At Inther Software Development (ISD), we believe technology matters most when it supports a greater purpose. That’s what brought us into the MCharity project five years ago, a platform created to help people in moments of real need. From the beginning, we saw an opportunity to contribute more than code, to strengthen a mission that resonated with us. Here’s how this partnership grew and evolved over the years.

2020: A Vision Is Born

When mcharity.org was launched (around 2020), its founder, Tatiana Rusu, brought with her a clear vision shaped by years of volunteering and helping families in need while living abroad.

In Tatiana’s words, the “M” in MCharity originally stood for Moldova but later evolved into Moment – reflecting the belief that a single moment of kindness can change a life. As our client, she came to ISD with a mission that extended far beyond technology, and our role was to help her turn that mission into a stable, scalable platform.

From the very start, ISD stepped in as a technical partner. Our mission was to build a reliable, scalable platform that could support charity campaigns, donations, storytelling, and community engagement.

2021: Initial Release and Early Challenges

In the first production year, MCharity’s architecture reflected its purpose: a template-driven content system that allows creation of independent “stories,” campaigns, and news, each rendered as a separate page. This flexibility meant that the foundation could easily run different campaigns, each with its own landing page.

However, real-world use revealed performance bottlenecks. As the volume of content, visitors, and donors grew, load times slowed. The growing load began to overwhelm the system, leading to intermittent downtime.

Because the frontend was based on a client-side architecture (browser-based rendering), metadata wasn’t reliably picked up by search engines or social platforms, which limited the platform’s visibility and reach.

2022–2023: Optimizing for Impact

Recognizing these challenges, ISD began a focused effort to optimize performance. We introduced caching, optimized the way data is loaded on the website, database query tuning, and efficient rendering, reducing page load times and server strain.

We still faced one significant challenge: a complex SEO issue that limited how well the platform was recognized by popular search engines and social media platforms, and for a long time we couldn’t find a quick or reliable solution to address it.

With no straightforward fix for making metadata visible to Facebook and Google crawlers, ISD brought in an external consultant to develop a stable solution. Together, we added a server-side rendering (SSR) layer using Node.js, allowing pages to be pre-rendered before they reach the browser. This change improved indexing by search engines and social platforms, helping MCharity’s mission be discovered by more people. Over time, Google Analytics data confirmed better organic traffic and engagement.

2023–2024: A Complete Redesign for a Stronger Platform

By 2023, the time had come for a full redesign, not just cosmetic, but structural. We overhauled the frontend, modernizing the UI/UX to make storytelling more compelling, intuitive, and mobile-friendly. Independent campaign pages now felt more like human- centric narratives rather than static templates.

Visitors weren’t just browsing, they were looking for clarity, trust, and a smooth, reliable experience. A cleaner and more structured interface helped them understand each story faster, navigate with confidence, and connect emotionally with each campaign.

At the same time, the redesign brought essential technical improvements: a modernized frontend architecture that improved responsiveness, reduced rendering time, strengthened SEO in combination with the new SSR layer, and removed legacy constraints that limited scalability. Together, these changes created a platform that feels intuitive for users while remaining flexible, stable, and ready to support future growth across both Moldova and Romania.

Behind the scenes, we strengthened the backend as well, making sure the platform could handle more users, more campaigns, and increasingly complex donation flows.

• Expanded and stabilized payment integrations to ensure reliable contribution channels:
  • Moldova: PayPal, Paynet API, SMS donations, voice-call donations, bPay, MAIB tools, and manual import of donation
  • Romania: Banca Transilvania (BT) API for bank card payments, PayPal, and redirect to
• Enhanced accounting and reporting through automated daily and monthly donation reports, making financial reconciliation faster, clearer, and more transparent for the foundation’s
• Optimized media storage using AWS cloud solutions to ensure secure, scalable management of all campaign assets.
• Unified all services on Amazon EC2 instances, providing the flexibility, stability, and scalability needed to support new features and peak traffic during major

Together, these improvements delivered a platform that is not only more engaging and intuitive for users, but also more robust, efficient, and ready for long-term growth.

