Imagine this: your Kubernetes cluster is running like a well-oiled machine. Applications are deployed, traffic is flowing, and everything seems perfect. But then, something changes. An attacker slips in unnoticed, exploiting a vulnerability in your environment, executing a command inside a container, and begins moving laterally through your system. By the time you realise something’s wrong, the damage is done. 

Now, picture a different scenario. The moment the attacker attempts to execute an unauthorised command, an alert is triggered. Security teams are notified instantly. Before the attacker can do any harm, the compromised container is automatically terminated, and the breach is contained. This isn’t just a fantasy. This is the reality when you deploy Falco, Falco Sidekick, and Falco Talon.

Kubernetes Security: More Than Just Static Defenses

In the world of Kubernetes, security isn’t a one-and-done thing. It’s an ongoing process. Think of it like building a fortress. Static security measures are your walls and gates, container image scanning, RBAC, network policies, and things you put in place before your workloads even reach the cluster. They’re important, but what happens when the gates are breached? How do you defend the fort once the attacker is already inside? 

That’s where dynamic security steps in.

The Need for Dynamic Security: Defending the Runtime

Here’s the thing about modern containers: they’re ephemeral. They spin up, run, and disappear. Attackers can exploit vulnerabilities before traditional security measures even have a chance to spot them. And with zero-day attacks or malicious insiders, even trusted containers can be hijacked, leaving your system vulnerable. 

This is where dynamic security becomes crucial. It's all about monitoring live workloads and detecting malicious behavior in real time. It's about having a system that not only identifies attacks but also reacts instantly before the damage is done.

Now, imagine having a silent guardian that never takes its eyes off your Kubernetes environment. Falco is that guardian. Developed by Sysdig, Falco is an open-source security tool that monitors system calls in real time. It’s like having a security camera watching over every container, detecting suspicious activity before it turns into a real threat.

Every action inside your Kubernetes containers generates system calls, and Falco is listening. Using eBPF (Extended Berkeley Packet Filter), Falco compares these system calls against predefined security rules. If something suspicious happens, whether it’s an unauthorised shell opening, a privilege escalation, or an unexpected network connection, Falco immediately raises an alert.

A shell being opened inside a running container 

Unauthorised file access (e.g., reading sensitive files) 

Interaction with the Kubernetes API from within a pod

An engineer unknowingly deploys a container with excessive privileges. A hacker takes advantage of this misconfiguration, gains access, and starts executing unauthorised commands. With Falco in place, the moment that hacker opens a shell, an alert is triggered, notifying security teams before real damage can occur.

Great, Falco is watching for threats. But what happens when it detects something suspicious? How do you ensure the right people are notified immediately? 

Falco Sidekick is the messenger sending alerts where they need to go. Whether it’s Slack, AWS Lambda, SIEM systems, or PagerDuty, Sidekick ensures that the right team receives the right message in real-time.

Customisable Alerting: Alerts can be sent to different destinations, ensuring a rapid response. 

Event Enrichment: Sidekick can add more context to alerts, making them more actionable. 

Seamless Integration: Works with existing security and monitoring tools. 

Multi-Channel Notification: Guarantees that alerts won’t be missed by distributing them across multiple platforms.

Let’s say Falco detects a shell being executed inside a container. Without Sidekick, the alert might just sit in a log file, unnoticed. With Sidekick, that same alert is instantly sent to Slack, notifying your security teams in real time, ensuring they can act immediately. The alert can also be forwarded to an SIEM system for long-term analysis, making it easier to track trends over time.

Detection and alerting are essential, but how about stopping threats automatically? That’s where Falco Talon enters the picture. 

Falco Talon is the enforcer of your security policy. Once an alert is triggered, Talon takes immediate action, responding to threats in real time. It's like having an automated incident response team that steps in to neutralise the threat before it can cause significant damage.

Restart services after clearing malicious processes

Trigger automated security playbooks (e.g., Ansible)

Say a hacker successfully gains access to a container and begins executing malicious commands. Falco detects the suspicious activity and sends an alert through Sidekick. But before the attacker can escalate the attack, Falco Talon kicks in and automatically terminates the compromised container, cutting off the hacker’s access. 

