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.

Moving onto an example, a platform team might adopt security-as-code principles, automating security checks and ensuring that security policies are followed throughout the entire application lifecycle.

Further emphasising the role of structured pipelines, Sanjay Srivastava, chief digital strategist at Genpact, explains how platform engineering streamlines processes. “Platform engineering allows us to build a common pipeline and methodology for every product we deploy,” he says. This consistency not only simplifies security enforcement but also addresses talent gaps.

“We found this particularly helpful when it comes to skills and talent, which are hard to find and retain.”

4. Multi-Cloud and Hybrid Cloud Strategies

Platform teams are increasingly managing infrastructure across multiple cloud providers and on-premises environments as part of multi-cloud and hybrid cloud strategies. This approach provides flexibility, scalability, and resilience while optimising costs by leveraging the strengths of different providers. Organisations can mitigate vendor lock-in, enhance disaster recovery, and tailor infrastructure to business needs. For instance, a retail company might adopt a hybrid cloud strategy by using the public cloud for scalable e-commerce and a private cloud for sensitive data, ensuring both performance and security.

For CTOs, these strategies are critical to driving innovation and ensuring business continuity. Multi-cloud adoption reduces dependency on a single vendor, enabling cost-effective scaling and improved risk management. CTOs can leverage these approaches to modernise IT operations, support AI-driven applications, and enhance collaboration across teams, ultimately delivering faster and more reliable services.

Platform engineering plays a key role in enabling these strategies by abstracting infrastructure complexities and automating tasks like provisioning and scaling. Tools such as VMware vRealise, HashiCorp Terraform, and Microsoft Azure Arc help standardise operations, ensuring seamless integration and consistent performance across diverse environments. This allows CTOs to maintain operational efficiency and security while focusing on strategic growth.

A significant majority of enterprises, over 84%, have adopted multi-cloud strategies to enhance cost efficiency, and business agility, and leverage top-tier services from various providers. According to Google, it is expected that more than 85% of organisations will adopt a cloud-first approach by 2025, with over half utilising multi-cloud strategies to foster business innovation and accelerate digital transformation.

In platform engineering, success hinges on providing a great developer experience. Just like a company’s performance is often judged by customer satisfaction, a platform engineer’s impact is measured by how easy and enjoyable it is for developers to work with the platform.

If the platform feels clunky, overly complicated, or inefficient, developers won’t want to use it. And if developers don’t use it, the platform’s value drops significantly.

At PlatformCon2024, Darren Evans (EMEA Practice Solutions Lead, Application Platform) delivered a talk titled "Improving your developers' platform experience by applying Google Frameworks and Methods”, where he discussed Google's HEART Framework, which offers a comprehensive perspective on the developer experience within an organisation by using actionable data. This was a major point in creating developer experience as a trending pinpoint for 2025 in platform engineering.

In platform engineering, the HEART framework can be adapted to fit different goals and situations. For example, enhancing the onboarding experience for new developers might prioritise adoption, task success, and satisfaction. On the other hand, rolling out a new feature could focus more on adoption and happiness. To boost overall platform usage, it may be important to track metrics like engagement, retention, and task success.

Platform teams are increasingly focusing on improving the developer experience by offering self-service tools and easy-to-use interfaces. This shift leads to higher developer productivity and satisfaction, as it reduces the need for platform teams to handle routine tasks. As a result, teams can launch new applications and features more quickly. A platform team might provide a self-service portal that allows developers to provision resources, deploy applications, and monitor their infrastructure without needing constant assistance from the platform team.

Platform engineering in 2025 is evolving rapidly. By embracing these trends, platform teams can empower developers, drive innovation, and deliver exceptional business value. As technology continues to advance, platform teams will play a critical role in shaping the future of digital enterprises.

Platform engineering has become a key focus in IT and operations (I&O) as companies work to handle the growing complexity of cloud-native and distributed systems. Over the past decade, more organisations have adopted platform engineering to simplify workflows and better support their development teams. These efforts have come a long way, proving they can boost scalability and improve developer productivity.

