We know what application resiliency is and how to measure it. Now there’s the big question: How do you actually improve it? Unfortunately, there’s no simple answer. Building and managing resilient cloud-native applications is challenging, affecting everything from your development to your infrastructure to your services. So becoming more resilient is an ongoing, iterative process that involves testing, learning from outages, and evaluating your service providers.
But it is possible, and the tools you use can make a big difference. For example, your data protection platform can reduce your RTO and boost your resilience.
So what are you using for data protection for your cloud-native apps? And is it helping or hurting your resiliency?
Data Protection for the Cloud: What Boosts Application Resiliency?
Data protection for cloud-native applications typically takes a few forms. You might use legacy backup solutions that existed pre-cloud, the tools inside of your cloud environments, or solutions built specifically for the cloud.
But which of these gives you the best protection and recovery capabilities so you can restore fast when the unexpected happens? Let’s take a look.
Legacy data protection
Legacy data protection options, as the name suggests, have been around before the cloud. Because of that, they’re not built for dynamic, containerized workloads. Instead, they:
- Work best for monolithic, static applications: Pre-cloud applications weren’t as flexible or scalable, so their data protection approach didn’t need to be either. Instead, they didn’t change often and often depended on their operating system.
- Primarily capture data volumes only: Legacy data protection focuses on storage and data volumes, aiming to protect data in its purest form.
But legacy providers have evolved and some offer protection for Kubernetes and containers, too. Unfortunately, that protection doesn’t cut it either. For example, some vendors require a virtual machine or bare-metal host to protect Kubernetes, increasing overhead and adding infrastructure.
These solutions also don’t scale as your environment does, which is a huge benefit to using containers in the first place. And they’re not multi-tenant, meaning they’re not set up to support the very architecture that cloud infrastructure is built on.
Because of these limitations, using a legacy data protection solution with your cloud-native applications introduces a layer of complexity. So when outages happen, you’re spending more time and money to restore your data and operations. As a result, your resiliency takes a hit.
Nicholas Merizzi, a principal at Deloitte Consulting, sums it up in a recent Tech Target article:
“When we think of backup and recovery in the cloud, traditional methods need to evolve.”
Your cloud storage and database providers offer some backup for your applications. But are they enough? The short answer is no, especially if you’re running multiple cloud-native apps in production. Here’s why.
Most cloud storage and database providers can take snapshots that can then be combined via scripts to restore your data in the event of an outage. But this approach has limitations, such as:
- Reliance on manual tasks and individuals: Writing scripts is a manual process that relies on individuals, making errors more likely. Because K8s apps are dynamic and constantly changing, your scripts have to reflect those changes, too. And rewriting scripts takes time, resources, and specialized skills that are often difficult to find.
- Incomplete data: Snapshots aren’t complete pictures of your applications. Instead, they leave out critical context, like metadata, that you need to restore your application and resume operations.
- Inability to scale: They also don’t scale along with your applications. As you grow and have more apps in your environment, you have to identify what storage and what database go together. When outages happen, “it can be difficult to find the right snapshot to restore and to decide what to keep and what to delete,” points out Enrico Signoretti of GigaOm.
- More susceptible to disaster: Many snapshots are local to the storage system, making them less disaster-proof.
With snapshots of your data only, you’ll need more resources—time, money, and people—to rewrite scripts as your apps change and to manage the process. And when an outage occurs, you’ll need to determine what point-in-time snapshot to restore and what application it’s associated with, a big challenge with the dynamic nature of Kubernetes applications.
This strain on your resources hurts your resiliency, too. Now what?
Cloud-native data protection
The third and best option for making resilient cloud-native applications? Cloud-native data protection. These platforms were built in the cloud and for the cloud, so they scale with you easily. And the best ones can run on any cloud, making it easier to backup your environment no matter your infrastructure.
Here are some key reasons to use data protection built for the cloud.
- Native K8s integration: Solutions that are cloud native are dynamic and can scale up and down depending on your needs. This helps you use your resources efficiently. Additionally, Kubernetes-native platforms can support new Kubernetes versions quickly to keep up with the tech and keep you protected.
- Comprehensive protection: Cloud-native data protection platforms support way more than just your data. Instead, they backup your application at every level, right down to your metadata and K8s objects. And they allow you to backup your applications based on how you manage them—whether it’s by namespace, label, Helm, or Operators.
- Multi-tenant and self serve: Because Kubernetes is multi-tenant, your data protection should be, too. This way, you can ensure that the right people can perform the tasks they need to without needing admin help. So when you need to backup, restore, or migrate, it’s faster and more efficient.
- Versatility: Since Kubernetes is a multi-cloud cloud operating system, your data protection solution must be able to manage applications running in different K8s clusters spanning multiple clouds or data centers.
Mike Williams, a managing delivery architect at Capgemini North America, outlined another benefit in a Tech Target article:
“The most important benefit of this approach is that it enables cloud storage and data protection management via code, aligning it with cloud-native paradigms and not sacrificing or exposing data.”
What does all of this mean for you? Faster recovery times. Limited data loss. Efficient operations. Continued service. More resilient cloud-native applications. The choice is clear.
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Cloud-Native Data Protection Features to Look For
Cloud-native data protection is the way to go. But with so many options out there, how do you choose the right one? And what features do you need to boost resiliency?
Prioritize those that…
Work for all clouds, storage, and K8s distributions: This means you can easily move your data between services, giving you flexibility and avoiding vendor lock-in.
Are application-centric: Then, look for platforms that allow you to backup and restore all components of your applications (data, metadata, and all Kubernetes objects) and all ways of managing them (by namespaces, labels, Helm, and Operators).
Scale with you: Another key feature is scalability. Make sure your tool will grow with you, even if you add more clusters, new applications, or an additional cloud.
Are easy to manage: Find a platform that allows you to take advantage of multi-tenancy and to easily manage your data across clouds and clusters without a separate CLI. The right tool should be integrated into your Kubernetes API. Also, platforms with automation features like disaster recovery policies make management a breeze.
What Cloud-Native Data Protection Platform Will You Choose?
Ultimately, your data protection solution should help you achieve faster recovery times through things like multi-tenancy, automatic disaster recovery policies, and application-centric backup. And that leads to more resilient cloud-native applications and organizations.