Post Syndicated from David Johnson original https://www.backblaze.com/blog/the-storage-fix-devops-has-been-waiting-for/

Developer operations (DevOps) engineers sit at the intersection of development and operations. Their job is to keep pipelines humming, environments consistent, and deployments on schedule, all while juggling uptime, costs, and compliance.

This balancing act leaves little tolerance for surprises. Unfortunately, storage from major cloud providers often delivers exactly that. Built to cover every use case from backups to analytics to streaming, general-purpose storage prioritizes breadth over focus. The result is complexity:

• Tiering rules that shift data unexpectedly
• Pricing models that change with every access pattern
• Dependencies that ripple across services

For DevOps, this type of one-size-fits-all system means hidden costs, shifting performance, and integration headaches right when predictability matters most.

The good news: you don’t need to overhaul your entire stack to regain control. Adding a specialized, always-hot storage layer can resolve DevOps engineers’ biggest storage headaches without forcing major workflow changes.

This post is the second in our three-part series on how specialized storage helps every member of a cloud-native team, including developers, DevOps engineers, and site reliability engineers (SREs). Today, we’ll focus on the payoffs for DevOps engineers.

Storage that works the way DevOps does

For DevOps engineers, storage issues often show up in the middle of critical workflows. A change meant to speed deployments triggers cascading adjustments. A spike in access patterns turns into sprawling invoices and finance tickets. A misaligned rule blocks data right when pipelines need it most.

In the sections below, we’ll dig into how these problems derail day-to-day operations, and how purpose-built cloud storage removes the friction so DevOps teams can stay focused on building and delivering.

Migration without migraines

Swapping a storage layer usually comes with the fear of broken pipelines, incompatible APIs, or weeks of retraining. And the big three cloud providers compound this by tying services together so tightly that even small changes can ripple through deployments. 

That means a tweak meant to improve storage can unexpectedly force adjustments in compute, networking, or identity and access management (IAM). Now, you’re slowing down releases instead of speeding them up.

Specialized storage avoids this trap. With drop-in S3 compatibility and no tier juggling, adding it to your stack requires little more than updating an endpoint and credentials. Pipelines keep running, Terraform and Kubernetes scripts stay intact, and deployments continue smoothly, so storage upgrades feel like routine maintenance, not full migrations.

Invoices without inquisitions

Engineers shouldn’t have to be accountants. But with major cloud providers, storage costs often spike without warning when charges are tied to shifting access patterns, such as frequent reads, writes, or transfers. 

The result is sprawling invoices packed with egress fees, API surcharges, and delete penalties. Finance teams see the bill and demand answers. DevOps teams could spend hours untangling storage math instead of improving automation or hardening pipelines. Every unexplained charge turns into a ticket, and every ticket drags engineers away from engineering.

Specialized storage removes this ordeal. Flat, transparent pricing and no hidden penalties make costs easy to predict and explain. That clarity keeps tickets low and escalations rare. DevOps teams can walk into finance reviews with confidence, backed by numbers that are simple to explain.

Engineering without entanglements

Major cloud provider environments come with a maze of tiers, lifecycle policies, IAM rules, and cross-service dependencies. Managing these isn’t a one-time task; it’s a cycle of effort that eats into engineering time:

• Writing: Defining lifecycle policies and IAM rules to control when data moves between tiers or who can access it.
• Testing: Validating every rule to make sure it doesn’t archive active data, block critical access, or violate compliance requirements.
• Maintaining: Updating policies as workloads evolve, with new buckets, new services, or shifting security mandates.
• Troubleshooting: Debugging typos, misaligned automations, or unexpected interactions that can lead to outages, delays, or surprise costs.

For DevOps, every new policy is another layer of overhead and another chance for something to break. 

Specialized storage ends this cycle. With no lifecycle rules to script or tiers to monitor, you don’t have to spend hours debugging brittle policies. That reclaimed time goes back into what matters: strengthening automation, refining observability, and improving the pipelines your developers depend on.

Growth without gridlock

DevOps isn’t just about keeping today’s pipelines running; it’s also about ensuring infrastructure won’t collapse under tomorrow’s demands.

As organizations layer on AI/ML pipelines, streaming services, or analytics workloads, data volumes surge and access patterns become less predictable. General-purpose storage often struggles under these conditions, throttling performance and forcing DevOps engineers into troubleshooting slowdowns and capacity crunches whenever workloads outpace storage. 

Specialized storage meets these challenges. Its high throughput and penalty-free design scale with demand, so performance holds steady even as workloads expand. Whether supporting AI training jobs or streaming analytics, your infrastructure grows without bottlenecks—and without turning DevOps into crisis management.

Rethink your storage, not your stack

The demands on DevOps engineers aren’t slowing down. They’re expected to deliver speed, reliability, and cost control, all at once. The wrong storage layer makes that harder; the right one makes it easier.

Backblaze B2 was built to make DevOps engineers’ lives easier: 

• Minimal changes: S3-compatible APIs work with Terraform, Kubernetes, ArgoCD, and more.
• Predictable costs: Transparent pricing and little-to-no egress fees.
• Simplified operations: Always-hot access, no tier juggling, no lifecycle headaches.
• Future-ready: High throughput and AI-ready integrations.

You don’t have to rebuild your stack to gain these benefits. Just swap the storage endpoint, redeploy, and get back to engineering.

Tired of troubleshooting tiers or decoding invoices? There’s a simpler path forward. Explore how Backblaze B2 fits into your DevOps workflows, and how much smoother things run when storage isn’t slowing you down.

The post The Storage Fix DevOps Has Been Waiting For appeared first on Backblaze Blog | Cloud Storage & Cloud Backup

Post Syndicated from David Johnson original https://www.backblaze.com/blog/why-cloud-native-developers-need-a-specialized-storage-layer/

Cloud-native developers move fast. Continuous integration and continuous development/deployment (CI/CD) pipelines, containerized environments, and growing performance demands leave little room for delays. Even small bottlenecks can slow momentum, and a common source of slowdown is storage.

Most cloud-native teams default to storage from major cloud providers because it’s convenient and deeply integrated with other services, such as compute, networking, and machine learning (ML). But that convenience isn’t always optimized for development velocity. These platforms prioritize flexibility for a wide range of use cases, not the consistency and speed that fast-moving dev teams need. 