Talon can also revoke any unauthorised Kubernetes API tokens and isolate the affected pod, ensuring that the attacker’s movements are stopped in their tracks.

Bringing It All Together: A Comprehensive Security Shield

So, what does this all mean in the context of your Kubernetes environment? By implementing Falco, Falco Sidekick, and Falco Talon, you create a multi-layered defense that’s always active and always prepared.

Falco is your ever-watchful guardian, detecting suspicious behavior in real time.

Falco Sidekick ensures alerts reach the right teams instantly via multiple platforms.

Falco Talon takes swift, automated action to neutralise the threat and prevent further damage.

Together, they form a dynamic, responsive security framework that goes beyond static defenses and ensures your Kubernetes environment is protected at runtime.

It's a fast-paced, threat-driven world. Right now, static security just isn’t enough. Kubernetes environments need dynamic, real-time defenses that can detect and stop threats before they escalate into disasters. With Falco, Falco Sidekick and Falco Talon, you have the power to not only monitor your clusters but also respond to incidents automatically, ensuring your workloads stay secure. 

The question is no longer whether an attack will happen but when. With this powerful security trio in place, you can rest easy, knowing you’re ready for whatever comes next.

Securing Kubernetes Runtime with Falco

For years, being a software engineer meant being really good at writing code. If you could architect scalable systems, optimise performance and push clean code, you were set. But today, things are different.

Claude 3.7 Sonnet, GPT-4, and GitHub Copilot

 than ever. AI can now generate boilerplate code, refactor functions, and even suggest architectural improvements.

If your only skill is writing code, you’re at risk of being 

 by those who can do more. The best engineers today aren’t just coding, they’re designing, thinking strategically, and deeply understanding users.

 is more than just a software developer. They don’t just execute someone else’s vision, they help 

 – They don’t just build features; they ensure they are intuitive and easy to use and solve real problems.

 – They care about how things look and feel, not just how they function.

 – Instead of relying on second-hand information from product managers, they engage with customers to understand pain points firsthand.

 – They’re aware of what competitors are doing and where opportunities lie.

 – Instead of fearing AI, they use it to 

. The best engineers today don’t just take orders; they help define the roadmap.

Why UX, Design, and Talking to Users Matter

. Engineers would just build whatever was written in a spec document. But the most successful products today aren’t just feature-rich; they’re 

1. UX is the Difference Between a Good Product and a Great Product

Think about the most popular apps, Apple’s ecosystem, Stripe’s payments dashboard, Figma’s design tools. They all have 

– A product should be snappy and responsive.

 – Users shouldn’t have to think too much to complete a task.

– Small details, animations, and feedback loops improve engagement.

Product Engineers don’t just make things 

2. Good Design Isn’t Just About Aesthetics, It’s About Functionality

Great design isn’t just about how something looks; it’s about 

If a feature is technically impressive but confusing to users, 

If an interface is cluttered, overwhelming, or inconsistent, 

 build products that people actually enjoy using.

Traditional engineers work in silos, they get a ticket and build it. But the best engineers today are 

 to see how they interact with the product.

“Why do people churn? Why do they hesitate before completing an action? What do they wish existed?”

When engineers engage with users directly, they make 

 problems, not just shipping features for the sake of it.

 made sense in an era where software development was slow and expensive. But AI, cloud computing, and modern tooling have 

Now, companies, especially startups, want 

 – Engineers understanding product strategy 

 make smarter trade-offs between speed, performance, and usability.

 – When engineers talk to users directly, they build what 

The best engineers today don’t wait for instructions. They lead.

Empowering engineers to think like product owners isn’t just about tools or individual skills; it’s about changing how teams work and how companies think.

To truly support this evolution, organisations need to foster a culture that values 

, contribute ideas, and take the lead on product decisions.

Breaking down the traditional silos between engineering, design, and product.

