Private Cloud Software

What I dislike is that pricing can still feel high, especially since advanced AI and data capabilities are often sold separately, so costs can add up quickly. The agent-first approach also adds complexity, because teams need to learn governance, observability, AI safety, and performance tuning in addition to the usual admin and development skills. Review collected by and hosted on G2.com.

Salesforce Headless 360 solves the problem of rigid, UI-bound automation by exposing Salesforce as an API-first, agent-ready backend that can be used from anywhere. In today’s scenario, its biggest benefit is that Flows, Apex, Lightning Web Components, and integrations can work together not just inside Salesforce, but also through AI agents and external apps, which reduces manual work, speeds up delivery, and lowers cost for clients. It also helps teams build faster across web, mobile, chat, and other channels without recreating business logic for each one, while still keeping governance, security, and reliability intact. Review collected by and hosted on G2.com.

The UI isn’t great. It’s not very intuitive, and it takes a while to find things you’d expect to be just a click away. It could really use a cleaner, more user-friendly design to make navigation feel simpler and more straightforward. Review collected by and hosted on G2.com.

We mainly use it for backup and email security, and both of those work great for us. It also comes with a lot of other features packed in, but we just don’t end up using them as much. Review collected by and hosted on G2.com.

What I dislike most about VMware Cloud Foundation (VCF) is the sheer operational complexity that comes with managing the entire stack. The promise of automated lifecycle management sounds great on paper, but the reality can be rough during initial bring-up or when running updates. Because everything is so tightly coupled through the SDDC Manager, a single failed pre-check can derail an entire upgrade window. And when something does break, troubleshooting turns into a major time-sink: the error messages are often vague, so you end up digging manually through root SSH log files across vCenter, NSX, and vSAN just to pinpoint the underlying failure. Review collected by and hosted on G2.com.

The main problem VMware Cloud Foundation (VCF) solves for us is the fragmented, chaotic reality of managing traditional, siloed infrastructure. Before we adopted it, compute, storage, and networking were handled as completely separate layers, and our engineering team spent far too many cycles just keeping everything compatible. VCF brings that entire stack together into a single, software-defined fabric. On a day-to-day basis, that means a huge reduction in administrative friction: we can scale resources quickly and troubleshoot from a single pane of glass, rather than bouncing between multiple management interfaces. Review collected by and hosted on G2.com.

What I dislike most about VMware vSphere is how unnecessarily tedious troubleshooting becomes when a core service goes down. If vCenter hits a database lock or an internal service crashes, the web interface can effectively lock you out and only surface vague, generic errors. At that point, you’re pushed into logging into the appliance through root SSH or the VAMI interface, digging through huge directories of scattered log files, and manually restarting services from the CLI. For a platform that presents itself as a premium cloud console, having to rely so heavily on manual command-line triage during critical outages feels outdated and adds avoidable stress during maintenance windows. Review collected by and hosted on G2.com.

The main problem VMware vSphere solves for us is the huge waste and physical clutter that comes with running an unvirtualized data center. Before we adopted it, deploying a new application usually meant ordering, racking, and configuring a dedicated physical server—only for most of that hardware to sit idle, using just a fraction of its real computing capacity. vSphere addresses this hardware sprawl by cleanly abstracting our physical RAM and CPU cores into a flexible, shared pool of resources. The day-to-day payoff is strong operational agility: we can spin up standardized, isolated guest VMs in minutes, while significantly reducing our power and cooling needs and shrinking our overall data center footprint. Review collected by and hosted on G2.com.

One thing I dislike about AWS Lambda is that it can take some time to understand and configure properly, especially when you’re new to the AWS ecosystem. Cold starts can also be an issue for certain applications where quick response times are important. Debugging and monitoring can sometimes feel a bit complicated compared to running a traditional application on a server. Review collected by and hosted on G2.com.

AWS Lambda helps solve the problem of having to manage and maintain servers for small services and backend tasks. I can run code based on events without worrying about provisioning servers or scaling them manually. This saves time and reduces infrastructure work, which lets me focus more on building features and delivering applications. The automatic scaling is also useful when workloads change frequently. Review collected by and hosted on G2.com.

Nothing till now Review collected by and hosted on G2.com.

Akamai Cloud Computing makes it easy to follow up on payments with end-of-month billing, provides quick customer service, and allows flexible instance management. The cheap rates for instances and effective use of APIs and GPUs are crucial for my voice agent services. Review collected by and hosted on G2.com.

There is nothing I dislike about Kinsta. Review collected by and hosted on G2.com.

Kinsta makes deploying and managing WP sites extremely simple while providing me with easy access to all the tools and functions that used to take countless extra hours for us to implement and manage at other hosts, such as Media Temple. Kinsta goes out of its way to help troubleshoot and solve problems every single time I go to them to ask if there are any service-level issues I should know about before I troubleshoot client site issues. Rather than simply update me on system status, they always dive in and solve the problems even if they're technically our problems and not service level. Review collected by and hosted on G2.com.

