick naming note before we go further: if you know this company as Pure Storage, that’s still the same company — it rebranded to Everpure in early 2026. Same team, same technology, new name showing up across their products and docs.

So what is it, in plain English?

Strip away the marketing language and Everpure Cloud is a hybrid, multi-cloud storage service that extends enterprise-grade storage across your on-prem environment and the public cloud — specifically AWS and Azure — through what they call a “unified data plane.” The pitch is simple: manage, protect, and move your data the same way, with the same operating model, no matter which side of the hybrid line it’s sitting on.

It comes in two flavors, which we’ll unpack properly in Post 2:

• Everpure Cloud Azure Native — fully managed, baked right into the Azure portal
• Everpure Cloud Dedicated — customer-managed, available on both Azure and AWS

There’s also a cost angle here that caught my attention as a former customer who’s had to defend infrastructure spend in front of a CFO more than once: predictable, subscription-based pricing instead of the usual cloud storage surprise-bill anxiety.

Why I’m doing this as a series, not a single post

Because a single post would either be 4,000 words nobody finishes, or a shallow overview that doesn’t actually help you make a decision. Instead, I’m going to break this down the way I’d want it broken down if I were the one evaluating it for my own environment:

1. Why Everpure Cloud? — you’re reading it
2. Everpure Cloud 101: Azure Native vs. Dedicated — the two deployment models, side by side
3. Architecture Deep Dive: The Unified Data Plane — how the tech actually works
4. Real-World Use Cases — Azure VMs, AVS, EC2, EVS, and SQL Server on Azure
5. The Cost Angle: FinOps & Data Efficiency — what it actually means for your budget
6. Data Protection & Getting Started — snapshots, recovery, and a walkthrough of the trial

If you’ve got specific questions you want answered along the way — cost comparisons, migration gotchas, how this stacks up against tools you’re already running — drop them in the comments or find me on LinkedIn. I’ll work them into later posts where it makes sense.

Let’s go

I’ll be honest, I don’t know yet where I’ll land on this by Post 6. That’s kind of the point of doing it out loud instead of writing a tidy conclusion after the fact. If you’re wrestling with hybrid storage strategy, cost predictability, or just want to understand what “unified data plane” means beyond the buzzword, stick around.

Subscribe below to get the rest of the series as it drops — I’m aiming for every other week so this doesn’t turn into another multi-year gap like my posting history apparently allows for. 😅

Next up: Post 2, where we break down Azure Native vs. Dedicated and talk about who each one is actually for.