Logo of Osakidetza, the Basque Health Service, featuring a modern design with clouds and abstract elements.

256_cta-background.webp

384_cta-background.webp

640_cta-background.webp

750_cta-background.webp

828_cta-background.webp

share_osakidetza-logo.jpg

thumbnail_cta-background.webp

osakidetza-logo

Daar hebben wij de oplossing voor

Wilt u efficiënter werken? 

Abstract digital background featuring interconnected lines and glowing points in shades of blue and green.

1080_background.webp

1200_background.webp

256_background.webp

384_background.webp

640_background.webp

750_background.webp

828_background.webp

share_atmosphere-water-sky-azure-electricity-astronomical-object-slope-electric-blue.jpg

thumbnail_background.webp

atmosphere-water-sky-azure-electricity-astronomical-object-slope-electric-blue

Logo of Zen Software in white on a transparent background.

1080_zen-logo-white.webp

1200_zen-logo-white.webp

256_zen-logo-white.webp

384_zen-logo-white.webp

640_zen-logo-white.webp

750_zen-logo-white.webp

828_zen-logo-white.webp

share_zen-logo-white.jpg

thumbnail_zen-logo-white.webp

zen-logo-white.webp

ZEN Software

1080_zen-logo-black.webp

1200_zen-logo-black.webp

256_zen-logo-black.webp

384_zen-logo-black.webp

640_zen-logo-black.webp

750_zen-logo-black.webp

828_zen-logo-black.webp

share_západoslovenská energetika-logo.jpg

thumbnail_zen-logo-black.webp

západoslovenská energetika-logo

All services at a glance

Modernise legacy systems

Build and run custom software

Cloud & platform

What does it cost?

What we do

Cases

About us

News

Contact

Done! You're on the Standup & Deliver list.

Everything that matters in measuring software development and production platforms, in your inbox.

Standup & Deliver, ZEN Software's newsletter

In 1988 a student took down a tenth of the internet. What did we do next?

Een groene rups kruipt over een uitgerolde band met ponstape en laat een spoor van steeds kleinere kopieën van zichzelf achter; links knielt een engineer die een pion en een koordje over het pad zet

morris-worm-1988.webp

In November 1988 a student at Cornell wrote a small program to count how many computers were on the internet. A bug took down a tenth of that internet. What happened next is more interesting than the outage itself, and it is the playbook we need again now.

OpenAI's AI agents broke into another company. So why are we calling it a conspiracy?

Illustratie: een klein robotje typt rustig aan een bureau terwijl de bureaulamp een reusachtige monsterschaduw op de muur werpt, naast een serverkast die wagenwijd openstaat met de sleutel nog in het slot

hugging-face-hack-beveiligingsincident.webp

OpenAI's AI agents broke into Hugging Face, another AI company, this summer. Dwarkesh Patel called it an AI civilisation, Alexander Klöpping the most dangerous hack in history. I run AI agents every day myself, so I read the reports, and I came out a good deal calmer than I went in. What does keep nagging at me: why are we suddenly calling this a conspiracy?

AI Makes Code Cheap. Your Organization Is Still Expensive.

Illustratie: een koerier op een step levert een pakketje af bij een rij van vijf bureaus met stempels en kalenders, met een dichte deur aan het eind

organisatie-is-duur.webp

Developers in a controlled trial were 19% slower with AI and believed they were 20% faster. Meanwhile DORA found that organizations really did speed up, and paid for it in stability. What changed when code got cheap is not what most engineering leaders think.

A $200 AI subscription delivers $14,000 of compute. But does the maths hold up?

Balance scale with one small coin on one pan and a large melting block of ice on the other, hanging level, while a small robot mops the puddle

17-ai-abonnement-subsidie.webp

A $200 ChatGPT Pro subscription supposedly delivers $14,000 a month of compute. That is how the screenshot goes round. I followed the number to its source, and the maths does not quite hold up. But under that sum sits a better question, and it is about how long an AI model actually lasts.

My AI Agent Works Through the Night. It Just Can't Decide Anything.

Leeg bureau in ochtendlicht met een koffiekop en een uitgeprint rapport met vinkjes en één kruisje; een kleine robot kijkt toe met de handen op de rug

16-agent-werkt-s-nachts.webp

Since August, an agent runs every weekday at half past seven, reads our open merge requests and forms an opinion on each. It cannot merge, close or decide anything. That is not a restriction I bolted on afterwards. It is the design.

48 major outages in twelve months. What is going on at GitHub?