Here’s the good news: Adding a specialized, always-hot storage layer can reduce friction and unlock faster, smoother development—without changing the tools you already use.

This post kicks off a three-part series on how specialized cloud storage benefits every member of a cloud-native team: developers, DevOps engineers, and SREs. 

First up: the developer.

When storage slows you down and how to fix it

When storage underperforms, it disrupts your development loop. Cold-tier delays, unpredictable time to first byte (TTFB), and inconsistent throughput take time away from building and shipping applications, or from supporting AI/ML workloads that depend on fast, consistent data access.

In the sections below, we look at how these issues show up in practice and how specialized cloud storage can help remove the roadblocks to faster development.

Build-test loops without the bottleneck

Fast feedback loops are the heartbeat of cloud-native development. Every delay in retrieving files, artifacts, or dependencies drags out build-test cycles and can also slow AI/ML workloads that rely on quick, repeated access to large datasets.

Delays often come from the way cloud providers structure tiered storage. Data is divided into hot, cool, and cold tiers. While cooler tiers cost less, they’re built for retention, not speed. When builds depend on files stored in these tiers, retrieving them adds latency.

Lifecycle policies compound this by automatically moving files into cooler tiers if they haven’t been accessed for a set period. When developers need those files again, they first have to retrieve them from a slower tier, adding latency and sometimes fees.

A specialized, always-hot storage layer eliminates these delays by removing tiers and retrieval hurdles altogether. All data stays instantly accessible, so artifacts and dependencies are always ready the moment they’re needed. Builds run without waiting for restores, tests execute without interruption, and feedback loops stay tight.

Consistent throughput, no tuning required

With general-purpose storage from major cloud providers, consistent performance doesn’t come out of the box. Developers are left to manage it themselves, often through manual tweaks such as file-size tuning or other trial-and-error adjustments.

But tuning only goes so far. Even if developers adjust file sizes or request patterns, those tweaks can’t overcome the built-in delays of tiered storage systems. To compensate, many teams add caching layers or complex configurations. Those workarounds may patch performance gaps in the short term, but they create their own set of burdens:

• Extra rules and scripts: Moving data between tiers or maintaining caches often requires custom automation.
• Added complexity: Each workaround becomes another system to monitor and maintain, increasing the risk of errors.
• Slower workflows: Rather than focusing on development, teams burn time managing storage mechanics.

Specialized storage eliminates the need for tuning or caching altogether. With high-throughput performance available from the start, developers don’t have to waste time building or maintaining workarounds. No scripts, no caches, and no trial-and-error.

Predictable performance under real workloads

General-purpose cloud storage can stumble when workloads scale. Because storage is tightly coupled with compute, networking, and access controls in big cloud providers’ environments, conflicts between these layers can slow requests or, in some cases, cause downtime. 

These mismatches happen for several reasons:

• Competing goals: Major cloud providers build storage to handle many use cases at once, but that broad design isn’t optimized for any one workload. Compute jobs, in particular, demand consistent speed. The result is a mismatch: infrastructure built for broad efficiency can struggle to deliver reliable performance when applications scale in production, or when AI pipelines push storage and compute simultaneously.
• Complex rules: In big cloud provider environments, storage doesn’t operate in isolation. Access controls, security policies, and service dependencies pile up across layers, and they don’t always work in sync. A permission, routing choice, or automation can create unexpected bottlenecks when combined with other rules.
• Network constraints: High egress and cross-region transfer fees discourage data from moving freely between services or locations. Teams may delay or limit transfers to avoid unexpected costs, but that hesitation creates bottlenecks when workloads need to pull data across clouds or regions.

Together, these issues create hidden instability. Performance that seems fine in testing can falter in production as heavier workloads expose bottlenecks and small delays ripple through applications. 

Specialized storage removes this uncertainty by eliminating the hidden conflicts that come from tightly coupled, general-purpose systems. With reliable, low-latency access that stays steady even under production load, teams don’t have to scramble to fix surprises mid-release. 

It’s time to rethink the storage layer

You don’t need to rip and replace your entire cloud strategy to get better performance. You just need to be strategic about which layers serve which purposes.

For cloud-native developers, that means choosing storage that keeps pace with your workflows, so you can move fast, stay in flow, and focus on code instead of configuration.

Backblaze B2 was built with developers in mind:

• Always-hot access to every object.
• S3-compatible APIs that work with your existing tools.
• Enterprise-grade reliability with the best price to performance in the industry.

Because it plugs directly into the tools you already use, you can add Backblaze B2 to your stack without rewriting workflows or retraining teams. Instead of working around storage, you finally get storage that works with you.

Tired of babysitting your storage or coding around its quirks? There’s a better way. Explore how Backblaze B2 fits into your cloud-native stack, and how much faster things can move when builds run without bottlenecks, performance stays consistent, and new features ship without delay.

The post Why Cloud-Native Developers Need a Specialized Storage Layer appeared first on Backblaze Blog | Cloud Storage & Cloud Backup

Post Syndicated from David Johnson original https://www.backblaze.com/blog/cloud-storage-myths-debunked-part-four-managing-multiple-clouds-is-too-complicated/

Today’s myth feels familiar, because it’s exactly what major cloud providers want you to believe:

Multi-cloud? Sounds like a recipe for chaos. Best stick with one and avoid the hassle.

On the surface, it sounds reasonable. The “big three” clouds promote their all-in-one ecosystems as seamless and unified. One provider, one bill, one console. That should make life easier, right?

Not so fast. The promise of simplicity often hides a different reality: deep complexity, rigid architecture, and vendor lock-in. For many cloud-native teams, what’s pitched as convenience ends up costing time, money, and agility.

This is the final post in our blog series debunking persistent myths about cloud storage. (You can read the first, second, and third articles in the series to get up-to-date.) And, if you’ve ever been told that multi-cloud is messy or risky, this one’s for you.

Integrated ≠ simple

The idea that one provider equals less overhead is seductive. But in practice, integration can mean entanglement. Instead of reducing operational drag, it creates a tightly woven web of interdependent services and proprietary systems, which makes changes slow and expensive.

