If your Atlassian tools have become business-critical and you’re starting to have concerns around availability and scalability issues, it might be time to make the switch from Atlassian’s Server products to Atlassian’s Data Center products.
Data Center is Atlassian’s clustered product that handles multiple application servers for the Jira family of products, Confluence, Bitbucket and/or Crowd. You can host Data Center on-premises or in the Cloud; either way you’ll get a system that can add considerable value to your business by addressing these availability and scalability concerns.
When is it time to move to Data Center?
Generally speaking, it’s time to move from Server to Data Center when your Atlassian tools have become critical to the business. At that point, availability and scalability issues make the Server versions of the tools inadequate. For example…
- Usage of your Atlassian tools is very high – You’ve got a lot of users, and this is putting a large load on the system. Consequently, things have slowed to a crawl. It seems like it takes forever to do things, and this is driving people crazy.
- Everyone panics when the system goes down – Jira falls over, and everybody starts screaming at the IT Director, demanding to know why the system isn’t more reliable.
- Disruptions cause serious problems – BitBucket goes down and all development stops, because your developers can’t access source control. Confluence goes down and your remote sales force suddenly can’t write proposals, review proposals or even see their notes. Jira Service Desk goes down and your Customer Service team is unable to accept and resolve service tickets. Of course, this last scenario can seriously harm your company’s brand image. What happens when social media starts lighting up with stories about your suddenly non-existent customer support?
- Service Level Agreements are being demanded – Because of all this, the business’ expectation is now that the system will always be up and available. And they’re demanding that you make this happen.
Once you’ve crossed over this threshold, it’s fairly easy to calculate the return on investment (ROI) associated with moving to Data Center. Simply look at the cost of your people. For example, if your engineering team is only 50% effective when Jira is down, what does an 8-hour outage cost you? Keep in mind that eight hours is a common outage length if data is corrupted and you have to restore from backup. What if this eight-hour outage gets spread across two days? If that downtime would cost you $15,000, and a Data Center license costs less than that, there’s your ROI.
Can you handle a move to Data Center?
If the above discussion points to a need to move to Data Center, the next thing to consider is the complexity of setting up and operating Data Center.
- Can your staff handle the extra complexity? At a minimum, moving from Server to Data Center means introducing a load balancer and shared storage to your environment. If yours is a shadow IT organization and not a full-service IT shop, you may not have that expertise in-house. In addition, there’s the issue of your database. When you’ve got a single database server a System Administrator can usually manage it. Once you move up to a clustered database with high availability, management might require the higher-level skill set of a full-time Database Administrator.
- Does the equipment investment make sense? If you do not already have a shared storage environment, does it make sense to investment in one for this purpose? Same with the load balancer. If you don’t already have a load balancer, does it make sense to buy a hardware load balancer for this one purpose? If not, running the environment on-prem might not be the best option.
Should you run your Data Center in the Cloud?
Cloud service providers offer robustness in their design, flexibility and the ability to let you focus on your core business competencies without having to put so much resources into infrastructure management. However, running Data Center in the Cloud is not the right decision for every organization. Here are two important things to look at:
- Running in the Cloud may not be inexpensive. There’s a perception out there that running in the Cloud on AWS or Azure is an inexpensive way to operate. Because you typically pay a few pennies or less per minute, that’s true for services that don’t remain on round-the-clock. However, when you’re running your services 24x7x365, the Cloud can get rather expensive. And when you add in the complexity of the Data Center environment with a highly available database, shared storage, many application nodes and a load balancer, the cost can add up quickly.
If you already have a VMware environment up and running on-prem, you’ve already paid for that equipment. In this case, moving to the Cloud might not make sense from the “cost of equipment” standpoint.
- You may not have the expertise to manage a Cloud environment. That said, there’s also the issue of staff expertise. If you want to do all of the “cool stuff” in the Cloud and make use of all of the great features that are available, this requires a very different level of expertise than just running VMware in your server room.When you’re running an on-prem system you usually have different teams of people managing the security, network, storage, servers and databases. In other words, in the physical world you may have many people running the environment, each of whom is a subject matter expert in their narrow area. In contrast, when you’re managing a Cloud environment you usually have just one person handling all of that. So to effectively manage the environment in-house you need one person who has all of these skills. Of course, another option here is to work with a company like Coyote Creek; our Cloud Services division can manage your entire Cloud environment for you.
Want to learn more about running Data Center?
Watch our free recorded webinar on “How to Run Atlassian Data Center Products on Azure.” Attendees will learn about the details of Data Center, data migration considerations, and issues surrounding running Data Center on Azure. Then we’ll see how it all comes together by taking a close look at a client use case where we implemented Confluence Data Center in Azure.