Illustration: a bridge resting on two piers, the right one cracked and held up by scaffolding, while traffic keeps flowing across it.

github-gitlab-bridge.webp

Eight hours down in a single afternoon, 48 major outages in a year, and the largest cause is capacity. On GitHub becoming a Microsoft division, the reverse Midas touch, Bitbucket as the warning, and why we want both of them to stay healthy.

What you're missing with AI agents is rarely a tool

Illustration: four glowing screens each send a stream of data tiles into a single funnel, where the work piles up beside an empty chair

geen-gereedschap-v2.webp

I have been running several AI agents side by side for months. After five hours of DHH on programming with agents, my tooling turned out to be right. What was missing were three habits, and none of them can be installed.

The creator of Ruby on Rails doesn't write code any more

Bar chart: the same Python-to-Rust translation cost 550 dollars with Fable, 46 dollars with GPT Sol and 23 dollars with DeepSeek V4 Pro

dhh-podcast-en.webp

The creator of Ruby on Rails no longer writes a line of code himself and drives sixteen agents at once. From five hours with Lex Fridman, the three things you can use on Monday, including the one number in the episode a buyer can actually use.

Code is getting cheap. Engineering isn't.

Two panels: implementation priced at 150 euro an hour, struck through with a downward arrow, beside engineering judgement marked scarce with an upward arrow.

code-is-getting-cheap-en.webp

A developer with twenty years' experience stopped coding with AI. Not because it failed, but because it worked too well. His diagnosis is sharper than most of what the vendors are selling. We just reach a different conclusion: not less AI, but better engineering around it.

AI Vampires: The Hidden Price of Twenty Agents

Vriendelijke cartoonvampier achter een laptop bij zonsopgang, met negen zwevende schermen waarop AI-assistenten tegelijk code schrijven

ai-vampires-v5.webp

On Joe Rogan, Marc Andreessen describes a new kind of programmer: one who stops sleeping because twenty agents are waiting on an answer. He calls them AI vampires, and he files them under good news. The observation is right. The filing is not.

AI-Assisted Development under GDPR, NIS2 and DORA

Drie gekleurde transparante vlakken boven één doorlopende lichtlijn, die elkaar overlappen en daar van kleur mengen.

zen-hero-compliance-regelgevingslagen.webp

The moment you attach a coding agent to your codebase, you touch three regulatory regimes at once. Not because AI is separately regulated, but because it touches existing rules in places your delivery pipeline never had to think about before.

Reviewing AI-Generated Infrastructure Code: What to Actually Look For

Rij gesloten deuren met in elk slot nog de sleutel, waarvan er één rood is.

zen-hero-iac-sleutels-in-de-sloten.webp

Application code that is wrong usually breaks. Infrastructure code that is wrong works. And that is exactly the problem. An agent writing Terraform hands you something that plans, applies and runs. Whether it is safe is not visible in the output.

What Thirty Minutes of Waiting per Engineer per Day Really Costs

Rekensom in vier stappen: dertig minuten wachten per dag wordt 495.000 euro per jaar bij honderd engineers.

zen-hero-wachttijd-rekensom.webp

Half an hour a day. It sounds like nothing. But work it through and it is €5,000 per engineer per year, or half a million euros across a hundred engineers: money that appears on no line of your P&L and that nobody ever approved.

Reading DORA Metrics When AI Writes Half Your Commits

Vier DORA-metrics met pijlen die de beweging tonen; change failure rate is rood gemarkeerd als het risico.

zen-hero-dora-beweging.webp

Your DORA dashboard still shows the same four numbers. They no longer mean the same thing. Once a serious share of your code is not written by hand, what each metric tells you shifts, and the naive reading points in exactly the wrong direction.

How to Plan a Cloud Migration (Without Losing Your Mind)

Gantt met vier overlappende planfases van een cloudmigratie over vijf weken.

zen-hero-migratie-fases-gantt.webp

You know you need to move to the cloud. But you're terrified: What if we lose data? How long will this take? What if it costs more than staying on-premises? Are we picking the right provider?

In recent years, we've migrated 8 production systems to AWS, Azure, and Google Cloud. Here's what we've learned: most cloud migrations succeed. The ones that fail usually fail because of poor planning, not bad execution.

You know you need to move to the cloud. But you're terrified: What if we lose data? How long will this take? What if it costs more than staying on-premises? Are we picking the right provider?
    
In recent years, we've migrated 8 production systems to AWS, Azure, and Google Cloud. Here's what we've learned: **most cloud migrations succeed**. The ones that fail usually fail because of poor planning, not bad execution.