The all-in-one trap

Big cloud providers’ platforms are sprawling by design. They’re built to meet every need under one roof. However, the supposed benefit of simplicity falls apart once you actually start using that provider’s full range of services. 

When it comes to storage alone, teams must navigate:

• Multi-tier systems (hot, cool, cold) with different costs, speeds, and access methods, each requiring its own performance and cost configuration.
• Complex lifecycle policies and scripts to automate data movement between tiers.

• Intricate IAM setups to manage roles, policies, and permissions across services.

• Proprietary APIs and tooling that create migration headaches and limit portability.
• Console UIs and behaviors that change depending on region or storage class, adding to the learning curve.

• Deep interdependencies across services, where a small change in storage can ripple through compute, networking, and security layers.

What starts as a unified experience quickly becomes a maze of shifting rules and unstable configurations. And the more deeply your architecture relies on these moving parts, the more frustrating your operations become.

Frustration, not flexibility

Not only is it tedious to manage all of this, but it can be risky. Miss a lifecycle rule, and you might incur unexpected fees. Misconfigure access policies, and you could lose visibility into or even access to your own data.

These aren’t edge cases. They’re everyday realities in cloud-native environments where time is tight, systems are complex, and DevOps teams are stretched thin. Here’s what that might look like in practice:

• A developer spins up a test environment without realizing data is landing in a high-cost tier.
• An SRE responds to a latency issue, only to discover the data lives in cold storage and restoring it generates retrieval costs and delays.
• A backup job fails silently because of a permissions misconfiguration buried deep in nested IAM roles.

And when something breaks, support isn’t always fast or personal. Unless you’re a top-tier customer, you’re likely working through ticketing systems, documentation loops, or community forums.

These moments don’t just cause frustration—they drain time, inflate costs, and hinder your team’s ability to move fast with confidence.

Complexity isn’t a multi-cloud problem. It’s a design problem.

Let’s revisit the myth: Multi-cloud is too complicated.

It’s an understandable concern, but one that’s often based on frustration inside a major cloud provider’s ecosystem. When teams talk about complexity, they’re usually describing the friction that comes from navigating sprawling services, managing brittle configurations, and troubleshooting opaque policies within one provider.

The real issue isn’t how many clouds you use. It’s how much complexity one provider can introduce when you try to adapt, integrate, or scale. Vendor-specific tooling, tightly coupled services, and unpredictable costs create the illusion of simplicity—until you need to do something the platform didn’t anticipate.

That’s not a multi-cloud problem. That’s a design problem.

Making multi-cloud work for you

For many teams, multi-cloud isn’t a grand strategy, but something that happens organically. AI workloads move to GPU providers. Content gets delivered through specialized CDNs. Backups shift to more cost-effective and geographically separated storage. Whether by design or necessity, most modern architectures already span multiple clouds.

So the smarter question isn’t “Should we avoid it?” It’s “How do we make it sustainable without adding unnecessary complexity?”

That’s where Backblaze B2 comes in.

Backblaze B2 is purpose-built to make multi-cloud not only possible, but practical—for DevOps, SREs, and developers alike. It’s focused, interoperable, and refreshingly straightforward:

• Always-hot storage: No tier juggling. No lifecycle scripts. Just fast, consistent access.
• S3-compatible APIs: Seamlessly integrates with the tools and platforms you already use, such as Terraform, Kubernetes, ArgoCD, boto3, and more.

• Streamlined IAM and UI: Control access and monitor usage without wading through layers of enterprise-grade configuration.

• Free egress: Move data where you need it and when you need to, without the surprise charges that make multi-cloud cost-prohibitive.

Many teams start small with offloading archives, mirroring backup buckets, or feeding GPU pipelines for AI training. As modular architectures grow, Backblaze B2 scales with them, but without the rigidity or lock-in.

In fact, a 2025 Enterprise Strategy Group study found that many operational tasks, such as storage deployments, storage management, and integration with the hardware and software that they already used took up to 92% less time.

The simple interface contrasted sharply with other Cloud Service Providers’ interfaces that have confusing navigation and multiple options to sort through.

—Enterprise Strategy Group, “Analyzing the Economic Benefits of the Backblaze B2 Cloud Storage Platform,” May 2025.

Multi-cloud doesn’t have to be messy. With the right storage layer, it becomes your cleanest, most strategic advantage.

Want to dig even deeper?

Download the full ebook New Cloud-Native Times Call for New Cloud Storage Approaches to explore how modular, interoperable strategies are changing the cloud-native game.

The post Cloud Storage Myths Debunked, Part Four: Managing Multiple Clouds Is Too Complicated appeared first on Backblaze Blog | Cloud Storage & Cloud Backup

Post Syndicated from David Johnson original https://www.backblaze.com/blog/cloud-storage-myths-debunked-part-three-onboarding-specialized-providers-is-too-hard/

Here’s a myth we hear again and again:

Integrating a new storage provider is too complicated. Migrating data, retraining teams, and reconfiguring tools will take too long and create too much risk.

It’s understandable. Data migrations have a reputation for being messy and disruptive. And let’s be honest, nobody wants to babysit infrastructure when there are products to build. For many teams, just the thought of switching cloud providers feels like a detour they don’t have time for.

But in reality, that fear is often bigger than the actual lift. If your workflows already use standard tooling like S3-compatible APIs, switching to a specialized provider is more like a well-marked exit than a hard left turn.

This is the third post in our series debunking persistent myths about cloud storage—check out the first and second posts—and why a best-of-breed, interoperable approach is actually less disruptive than sticking with legacy hyperscaler models.

Migration anxiety vs. reality

“Storage migration” can sound like it requires weeks of planning and an army of engineers. But if your apps are already using S3-compatible workflows, most of the heavy lifting is already done.

If you know S3, you’re already ready

Many specialized storage providers now support S3-compatible APIs, allowing teams to keep the tools, scripts, and services they already know, such as Terraform, Kubernetes, ArgoCD, boto3, and MinIO.

And because your teams are already familiar with the S3 API and related tools, retraining isn’t a hurdle. The same skills, scripts, and automation frameworks carry forward, keeping onboarding time minimal. In fact, most teams are surprised by how little they need to change to get started.