The platform engineering community has also grown, with over 15,000 engineers now sharing ideas and best practices. Events like PlatformCon 2023, which recently held its second edition, show how much interest this field is gaining. These conferences are a great way for CTOs and tech leaders to stay updated on the latest trends, tools, and strategies shaping the future of platform engineering.

This article is based on sources such as Gartner, cio.com, and studies based on industry trends. The specific impact and relevance of these trends may vary depending on the individual organisation and its specific needs.

I hope this article provides a valuable overview of platform engineering trends for 2025!

Top 5 takeaways from the State of Platform Engineering Report 2024

CIOs take note: Platform engineering teams are the future core of IT orgs | CIO

The Role of Platform Engineering in Multi-Cloud Strategies for 2025 | Improwised Technology

How platform engineers can improve their developers’ experience | Google Cloud Blog

Platform Engineering Trends in 2025: A CTO's Guide

This article is aimed at test analysts and other stakeholders who engage in software quality assurance in a managerial capacity. The article discusses some of the unique challenges and opportunities associated with testing an Internal Developer Platform product like SkyU and shares a few reasons why buying one is better than building one in-house.

The International Software Testing Qualifications Board defines testing as “a set of activities to discover defects and evaluate the quality of software artifacts” [1]. Typical software testing activities include activities such as analysing requirements, designing test cases, executing test cases, and comparing expected results with the actual results to identify defects. Based on criteria such as the product architecture, technologies, and business requirements, these testing activities' effort, complexity, and risk tolerance can vary greatly.

To understand this idea, imagine how a product team developing a food order management system for the internal use of an organization might settle for simpler less effortful solutions with higher risks related to the quality of their product compared to a mission-critical food order management system that is built to cater to an entire nation which would demand a much lower tolerance of risk at higher complexity and effort. SkyU, as a PaaS product open to organisations with product development aspirations on both ends of this spectrum, the SkyU QA team has to ensure the product meets the quality assurance expectations of both mission critical software projects as well as software projects catering to trivial business needs.

Challenges and Opportunities Testers of Platform Engineering Products Can Expect

The challenges of testing a platform engineering product like SkyU can be categorised into,

Challenges that arise from the large number of 3rd party services and technologies that need to be bundled in.

Challenges associated with conducting manual and automated end-to-end testing.

Though internal developer platforms are built specifically to meet an organisation's needs, with an OOTB platform engineering product like SkyU, you can't offer a narrow set of features and configurations. This results in the need to support a large number of third party services such as Github Actions, Docker Hub, AWS EKS, and ChatGPT, as well as technologies like Docker, Kubernetes, Helm, and Kustomize. These services and technologies need to work seamlessly across the various layers that make up the product. From a quality assurance perspective, the interconnectedness of these components increases testing activities.

When it comes time to design test cases, a tester will analyse the functionality offered by these 3rd party services and identify how it relates to the functionality offered to the end user. The tester will then employ test design techniques such as 

pairwise testing, decision tables, state transfer diagrams,

 to design the optimal number of test cases to cover the feature. A pain point unique to IDP products to this end is the identification of all the expected results for a given test case.

For example, if a new Cloud CI service is being introduced as a feature (say BitBucket), when creating test cases, a tester may need to identify the expected results to look for in the GUI under the ‘Developer Control Plan’, ‘Integration’, and ‘Delivery Plane’ and the ‘Monitoring Plane sections’. The tester will then need to identify any expected results related to the database that is only accessible through the API layer. Finally, the tester will need to look at the expected results that need to be accessed in the 3rd party service, such as the commit history or pipeline information.

Another pain point associated with testing IDP products is the complexity involved in creating end-to-end test automation scripts. The automation scripts require adaptation to interface across multiple services, architectures, and interface types while maintaining synchronisation between the scripts and the system under test. This is to ensure a reliable test execution.

