Atlassian Cloud features you won’t get in the Data Center. What do you need to know in 2025? 

A quick reality check: In 2025, your Atlassian Data Center per-seat costs will go up again. Not “might”.  Not “could”. Will. History has taught us that.

And that’s before you even factor in the extra costs, like server maintenance, security, and dealing with outages. 

DC users are paying more for yesterday’s tech. Meanwhile, Cloud users are getting new features: AI, automation, and consistent integrations. 

At what point does staying on-prem stop being a preference and start being a bad business decision? 

Let’s talk about what you’re missing.

Keeping everything up to date on-prem takes time and extra effort. Hardware needs regular upgrades, adding to costs and complexity. When something breaks or an incident happens, IT teams have to drop everything to fix it. It leads to delays and frustration.

In the data center, the entire security and compliance workload falls on you. You have to stay on top of patches to prevent vulnerabilities. Admins need to manage backups regularly to avoid data loss. Keeping threats out requires constant monitoring and making sure everything meets compliance standards. 

Marketplace vendors are moving on. Many Atlassian apps are now cloud-first. It leaves data center users with fewer options and outdated versions. As more vendors shift focus, finding compatible apps will only get harder. 

Atlassian adds AI-powered automation, smart issue resolution, and predictive analytics exclusively to the cloud. There is no first-party Atlassian AI for DC. Teams on-prem need custom solutions to add some level of automation or AI. 

The changes are coming. And the later you migrate, the more expensive and stressful it gets. In some cases, delayed migrations have led to increased consulting fees and support challenges. 

It highlights the potential financial risks of postponing the move to cloud solutions. Specific impacts, however, depend on the organization’s unique circumstances.

Cloud solutions offer many modern features and benefits. Still, organizations should evaluate technical and financial aspects before deciding on a migration timeline.

The corporation officially ended support for the server in February 2024. And now, all signs indicate that DC is on the same phase-out path. 

The data center pricing increased by 30% in February 2025. However, if your company uses it, you might have noticed that new features are slowing down. 

Meanwhile, the cloud hosting keeps getting updates.

Why is this happening? There are 3 main reasons for that: 

At the same time, data center users must handle some things manually or find workarounds. Here’s a quick look at what’s exclusive to the cloud and where DC has its limitations:

Cloud users are getting more productive. Data center users still have to struggle with manual processes. 

IT teams handle a high volume of service requests daily. They include tasks from password resets to critical system failures. Without AI automation, they spend countless hours manually categorizing and assigning issues. This leads to slower response times, higher operational costs, and employee burnout.

Atlassian Cloud uses AI to automate key processes, including:

Use case example: Thumbstack resolves 15% of requests with no human involvement, but automation and smarter processes. They saved 180+ hours per month by automating repetitive tasks. It freed up their agents and gave them more time to build a strong knowledge base. 

Data center limitation: Without automation, teams must rely on manual ticket handling. It is time-consuming and increases costs.

Security updates in the data center don’t happen often and require manual installation. For example, you can have SSO and user provisioning only through SAML plugins, Crowd, or LDAP. Not to mention your admin’s time and technical knowledge. 

When it comes to the cloud, Atlassian makes sure businesses always have the latest tools. The company focuses on automation capabilities and security improvements. 

On top of that, updating the hosting doesn’t require any additional effort from the team’s side. Cloud is automatically patched on Atlassian’s schedule.

Atlassian Cloud provides:

Use case example: Rivian company saved 36% of annual tool costs by centralizing on the Atlassian cloud. What also matters is that they’ve consistently had reliable support whenever they needed it. During the discovery phase, Atlassian shared recommendations. During migration, they could use Atlassian tools to ease the transition. Since then, the company has remained open to other improvements. 

Data Center limitation: IT teams must wait for periodic updates, delaying access to innovations. And even when they’re available, admins still have to install them manually. This costs teams more time and is more risky. 

Marketplace vendors have to follow Atlassian’s guidance. As a result, they prioritize Cloud, leaving Data Center users with fewer options to extend the native features. 

Modern enterprises rely on integrations between tools like Jira, Confluence. But it’s not only about Atlassian. Teams also use Slack, Microsoft, G-suite, or Salesforce daily. This is why seamles connection has a great value. Cloud gives it to you natively. 