Rewarding not just the speed of delivery but the 

This kind of shift doesn’t happen overnight. It requires buy-in from leadership, a mindset of 

great ideas can come from anywhere, especially from those closest to the code and the customer

In an ideal world, this would already be the norm. But increasingly, it's becoming a 

. Especially in a landscape where speed, adaptability, and deep user understanding define the most successful team

talk to our users and potential customers

, ensuring that what we build is both powerful and easy to use.

, making decisions that improve the overall experience.

If you’re an engineer today, ask yourself:

, or are you disconnected from the people using your software?

 changing what makes an engineer valuable. The best engineers of the future won’t be those who can just 

The Rise of the Product Engineer: Why Just Writing Code Won’t Cut It Anymore

You’ve seen developer onboarding go well and also seen it go sideways in ways that make you wonder how companies ever ship anything. Bringing new engineers into a team is like adding a new instrument to a band. If you just hand them a guitar and point to the stage, it will not sound the best. But give them a clear process, some guidance, and a chance to practice, and suddenly, they’re making music.

The problem is, that onboarding isn’t always a priority. Companies focus so much on hiring the best talent, but then they throw them into the deep end with little more than a Slack invite and a Jira ticket. And then they wonder why it takes months for new developers to be productive.

So, let’s talk about how to do this right. Here’s an onboarding checklist that works. One that doesn’t just help new devs survive their first few months but sets them up to thrive.

The best onboarding begins before a developer even logs in for the first time. Think about it: the first days are overwhelming enough without having to chase down access credentials and figure out who to ask for help.


Set up their accounts in advance. Provide a clear onboarding document with links to everything they’ll need, from internal tools to team structures. Give them a buddy or mentor who can answer the “dumb” questions (which, let’s be honest, aren’t dumb at all). Maybe even send them a welcome email with some context about what to expect in their first week. A little preparation goes a long way in making new hires feel like they belong from day one.


2. Make the First Day About People, Not Just Process

Nobody joins a company just to write code. They join a team. Yet, so many onboarding processes focus purely on getting through paperwork and setting up environments.

You should take the time to introduce new devs to their teammates. Schedule one-on-ones with key people they’ll be working with. Have a welcome lunch (virtual or in-person). Consider assigning them a project “tour guide” who can walk them through how things work in the company’s codebase and development workflow. Your goal is to make them feel like part of the team, not just another name in a Slack channel.

Nothing kills enthusiasm faster than spending three days wrestling with local development setup. If you want your new devs to contribute quickly, then remove unnecessary friction.

A good onboarding checklist includes a clear, repeatable way to get up and running:

One-click environment setup (Docker, anyone?)

Clear documentation for installing dependencies

Pre-configured development environments with access to logs, databases, and cloud environments

But we know that environment setup means more than getting code to run locally. Developers must understand how to debug and test their changes effectively.

Your new hires should have immediate access to:

Logging and monitoring tools: Whether it’s Datadog, Grafana or another monitoring stack, they need to know how to track down issues in production.

Debugger setup: Debugging workflows for local, staging and production environments should be clear from day one.

Test environments and CI/CD pipelines: Where do tests run? How do they ensure they don’t break something when pushing changes? A clear introduction to test automation and CI/CD processes removes unnecessary anxiety around deployments.

 as much of this as possible. The faster a dev can push their first PR, the faster they feel like they’re making an impact. Investing in scripts, containerised setups, or developer platforms can drastically cut down on lost time and frustration.

The classic mistake: assigning new developers something massive and vague like “get familiar with the dev environment.” 

Instead, you should guide them through bite-sized, meaningful contributions:

Fix a small bug that introduces them to a key part of the system.

Improve a piece of documentation based on their onboarding experience.

Write a test for an existing feature to understand code quality expectations.

These tasks help them understand the dev environment in a hands-on way while also making them feel useful from the start. They also serve as natural conversation starters for asking questions and learning the team’s workflow.

5. Document the Right Things (and Keep It Updated!)

There’s nothing worse than documentation that’s either nonexistent or so outdated that it’s more confusing than helpful. But let’s be honest. Nobody likes writing docs.

Keep README files current and ensure they actually reflect how things work.

Maintain an internal wiki or Notion page with onboarding guides, team norms, and architectural decisions.

