What are your options for migrating enterprise applications to the Cloud?

Posted in: Technical Track

Migrating your enterprise applications from on-premises infrastructure to the public cloud is attractive for a number of reasons. It eliminates the costs and complexities of provisioning hardware and managing servers, storage devices, and network infrastructure; it gives you more compute capacity per dollar without upfront capital investment; and you gain opportunities for innovation through easier access to new technologies, such as advanced analytical capabilities.

So how do you get there?

You have a few options. At one end of the spectrum, you could simply wait and rationalize, making continuous incremental changes to gain efficiencies. This is obviously a “slow burn” approach. In the middle is a “lift-and-shift” from your current environment into the public cloud. And at the far extreme, you could plunge right in and re-architect your applications—a costly and probably highly complex task.


In fact, a true migration “strategy” will involve elements of each of these. For example, you could perform short-term optimizations and migrations on a subset of applications that are ready for the cloud, while transforming the rest of your application stack over the longer term.


What to expect from the major public cloud platforms

There are three leading public cloud platforms: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). As Google doesn’t seem to be driving customers to lift-and-shift their applications to GCP, I’m going to focus on AWS and Azure as potential cloud destinations and, for specificity, take Oracle enterprise databases as the use case.


Amazon Web Services

You have two options for migrating Oracle databases to the AWS cloud: infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS).


Deploying Oracle applications in AWS IaaS is much like deploying them on your in-house infrastructure. You don’t get flexible licensing options, but you do have the ability to easily allocate more or less capacity as needed for CPU, memory, and storage. However, because AWS IaaS is virtualized infrastructure, you may experience slower performance due to suboptimal CPU core allocation or processor caches. You’ll also have less flexibility with instance sizes, network topology, storage performance tiers, and the like.


AWS Relational Database Service (RDS) for Oracle is a managed PaaS offering where, in addition to giving you the benefits of IaaS, Amazon takes on major DBA and system administrator tasks including provisioning, upgrades, backups, and multi-availability zone replication. This significantly simplifies your operations—but also results in less control over areas such as configuration, patching, and maintenance windows. AWS RDS for Oracle can also be used with a pay-as-you-go licensing model included in the hourly rate.


Microsoft Azure

Azure does not have a managed offering for Oracle databases, so the only way to run Oracle Database on Azure is through its IaaS platform. The benefits are very similar to AWS IaaS, but Azure offers additional licensing options (with Windows-based license-included images) and its instances are billed by the minute rather than by the hour. What’s important to keep in mind is that Azure is not as broadly adopted as AWS and offers less flexibility for storage performance tiers and instance sizes. Oracle Database software running on Windows is also not as common as running on Linux.


For more in-depth technical details on these options, I encourage you to read our white paper, Migrating Oracle Databases to Cloud. My next blog in this series will look at one other option not discussed here: migrating to Oracle Cloud.


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About the Author

What does it take to be chief technology officer at a company of technology experts? Experience. Imagination. Passion. Alex Gorbachev has all three. He’s played a key role in taking the company global, having set up Pythian’s Asia Pacific operations. Today, the CTO office is an incubator of new services and technologies – a mini-startup inside Pythian. Most recently, Alex built a Big Data Engineering services team and established a Data Science practice. Highly sought after for his deep expertise and interest in emerging trends, Alex routinely speaks at industry events as a member of the OakTable.

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