However, it's not all pain for the tester, as Churchill is known to have once said “A pessimist sees the difficulty in every opportunity; an optimist sees the opportunity in every difficulty”, the very challenges associated with testing an IDP can be the strengths that can propel the careers of testers of an IDP product past that of their peers in this day and age of AI prompt based software engineering. As testers work their way into the innards of the product, they will get opportunities to up their DevOps skills and knowledge which is still highly sought after. Coupled with their experience in quality assurance, they will be able to uniquely position themselves in the job market.

The benefit of going with platform engineering products on an organisation's software quality assurance function

One of the main selling points of going with a platform engineering product like SkyU, as opposed to building a platform in-house, is the lowered cost of ownership. One reason why this is a valid point is the quality assurance-related effort that goes into the delivery of an IDP product. Organisations can piggyback on the process of testing which the vendor has already put into the product. They can benefit from the feedback cycle from other users who’ve used it and the community as a whole.

Ideally, the IDP product vendor should ensure the quality of the three lower levels of the test pyramid. That is the component level testing through developer unit tests; integration level testing through component integration testing and API testing and system level testing through end-to-end testing. Meaning, organisations can focus on the different acceptance tests such as operational acceptance, regulatory acceptance, and user acceptance. All of this will lead to a cheaper and faster ownership of the IDP.


In summary, this post aimed to provide an overview of the challenges and opportunities that IDP product testers may encounter. It also highlighted the benefits organisations can gain by purchasing an IDP rather than building one in-house, particularly in terms of the advantages it offers to the quality assurance function and the impact on the bottom line.

https://www.istqb.org/certifications/certified-tester-foundation-level

https://qacraft.com/levels-of-testing-in-software-testing

Testing an Internal Developer Platform: Why Out-of-the-Box Solutions Make Sense

TLDR: We launched automated release management for SkyU.io! Share, discover, and implement the feature built to automate your experience as a release manager. Learn how, why, and what to try first, below.

Hey all, Heshan here. Here’s a little about the "Project Releases" feature the team has been working on.

If you've ever shipped software, you know the drill. Release days can be absolute nightmares. Last-minute fixes, versioning confusion, and that awful moment when something goes wrong in production... it's hectic!

But with "Project Releases," we're finally tackling this head-on.

Streamlined releases, from start to finish:

 Get a clear view of your entire release process, from code freeze all the way to deployment. No more scattered tools and endless email chains.

Automation that actually makes a difference:

 Ditch the manual work and embrace automated deployments, testing, and even rollbacks.

Ship with confidence, every single time: 

"Project Releases" helps you reduce errors, keep tabs on your progress in real-time, and release with peace of mind.

In the end, we’re building a culture where releases are smooth, reliable, and even (dare I say) enjoyable. We want to help you reclaim those release days and turn them into a celebration of your team's hard work.

So give "Project Releases" a shot and let us know what you think! We're always looking for feedback.


Solving for X: So what is “Project Releases”?

Imagine the time and effort involved when getting your application deployed out there. In most development cases, this consists of the deployment of multiple environments for the app as well. It could be development environments, staging environments, or production environments. It could be N number of environments depending on the specific deployment strategy followed by a specific team.


Now imagine having a microservices architecture. Each service is deployed across multiple environments, collectively working together to provide functionality to an application. With each new service and environment, the deployment 

 increases drastically while also introducing a lot of other challenges.

How do you track applications that are up to date?

Did each application deploy successfully?

If one fails, do you proceed with the deployment of others?

If one failed, where and why did it fail?

Moreover, these services and applications can be of many different types. Mobile apps, web apps, Kubernetes orchestrations, Lambdas, etc.


The SkyU platform offers a wide range of features when it comes to deployments, and one of its core features is “Project Releases”.