Encourage developers to update documentation as part of their PRs, rather than treating it as an afterthought.

It should also help developers understand who owns what. A new hire should be able to quickly answer:

Where do dependencies live, and how do they interact?

How does deployment work, and what are the post-deployment steps?

Interactive documentation tools (like the features offered by our SkyU platform) can help make ownership clear, providing service maps, API references, and dependency graphs that let developers explore rather than just read static pages.

It's a known fact that new developers often get stuck focusing only on the tasks in front of them. However, understanding the “why” behind the code is just as important as knowing the “how.”

What you need to do is give them a broad view of the product and its users.

Walk them through the customer journey with real user stories.

Show them the company roadmap and how their work fits into larger initiatives.

Explain business goals, product priorities, and technical trade-offs the team is currently navigating.

When your developers understand the impact of their work, they’re more engaged, make better architectural decisions and contribute more meaningfully.

New hires also need to understand how incidents and operational workflows fit into the big picture.

Incident management: What happens when a service goes down? Who gets paged? How do post-mortems work?

Runbooks & playbooks: If a service starts failing, where do they go to diagnose and resolve it?

Security & Compliance: Are there coding practices or security protocols they need to follow from day one?

Understanding the bigger picture helps in making sure developers don’t ship something that accidentally breaks everything else.

Asking questions is a huge part of getting up to speed on things.

The best thing you can do to foster a culture where it’s okay to not know everything. Some ideas:

Have a dedicated Slack channel for onboarding questions where no question is too small.

Make it normal for senior devs to share their learning experiences and past mistakes.

Encourage pair programming, knowledge-sharing sessions, and shadowing opportunities.

A strong support system during onboarding speeds up the learning process and helps new hires integrate into the team more smoothly.

Onboarding doesn’t end after the first week (or even the first month). It takes time to get fully integrated into a team.

A casual end-of-week chat to see how things are going.

A structured 30-day and 90-day review with clear milestones.

Opportunities for new hires to provide feedback on the onboarding process itself.

Onboarding isn’t a one-size-fits-all process, and regular check-ins allow you to adapt based on each developer’s unique experience and needs.

And Here’s Where Things Get Interesting…

You might be thinking: “This all sounds great, but it also sounds like a lot of work.” And you’d be right. Doing onboarding well is work. But it pays off. Teams that get this right see higher retention, faster productivity, and a better developer experience overall.

That’s why some companies are looking beyond just onboarding checklists and toward developer experience platforms that handle the 

. For example, platforms like SkyU are helping teams automate environment setup, streamline workflows, and make it easier for new devs to contribute from day one. When you remove friction, you don’t just onboard developers; you set them up to stay and succeed.

So if you’re still relying on tribal knowledge and outdated Google Docs to get new hires up to speed, maybe it’s time to rethink how you do onboarding. Because a great onboarding experience isn’t just nice to have. It’s a competitive advantage.

Want to see how SkyU can simplify onboarding and improve developer experience? Teams using SkyU reduce onboarding time by 30%.

SkyU’s recent success with a leading RegTech company highlights how automated DevOps workflows can reduce deployment time from a full day to minutes, improving developer onboarding, security, and scalability.

Why Your Dev Onboarding Fails (And How to Fix It)

Building a system takes more than just the development effort; maintaining and covering features takes much more. There is scalability, maintainability, availability, usability. The list goes on and on. With so many things to focus on, how do you keep the platform up and running? A better question might be - what do these even have in common? How do these add value to our systems? Each of these priorities bring value to the table. This includes service reliability alternatively referred to as SR. Yet, the question is how does it add value?

At its core, reliability is about delivering a usable and dependable product for the user. Why focus on the user? Because reliability is all about their experience with your service. If your metrics and measurements don’t account for the user’s perspective, you are missing the point of what reliability truly means.

But why is the customer experience so tied to reliability? Imagine your service has an impressive 99.999% uptime, but customers are dealing with inconsistent performance. In that case, your service is not reliable. On the flip side, if a significant portion of your back-end services are down, but customers don’t notice because of effective mitigations, your service is still reliable.