That means:

• No need to learn a new SDK or storage interface
• No retraining your DevOps team
• No rewriting automation pipelines or batch jobs

In most cases, all it takes is updating your endpoint URL and refreshing credentials. The mental model stays the same, the tools stay the same, and your workflows continue as-is.

You don’t need to rip and replace

Downtime concerns are one of the biggest sources of hesitation when switching providers. But in practice, migrations to S3-compatible cloud storage providers rarely require full cutovers or risky, all-or-nothing switchovers. With a bit of planning, most teams handle migrations incrementally:

• Start by migrating lower-risk datasets, such as backups or archives.
• Validate configurations and permissions as data lands in the new system.
• Slowly expand to production datasets as confidence grows.

Better yet, you don’t have to move everything at once. Many teams adopt phased transitions, running some buckets side-by-side or writing to both systems during the handoff to minimize risk. With a bit of planning and the right migration tools and guidance, you can keep operations stable while gradually shifting workloads at a comfortable pace.

Metadata isn’t a blocker

Migrating files without metadata continuity can break downstream systems, especially if your applications rely on timestamps or version tracking.

Fear not. S3-compatible cloud storage providers can preserve metadata during migration, including timestamps. That means your historical data stays intact and compliant with internal policies or regulatory needs, and you won’t need to reset or alter your data management policies.

Moving isn’t the risk. Staying locked in is.

Let’s flip the narrative. The real risk isn’t switching; it’s staying stuck.

Major cloud provider ecosystems are designed for lock-in. The deeper you go, the harder it becomes to leave. Features that look like conveniences, such as integrated IAM policies, tiered storage, and custom APIs, often become entanglements over time.

Each of these layers is built to reinforce reliance:

• IAM rules tie access tightly to the provider’s own tooling.
• Tiered storage creates dependencies on lifecycle rules and retrieval thresholds. 
• Custom APIs mean even basic storage functions can require provider-specific logic.

And as you expand your usage—adding compute, networking, and security services—everything becomes interdependent. What starts as convenience evolves into constraint. Even small changes to your stack can trigger cascading reviews, system audits, or full reconfigurations.

The result? Innovation slows. Costs creep up. Flexibility disappears.

With a specialized provider, you break that cycle.

Specialized Doesn’t Mean Complicated

Specialized storage doesn’t complicate onboarding. It streamlines it. Solutions like Backblaze B2 are purpose-built to make this shift smooth and sustainable, without the trade-offs or surprises you might expect from switching providers.

• S3 compatibility allows for seamless integration with the tools and workflows your team already uses.

• Granular control means you can choose the tools and providers that work best for your architecture, not the ones bundled into a vendor’s ecosystem.

• Metadata continuity is supported through features like custom upload timestamps, preserving file context during migration.

• Transparent pricing ensures there are no hidden egress fees, transaction charges, or retention penalties to catch you off guard.
• Hands-on support helps you plan, validate, and scale your migration with confidence and minimal disruption.

Breaking out of a single-vendor ecosystem may feel intimidating, but it’s often the fastest way to simplify operations, improve performance, and regain control over your cloud strategy.

The best part? Once you’ve made the move, you’re free to experiment. Multi-cloud strategies become more accessible. Your architecture becomes more modular. And your team can focus on building, not babysitting infrastructure.

Next Up: In the final post in this series, we’ll tackle Myth #4: Managing multiple clouds is complicated. (Spoiler: It doesn’t have to be.)

Want to dig even deeper? Download the full whitepaper New Cloud-Native Times Call for New Cloud Storage Approaches.

The post Cloud Storage Myths Debunked, Part Three: Onboarding Specialized Providers Is Too Hard appeared first on Backblaze Blog | Cloud Storage & Cloud Backup

Post Syndicated from David Johnson original https://www.backblaze.com/blog/cloud-storage-myths-debunked-part-two-storage-isnt-a-big-enough-problem-to-remediate/

Today’s myth might sound familiar:

Storage is a minor cost, so it’s not worth switching from major cloud providers.

It’s easy to see how this thinking takes hold. In many cloud-native projects, storage can be the last concern. Compute, networking, and database services often drive most of the costs. Storage? That’s just where your data sits.

But hidden fees, unpredictable retrieval charges, and surprising performance constraints make storage far more impactful than many teams realize—especially for cloud-native workflows.

This post is the second in our blog series unpacking four of the most common myths and misconceptions about specialized cloud storage—see the first post here—and why an interoperable, best-of-breed approach can enhance and streamline cloud-native app development.

Underestimate the importance of storage at your peril

Major cloud providers offer plenty of storage options, but the real costs aren’t always clear up front. 

The charges you don’t see coming

Between egress charges, API call fees, transaction costs, and minimum retention charges, even small changes in how your application moves or retrieves data can quickly inflate your bill.

What looked affordable at launch can snowball into sticker shock once traffic increases or new workloads start driving more data in and out of storage. A single spike in user activity or analytics queries can trigger thousands (or millions) of storage transactions, each billed individually.

These expenses add up fast, and they’re tough to predict.

The egress trap

Egress charges might be one of the best-kept open secrets among the “big three” cloud providers. Every time data leaves their environment—whether to a CDN, another cloud, or end users—egress fees kick in. And they aren’t trivial.

Frequent data transfers, a hallmark of cloud-native architectures, can quietly devour budgets. The big dogs know this. Once your data is deep in their ecosystem, pulling it out becomes financially painful.

This creates a subtle but powerful form of vendor lock-in, making it harder to shift workloads or storage to more specialized providers.

Vendor lock-in, by design

Major cloud providers bundle storage, compute, networking, and a long list of services into tightly coupled ecosystems. On paper, that integration offers convenience. In practice, it creates real friction if you ever want to move.

Even when using open standards like the S3 API, migrating workloads can require new tooling, careful planning, and extensive testing. Under tight deadlines, the mere prospect of switching providers can feel too risky to attempt.

It’s not just inertia; it’s engineered friction designed to keep you tethered.