We built the Project Releases feature to simplify and streamline the deployment process for software release/delivery teams. As we discussed, as applications grow in complexity, managing multiple services and their dependencies becomes increasingly difficult. This feature enables release managers to handle all applications and their dependencies as a single “bundle”. This makes it easier to maintain consistency, reduce human error, and improve deployment efficiency. By offering the ability to promote or roll back multiple components at once, we empower teams to deploy with confidence and agility. Save time and reduce the risk of deployment-related issues.

Let’s imagine a simple coffee shop scenario. The overall project is the coffee shop itself, which we’ll call “Bean & Brew.” This project includes a website (a web application) and services for handling user authentication, orders, carts, and catalogues (containerised APIs).


Once we create these five applications in SkyU service catalogue, the setup might look something like this:

Let’s take a look at how we can overcome the above-mentioned challenges in the context of Bean & Brew.

At a glance, this can be seen via the colour variations. However, behind the scenes, SkyU compares commit SHAs. Why? So you don’t have to!

The development environment is updated each time changes are made in the application repositories, thanks to straightforward “Git” operations running in the background. If your team follows a specific branching strategy, “Staging” and “Production” environments are also updated periodically through designated branch patterns and merges. However, the SkyU project release feature is flexible and will work even if you have just a single main branch for each application.


How do you deploy EVERYTHING, EVERYWHERE ALL AT ONCE?

SkyU makes it easy to promote these applications across environments, giving complete control to the person handling the release. You can choose to deploy all applications at once or selectively pick the ones you want to deploy.

This will start the deployment process of these applications as you can see here.

Give it a few minutes and then it’s done.

Did individual applications deploy successfully?

Yes, and you can confirm this visually from the SkyU console. The platform verifies that all promoted applications were successfully deployed. Verifying updates depends on the application type: for instance, if it's a web application, you only need to check if the newly promoted environment reflects the changes from the previous environment.


If even one application fails, the deployment enters a "Ready to deploy" state. From here, you can decide whether to partially deploy the successful applications. This decision is left to the user and may depend on factors such as the interdependencies between services.

To demonstrate, let's intentionally fail a deployment. A failed deployment is marked with a red dot, which links to the pipeline's execution logs, showing where and why the issue occurred.

The specific issue can be uncovered from these logs afterwards. Along with many other SkyU features like AI-powered debugging and AI-suggested solutions to fix these issues.

Rollbacks are just as simple as releases. This is because SkyU tracks the release history of your project.

This makes it so that going back to a previous deployment is as easy as selecting the deployment you want to roll back to. That’s it.

This approach works seamlessly for a straightforward project, like our Coffee shop example. But what about a more complex scenario? We decided the ultimate test case for SkyU was… SkyU itself. Enter the concept of “SkyU on SkyU.”


SkyU is a sophisticated application, with over 25 microservices and a continuously evolving tech stack. And, currently, 100% of SkyU’s deployments are managed by SkyU itself. This automation allows our developers to focus on development rather than deployment complexities, making “SkyU on SkyU” a true showcase of the platform's potential.

In our view, deployment doesn’t get more complex than this. And if it does, it may signal inefficiencies in the process. That’s where we can help, so feel free to reach out if you're facing deployment challenges.

Experience the power of SkyU's seamless deployment management for yourself. Get access to the “Project Releases” feature in any of the pricing tiers available with the SkyU platform (Startup, Growth or Enterprise). 

. Or if you would like to chat about releases and how you can improve your development velocity, 

Introducing “Project Releases” on the SkyU Platform

In platform engineering, two common metaphors illustrate the impact of design choices: 

. Both represent an opinionated approach to platform design, but their outcomes are strikingly different. This article explores the delicate balance between structure and flexibility, the importance of avoiding traps, and how the decision between 

Golden Path: Guidance Without Restriction

 is the ideal many platform teams aspire to create—a curated experience that provides developers with a smooth, efficient, and secure route to deliver value. By using standardised workflows, approved tooling, and best practices baked into the platform, developers enjoy:

: Reduced complexity for new team members.

: Fewer distractions from operational tasks.

: Compliance and reliability are built into the workflow.