Building a PWA in 2026: What a Regular React Developer Actually Needs to Learn

Diagram met twee routes vanaf de service worker: groen naar de cache, rood naar het netwerk.

zen-hero-service-worker-routes.webp

If you have already built React applications, Progressive Web Apps are probably less intimidating than they sound.

The term still carries some early-2019 energy. Back then, PWAs were pitched as “websites that behave like native apps” and somehow promised to replace app stores entirely. That prediction aged… unevenly.

If you have already built React applications, Progressive Web Apps are probably less intimidating than they sound.
     
The term still carries some early-2019 energy. Back then, PWAs were pitched as “websites that behave like native apps” and somehow promised to replace app stores entirely. That prediction aged… unevenly.
     
But PWAs quietly became useful.
     
For internal business tools, customer portals, ecommerce experiences, booking flows, field-service apps, dashboards, and products where “installability” matters more than App Store prestige, they’re often a practical middle ground between a website and a mobile app.
    
The good news: if you’re already comfortable with React, Next.js, Vite, or modern frontend tooling, you’re probably closer than you think.
     
The bad news: there are a few concepts web developers tend to underestimate.

Cloud Cost Optimisation: How We Helped a SaaS Company Reduce Cloud Spend by 35%

reducing-cloud-costs.webp

A small SaaS company with around 50 employees approached us with a concern that had begun to surface in budget discussions. Their product was stable, usage was growing steadily, but cloud costs were no longer behaving predictably. Monthly infrastructure spend was roughly €10,000. It wasn’t extreme, but it was drifting upward without a clear explanation. For a company of their size, even a few thousand euros of inefficiency per month was becoming noticeable.

5 Things to Consider When Building a Website That Actually Ranks Well

Diagram dat een goed gekoppelde sitestructuur naast losse weespagina's zet.

08-sitestructuur.webp

A lot of SEO advice still sounds like it came from 2014. Endless keyword checklists, “content is king,” and obsessing over density scores nobody cares about anymore. Meanwhile, plenty of technically decent websites still struggle to rank because they ignore the things search engines have quietly become very good at evaluating: structure, clarity, speed, and whether a site feels maintained by people who know what they’re doing.

A lot of SEO advice still sounds like it came from 2014. Endless keyword checklists, “content is king,” and obsessing over density scores nobody cares about anymore. Meanwhile, plenty of technically decent websites still struggle to rank because they ignore the things search engines have quietly become very good at evaluating: structure, clarity, speed, and whether a site feels maintained by people who know what they’re doing.
       
Good rankings usually come from a combination of strong technical foundations and content that doesn’t feel manufactured purely for search engines. The number of websites that still publish lifeless, over-optimised pages suggests otherwise.

Why IAM Might Be the Most Dangerous Part of Your Cloud

Gesloten kluisdeur naast een wand die vol kleine, legitiem uitgesneden doorgangen zit.

09-waarom-iam-misschien-wel-het-gevaarlijks.webp

Ask someone where cloud risk lives, and you’ll usually get the same answers: exposed databases, misconfigured storage buckets, maybe a server left open to the internet. Those are the things people screenshot, write postmortems about, and use in security presentations. They’re also not where most of the interesting problems come from.

Ask someone where cloud risk lives, and you’ll usually get the same answers: exposed databases, misconfigured storage buckets, maybe a server left open to the internet. Those are the things people screenshot, write postmortems about, and use in security presentations. They’re also not where most of the interesting problems come from.
      
If you spend enough time looking at real systems, you start noticing a different pattern. Things don’t usually break because someone hacked through layers of infrastructure like in a movie. More often, access was already there. Just… a bit broader than anyone realised. That’s IAM.

If AI Replaces Junior Roles, Where Do Senior Developers Come From?

Monumentale trap waarvan de onderste treden ontbreken, zodat het bovenste deel in de lucht begint.

10-als-ai-de-juniorrollen-overneemt-waar-ko.webp

There’s a quiet contradiction in how people talk about AI in software development. On one side, there’s excitement about replacing junior work. Boilerplate, simple features, small bug fixes—things that used to be entry points are now increasingly handled by AI. The argument is that this frees up time, reduces costs, and lets teams move faster. That part is hard to argue with. But it leaves an uncomfortable question hanging in the background: if fewer people start at the junior level, where do senior developers come from later? 

There’s a quiet contradiction in how people talk about AI in software development.
      