EC2 can become hard to manage once you have a lot of instances, since tracking instance types, security groups, storage, backups, and permissions takes time and attention. The AWS console can also feel overwhelming for beginners because there are so many options and settings to navigate. Pricing is another concern: costs can rise quickly if instances or attached resources are left running unnecessarily, so ongoing cost monitoring is important. Performance is generally good, but selecting the right instance type still requires a solid understanding of the workload. Better cost visibility, simpler configuration, and clearer recommendations for instance selection would make EC2 much easier to manage. Review collected by and hosted on G2.com.

We previously hosted our e-commerce platform’s UA environment on a physical VMware VM, which meant extra effort for server maintenance, hardware dependency, resource management, and scaling. After migrating the UA server to an Amazon Linux 2 EC2 instance, we’ve been able to manage it much more easily and adjust resources as our requirements change. EC2 also integrates smoothly with other AWS services and gives us greater flexibility around monitoring, backups, networking, and security. This move reduced our reliance on physical infrastructure and made provisioning, updates, and other server changes significantly faster. Overall, EC2 has made our e-commerce infrastructure more flexible, easier to maintain, and better positioned for future growth. Review collected by and hosted on G2.com.

The main downside I’ve noticed is that some of the more advanced configurations aren’t very beginner-friendly. If you’re completely new to VPS or cloud hosting, a few of the settings can feel a bit overwhelming at first and may take some time to get used to. Also, certain premium features are only available on higher-tier plans, so when you scale up, the monthly cost can rise faster than you might expect. Review collected by and hosted on G2.com.

We experienced a temporary slowdown on one project’s website during a traffic spike, and the support team quickly helped us optimize server-level caching and resource allocation. After those adjustments, the site’s loading speed became noticeably more stable and consistent. I also appreciated that their technical guidance was practical and solution-focused, rather than relying on generic support replies. Review collected by and hosted on G2.com.

I’m Derek Ortiz, Corporate Technical Content & Instructional Visual Designer at Austin Industrial Tech Documentation Group, a 92-person enterprise industrial software firm in Austin, Texas. I build hardware diagrams, workflow schematics and instructional visuals using SaviDraw. Our team hosts our Confluence knowledge base, DAM asset library and documentation preview environments on DigitalOcean droplets. I manage visual asset version trails and archive customer-identifiable graphics to meet CCPA privacy rules, and I test documentation previews during high-volume release sprints.

The biggest frustration I run into with DigitalOcean is the limited native file versioning and snapshot granularity for our static design asset storage. When I upload exported SVG and PNG technical diagrams to our DAM hosted on DigitalOcean droplets, snapshots only capture full server states, not individual asset file revisions. If I overwrite a SaviDraw-generated workflow schematic and need to revert only that single graphic, I cannot restore just one file. I have to roll back the entire droplet snapshot, which reverts every other team member’s documentation edits on the server. During our last major industrial software release sprint, I accidentally uploaded a mislabeled hardware component diagram and needed to revert it. Rolling back the snapshot erased three other writers’ Confluence page updates, forcing our team to manually recreate that work and pushing our documentation deadline back by half a day. This creates risky, disruptive workflow breaks for our content team.

A second key pain point is inconsistent file upload throughput and slow asset preview rendering when handling high-resolution vector exports. I frequently upload batches of layered PNG and SVG instructional visuals from SaviDraw to our DAM hosted on DigitalOcean. When I push 20+ large diagram files at once during release crunch periods, uploads stall intermittently, and web-based previews of vector graphics lag heavily. Last month, I spent nearly two hours re-trying batch uploads for a set of machine hardware schematics. The slow preview speeds also make it hard for our sales enablement team to quickly review draft visuals hosted on the droplet for feedback. This eats into my diagram drafting time and delays content reviews.

DigitalOcean also lacks simple built-in audit trails for file access to support our CCPA compliance work. I need to track who accesses customer-identifiable visual assets embedded in our technical illustrations, but DigitalOcean does not log file-level reads and downloads natively. I have to add extra third-party logging tools on top of the droplet to capture this activity, which adds setup overhead and maintenance work. There is also no native direct integration with Confluence or our DAM; I rely on manual file transfers or custom scripts to move SaviDraw exports onto the server, which introduces extra room for human error.

Suggestions: I’d like DigitalOcean to add file-level versioning alongside full droplet snapshots, so I can revert individual assets without rolling back the whole server. Improve batch upload stability and vector graphic preview rendering for large batches of SVG/PNG design assets. Build native file-access audit logs for compliance tracking, to simplify CCPA reporting for teams storing customer-related visual content. Native integrations with Confluence and DAM platforms would remove custom scripting work when moving design assets to documentation environments. While DigitalOcean droplets are reliable for hosting our documentation stack, these limitations create extra manual work and release risk for technical content teams managing large libraries of visual instructional assets. Review collected by and hosted on G2.com.

