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Modern Performant Applications Require Modern Storage

Gary Ogasawara
Cloudian

Modern, cloud-native applications have been steadily expanding beyond development environments to on-premises production workloads. For enterprises, one of the primary drivers for making this move has been to ensure performance and avoid the cost and complexity of moving large workloads to the cloud.

As a result, organizations require a modern storage foundation that can fully support cloud-native environments and emerging technologies, such as Kubernetes, serverless computing and microservices which are significant components of these environments.

The following is an easy-to-follow checklist for building the ideal modern storage foundation:

1. S3 Compatibility

Complete S3 compatibility is critical for today's modern storage foundation as it ensures that applications developed for the public cloud can also work seamlessly on-premises. In addition, S3 compatibility simplifies and streamlines the ability to move applications and data across hybrid cloud environments.

2. Performance

High-level, predictable and scalable performance is a must for today's modern storage foundation. This includes the ability to rapidly complete a read or write operation, execute a substantial number of storage operations per second, and provide high data throughput for storage and retrieval in MB/s or GB/s.

3. Scalability

A modern storage foundation must be highly scalable across four dimensions:

■ Throughput scalability - the ability to run more throughput or process more data per second

■ Client scalability - the ability to increase the number of clients or users accessing the storage system

■ Capacity scalability - the ability to grow storage capacity in a single deployment of storage systems

■ Cluster scalability - the ability to grow a storage cluster by deploying additional components

4. Consistency

Consistency is another key element of modern storage. A storage system can be described as "consistent" if read operations promptly return the correct data after it's written, updated or deleted. If new data is immediately available for read operations by clients after it's been changed, the system is "extremely consistent." However, if there is a lag until read operations return the updated data, the system is just "eventually consistent." In this case, the read delay must be considered against the recovery point objective (RPO) because it represents the maximum amount of data loss in the case of component failure.

5. Durability

A modern storage foundation must be durable and protect against data loss. Truly durable platforms ensure that data can be safely stored for extended periods of time. This requires the inclusion of multiple layers of data protection (including support for numerous backup copies) and multiple levels of redundancy (such as local redundancy, redundancy over regions, redundancy over public cloud availability zones and redundancy to a remote site). To be truly durable, storage platforms must also be capable of identifying data corruption and automatically restoring or reconstructing that data. In addition, the specific storage media that comprises a cloud-native storage platform (e.g., SSDs, spinning disks and tapes) should be inherently physically resilient.

6. Deployability

Cloud-native apps are extremely portable and easily distributed across many locations. As a result, it's critical that the storage foundation supporting such apps be capable of being deployed or provisioned on demand. This requires a software-defined, scale-out approach, which enables organizations to immediately grow storage capacity without adding new systems. A storage architecture that leverages a single namespace is ideal here. Because such an architecture connects all nodes together in a peer-to-peer global data fabric, it's possible to add new nodes (and more capacity) on demand across any location using the existing infrastructure.

7. High Availability (HA)

A modern storage foundation must maintain and deliver uninterrupted access to data in the event of a failure, no matter where that failure occurs. To be considered highly available, storage systems should be able to heal and restore any failed components, maintain redundant data copies on a separate device and handle failover to redundant devices/components.

8. Security

Comprehensive end-to-end security is essential for modern storage. This includes encryption for data in flight and at rest, RBAC/IAM and SAML access controls, integrated firewall and certification with stringent government security requirements such as Common Criteria, Federal Information Processing Standard (FIPS) and SEC Rule 17a-4(f). In addition, modern storage foundations should offer data immutability (i.e., ensure the data cannot be changed/altered/deleted for a designated period of time) to protect data and operations from cyberattacks such as ransomware.

Gary Ogasawara is CTO at Cloudian

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Modern Performant Applications Require Modern Storage

Gary Ogasawara
Cloudian

Modern, cloud-native applications have been steadily expanding beyond development environments to on-premises production workloads. For enterprises, one of the primary drivers for making this move has been to ensure performance and avoid the cost and complexity of moving large workloads to the cloud.

As a result, organizations require a modern storage foundation that can fully support cloud-native environments and emerging technologies, such as Kubernetes, serverless computing and microservices which are significant components of these environments.

The following is an easy-to-follow checklist for building the ideal modern storage foundation:

1. S3 Compatibility

Complete S3 compatibility is critical for today's modern storage foundation as it ensures that applications developed for the public cloud can also work seamlessly on-premises. In addition, S3 compatibility simplifies and streamlines the ability to move applications and data across hybrid cloud environments.