On one side, there’s excitement about replacing junior work. Boilerplate, simple features, small bug fixes—things that used to be entry points are now increasingly handled by AI. The argument is that this frees up time, reduces costs, and lets teams move faster. That part is hard to argue with.
       
But it leaves an uncomfortable question hanging in the background: **if fewer people start at the junior level, where do [senior developers](/what-we-do/products-and-services/staff-augmentation) come from later?** Because senior engineers don’t appear fully formed. They’re shaped over time, often by doing exactly the kind of work that is now being automated away.

Cloud Observability vs. Cloud Monitoring

Diagram dat vooraf gedefinieerde monitoringchecks naast doorzoekbare observability-dimensies zet.

11-observability.webp

The difference between monitoring and observability only really shows up when something goes wrong, and the usual tools don’t help you understand why. That’s when the gap becomes obvious.

The terms Cloud Observability and Cloud Monitoring are used all the time interchangeably.
      
Dashboards, alerts, logs, traces—everything ends up under the same umbrella, and for a while, that feels fine. You can ship features, monitor metrics, and respond when something breaks.
      
The difference between monitoring and [observability](/what-we-do/solutions/zen-devops-accelerator) only really shows up when something goes wrong, and the usual tools don’t help you understand why.
       
That’s when the gap becomes obvious.

Will Software Security Improve with AI Coding Agents Like Claude Mythos, or Get Worse?

Schaar die twee tegengestelde schaduwen werpt: de ene sluit een naad, de andere opent hem.

12-wordt-softwarebeveiliging-beter-met-ai-c.webp

Every new wave of tooling in software development comes with the same split reaction. Some people see leverage. Others see risk.

Claude Mythos sits right in that space. It’s not just another coding assistant. It can read large codebases, identify vulnerabilities, and in some cases go a step further, figuring out how those weaknesses could actually be exploited.

That combination is what makes it interesting, and also what makes it uncomfortable to reason about.

Every new wave of tooling in software development comes with the same split reaction. Some people see leverage. Others see risk.
       
[Claude Mythos](https://red.anthropic.com/2026/mythos-preview/) sits right in that space. It’s not just another coding assistant. It can read large codebases, identify vulnerabilities, and in some cases go a step further, figuring out how those weaknesses could actually be exploited.
       
That combination is what makes it interesting, and also what makes it uncomfortable to reason about.

What Happens When a Cloud Region Goes Down

Raster van verbonden blokken waarin één district grijs is geworden en de lijnen ernaartoe afbreken.

13-wat-er-gebeurt-als-een-cloudregio-uitval.webp

Most teams build their systems expecting small failures.
      
A container crashes. A node disappears. Maybe an availability zone has had issues for a while. These are the scenarios architecture diagrams usually prepare you for, and most platforms handle them well enough that you barely notice.

Most teams build their systems expecting small failures.
      
A container crashes. A node disappears. Maybe an availability zone has had issues for a while. These are the scenarios architecture diagrams usually prepare you for, and most platforms handle them well enough that you barely notice.
      
A region outage is something else entirely. It doesn’t show up often, which is probably why it’s easy to push it out of mind. But when it happens, the impact is immediate and hard to contain. Instead of one part of the system misbehaving, entire layers become unavailable at the same time.
      
The first thing you notice isn’t always a clear failure. Things just stop working in strange ways. Requests hang. Some endpoints return errors while others time out. Background jobs stop processing, but without obvious alerts. Systems that depend on each other begin to fail in sequence, and it’s not always clear where the problem started.

 Cloud Security Basics Developers Often Ignore

Gesloten gevel waarin één zijdeur met een verweerd blokje wordt opengehouden.

14-cloudsecurity-basics-die-developers-vaak.webp

Cloud security is often framed as a shared responsibility. In practice, that usually translates to something like: “the platform handles most of it.” That assumption is where problems start.
      
Modern cloud providers do a good job securing infrastructure — physical hardware, networking layers, and managed services. But the moment you start building on top of that, responsibility shifts quickly. Misconfigurations, overly broad permissions, and implicit trust between services remain among the most common causes of incidents.

Cloud security is often framed as a shared responsibility. In practice, that usually translates to something like: *“the platform handles most of it.”* That assumption is where problems start.
      
Modern cloud providers do a good job securing infrastructure — physical hardware, networking layers, and managed services. But the moment you start building on top of that, responsibility shifts quickly. Misconfigurations, overly broad permissions, and implicit trust between services remain among the most common causes of incidents.
      
What’s interesting is that these issues rarely come from a lack of tools. They come from small decisions made during development that don’t look risky at the time.