I’m Derek Ortiz, Corporate Technical Content & Instructional Visual Designer at Austin Industrial Tech Documentation Group, a 92-person enterprise industrial software firm based in Austin, Texas. I create hardware diagrams, workflow schematics and instructional visuals in SaviDraw. Our team hosts our Confluence knowledge base, internal DAM asset library and documentation preview environments on DigitalOcean Droplets. I manage graphic asset archives and edit version trails to satisfy CCPA requirements for customer-identifiable visual content during high-volume documentation release sprints.

We struggled with unreliable, expensive legacy VPS hosting that had confusing billing and slow scaling, forcing our small dev team to spend hours manually provisioning servers every time we kicked off a big documentation release sprint, but now we can spin up and resize DigitalOcean Droplets in minutes to host our Confluence instance and DAM library, which has resulted in cutting our infrastructure setup time by roughly 60% and reducing our annual cloud hosting costs by about 22%.

Before moving to DigitalOcean, our documentation stack lived on an older cloud provider with complicated billing tiers and hidden bandwidth fees. Every time we prepared for a major product release, we needed to spin up temporary preview servers for our technical diagrams and instructional content. Provisioning and configuring servers would take the dev team a full day, and unexpected bandwidth charges popped up when my team uploaded batches of high-resolution SVG and PNG schematics from SaviDraw. Our asset previews were slow, and scaling resources required lengthy support tickets. I also had limited ability to quickly create snapshots to back up our visual asset library. During one release cycle, a server crash wiped several draft hardware illustrations, and restoring the backup took nearly four hours, delaying our content review workflow. We also lacked simple firewall controls to lock down our preview environments, which created extra security review work for our engineering team.

Now we host our Confluence knowledge base and DAM asset library on DigitalOcean Droplets. The straightforward dashboard lets our dev team spin up new instances and resize CPU/RAM on demand, so we can temporarily boost server resources during our busy release sprints when I’m uploading dozens of layered technical diagrams. This has resulted in us cutting server provisioning time down from a full day to less than 30 minutes. The flat, predictable pricing eliminates surprise bandwidth charges when I upload batches of SaviDraw vector exports to our DAM. The cloud firewall controls are simple to configure, so we can restrict access to our preview environments only to internal writers and sales enablement stakeholders. I can quickly take full Droplet snapshots before major asset uploads, creating restore points for our entire documentation stack. During our last industrial software release, I uploaded over 40 workflow schematics and hardware component illustrations, and the snapshot feature let us roll back the whole environment quickly when we found a bad asset upload, only losing a few minutes of work instead of hours.

DigitalOcean Spaces object storage also pairs well with our workflow for archiving final visual assets. I export finished SVG, PNG and XAML files from SaviDraw and store them there, maintaining version trails for any customer-identifiable visuals to meet CCPA rules. The simple monitoring dashboard also alerts our team to high server load, so we can pre-empt performance issues before asset uploads start timing out.

Suggestions: I’d like DigitalOcean to add file-level versioning alongside full Droplet snapshots so I can revert single graphic assets without rolling back the entire server. Improve batch upload stability and vector graphic preview rendering for SVG/PNG design assets. Add native file-access audit logs for compliance tracking to simplify CCPA reporting for teams storing customer-related visual content. Native integrations with Confluence and DAM platforms would remove custom scripting work when moving design assets to documentation environments. Even with those gaps, DigitalOcean’s simple infrastructure and predictable pricing solved our biggest hosting pain points and gives our content team a stable environment to host our technical documentation and visual asset library. Review collected by and hosted on G2.com.

I really haven't had any dislikes with their platform as of yet. Everything has been a smooth experience. Review collected by and hosted on G2.com.

Control Plane is making it easy for me to run my SaaS company and easily spin up tenants for customers in whatever region I need while keeping my costs low. Being a small business, the low costs are an important aspect of this. Review collected by and hosted on G2.com.

- no german hoster available, only big american hosters Review collected by and hosted on G2.com.

Hosting our "mono repo drupal application" as a "poly site project".

Every tenant has their own:

- database

- filesystem

- feature flags activated

All from one code base.

Deployments can be triggered manually or automatically, easy to handle.

Setup of new client infrastructure can be automated. And is up in minutes to run the same code in a new project.

I can focus on developing the application and don't have to be afraid of handling the infrastructure for it.

We self-hosted Lagoon for 1/2 year and switched to a fully managed service by Amazee. Best decision ever for my work-life balance as CTO. Review collected by and hosted on G2.com.

