Matching the cloud database to real workload needs

Sponsored Feature It's easy to see why running enterprise applications in the cloud seems like a no-brainer for chief information officers (CIOs) and other C-suite executives.

Apart from the prospect of unlimited resources and platforms with predictable costs, cloud providers offer managed services for key infrastructure and applications that promise to make the lives of specific tech teams much, much easier.

When it comes to databases, for example, the burden and costs involved in deploying or creating database copies and in performing other day-to-day tasks just melt away. The organization is always working with the most up-to-date version of its chosen applications.Cloud providers may offer a variety of nontraditional database services, such as in-memory, document, or time-series options, which can help the organization squeeze the maximum value out of its data. That's the headline version anyway.

Database administrators (DBAs) know that the reality of running a complex database infrastructure in the cloud and maintaining and evolving it into the future isn't so straightforward.

Consider how an enterprise's database stack will have evolved over many years, even decades, whether on-premises or in the cloud. DBAs will have carefully curated and tailored both the software and the underlying hardware, whether regionally or globally, to deliver the optimal balance of performance, cost, and resilience.

That painstaking approach to hardware doesn't encompass only compute. It applies just as much to storage and networking infrastructure. International Data Corporation (IDC) research shows that organizations spent $6.4 billion on compute and storage infrastructure to support structured databases and data management workloads in the first half of 2023 alone, constituting the biggest single slice of enterprise information technology (IT) infrastructure spending.

As for the database itself, it's not just a question of using the latest and greatest version of a given package. DBAs know it's a question of using the right version for their organization's needs, in terms of both cost and performance.

That's why DBAs may worry that a managed service won't offer this degree of control. It might not support the specific license or version that a company may want to put at the heart of its stack. Moreover, some DBAs might think that the underlying infrastructure powering a cloud provider's managed database is a black box, with little or no opportunity to tune the configuration for optimal performance with their preferred software.

Many database teams - whether they're scaling up an existing cloud database project or migrating off-prem - might decide the best option is a self-managed database running on a platform like Amazon Web Services (AWS). This gives them the option to use their preferred database version and their existing licenses. It also means they can replicate their existing infrastructure, up to a point at least, and evolve it at their own pace. All while still benefiting from the breadth of other resources that a provider like AWS can put at their disposal, including storage services like Amazon FSx for NetApp ONTAP.

Costs and control

Though the self-managed approach offers far more flexibility than a managed service, it also presents its own challenges.

As NetApp Product Evangelist, Semion Mazor explains, performance depends on many factors: "It's storage itself, the compute instances, the networking and bandwidth throughput, or of all that together. So, this is the first challenge." To ensure low latency from the database to the application, DBAs must consider all these factors.

DBAs still need to consider resilience and security issues in the cloud. Potential threats range from physical failures of individual components or services to an entire Region going down, plus the constant threat of cyberattacks. DBAs always focus on making sure data remains accessible so that the database is running, which means the business' applications are running.

These challenges are complicated and are multiplied by the sheer number of environments DBAs need to account for. Production is a given, but development teams might also need discrete environments for quality assurance (QA), testing, script production, and more. Creating and maintaining those environments are complex tasks in themselves, and they all need data.

Other considerations include the cost and time investment in replicating a full set of data and the cost of the underlying instances that are powering the workloads, not to mention the cost of the storage itself.

That's where Amazon FSx for NetApp ONTAP comes in. FSx for ONTAP is an expert storage service for many workloads on AWS, says NetApp. It enables DBAs to meet the performance, resilience, and accessibility needs of business-critical workloads, with a comprehensive and flexible set of storage features.

As Mazor explains, it uses the same underlying technology that has been developed over 30 years, which underpins the on-prem NetApp products and services used in the largest enterprises in the world.

The data reduction capabilities in FSx for ONTAP can deliver storage savings of 65 to 70 percent, according to AWS. Mazor says that even if DBAs can't quite achieve this scale of compression, scaled up over the vast number of environments many enterprises need to run, the benefit becomes huge.

Another crucial feature is the NetApp ONTAP Snapshot capability, which allows the creation of point-in-time, read-only copies of volumes that consume minimal physical storage. Thin provisioning, meanwhile, allocates storage dynamically, further increasing the efficient use of storage - and potentially reducing the amount of storage that organizations must pay for.

Clones and cores

One of the biggest benefits, says Mazor, comes from the thin cloning capability of NetApp ONTAP technology. Mazor says that it gives DBAs the option to "create new database environments and refresh the database instantly with near zero cost." These copies are fully writable, Mazor explains, meaning that the clone "acts as the full data, so you can do everything with it."

This capability saves time in spinning up new development environments, which in turn speeds up deployment and cuts time to market. Mazor notes that, from a data point of view, "Those thin clone environments require almost zero capacity, which means almost no additional costs."

Moving these technologies to the storage layer, rather than to the database layer, contributes to more efficient disaster recovery and backup capabilities. also provides built-, giving DBAs another way to meet strict recovery time objective (RTO) and recovery point objective (RPO) targets.

These data reduction, snapshot creation, thin provisioning, thin cloning, and cross-region replication and synchronization features all help DBAs to decouple storage - and, crucially, storage costs - from the Amazon Elastic Compute Cloud (EC2) instances needed to run database workloads. So, storage can be scaled up or down independently of the central processing unit (CPU) capacity required for a given workload.

With fewer compute cores needed, costs and performance can be managed in a much more fine-grained way. DBAs can reduce the need for additional database licenses by optimizing the number of cores required for database workloads and environments. Of course, going the self-managed route means that enterprises can use their existing licenses.

This comprehensive set of capabilities means DBAs can more accurately . It also means the cost of running databases in AWS can be further controlled and optimized. It can all add up to a significant reduction in total storage costs, with some customers already seeing savings of 50 percent, according to AWS.

The decision to operate in the cloud is usually a strategic, C-level one. But DBAs can take command of their off-premises database infrastructure and gain maximum control over its configuration, cost, and performance by using Amazon FSx for NetApp ONTAP.

Sponsored by NetApp.

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