5 Tools Experienced React Developers Should Try in 2026

Vijf precisie-instrumenten op een rij, strak uitgelegd als een gereedschapsset.

15-5-tools-die-ervaren-react-developers-in-.webp

If you’ve been working with React for a while, your stack is probably already in a good place. You’re not looking for yet another state library or a new way to style buttons. Most of the common problems are already solved, and the ecosystem has settled around a handful of reliable defaults.
      
What tends to change at this stage is not what you use, but where the friction shows up. It’s no longer about getting things to work. It’s about reducing the amount of coordination between layers, avoiding performance work that feels repetitive, and keeping systems understandable as they grow.

If you’ve been working with React for a while, your stack is probably already in a good place. You’re not looking for yet another state library or a new way to style buttons. Most of the common problems are already solved, and the ecosystem has settled around a handful of reliable defaults.
      
What tends to change at this stage is not what you use, but where the friction shows up. It’s no longer about getting things to work. It’s about reducing the amount of coordination between layers, avoiding performance work that feels repetitive, and keeping systems understandable as they grow.
       
The tools worth exploring now tend to focus on those edges. They don’t replace React, but they reshape the parts around it that still feel heavier than they should.

Why Your CI/CD Pipeline Is Probably the Slowest Part of Your Cloud Stack

Twee pipelinetijdlijnen boven elkaar: serieel drie en een half minuut, gecacht en parallel anderhalve minuut.

16-pipeline.webp

Cloud platforms have become incredibly fast. You can spin up infrastructure in minutes, scale on demand, and deploy globally without much effort. And yet, getting a simple code change into production can still take far longer than expected.

Cloud platforms have become incredibly fast. You can spin up infrastructure in minutes, scale on demand, and deploy globally without much effort. And yet, getting a simple code change into production can still take far longer than expected.
       
The delay often has nothing to do with the cloud itself. It comes from the CI/CD pipeline that sits between writing code and releasing it. Over time, [pipelines](/what-we-do/solutions/zen-devops-accelerator) tend to accumulate extra steps, longer test suites, and inefficient processes that no one revisits. What starts as a simple workflow gradually turns into a system that slows everything down.

Why Most Cloud Migrations Fail Before the First Deployment

Architectonisch volume dat is opgetild en de bundel verbindingen eronder zichtbaar maakt.

17-waarom-de-meeste-cloudmigraties-mislukke.webp

Cloud migration often starts with confidence. The plan sounds simple: move existing systems to the cloud, reduce infrastructure overhead, gain scalability, and modernise the stack. In presentations and strategy documents, the path usually looks straightforward.

Reality tends to look different.

Cloud migration often starts with confidence. The plan sounds simple: move existing systems to the cloud, reduce infrastructure overhead, gain scalability, and modernise the stack. In presentations and strategy documents, the path usually looks straightforward.
      
Reality tends to look different.
       
Many [cloud migration](/what-we-do/solutions/zen-cloud-landing-zone) projects struggle long before the first production deployment happens. Teams spend months preparing environments, rewriting infrastructure, and untangling dependencies. Budgets grow. Timelines slip. The migration stalls.
        
The problem usually isn’t the cloud platform itself. It’s the assumptions carried over from the old architecture.

OTM 5.8: A Vehicle May Finally Have More Than One Fuel

Diagram: the singular fuel field with averageFuelConsumption becomes deprecated in OTM 5.8 in favour of fuels, a list holding diesel and electric, each with its own consumption

otm-5-8-en.webp

OTM 5.8 shipped on 13 March 2026. Its most striking change deprecates a field that 5.4 had only just added: one fuel per vehicle turns out not to work once your fleet goes hybrid.

 Bug Fixing in the Age of AI: How to Use Coding Agents Without Turning Your Codebase Into Spaghetti

Modulair paneel waarin één cel precies wordt vervangen, met ernaast een vak vol in de knoop geraakte kabels.

18-bugs-fixen-in-het-tijdperk-van-ai.webp

Bug fixing has changed.

Not because bugs are different. They’re still null references, race conditions, broken assumptions, and unexpected edge cases. The difference is that now, when something breaks, you’re no longer alone with the stack trace.

Bug fixing has changed.
      
Not because bugs are different. They’re still null references, race conditions, broken assumptions, and unexpected edge cases. The difference is that now, when something breaks, you’re no longer alone with the stack trace.
       