To dig deeper, we will break reliability into smaller, more manageable pieces, and we will draw on how reliability is defined in manufacturing and engineering, using quality metrics as a guide.

According to the American Society for Quality, reliability is the likelihood that a service will perform its intended function over a specific period. This includes several key components such as probability of success, durability, dependability, availability to perform a function, and quality over time. Let me give you more details about this.

Building Blocks of Service Reliability: What Makes It "Good"!

This is about the ratio of successful requests to unsuccessful ones. For example, in a back-end REST service, a request is considered unsuccessful if it results in server errors, such as HTTP 500 status codes. But what about client errors like 400 (Bad Request) or 401 (Unauthorised)? In a healthy system, these errors should not typically count against the service’s success metrics since they result from incorrect client requests rather than issues with the back-end itself. However, this assumes that the client is functioning correctly and not introducing errors due to defects in its implementation—such as a faulty UI incorrectly invoking the API. Here, we focus on measuring the reliability of the back-end REST service as an isolated component of the system, separate from potential client-side issues.

This means how well your system can recover when things go wrong. If a database fails, can the user pick up where they left off, or is the data corrupted? Does it require a manual cleanup? If an instance of the system goes down, can traffic automatically reroute to another instance? Without a second doubt, fail instances happen in software and durability ensures that your service can handle them gracefully.

A dependable product or service works the way customers expect it to. It delivers the value you’ve promised and meets your service-level agreements (SLAs). While this isn’t always easy to measure directly, customer feedback, reviews, and quality indexes can help. If customers are leaving your product over time, it might be a sign that your service isn’t dependable enough.

Availability, or uptime, is a key part of reliability—but it’s not the whole story. People often confuse the two, thinking they’re the same. However, a service can have high availability but still lack reliability if, for example, it has a low probability of success. Even if only a small percentage of customers are affected by downtime, their experience still matters.

If redundancies or mitigations are in place to minimise the impact of availability issues, reliability can remain strong. For instance, if a service is down in one region or operating at half capacity, but 99% of customer transactions still go through, the overall reliability might still meet expectations.

In software, availability is often measured in “nines.” You might hear terms like “three nines” (99.9%) or “five nines” (99.999%) over a month. Availability is calculated by dividing uptime by the total of uptime and downtime, usually measured over a consistent period like a month or quarter. Keep in mind that not every service needs the same availability target—it depends on its specific use case.

Finally, quality over time helps us understand how reliability and the customer experience evolve. Are things getting better or worse? Are there underlying issues causing these changes? How can we improve or maintain stability? This varies from service to service, but even slow changes in metrics over time can signal areas that need attention.

How Scaling Teams Are Solving the Reliability Puzzle

As teams grow, keeping everything running smoothly gets more complicated. To handle this, companies are moving away from just putting out fires when things go wrong and instead focusing on building reliability into their processes from the start. By using tools like Platform Engineering and Internal Developer Platforms (IDPs), teams can create standardised infrastructure, automate repetitive tasks, and cut down on operational headaches. This makes it easier to deploy updates consistently, even as the team scales.

Advanced observability tools and AI-powered monitoring are also changing the game. They help teams catch potential issues before they turn into major outages, giving them a chance to fix things proactively. Pair that with automated CI/CD pipelines, and you’ve got a system that reduces human error and ensures deployments are stable and repeatable. And let’s not forget Chaos Engineering—it’s like a stress test for your systems, helping you find weak spots and make your architecture more resilient before real users ever notice a problem.

To make sure reliability aligns with business goals, many teams are turning to Service Level Objectives (SLOs). These set clear performance targets so everyone knows what “good” looks like. Add in self-healing infrastructure, which can automatically fix issues and reduce downtime, and you’ve got a recipe for scaling efficiently without sacrificing reliability. By weaving these strategies together, teams can keep systems up and running, boost developer productivity, and deliver a better experience for users—no matter how big they grow.

What strategies have companies embraced to keep SR?