2024–2025: Stability, Growth s Measurable Success

The redesign and optimization efforts had transformed MCharity into a stable, high- performing platform. Monitoring tools and Google Analytics showed consistent traffic growth, stronger SEO visibility, and higher donor conversion rates. These improvements highlighted ISD’s technical craftsmanship and the strength of our long-term partnership with MCharity.

The platform now supports:

• A template-driven storytelling engine, where each campaign is dynamically generated, but with its unique voice and
• Customization per country: The system adapts functionality depending on whether the campaign is managed by the Moldovan foundation or its Romanian
• Financial integrations that are robust and
• Operational tools, such as automated accounting reports, email newsletters, and notification systems to keep donors and stakeholders

Beyond Code is Partnership

ISD’s role in MCharity is more than just technical. Over these five years, our team has grown deeply invested in the mission: We support key campaigns not only by building their digital infrastructure but by contributing to their planning and execution. The project where ISD is a partner for each year, is Frumusețe fără limită, fashion show events featuring people with disabilities. fashion show events featuring people with disabilities.

Our developers, designers, and product managers engage with the MCharity team, capturing the human stories behind the donations, helping shape digital appeals, and ensuring the user journey is compassionate and effective. We’ve joined MCharity in its long-term vision: not just raising funds, but building a community where people are heard, supported, and empowered.

“The partnership between the MCharity Foundation and ISD has been one of the key pillars of our humanitarian work over the past five years. The platform .mcharity.org is more than a website, it is the heart of our mission, where hope takes shape and where a simple gesture can become a life saved. From the first concept to today’s continuously evolving version, ISD has been by our side with professionalism, patience, and solutions we could rely on. Their ongoing support, the way they adapted the platform as our campaigns grew, and their quick help in urgent moments have strengthened our trust and made our work possible. Thanks to this partnership, people can donate safely and easily from anywhere in the world, and hundreds of lives have been touched. We are truly grateful to the ISD team for their dedication and openness. Together, we are confident we will continue building a strong, modern platform that brings light where it is needed most.”

 

Tatiana Rusu

Director, MCharity Foundation

Why This Matters (And Why It’s a Win for ISD)

• Social impact: Our work helps support real people, from medical cases to repatriation, elderly care, and stories that bring
• Technical excellence: We turned early issues into a stable, fast platform with solid SEO, AWS infrastructure, and secure
• Long-term trust: Five years of collaboration built a shared ISD is not just a vendor, but a committed partner.
• Visibility and growth: Better SEO and stability help MCharity reach more people, and inspire more donations.

Looking Ahead: Join Us in Bringing Hope

MCharity’s mission continues to grow, and every new supporter makes a real difference. Whether it’s helping a child receive medical care, supporting an elderly person, or giving a family strength in a difficult moment, every act of kindness matters.

Together with MCharity, we believe that hope is something we build together. And you can be part of it.

Join  the  initiative.  Read  the  stories.  Support  a  campaign.  Spread  kindness.

Visit mcharity.org and help transform a life today.

 

Anna Hirjeu

Senior Java Developer

in

The post Supporting Lives Through Technology: ISD & MCharity’s Shared Mission appeared first on ISD | Software Development.

Now, before we all start picturing a robot uprising on the loading docks complete with cold, metallic beeps and smug, circuit-board grins, let’s hit the brakes. Because if that’s your vision, you’re only seeing half the pallet, and trust me, there’s a lot more to unpack here.

With over 11 years of experience in industrial automation and PLC systems, mainly in the warehouse and logistics sector, I’ve seen the impact of automation from both a technical and human perspective. Working at ISD has been the key part in shaping this understanding by giving me the opportunity to be a part of projects where technology and people evolve together. Each time my team and I start a new project, we encounter the same concern from employees: “Are these systems going to replace us?” This is a genuine fear that we address on every implementation.