You have AI assistants that can:
       
- Suggest fixes instantly
       
- Refactor entire functions
       
- Generate tests
       
- Explain unfamiliar code
       
- Propose architectural changes
       
That kind of power shifts how developers approach problems. The temptation is obvious: paste the error, accept the suggestion, move on.
        
Sometimes that works, bun speed without understanding creates a new class of problems. Quick patches that ripple across modules. Defensive checks that hide deeper issues. Refactors that quietly alter system boundaries. Code that passes today’s test but complicates tomorrow’s change.
       
The challenge isn’t whether to use AI when fixing bugs. It’s how to use it in a way that makes your life easier without slowly degrading your codebase — and without outsourcing your learning process.

AI Fatigue in Development: Why Constant AI Assistance Can Wear You Down

Volle bak met stapels papier naast een lege werkbak.

19-ai-moeheid-in-development-waarom-constan.webp

There’s a familiar pattern among developers who have spent any time with AI-assisted tools: initial curiosity, followed by a period of regular use, and then — surprisingly — weariness. Many engineers report a sense of exhaustion, irritation, or even dread at the idea of interacting with AI daily. For teams that expected AI to save time and reduce toil, this is a disorienting experience.
     
It’s not that the tools are inherently bad. It’s that interacting with AI changes how developers think, work, and maintain focus — and those changes can be draining in subtle ways that traditional productivity metrics don’t capture.

There’s a familiar pattern among developers who have spent any time with AI-assisted tools: initial curiosity, followed by a period of regular use, and then — surprisingly — **weariness**. Many engineers report a sense of exhaustion, irritation, or even dread at the idea of interacting with AI daily. For teams that expected AI to save time and reduce toil, this is a disorienting experience.
       
It’s not that the tools are inherently bad. It’s that interacting with AI changes how developers think, work, and maintain focus — and those changes can be draining in subtle ways that traditional productivity metrics don’t capture.
       
In this article, we’ll unpack what AI fatigue looks like in software development, why it arises, how it affects individuals and teams, and what organisations can do to understand and mitigate it.

Remote Cloud Sandboxes: Reducing Merge Conflicts in Distributed Teams

Diagram dat één gedeelde ontwikkelomgeving vergelijkt met een tijdelijke sandbox per engineer.

20-sandboxes.webp

In distributed engineering teams, merge conflicts are a recurring headache. They slow down development, frustrate engineers, and introduce subtle bugs that sometimes go unnoticed until deployment. While traditional local development environments work well for small teams, scaling to remote or multi-location teams demands a more robust approach. Enter remote cloud sandboxes—isolated, cloud-based environments that can transform collaboration and reduce friction in distributed software development.

In distributed engineering teams, merge conflicts are a recurring headache. They slow down development, frustrate engineers, and introduce subtle bugs that sometimes go unnoticed until deployment. While traditional local development environments work well for small teams, scaling to remote or multi-location teams demands a more robust approach. Enter **remote cloud sandboxes** — isolated, cloud-based environments that can transform collaboration and reduce friction in distributed software development.

CI/CD Pipelines Shouldn’t Be a Full-Time Job

Kleine machine die vrijwel volledig schuilgaat achter een uitgegroeide steigerconstructie.

21-ci-cd-pipelines-horen-geen-fulltime-baan.webp

If you’ve ever felt like your CI/CD pipeline is working against you rather than for you, you’re not alone. The promise of continuous integration and continuous delivery was supposed to be freedom: faster feedback, automated testing, reliable deployments, and more time for coding. In reality, for many teams, CI/CD has become a second full-time job.

If you’ve ever felt like your [CI/CD pipeline](/what-we-do/solutions/zen-devops-accelerator) is working against you rather than for you, you’re not alone. The promise of continuous integration and continuous delivery was supposed to be freedom: faster feedback, automated testing, reliable deployments, and more time for coding. In reality, for many teams, CI/CD has become a second full-time job.

What Is a Cloud Landing Zone — And Why You Need One Before You Scale

Moving to the cloud is deceptively easy.
       
You create an account, spin up a few services, deploy your first workload, and everything works. At least at first. The problems usually don’t appear when you’re experimenting — they show up when the platform starts to grow, when more people touch it, and when real business data and compliance requirements enter the picture.
       
This is the point where many teams realise they’ve been “using the cloud,” but not really operating in it. That’s where the idea of a Cloud Landing Zone becomes critical.

News & articles

Custom software & modernisation

Cloud & platform

Artificial Intelligence

Ways of working

All articles

What's new in software development?

We're confident we can supercharge your software operation

Contact Form

Standup & Deliver, ZEN Software's newsletter