. Developers can choose to diverge from the opinionated path when their use case demands innovation or customisation, enabling them to tackle unique challenges without hindrance.

Golden Cage: Over-Optimisation Gone Wrong

, on the other hand, results when platforms are designed with too many constraints, turning guidance into restrictions. Developers might find themselves stuck in rigid workflows that don't cater to their unique needs or the evolving demands of the business. This happens due to:

: Tools and processes that cannot evolve with technology.

: Developers spend more time bypassing the system than delivering value.

The Golden Cage stifles innovation, frustrates teams, and ultimately slows down the organisation.

Flexibility is the antidote to the Golden Cage. A great platform balances opinionated guidance with the freedom to adapt. Here's why flexibility should be at the core of any platform:

: Teams can innovate without being locked into a single way of working.

: Platforms can grow with the organisation, integrating new tools and workflows as needed.

: Flexible systems adapt to change, preventing obsolescence.

Flexibility doesn't mean chaos; it means offering curated paths with the option to step off-road when necessary.

 your platform profoundly affects whether you achieve a Golden Path or fall into a Golden Cage. Each approach has its merits and trade-offs, and the right choice depends on your organisational goals, resources, and expertise.

Building your platform offers the ultimate in customisation. With tools like Spotify's Backstage, organisations can create a fully tailored experience. However, building is not without challenges:

: Building an internal platform requires a significant upfront commitment in terms of time, money, and skilled personnel.

: A dedicated platform engineering team is essential for development, iteration, and maintenance.

: Beyond the initial build, ongoing upkeep, scaling, and adapting to new technologies demand continuous effort.

While building offers complete control, the cost in resources and operational burden can be prohibitive for teams without extensive platform engineering expertise.

Buying a platform offers an immediate return on investment (ROI), especially for teams that need to hit the ground running. Solutions designed for internal developer platforms (IDPs) deliver:

: Platforms like SkyU provide workflows, integrations, and compliance out of the box, minimising the time to value.

: Prebuilt platforms reduce the need for large platform engineering teams, freeing resources to focus on business outcomes.

: Vendors often provide ongoing updates and support, ensuring the platform stays relevant as your organisation grows.

Buying a platform lets you focus on delivering software rather than building infrastructure. It strikes a balance between the Golden Path’s efficiency and the flexibility needed to avoid the Golden Cage.

In platform engineering, the difference between a Golden Path and a Golden Cage comes down to design choices that prioritise flexibility and developer empowerment. Whether you choose to build or buy, the goal should be the same: to create a platform that enables developers to deliver value efficiently while preserving the freedom to innovate.

For teams ready to invest deeply in customisation, building a platform may offer unmatched control—but it comes at a cost. For those seeking immediate productivity gains and long-term adaptability, buying a solution offers an easier path to success. Platforms like SkyU exemplify this approach, enabling teams to embrace the benefits of the Golden Path without the risk of becoming trapped in a Golden Cage.

Golden Path vs. Golden Cage in Platform Engineering: Why Flexibility Matters

In the fast-paced world of Formula 1, speed and precision are everything - every millisecond counts and a tiny misstep can mean missing out on the podium. It’s a lot like platform engineering, where the goal is to deliver software quickly and efficiently while juggling complex systems. Just as F1 teams fine-tune every detail, from engine performance to pit stops, platform engineers analyse data and make split-second decisions to stay ahead. The bottom line? In both, being “slow and steady” just doesn’t cut it. If you want to win, you’ve got to prioritise speed and adaptability.

Platform engineering, much like F1, operates in a high-pressure, high-speed environment. The demand for continuous integration, continuous deployment (CI/CD), and fast iteration cycles mean that platform teams need to design systems that are not only stable but also capable of supporting rapid changes and scaling without delay. In modern businesses, the ability to release software updates quickly and reliably is crucial to staying competitive.

Platform engineers must continuously improve infrastructure, deployment pipelines, and observability tools to keep everything running at top speed. This has gotten increasingly complex as the cloud-native computing landscape is a lot to take in!