Complex storage slows down everything

Bundling storage inside a big cloud provider’s stack might seem efficient, but it often creates fragile setups that slow teams down. Configurations get complicated fast:

• Hot and cold storage tiers
• Lifecycle rules
• IAM policies
• Interdependent compute pipelines

Every added layer increases the odds that something breaks, pulling engineers into troubleshooting instead of building.

Latency-sensitive workloads such as real-time analytics or streaming services are especially vulnerable. Even small missteps can ripple through the user experience.

And when those issues hit, teams scramble to patch things up, burning time and resources that could be better spent moving products forward.

AI workloads bring storage costs into sharp focus

AI-powered applications, from model training to updating retrieval-augmented generation (RAG) pipelines, put heavy demands on storage. These workloads hammer systems with high-throughput reads and writes.

Each refresh or update adds to your bill:

• Delete penalties
• Retention minimums
• API call surcharges

When teams start rationing runs, batching updates, or delaying refreshes just to control costs, innovation slows.

Specialized storage keeps costs predictable and workloads agile

Unlike the “big three” cloud providers, who often hide complexity behind convenience, specialized cloud storage providers like Backblaze B2 take a more transparent approach:

• Clear, predictable pricing means no surprise egress fees, retrieval costs, API charges, or deletion penalties.
• Always-hot storage eliminates the need for lifecycle policies and tier management.
• Open architecture means you stay in control—no proprietary hooks, no walled gardens, and no painful unwinding if your needs change down the road.

For cloud-native teams, this isn’t just a storage swap; it’s an operational upgrade. Streamlined management, lower risk, and transparent costs mean teams can focus on shipping new products and features, not decoding their storage bills.

In fact, Enterprise Strategy Group released a comprehensive analysis of the economic benefits of Backblaze B2 in May 2025. The analysis concluded that Backblaze B2’s storage costs (monthly storage cost + cost of downloads + cost of transactions) were 3.1x to 3.2x lower than alternative cloud storage providers.

Simple, transparent, affordable pricing enabled Backblaze B2 users to spend far less on storage and use the savings to innovate and grow.
—Enterprise Strategy Group

What’s next for you and storage?

If you liked this article, check out the first in the series, “Cloud Storage Myths Debunked: Hyperscaler Storage Is Good Enough for Cloud-Native Apps.” And, stay tuned for the next post in this series, where we’ll tackle myth #3, addressing whether onboarding specialized providers is too hard. (It’s easier than you think.)

Want to dig even deeper? Download the full ebook “New Cloud-Native Times Call for New Cloud Storage Approaches.”

The post Cloud Storage Myths Debunked, Part Two: Storage Isn’t a Big Enough Problem to Remediate appeared first on Backblaze Blog | Cloud Storage & Cloud Backup

Post Syndicated from David Johnson original https://www.backblaze.com/blog/cloud-storage-myths-debunked-hyperscaler-storage-is-good-enough-for-cloud-native-apps/

The big cloud providers already offer everything you need, including storage. So, why complicate things, right?
At first glance, that sounds convincing. Hyperscalers like AWS, Azure, and Google Cloud offer massive service catalogs, global infrastructure, and a wide range of storage options. For many teams, they seem like a convenient one-stop shop.

But in practice, things aren’t nearly as straightforward.

While hyperscalers offer extensive storage capabilities, their multi-tier systems prioritize versatility over optimization. The result? Hidden costs and performance headaches that cloud-native teams can’t afford to ignore.

The claim that hyperscaler storage meets all cloud-native needs because of scale and functionality is a stubborn myth, one of many that still permeate the development landscape.

This post kicks off a blog series tackling these myths and misconceptions about specialized cloud storage and what a best-of-breed, interoperable approach to storage and infrastructure entails.

Reading the fine print of hyperscaler storage

On the surface, hyperscaler storage looks comprehensive and capable. But dig a little deeper, and some underlying cracks start to show.

Premium performance isn’t the default

Hyperscalers can deliver high performance, but not without tradeoffs: 

• They charge more. Premium tiers designed for workloads like analytics or streaming can cost five to eight times more than interoperable solutions.

• They prioritize themselves. When hyperscalers face high-performance demands (e.g., AI workloads competing for GPUs and storage bandwidth), they tend to prioritize their own data centers. Smaller teams might have to navigate opaque processes to request higher performance, and their access to advanced optimizations can be limited. 

• They play favorites. File size adds yet another layer of difficulty. Many hyperscaler storage systems handle large files more efficiently than small ones because of I/O overhead. Hyperscalers may help their biggest customers fine-tune configurations, but most are left to troubleshoot bottlenecks on their own.

Juggling tiers (and hoping nothing gets dropped)

Hot, cool, and cold storage options may look flexible on paper, but they require separate access controls, replication rules, and performance tuning. Teams are left juggling interfaces like AWS Identity and Access Management (IAM), scripting policies, and managing tooling just to keep systems functional.

And the more storage types you manage, the greater the chance for human error. A misplaced lifecycle rule or a mistyped IAM permission can result in:

• Unexpected data unavailability
• Delayed retrievals
• Accidental deletions

When complexity undermines reliability

Keeping storage tied tightly to hyperscaler infrastructure may seem efficient—but it often results in brittle setups. Misaligned storage, compute, and access layers can lead to latency issues or even full-blown downtime.

Performance-sensitive applications like real-time analytics or video streaming suffer most. Even a small delay can ripple through the user experience and cause customer churn. To patch gaps, teams often layer on caches, fine-tuning, or quick fixes that only add technical debt.

Who has time to babysit storage?

Developers, DevOps, and site reliability engineers (SREs) are always racing to ship features, scale services, and maintain uptime. For cloud-native teams, optimizing storage isn’t usually at the top of anyone’s to-do list.

Let’s face it: proactively analyzing storage access patterns and configuring tiering rules takes time that cloud-native teams often don’t have. Many teams therefore operate reactively and address storage issues only after performance degrades or surprise bills arrive.

Support tickets don’t feel your pain

Finally, there’s support. Unless you’re a premium customer paying for top-tier service contracts, you’re often stuck with ticketing systems and community forums. That might suffice for routine issues, but when storage problems impact production workloads, waiting for responses through standard channels adds unnecessary stress and delays.

