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Data Engineering

4 Ways Data Observability Improves the Cloud Migration Process

March 17, 2022
10 Min Read

Hosting business systems and data environments in the cloud offer benefits to enterprises that help them derive greater value from their technology investments and gain competitive advantages. Among these benefits are lower costs, more scalability, better business agility, and more resilient operations. So, it’s no surprise enterprise cloud adoption is on the rise.

Any attempt to migrate data and workloads to a cloud environment must be done with a thoughtful plan that aligns with an organization’s data strategy.  It must include both cloud migration best practices, and a data observability solution that provides a granular view of your data and infrastructure layers to help track costs and performance.

Data Observability to Baseline Performance, Usage, and Cost

Migrating to the cloud offers speed, scale, and performance advantages, but it also introduces variables such as external service providers and usage-based pricing. Data observability can help your team create effective SLAs / SLOs for external service providers and optimize your data operations to get the most out of usage-based pricing.

Making your existing application, infrastructure, and data layers more observable should be your first priority — even before you begin your cloud migration process— because data observability gives you performance, usage, and cost baselines that can inform all your cloud migration decisions.

For instance, data observability can help you track memory availability, CPU resources, and cluster-node status. It can alert data flow congestion, outages, and runaway users or applications. And it can make it easier for data teams to identify root cause problems.

The AI-driven features of a top-end data observability solution can also help you calculate future capacity requirements based on available capacity, necessary buffers, and expected workload growth. And it can also forecast when starved resources or runaway workloads might create performance redlines.

Understand Current and Future Infrastructure Requirements

Start by assessing your current environment. Take inventory of the resources your current, on-premises applications require and the data tools and resources that support them. This will help you determine your cloud server needs and avoid paying for more resources than is needed.

Another important consideration is security and the inherent shared responsibility model of cloud environments. Generally, the cloud is more secure than on-premises environments, but that doesn’t mean you should ignore security. Because you’ll have more areas to secure, it’s easier to make mistakes that will leave you more vulnerable.

To ensure your applications are secure, be sure to take the following steps:

  • Look for cloud solutions with robust security features, such as the ability to encrypt data at rest, or multiple layers of network security to make managing network traffic easier
  • Determine what resources should be private instead of being public
  • Evaluate your internal risks and take steps to mitigate them, such as two-factor authentication

Finally, you should consider how you need your applications to perform after they’re migrated to the cloud.

One of the most common performance concerns is storage access time. For instance, applications that require a high volume of input and output operations per second (IOPS) need to access data quickly. If the cloud storage access is even a few milliseconds slower than your current on-premises system, it doesn’t take much to create an outage. Having those metrics available will help you select a cloud solution with greater hardware resources to meet your needs.

Server node location is also an important factor in choosing a cloud provider. If your users are primarily on the west coast, for example, you’ll need a provider with servers that are also on the west coast.

It’s also important to consider your general requirements, such as user volume, network bandwidth, and storage space. Providers typically offer a variety of options to let you select a system that works best for your needs.

Aligning the Cloud Infrastructure for Your Needs

You might think of the cloud as a big, single entity, hanging out there in the atmosphere, ready to provide you with unlimited storage space. But there are several clouds that serve different business and operational needs.

Understanding these different clouds is important when choosing which one(s) is right for your business.

Public Cloud

This is what most people think of when you mention the cloud. Public clouds are services offered by third-party vendors like Amazon Web Services (AWS), Google, or Microsoft.

Generally, public cloud services are very cost-effective, offered on a pay-per-use basis, or even free in some instances. Because they’re provided by large companies, they have the advantages of constant uptime, good security, and easy scalability.

But the best thing about public clouds is their simplicity. Providers usually have plenty of tutorials, customer support, and other resources available. They don’t require any on-premises infrastructure, and you won’t need your in-house IT engineers to manage your cloud applications.

The ways organizations can use a public cloud include a wide range of possibilities. Many enterprises use them for their website CMS software, CRM, and email. Additionally, companies that don’t have specific needs — especially smaller companies — favor public clouds for their simplicity.

Private Cloud

A cousin to the public cloud is the private cloud. Like the public cloud, private clouds are offered by third-party providers, including the same providers listed above, plus others like Oracle, Hewlett-Packard.

In addition, any organization can set up its own private cloud using its own data center. Private clouds are the most expensive option, as they offer a lot of custom options so they can be tailored to an organization’s specifications.

That makes them ideal for companies and organizations that need maximum control and customization. Government agencies and financial institutions that need to comply with specific security regulations often use private clouds. Private clouds are also ideal for large enterprises whose requirements are complex, as they often have the in-house IT talent to manage the platform.

Hybrid Cloud

As you might expect from the name, a hybrid cloud is a combination of public and private clouds, along with on-premises applications. Companies will typically take this approach if they have sensitive data that needs to be stored securely on the private cloud but still want the simplicity of the public cloud for non-sensitive operations.

The main benefit of the hybrid cloud is flexibility, as it lets you move resources and data between the two as you like. However, it’s more complex because it requires on-site hardware and greater in-house IT capabilities than the public cloud.

Cloud Data Migration Strategies

Cloud migration is not a process that should be executed without a plan. It’s important to determine the best way to prioritize and move data and applications from your existing, on-premises architecture to the cloud.

Once you integrate data observability as part of your cloud environment, you need to understand your requirements and determine the best cloud for your needs, which will allow you to build your migration strategy. There are six main migration strategies, known as the “6 Rs of Migration.”

Rehosting (Lift and Shift)

This strategy involves lifting your entire stack from your on-premises host and shifting it to the cloud. Shifting an exact copy, with few or no changes, offers the fastest migration. This strategy is best for companies that don’t plan to use advanced cloud capabilities in the future.


This strategy involves moving your stack from one cloud to another, keeping the core architecture the same but making additional adjustments to optimize for the new platform. This is a good strategy for conservative companies still gaining trust in the cloud.


Under this strategy, you move your applications to a new, cloud-native product, typically a SaaS platform. Because you’ll be moving from a familiar system to a completely new one, it usually requires re-training on the new platform. This strategy works well for companies moving from a highly customized legacy landscape.


This strategy involves starting over and rebuilding applications from scratch. Companies will typically follow this approach when they need to obtain cloud capabilities their current environment doesn’t offer. It’s the most expensive option, but it’s also the most compatible with future versions.


During the migration process, you may find certain applications to be no longer useful. Under this strategy, you simply turn those applications off. It makes migration easier and lets you focus on the applications you still need.


This migration strategy is not migrating at all and instead keeps certain applications on-premises. Companies may decide to take this approach for a variety of reasons, including maintaining compliance, using recently upgraded applications, or putting off the migration of an application to revisit in the future. Sometimes, it simply makes more sense for an application to remain on-premises.

Operational & Spend Intelligence with Data Observability

Migrating to the cloud is just the beginning. A bigger, more important ongoing challenge is to scale data infrastructure, meet performance baselines, and keep costs under a budget. Acceldata can help you juggle these three priorities effortlessly.

Acceldata can help you validate the migration against existing baselines. It can help you reconcile data during cloud migrations. It can help you optimize performance, infrastructure usage, and cost. And it can help you scale.

Get a demo of the Acceldata Data Observability Platform and learn how you can optimize your data spend, improve operational intelligence, and ensure data reliability.

Photo by Mathew Schwartz on Unsplash

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