Platform teams need to choose the right tooling and figure out how best to create toolchains that work. Source: 

Why “Slow and Steady” Fails in Platform Engineering

Platform engineers must keep up with the fast-moving technological landscape. With rapid innovations in cloud computing, DevOps practices, and container orchestration, moving slowly risks falling behind. Those who aren’t constantly improving their platforms may be overtaken by competitors with more agile, modern systems.

They need to solve problems in real-time. Quick responses are essential, whether it's handling unexpected traffic spikes, mitigating security vulnerabilities, or fixing failed deployments. Slow responses in either environment can lead to catastrophic results, whether that’s a car retiring from the race or an outage that costs a company millions in lost revenue.

Every experience offers new lessons, and teams must adjust accordingly. Platform engineering operates under the ethos of 

. Static systems that evolve slowly will eventually struggle under new demands. Continuous delivery pipelines, automated testing, and infrastructure as code help engineers maintain the pace needed to deliver value quickly and consistently.

The most effective systems are those optimised for high performance while maintaining control. Platform engineers strive to create systems that can handle high traffic, scale efficiently, and remain reliable under heavy workloads. While a cautious approach may reduce risks, it can also limit opportunities for innovation.

In all these aspects, just as in racing, the key to staying competitive lies in agility, quick decision-making, and a commitment to continuous improvement.

A well-designed technology platform can make a huge difference here - not just for the Platform team but for the entire “pit crew” of your organisation (Infra, Ops, Security, Information Systems, Site Reliability and more). The concept of an internal developer platform is not new. It emerged as a modern way to run engineering teams with elite teams self-building IDPs for around 5 years prior (for example, Spotify, Airbnb).

Build vs Buy: Internal Developer Platforms in the Race for Speed

Platform engineering teams face a critical decision now: should they build an internal developer platform (IDP) from scratch, or should they buy an off-the-shelf solution? Platform engineers must assess which will get them across the finish line faster.

For many teams, the best approach is often a 

. They may start with a bought solution that covers their core needs and then customise or extend it where necessary, combining the best of both worlds.

SkyU: A Solution to Accelerate Your Platform Engineering

 option for an internal developer platform, SkyU is a powerful solution designed to meet the demands of modern platform engineering. SkyU is built to help teams streamline their development processes, enabling faster software delivery while maintaining the stability and scalability needed to compete in today’s fast-paced environment.

With SkyU, platform engineering teams can:

 SkyU's pre-built platform ensures you can get started quickly, reducing the friction and delays associated with building an IDP from scratch.

 By providing streamlined workflows and automation tools, SkyU helps your engineering teams focus on innovation rather than infrastructure management.

 As your organisation grows, the platform scales effortlessly, ensuring that your internal systems are always ready to handle increasing demands.

The platform offers continuous updates and support, allowing platform engineers to focus on delivering value rather than worrying about maintaining the platform itself.

Choosing SkyU lets you bypass all of the complexities and time constraints of building a custom platform. At the same time, it modernises your software delivery, accelerating and transforming your customer experience entirely.

In F1, the winner isn’t the one who drives the safest, but the one who drives the fastest while making the fewest mistakes. In platform engineering, the same holds: speed, agility, and continuous improvement are the keys to success.

So, buckle up - slow and steady won’t win this race. 

F1, DevOps & Platform Engineering: Why Slow and Steady Won’t Win the Race

Blue/Green deployment strategies allow you to minimize downtime and reduce risk during application updates. In this article, I will walk you through setting up an Amazon ECS (Elastic Container Service) Service with Blue/Green deployment using AWS CodeDeploy.

This approach ensures that your service remains available while rolling out new application versions. AWS CodeDeploy enables you to deploy new versions of your application without causing downtime. It allows for a gradual shift of traffic from the old version (blue) to the new version (green).

Here is the Overview of a Blue-green deployment:

In the architecture shown above, we use several key AWS services to manage the automated blue-green deployment:

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