When one size doesn’t fit your cloud

Unlike hyperscaler storage that takes a one-size-fits-all approach, specialized cloud storage solutions directly tackle these challenges. Backblaze B2 is purpose-built to simplify storage for cloud-native teams:

• A single, high-performance tier gives you instant access to all your data, with no tier juggling or lifecycle policies.

• Predictable, transparent pricing means no unexpected fees or surprise retrieval charges.

• S3-compatible APIs simplify integration, allowing you to plug Backblaze B2 directly into your existing cloud-native stack.

For cloud-native teams who value speed, simplicity, and cost control, specialized storage isn’t a complication; it’s a simplification. You get the performance you need, without the complexity you don’t.

Stay tuned for the next post in this series where we tackle Myth #2: Storage isn’t a big enough problem to remediate. (Spoiler: It is.)

The post Cloud Storage Myths Debunked: Hyperscaler Storage Is Good Enough for Cloud-Native Apps appeared first on Backblaze Blog | Cloud Storage & Cloud Backup

Post Syndicated from David Johnson original https://www.backblaze.com/blog/hyperscale-doesnt-mean-hyper-resilient/

Last week, a misconfiguration in Google Cloud’s API infrastructure led to a major global outage. Not long before that, IBM Cloud suffered its second significant disruption in a matter of weeks. The incidents impacted everything from enterprise infrastructure to consumer-facing apps—Gmail, Spotify, Cloudflare, and countless internal systems built on top of these platforms.

Understandably, much of the coverage has focused on what went wrong. But the more important question might be: Why does something like this ripple so far and wide in a system supposedly built for resilience?

Single points of failure in a multi-service world

One might assume that as cloud providers scale, their reliability scales with them. However, these outages reveal a critical distinction: the difference between data-layer resilience and control-plane fragility.

The problem is, that robust data layer can be rendered useless if the “front door” is locked. Hyperscale cloud platforms have grown so interdependent and complex that a fault in one layer can bring vast swaths of unrelated services to a halt. This is the risk of vertical integration: When one vendor provides compute, storage, networking, and identity, a simple bug or misconfiguration can cascade through thousands of applications, not because the applications are fragile, but because they’ve all tied themselves to the same operational backbone. 

Redundancy, or the illusion of it?

In theory, cloud architecture encourages redundancy. But in practice, many companies—even those using multi-cloud strategies—tend to consolidate key services like authentication and orchestration with a single vendor. When that vendor’s services go down, it doesn’t matter that your data is replicated across three availability zones in the same data center. If you can’t log in to access it, your redundancy becomes purely theoretical.

After last week’s outages, some companies may re-evaluate their cloud strategy—but it’s not as easy as flipping a switch. True diversification is complex, requiring time, engineering resources, and a cultural shift toward designing for failure.

The reality: Fewer assumptions, more contingencies

The knee-jerk reaction to events like these is often to demand better SLAs, more transparency, or faster recovery times. Those are valid asks. But they might miss the deeper lesson: Assumptions about uptime and “X-nines” reliability are only helpful until the moment they aren’t. What users need are not just better guarantees, but clearer paths to self-determination when things break.

That might look like:

• Designing for graceful degradation. What can your service do when its cloud provider is partially offline?
• Reconsidering dependencies. Are you tying core logic to a provider’s proprietary APIs, or abstracting where possible?
• Asking harder questions during vendor selection. Not just, “Can it scale?” but “What happens when it fails?”

What does that mean for you?

The answer isn’t to abandon the cloud, but to get smarter about how you use it. This means architecting systems that don’t just have data redundancy, but true operational independence.

Maybe that means replicating data to providers who specialize rather than consolidate. Or maybe it just means revisiting architectures that have become too reliant on invisible scaffolding.

What’s clear is this: reliability isn’t a feature you buy from the cloud. It’s a design philosophy that must be shared.

The post Hyperscale Doesn’t Mean Hyper-Resilient appeared first on Backblaze Blog | Cloud Storage & Cloud Backup

Post Syndicated from David Johnson original https://www.backblaze.com/blog/5-ways-event-notifications-strengthens-your-backup-strategy-automatically/

“Our backups are good, right?”

If you’re responsible for backup operations, you’ve probably heard this question more times than you can count. While the answer should be a simple “yes,” staying on top of backup activities often involves checking multiple systems, reviewing logs, and maintaining manual tracking processes.

Today, I’m sharing five ways you can implement Backblaze Event Notifications into your data protection strategy to keep you and your team informed. If you’re interested in Event Notifications for other use cases, check out our posts for media production and application workflows.

Event Notifications for IT backup: Simplified automation

Event Notifications monitors your B2 Cloud Storage buckets for data changes that you designate—like completed backups, file deletions, or policy violations—and delivers real-time alerts where you want them. These alerts can trigger automated actions in any system that accepts webhooks, from PagerDuty to Zendesk to Slack channels and more.

Think of it as your storage system’s notification service: instead of discovering changes during routine recovery verification checks, you get instant awareness when something happens to the data in your buckets.

5 ways to stay in the know with your backup strategy

Here are specific, practical ways you can take advantage of Event Notifications for immediate benefits to your backup and archive workflows.

1. Backup verification and reporting

When your backup software writes files to B2 Cloud Storage, Event Notifications helps verify successful completion of backup jobs. Each time a backup file lands in a bucket, you’ll receive a notification with key details like file size, timestamp, and backup job name. By feeding this data directly into communication tools like Slack, you can maintain comprehensive logs of backup activity without manual checks.

Backup monitoring workflow

Gone are the days of discovering backup issues hours or days later during routine reviews—you’ll know exactly when backups are uploaded. Teams can configure custom alerts for backup size thresholds, receive immediate confirmation of successful backups, and, with the help of Zapier, you can enable an alert when Event Notifications did not trigger, indicating a backup was not uploaded during a specified window.

2. Security and compliance monitoring

Event Notifications can help protect your backup data from unauthorized changes. Security teams can establish automated alerts for suspicious activities like mass deletions or modifications. These alerts integrate with your existing security information and event management (SIEM) systems to provide unified threat monitoring.