Of course, you can do some cross-product automation in DC with custom integrations or extra plugins. But it’s less “out-of-the-box” and intuitive. 

Atlassian Cloud simplifies integrations by offering:

Use case example: FATH company struggled with frequent system outages and limited plugin compatibility in their Data Center environment. After migrating to Atlassian Cloud, they achieved 99.9% uptime and reduced costs by 20%. They also gained access to a broader range of integrations and automation tools. 

Data Center limitation: With more vendors shifting to Cloud-first development, Data Center users face fewer integration options. 

A poorly handled incident can cause major downtime. Without automation, IT teams must manually assess the impact, notify stakeholders, and implement changes. Cloud-based ITSM supports real-time impact analysis. Jira Cloud gives teams automated escalations and controlled rollouts. It keeps services stable.

Atlassian Cloud supports ITSM with:

Use case example: Atlassian Intelligence in Jira Service Management Cloud fills in key incident details for you. Thanks to this, teams can quickly review and confirm everything before moving forward. 

Data Center limitation: Manual issue classification and outdated workflows slow down reaction times. This can lead to system issues that directly affect end users.

Software development requires code reviews and optimized DevOps workflows. Instead, in data center environments, developers spend unnecessary time linking tickets and summarizing pull requests. 

Atlassian Cloud optimizes development with:

Use case example: Atlassian Intelligence in Bitbucket helps users generate pull request summaries, release notes, and collect key information.

Data Center limitation: Without AI automation, developers must manually manage all administration work. As a result, they can’t focus on more important tasks, related to the strategic goals. This slows down the release of new features or products. 

Remote teams need a cloud environment for better collaboration. 

With hybrid and remote work being the new norm, teams need collaboration tools available from anywhere. Data center’s reliance on manual updates, separate instances, and limited cross-tool syncing becomes a real problem. 

Atlassian Cloud simplifies collaboration by providing:

Use case example: Mercedes-Benz has 30,000+ users who can collaborate seamlessly on Atlassian Cloud, and the number is still growing. 

Data Center limitation: Teams must manually share updates and ensure they’re in the loop. This causes back-and-forth communication and duplicate work. 

Data Center performance can be very fast if well-tuned.The difference is that with DC, you bear the responsibility. 

Maintaining the data center infrastructure requires costly servers, IT staff, and ongoing maintenance. 

It means that cloud hosting moves the performance and scaling off your shoulders. Meanwhile, DC can require a separate maintenance budget to achieve similar results. How does it work? 

Atlassian Cloud reduces costs by:

Use case example: Mercedes-Benz confirms the impact:

Mehmet Sari
Modern Collaboration Platform Team

Data Center limitation: Data center costs are already high and continue to rise. With Atlassian increasing prices, managing on-prem systems is becoming even harder. Companies must spend more on maintenance, security, and IT resources while getting fewer updates and improvements in return.

Traditional project management tools often require complex setups and structures. Of course, admins have to set up everything manually. The truth is it slows teams down and leaves them behind the competition. 

Cloud brings agility with flexible, ready-to-use solutions. They help teams plan and adapt faster. 

Atlassian Cloud brings innovation by:

Use case example: Nextiva transformed Confluence from a tool used only by IT to an enterprise-wide collaboration hub. Teams across marketing, HR, and sales now use built-in templates and automation to manage projects. It reduces setup time and increases adoption. 

Data Center limitation: Teams must manually structure their projects, plan workflows, and create documentation from scratch. This leads to inconsistent processes across departments.

Atlassian Cloud is advancing, while the gap between cloud and DC continues to grow. Cloud users benefit from automation, updates, and stronger security. 75% of surveyed customers reported tangible returns from cloud migration within three months. 37% of them saw results in under a month.

Meanwhile, data center users face higher maintenance costs, outdated tools, and limited integrations.

Staying in DC will only become more challenging. Vendors are focusing on cloud-first development, leading to fewer apps for on-rem. On the other hand, cloud hosting users are already automating tasks, improving ITSM delivery, and making the most of modern communication. 

Delaying migration isn’t just a technical issue, it’s a financial risk. The longer you maintain on-prem infrastructure, the more costly and complex the transition will be.