2. Performance

High-level, predictable and scalable performance is a must for today's modern storage foundation. This includes the ability to rapidly complete a read or write operation, execute a substantial number of storage operations per second, and provide high data throughput for storage and retrieval in MB/s or GB/s.

3. Scalability

A modern storage foundation must be highly scalable across four dimensions:

■ Throughput scalability - the ability to run more throughput or process more data per second

■ Client scalability - the ability to increase the number of clients or users accessing the storage system

■ Capacity scalability - the ability to grow storage capacity in a single deployment of storage systems

■ Cluster scalability - the ability to grow a storage cluster by deploying additional components

4. Consistency

Consistency is another key element of modern storage. A storage system can be described as "consistent" if read operations promptly return the correct data after it's written, updated or deleted. If new data is immediately available for read operations by clients after it's been changed, the system is "extremely consistent." However, if there is a lag until read operations return the updated data, the system is just "eventually consistent." In this case, the read delay must be considered against the recovery point objective (RPO) because it represents the maximum amount of data loss in the case of component failure.

5. Durability

A modern storage foundation must be durable and protect against data loss. Truly durable platforms ensure that data can be safely stored for extended periods of time. This requires the inclusion of multiple layers of data protection (including support for numerous backup copies) and multiple levels of redundancy (such as local redundancy, redundancy over regions, redundancy over public cloud availability zones and redundancy to a remote site). To be truly durable, storage platforms must also be capable of identifying data corruption and automatically restoring or reconstructing that data. In addition, the specific storage media that comprises a cloud-native storage platform (e.g., SSDs, spinning disks and tapes) should be inherently physically resilient.

6. Deployability

Cloud-native apps are extremely portable and easily distributed across many locations. As a result, it's critical that the storage foundation supporting such apps be capable of being deployed or provisioned on demand. This requires a software-defined, scale-out approach, which enables organizations to immediately grow storage capacity without adding new systems. A storage architecture that leverages a single namespace is ideal here. Because such an architecture connects all nodes together in a peer-to-peer global data fabric, it's possible to add new nodes (and more capacity) on demand across any location using the existing infrastructure.

7. High Availability (HA)

A modern storage foundation must maintain and deliver uninterrupted access to data in the event of a failure, no matter where that failure occurs. To be considered highly available, storage systems should be able to heal and restore any failed components, maintain redundant data copies on a separate device and handle failover to redundant devices/components.

8. Security

Comprehensive end-to-end security is essential for modern storage. This includes encryption for data in flight and at rest, RBAC/IAM and SAML access controls, integrated firewall and certification with stringent government security requirements such as Common Criteria, Federal Information Processing Standard (FIPS) and SEC Rule 17a-4(f). In addition, modern storage foundations should offer data immutability (i.e., ensure the data cannot be changed/altered/deleted for a designated period of time) to protect data and operations from cyberattacks such as ransomware.

Gary Ogasawara is CTO at Cloudian

Hot Topics

The Latest

Two years ago, almost every customer conversation about AI started with the same questions: Which model should we use? What can it do? Is it ready for the enterprise? Today, those discussions have moved on. CIOs are far more interested in how to govern AI, integrate it with existing systems, prepare their workforce and make it part of everyday operations. The challenge is no longer to prove that AI can deliver value. It's instead about how to embed AI into the business in a way that's secure, scalable and delivers measurable outcomes ...

 

Two things happened to production incidents between 2023 and now, and they did not happen at the same speed. The first is that a class of dependency that barely existed three years ago now accounts for one incident in ten. Incidents disclosed by AI model and AI application providers rose from 1.7% of all disclosed unplanned incidents in 2023 to 10.7% in 2026 year to date, roughly a sixfold rise; that counts only incidents at AI companies themselves, so the true share is higher. The second is that the time to close an incident has not come down ...

When an AI assistant gives an incomplete or incorrect answer, teams often blame the model. They adjust prompts, switch models, increase context windows or test a new retrieval strategy. However the model may not be a problem. In many enterprise AI workflows, the problem begins inside the document-ingestion pipeline ...

If you talk to any security or observability teams right now, they're all fighting the same fire: their tooling was built to ingest X, but their sources are pumping Y and soon to be doing Z. The knee-jerk reaction is always the same: we need more platform. However, this reaction is wrong. Let me explain why, because the solution to this problem is foundational, not financial. Instead of hurling yet more money at the problem, make sure you've done what's needed upstream ...

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

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Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

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