Security alert workflow

Beyond threat detection, Event Notifications enables preemptive policy enforcement. Teams can configure automatic notifications that guide employees when their actions might conflict with backup policies—like modifying file names, moving files, or even deletion. For persistent policy conflicts, managers can receive automated escalation alerts to address potential training needs or process gaps. This systematic approach helps maintain backup integrity through education and awareness before issues occur, rather than just detecting violations after the fact.

3. Storage management automation

Storage management becomes more efficient when Event Notifications feeds activity data directly to your management tools. As files are uploaded to and removed from your buckets over time, Event Notifications provides valuable data that helps you analyze storage utilization trends and backup data growth patterns.

Data usage monitoring workflow

This constant flow of information empowers teams to anticipate capacity needs and optimize resource allocation. Moving from reactive to proactive storage management helps control costs by notifying you when backups become larger on average.

4. Cross-bucket backup monitoring

Organizations using Cloud Replication or managing backups across multiple buckets gain valuable oversight through Event Notifications. This capability tracks file replication between regions and monitors backup activity across your entire footprint, giving you a comprehensive view of your distributed backup strategy. Teams can spot replication delays or issues immediately, rather than waiting for scheduled status checks.

Cloud Replication notification workflow

Understanding how data moves and grows across different locations ensures your distributed backup strategy performs as designed. Event Notifications makes it possible to track successful replications, monitor consistency between primary and replica buckets, and receive immediate alerts about any issues. This visibility is especially valuable for organizations maintaining geographic redundancy or managing complex multi-site backup strategies.

5. Integration with IT workflows

Event Notifications connects seamlessly with existing IT tools and processes through standard webhooks. Backup events can automatically flow into ticketing systems like Jira Service Management, monitoring dashboards like Grafana, or team communication channels like Microsoft Teams and Mattermost. This integration means teams can manage backup operations through familiar tools and processes, without needing to constantly switch between different interfaces or learn new systems.

Data integration workflow

The result is streamlined operations without the need for separate backup monitoring systems, ensuring backup activities receive proper attention within normal IT procedures. Teams can create ServiceNow tickets for failed backups, update Jira boards with backup status, or send notifications to Teams channels—all automatically and in real-time.

Why Event Notifications makes sense for backup teams

Managing backup operations has traditionally meant juggling multiple monitoring tools and hoping you catch issues before they impact recovery capabilities. Event Notifications transforms this approach by providing:

• Automated awareness: Replace manual checks with instant visibility into bucket changes.
• Enhanced security: Track backup data access and modifications as they happen.
• Simplified monitoring: Feed backup activity data directly to your management tools.
• Better operations: Free up time to focus on improving backup strategies rather than monitoring them.
• Flexible integration: Adapt backup monitoring to fit your existing processes, not the other way around.

How it works with your environment

Unlike traditional backup monitoring solutions that often require specific software for notification handling, Event Notifications works with any service that accepts webhooks. This fundamental difference means you aren’t locked into specific vendors’ ecosystems or forced to use particular monitoring tools.

Event Notifications is designed for reliability with at-least-once delivery, ensuring critical backup events are never missed. This reliability is especially important for teams building automated workflows that require consistency and transparency in their backup monitoring.

The pricing model is straightforward and predictable: Backblaze B2 Reserve customers receive unlimited notifications at no additional cost, while pay-as-you-go customers get 2,500 notifications free each day and pay just $0.004 per 10,000 additional calls. This transparent pricing applies regardless of which services you’re connecting to, enabling teams to build comprehensive backup monitoring without worrying about unpredictable costs.

Ready to automate your backup monitoring?

If you’re working with a Backblaze account manager, Event Notifications are already enabled—just ask them for setup guidance. Other existing customers can contact our Support team to request access.

New to Backblaze? Contact our Sales team to learn how Event Notifications can strengthen your backup operations.
Once enabled, visit the Event Notifications section in your B2 Cloud Storage buckets to configure your alerts. For detailed setup instructions and best practices, check out our Event Notifications documentation.

The post 5 Ways Event Notifications Strengthens Your Backup Strategy Automatically appeared first on Backblaze Blog | Cloud Storage & Cloud Backup

Post Syndicated from David Johnson original https://www.backblaze.com/blog/calculate-cost-cloud-storage/

With spending on public cloud services expected to double by 2028, many businesses are looking for ways to cut cloud costs—or at least gain predictability in their spend. Forecasting cloud storage costs should be straightforward once you know what to look for.

Here are five tips you can use when doing your due diligence on the cloud storage vendors you are considering. The goal is to create a cloud storage forecast that you can rely on each and every month.

Tip 1: Navigate tiered pricing structures carefully

Many cloud providers still use tiered pricing structures, which can be misleading if not carefully understood. For example:

AWS S3 Storage Pricing Example

For this post, we’re comparing with hypothetical data stored in AWS S3’s U.S. East Region (N. Virginia) using pricing available at the time of publishing. Note that many factors may affect your final price, including selecting a different region, choosing a different storage tier, etc.

• First 50 TB/month = $0.023 per GB
• Next 450 TB/month = $0.022 per GB
• Over 500 TB/month = $0.021 per GB

In order to receive lower pricing, you have to reach a specific amount of data stored. But, the lower rate only applies to data above the threshold for that tier. In other words, you don’t get a discount on the cumulative amount—each pricing tier is reflected in the data you’re storing. 

The mistake sometimes made is estimating your entire storage cost based on the level for the total data stored. For example, if you had 600TB of storage, you could wrongly calculate as follows:

600,000GB x $0.021 = $12,600/month

When, in fact, you should do the following:

(50,000GB x $0.023) + (450,000GB x $0.022) + (100,000GB x $0.021) = $13,150/month

That was just for storage. Make sure you consider the tiered pricing tables for data retrieval, and API transactions as well.

Tip 2: Don’t choose the wrong storage class

Many cloud providers, especially hyperscalers, now offer a wider array of storage classes than ever before. The idea is that you can trade service capabilities for lower costs. If you don’t need immediate access to your files or don’t want data replication or 11 nines of durability, you can choose to downgrade your service and gain cost savings. The biggest problem with this method is that you have to know what you are going to do with your data to pick the right service—as well as correctly anticipate future business needs—because mistakes can get very expensive. For example:

• You choose a low cost, cold storage tier that takes hours or days to restore your data. What can go wrong? You need some files back immediately (if, for example, your backups are corrupted by ransomware) and you end up paying 10-20 times the cost to expedite your restore.
• You choose one storage class and decide you want to upload some data to a compute-based application or to another region—features not part of your current service. The good news? You can usually move the data. The bad news? Even if you’re transferring within the same cloud storage company’s infrastructure, you’re often charged a transfer fee to move the data because you didn’t choose the right storage class when you started. These fees often eradicate any “savings” you had gotten from the lower priced tier.