Agile methodologies like Scrum, Kanban, and Lean are essential for maintaining service reliability while scaling teams. By breaking projects into smaller, iterative steps, teams can deliver services incrementally, test outcomes, and adapt quickly to changing demands. This approach ensures that as teams grow, they remain flexible and responsive to customer needs.

For example, cross-functional Agile teams can scale effectively by distributing responsibilities and maintaining clear communication channels. Regular sprint reviews and retrospectives help identify bottlenecks early, ensuring that service reliability doesn’t suffer as the team expands. Agile also fosters a culture of continuous improvement, empowering team members to take ownership and innovate, which is critical for scaling without compromising quality. Agile can also help deliver a product in a way that helps it mature.

Service design ensures that customer-centricity remains at the core of service delivery, even as teams grow. By mapping customer journeys and identifying key touchpoints, teams can design scalable processes that maintain reliability. Tools like customer personas, journey maps, and service blueprints help teams align their efforts, even when new members join or responsibilities shift.

As teams scale, service design provides a clear framework for onboarding new members and ensuring consistency in service delivery. By understanding customer pain points and expectations, teams can prioritise improvements that enhance reliability, regardless of their size. This structured approach prevents service quality from degrading as the organisation grows.

Automation and analytics are game-changers for maintaining service reliability during team scaling. Automation handles repetitive tasks, reduces human error, and frees up team members to focus on higher-value work. This is especially important as teams grow, ensuring that service delivery remains consistent and efficient.

Analytics, on the other hand, provides actionable insights into performance trends, helping teams predict and address issues before they escalate. For example, predictive analytics and AI can analyse historical data to forecast potential service disruptions, enabling teams to proactively mitigate risks. As teams scale, these tools provide the data-driven foundation needed to maintain reliability without overburdening team members.

Quality assurance is another aspect of service reliability, and thus, it can be used to mitigate the risk of reliability concerns. Tools such as Chaos Mesh can be used to test the fault tolerance and recoverability of infrastructure. Further, the availability of components such as API can be measured and approximated using performance testing tools.

Scaling teams successfully requires empowering employees to take ownership of service reliability. This means involving team members in decision-making, providing them with the right tools and training, and encouraging a culture of collaboration and innovation.

When teams feel supported and valued, they are more likely to adapt to scaling challenges and maintain high service standards. For instance, cross-training team members ensure that knowledge is shared, reducing dependencies on specific individuals and making the team more resilient as it grows. Empowered teams are better equipped to handle increased workloads and complexity without compromising reliability.

Stakeholder engagement is critical for maintaining service reliability during team scaling. Keeping customers, employees, suppliers, and partners informed and involved ensures alignment and builds trust. Transparent communication about changes, risks, and benefits helps stakeholders understand how scaling efforts will impact service delivery.

For example, involving stakeholders in feedback loops ensures that their needs are met as teams grow. This collaborative approach minimises misunderstandings and ensures that scaling efforts are aligned with stakeholder expectations. By fostering strong relationships, businesses can scale their teams while maintaining the reliability and quality of their services.

A reliable internal developer platform (IDP) is a game-changer for productivity and trust. Without it, even the most advanced applications can end up causing more headaches than they solve. Service reliability (SR) and IDPs are like two sides of the same coin—they work together to create smooth workflows, encourage team adoption, and speed up innovation.

At SkyU, our in-house IDP is built with reliability as its foundation. We rely on Kubernetes to power our deployment strategy, and its self-healing capabilities are a lifesaver when it comes to minimising downtime. Our deployment pipeline is carefully structured, moving code from development to production with rigorous testing and automated deployments. This not only cuts down on errors but also keeps things stable and predictable.

To keep things secure and running smoothly, we’ve baked in automated checks like vulnerability scanning and static code analysis. SkyU agents keep an eye on critical cluster metrics, sending alerts the moment something seems off so we can tackle issues before they escalate. Health probes are constantly checking to make sure services are up and running, while firewalls and API gateways act as our first line of defence against malicious traffic.

By combining proactive monitoring, automated recovery, and tight security controls, SkyU has built an infrastructure that’s not just robust but also highly reliable. It’s all about giving our teams the confidence to innovate without worrying about the platform letting them down.