One area that could be improved is greater transparency and predictability in pricing as applications scale. More detailed cost breakdowns, better resource usage insights, and additional control over infrastructure configuration would help developers optimize performance and manage costs more effectively. Review collected by and hosted on G2.com.

Railway simplifies the process of deploying and managing backend applications by reducing the complexity of infrastructure setup, server configuration, and deployments. As a backend developer working with Python, Django, and databases, it helps me deploy applications faster, manage environments easily, and spend more time building features instead of handling infrastructure. This improves development speed and makes application maintenance much easier. Review collected by and hosted on G2.com.

It always requires a strong, reliable internet connection to access the application. Also, because it’s serverless, debugging can sometimes become complex. Review collected by and hosted on G2.com.

It addresses infrastructure overhead and wasted costs during code execution by offering an event-driven, serverless compute model. Review collected by and hosted on G2.com.

While operating with a large chunk of server deployments, we face a few issues. Mostly they are simple to resolve from our end and in case it its a high priority issue, then we connect with Morpheus Customer Support Team who resolve our production issue at minimal time. Recently we had a problem with cloud sync and its support team updated the database schema which effectively resolved the problem. Review collected by and hosted on G2.com.

While working with backup integrations in AWS, Morpheus Data provides usage of stored procedures & credentials in its platform. This reduces the complexity involved with accessing the AWS resources as all the IAM roles and policies are defined in their utility. We can also provide specifications on runtime for our external systems without interrupting our tasks which is helpful. This eliminates the need to rebuild the plugin every time we do modifications to the user credentials and this feature saves a lot of time. Review collected by and hosted on G2.com.

Hostwinds known to be a little pricier than other providers perhaps, but I switched to them from a lower-priced provider so I could get honest feedback about my site and about my business. Review collected by and hosted on G2.com.

The service is not costly. Support is online any time I contact them. Review collected by and hosted on G2.com.

There isn't anything I dislike about HostArmada. I've had an extremely positive experience with them. Review collected by and hosted on G2.com.

I'm using it for my web hosting. They've made everything seamless. From the initial set up. To any issues, which have been minimal. And when I do, their level of support has been exceptional. Review collected by and hosted on G2.com.

So far nothing, UI is clear, integrations are clear and performance has been great. Review collected by and hosted on G2.com.

It allows us to have IT infrastructure inside the EU and with green technology while making it affordable for a company of our size. We also have the knowledge that there is someone we can reach out to without another bill attached for every conversation rather the opposite. Review collected by and hosted on G2.com.

Build times become more noticeable in monorepos and in projects with a large number of generated pages. Caching helps when enough of the previous build can be reused, but changes that invalidate a large portion of the project can still take a while. On a small application, that delay is easy to ignore. Once several developers are opening pull requests and each one generates a preview, concurrency and overall build consumption start to become part of the delivery conversation. Deploy Previews reduce the work of maintaining temporary environments, but they don’t make those environments free. Review collected by and hosted on G2.com.

A checkout redesign had already passed local testing when the client asked marketing, design, and QA to review the variants before anything reached production. The pull request produced a Deploy Preview with its own configuration, the Netlify Functions used by the new flow, and a payment variable pointing to the test environment. Design left feedback through the Netlify Drawer, and QA caught an issue that only showed up when a user returned from the payment provider. The Function logs made it clear that the same callback was being processed twice. We corrected the idempotency logic, updated the pull request, and everyone re-reviewed the fixed version using the same preview link, rather than waiting for another temporary environment to be set up. After release, a dependency triggered a failure on a less frequently used route, so we used Instant Rollback to restore the previous deploy while the fix was being prepared. Netlify didn’t prevent the defect, and it didn’t replace proper test coverage. What it did change was how quickly the team could review the real build, trace the problem to the exact Function version, and recover production without having to improvise a rollback while the client was already watching. Review collected by and hosted on G2.com.

Some development and multi-environment workflows are limited on the free plan, so teams may encounter plan restrictions earlier than expected.

Protected Preview deployments can also create friction when sharing a build with testers or reviewers. Authentication adds security, but it can make external review more complicated. Environment variables must be assigned carefully to Preview and Production, and a redeployment is usually required after changing them.

The dashboard is powerful, but deployment settings, domains, environment variables, build logs, and runtime information are spread across several sections. This can take time to learn when troubleshooting a release. Review collected by and hosted on G2.com.

Vercel provides the deployment and hosting workflow for our Next.js SaaS application without requiring us to maintain dedicated web infrastructure. It gives us isolated Preview environments for testing, automated Production deployments, custom-domain hosting, and visibility into build and runtime health.

The biggest benefit is release confidence. We can connect a deployment to an exact GitHub commit, test it before merging, and verify that the same approved code reaches Production. This has made our release process faster, safer, and easier to manage. Review collected by and hosted on G2.com.