Basically, if your needs change as they pertain to the data you have stored, you will pay more than you expect to get your data where you need it to be.

Tip 3: Don’t pay for deleted (or modified) files

Some cloud storage companies have a minimum amount of time you are charged for storage for each file uploaded. Typically this minimum period is between 30 and 90 days. You are charged even if you delete the file before the minimum period. For example (assuming a 90 day minimum period), if you upload a file today and delete the file tomorrow, you still have to pay for storing that deleted file for the next 88 days.

This “feature” often extends to files deleted due to versioning. If you set your system to keep three versions of each file, with older versions automatically deleted, you end up paying for those deleted versions for the full minimum duration.

In a typical backup workflow, let’s say you are using a cloud storage service to store your files and your backup program is set to a 30 day retention. That means you will be perpetually paying for an additional 60 days worth of storage (for files that were pruned at 30 days). In other words, you would be paying for a 90 day retention period even though you only have 30 days worth of backups.

Tip 4: Beware of hidden minimums

As the cloud storage market has matured, pricing models have become more complicated. To create an accurate budget, it’s crucial to understand all potential cost components, including some that might not be immediately obvious. Here are two key areas to examine:

1. Minimum monthly charges: Some providers charge a set fee regardless of how little you store. For instance, you might pay for 1TB even if you only use 100GB.
2. Minimum file sizes: Some services round up small files to a minimum billable size, often 128KB. While this might seem insignificant, it can add up quickly if you have millions of small files.

Tip 5: Be suspicious of the fine print

Misdirection is the art of getting you to focus on one thing so you don’t focus on other things going on. Practiced by magicians and some cloud storage companies, the idea is to get you to focus on certain features and capabilities without delving below the surface into the fine print. (And, sometimes the prices this technique generates feels like someone has pulled a rabbit out of a hat—to your company’s detriment.)

Read the fine print and as you scroll through the multi-page pricing tables and linked pages of all of the rules that shape how you can use a given cloud storage service. Stop and ask, “What are they trying to hide?” If you find phrases like: “We reserve the right to limit your egress traffic,” or “New users get free usage tier for 12 months,” or “Provisioned requests should be used when you need a guarantee that your retrieval capacity will be available when you need it,” take heed. 

And, even if it seems like you can turn the tables and use things like free credits in the short term, remember that you’ll want to have a plan for your long-term infrastructure when those credits run out as well. 

How to build a predictable cloud storage budget

As organizations increasingly rely on cloud storage for everything from day-to-day operations to long-term data archiving, the ability to accurately forecast and control these costs can significantly impact overall IT budgets and business planning.

The first place to start is data storage as it’s generally the easiest for a company to calculate. For a given month, you can calculate your data volume as follows:

Data stored = current data + new data – deleted data

Take that total and multiple by the monthly storage rate and you’ll get your monthly storage costs. 

Things can get more complicated if your business regularly uploads and downloads data. The data stored at the end of the month should get you at least in the ballpark. But, creating a predictable cloud storage budget requires a holistic understanding of your data needs, usage patterns, and the pricing structures of your chosen provider. It’s not just about estimating how much data you’ll store, but also how you’ll interact with that data over time. Will you be frequently accessing and modifying files, or primarily using the storage for long-term archiving? Are there seasonal fluctuations in your data storage or retrieval patterns? These factors can all influence your overall costs, and we’ll walk through a scenario to show that next.

Let’s do the math

To illustrate how to calculate your cloud storage costs, let’s work through an example using current Backblaze B2 pricing. We’ll focus on a single month for a growing business that is backing up business data to the cloud and verifying their backups have zero errors during recovery:

• Initial storage at the beginning of the month: 100TB
• New data added during the month: 10TB
• Data deleted during the month: 5TB
• Downloads during the month (egress): 75TB

Backblaze has built a cloud storage calculator that computes costs for all of the major cloud storage providers. Using this calculator, we find that Amazon S3 would cost $2,675 to store this data for a month, while Backblaze B2 would charge just $630.

Using those numbers for storage and assuming you download 75TB a month for backup validation testing, you get a total monthly cost of $8,725 for Amazon S3; Backblaze B2 would be $630 a month. 

The additional cost you see from AWS S3 is from download costs, also known as egress fees, and they can certainly take a toll on your budget. Backblaze offers free egress up to three times the amount you have stored so you can move data when and where you prefer.

The chart below provides the breakdown of the expected cost.

	Backblaze B2	Amazon S3
Storage	$630	$2,675
Egress	Free*	$6,050
Totals:	$630	$8,725

*Up to 3x of average monthly data stored, then $0.01/GB for additional egress.

Of course each month you will add and delete storage, so you’ll have to account for that in your forecast. And, as we mentioned above, there may also be other fees like minimum storage duration fees or API transaction fees. Using the cloud storage calculator noted above, you can get a reasonable estimate of your total cost over the budget forecasting period.

Finally, you can use the Backblaze B2 storage calculator to address potential use cases that are outside of your normal operations, such as if you delete a large project from your storage or you need to download a large amount of data. Running the calculator for these types of actions lets you obtain a solid estimate for their effect on your budget before they happen and lets you plan accordingly.

Understanding cloud storage pricing gives you options

Creating a predictable cloud storage forecast is key to taking full advantage of all of the value in cloud storage. Organizations like Austin City Limits, Amplify, and Runbiz were able to move to the cloud because they could reliably predict their cloud storage cost with Backblaze B2. You don’t have to let pricing tiers, hidden costs, and fine print stop you. Backblaze makes predicting your cloud storage costs easy.

The post Five Tips for Creating a Predictable Cloud Storage Budget appeared first on Backblaze Blog | Cloud Storage & Cloud Backup