Making sure services stay reliable as you scale isn’t just about throwing technology at the problem—it’s about finding the right balance between automation, security, and keeping a close eye on things. When teams start using internal developer platforms, it’s crucial to focus on standardisation, resilience, and observability. These are the building blocks for trust and efficiency.

By investing in things like self-healing infrastructure, well-structured deployment processes, and real-time monitoring, you’re not just making your systems more reliable—you’re also giving developers the freedom to innovate without constantly worrying about things breaking. At the end of the day, reliability isn’t just about keeping the lights on; it’s about creating an environment where teams can consistently deliver value, sustainably and without unnecessary stress.

Beyond the Buzzword: Why Service Reliability is a Must-Have for Scaling Teams

Platform engineering is no longer a niche function within IT. It is the cornerstone of modern digital enterprises. As businesses prioritise scalability, agility, and resilience, platform engineering is at the forefront of enabling innovation through infrastructure optimisation, automation, and AI integration. In 2025, platform teams are evolving from infrastructure providers to strategic enablers, driving business agility and innovation. This article explores key trends shaping the landscape of platform engineering, as informed by Gartner’s Top 10 Strategic Technology Trends for the upcoming year.

In this article, we take you through the hype cycle for platform engineering in 2024 by Gartner. As you can see, platform engineering has experienced a massive surge in recognition, with the discipline now appearing on over 10 different Gartner hype cycles—a nearly 5x increase from last year. Notably, there is now an entire hype cycle dedicated to platform engineering. This growth is mirrored in the platform engineering community, with job titles on LinkedIn and interactions at major conferences like PlatformCon showing a strong, upward trend.

Additionally, infrastructure platform engineering, a key subdiscipline, has been featured in 8 different hype cycles, including those for Cloud Computing, SRE, and I&O Automation. This further highlights the increasing importance of platform engineering in driving innovation and business transformation. As Chief Technology Officers (CTOs) seek to drive their organisations forward, platform engineering emerges as a critical focus area, empowering them to achieve unparalleled levels of efficiency, security, and innovation.

This overview of platform engineering trends will be concise and focused, presenting a streamlined list of key insights.

What is happening to platform engineering in 2025?

By 2026, 80% of large software engineering organisations will establish platform engineering teams as internal providers of reusable services, components, and tools for application delivery — up from 45% in 2022. This reflects the growing recognition of platform engineering's role in simplifying development processes and enhancing productivity, and this is exactly where the AI-powered platform engineering trend first starts to emerge.

As we already know, AI/ML is deeply integrated into platform operations, automating tasks like infrastructure provisioning, resource allocation, and incident response. Thus, AI in platform engineering enhances operational efficiency and reduces manual effort for platform teams. It improves resource utilisation and optimises costs through predictive analytics while enabling faster incident resolution and better application performance with proactive monitoring and anomaly detection.

For example, a platform team can use AI to predict and automatically scale resources based on anticipated demand, ensuring optimal performance and cost-effectiveness.

Platform architectures are becoming more modular and flexible, making it easier for businesses to adapt quickly to changing needs. By reusing pre-built components and services, teams can develop and launch applications faster while staying agile to respond to market shifts and customer demands. This approach also improves scalability and makes platforms easier to maintain over time.

For example, a financial services company could create a platform with reusable modules for authentication, payment processing, and data analytics, allowing it to roll out new financial products more quickly and efficiently.

Case in point, Bob Simms, director of enterprise infrastructure delivery at the US Patent and Trademark Office (USPTO), highlights how their platform engineering teams support over 200 applications by focusing on automation and observability. “We went from weeks to get a deployment done to minutes,” says Simms.

This rapid deployment capability is paired with infrastructure service-level monitoring and automated responses. “If we have a particular type of outage, our observability tool can also restart the application.” Such innovations demonstrate how composable platforms enable both scalability and resilience.

Security is now built into every stage of the software development process, with platform teams playing a key role in enforcing security policies and best practices. This integration helps reduce vulnerabilities and strengthens the overall security posture, while also speeding up the identification and fixing of security issues, by eliminating security-related obstacles, developer productivity increases.