Recently, Anthropic was in News for making 57 releases in 1 month. This was nearly 2 releases everyday. This is shipping a new release in less than 4 hours. This was a display how advanced their testing and release management is. Now, this is becoming a benchmark for most Tech Founders.

Over the last few years, deployment speed has improved across almost every growing engineering team. – Pipelines are faster, Releases are more frequent, Automation has replaced manual steps. On paper, this is what progress is supposed to look like. But inside many teams, the feeling is very different. Releases are quicker, yet hesitation has not gone away – what is something breaks?

I met a Tech SaaS AI company in the India AI Summit'26 – they recently moved from bi-weekly releases to multiple deployments per day. Their CI pipeline brought deployments had automated rollbacks and release level monitoring was in place.

From a metrics standpoint, they had improved significantly. But while their CTO was talking to me telling his DevOps problems – I could clearly witness a different pattern:

Engineers still preferred deploying during low traffic hours.
Critical releases were double checked manually before pushing.
Late evening deployments were avoided unless necessary.

Speed had improved. Confidence had not.

This gap is showing up across many teams operating at scale. Deployment frequency is increasing, but the perceived risk of change is not reducing at the same pace.

According to the Accelerate State of DevOps reports, elite teams are not just faster at deploying. They also maintain low change failure rates, meaning changes behave predictably once released.

You can explore the benchmarks here: https://cloud.google.com/devops/state-of-devops

Many teams have optimised for speed, but not for predictability. What creates this disconnect is not the deployment process itself, but everything surrounding it. In most growing systems:
Dependencies are not fully visible
Edge cases are discovered only in production
Rollback paths exist but are not always reliable
System behaviour changes based on load and timing
So even if deployments are technically faster, their outcomes are not always consistent.

This is where stronger teams operate differently.

They do not just focus on how quickly code can be deployed. They focus on how consistently the system behaves after deployment. This leads to a shift in how deployments are treated. Instead of asking – "How fast can we ship this"; The question becomes – "How predictable is this change once it goes live"

In these environments:
Deployments follow consistent paths
System responses are expected and repeatable
Recovery mechanisms are tested and not assumed
As a result, confidence does not come from speed. It comes from knowing what will happen next. This is why many teams today feel stuck in an unusual position. They have modern deployment systems. They ship faster than ever. But every release still carries a question mark.

The underlying issue is simple.
Speed improves execution.
Confidence comes from consistency.
Until systems behave predictably under change,
Faster deployments will continue to feel risky.
And that is what many teams are starting to realize.
The problem is no longer how quickly you can deploy.
It is whether your system responds the same way every time you do.

I am Ayesha Siddiqua – I work at the crossroads of cloud strategy and startup growth. Over the years, I've had hundreds of conversations with CTOs, Heads of Engineering, and founders trying to navigate the same hard questions — when to hire, what to automate, how much to spend on infrastructure, and when "good enough" is actually good enough.

I don't write about DevOps from a purely technical lens. I write about it because I believe the infrastructure decisions that get made (or ignored) in a startup's first two years quietly determine whether the company scales or stalls.

I'm associated with Frigga Cloud Labs, a DevOps consultancy built for growing startups.

This blog is my way of contributing to the conversation. If it made you think, I'd love to hear from you.

Let's connect on LinkedIn

The DevOps Lie: Faster Deployments ≠ Safer Releas