The reality is that automation is not about eliminating jobs but about transforming them. In the projects I have led and supported, I’ve seen how effective collaboration between people and technology leads to safer, more efficient, and more rewarding workplaces. Instead of replacing the human workforce, automation creates the conditions for better roles and higher-value contributions.

Why Are Warehouses turning to automation

Across the logistics industry, automation has become a necessity. The combination of e-commerce growth, workforce shortages, and demand for faster, error-free delivery has made it the most reliable path forward. Here’s the real story, stripped of the chrome and flashing lights:

1. According to Forbes the online sales reached $5.8 trillion in 2023 and intend to hit $7.9 trillion by 2027 creating unprecedented volumes in sorting, picking, and packing. Manual processes alone cannot keep up with this scale.
2. Labor Shortages: Physically demanding warehouse roles are increasingly difficult to fill, especially during seasonal peaks. Automation ensures continuity when the workforce is limited.
3. Demand for Speed and Accuracy: Customers expect same-day or next-day delivery with zero errors. Automation delivers the precision and throughput required to meet these expectations consistently.

In short, warehouses turned to automation not as an experiment, but as a necessity, to remain efficient, competitive, and responsive in today’s global marketplace.

What’s In It for the Business? (And Why Your CFO Will Love It)

Now, let’s get down to brass tacks and talk numbers. In the business world, the bottom line speaks volumes (and unlike your colleague Steve, who swore he scanned that pallet, numbers rarely lie).

Speed and Efficiency: From Sloth to Supersonic

Imagine boosting your operational speed by up to 300%. Sounds like science fiction, right? Well, with automated picking systems, it’s a very real, very profitable reality. Take Amazon, for instance. Their robotic pickers have been known to achieve an astonishing 400% increase in productivity. That’s not just an improvement; that’s practically teleportation by warehouse standards. To put it in perspective, we’re talking about transforming a process that might yield 250 lines per hour (roughly 4.2 lines per minute) into a powerhouse churning out 750 lines per hour (a blistering 12.5 lines per minute). This isn’t just about moving faster; it’s about fundamentally reshaping the velocity of your entire operation.

Accuracy: Getting Every Order Right, Every Time

Manual errors remain one of the most costly challenges in warehouse operations. They result in mis-shipments, customer dissatisfaction, and expensive returns. Automation significantly reduces this risk by improving picking accuracy from an average error rate of 2.5% to just 0.3% — a 90% improvement. The outcome is clear: fewer returns, lower operational costs, higher customer satisfaction, and greater confidence in inventory reliability.

Cost Savings: The Gift That Keeps on Giving

Fewer returns, fewer mistakes, leaner operations, it all adds to significant cost savings. While the initial investment in automated systems might seem substantial, the long-term benefits far outweigh the upfront costs. These systems don’t just pay for themselves, they become profit centers. By optimizing processes, reducing labor costs associated with manual tasks, and minimizing errors, automation delivers a compelling return on investment.

What About the People?

The reality is that automation is not designed to replace workers, but to change the nature of their roles. Routine and physically demanding tasks are shifted to machines, allowing employees to focus on higher value activities such as process optimization. This transition creates safer, more sustainable, and more engaging workplaces.

Creating Safer and More Sustainable Work Environments

Let’s be honest, warehouse work takes a toll. Carrying 20–30 kg (44–66 lb) totes and logging 15 km (9.3 miles) on foot each day is closer to an endurance sport than a relaxation routine. That’s exactly where robots excel. They take on the heavy lifting, the repetitive motions, and the endless walking, sparing human workers from the physical strain. Companies that adopt automation consistently report fewer workplace injuries, with claims often dropping by 25–40%. The result is a win-win: healthier employees, lower insurance costs, and safer, more sustainable operations.

New Careers, New Skills

The modern warehouse isn’t just about brawn, it’s about brains. Automation isn’t eliminating jobs, it’s creating new, more sophisticated roles. We’re talking about automation technicians, data analysts who can interpret the vast streams of information generated by automated systems. A compelling statistic from the World Economic Forum highlights this shift: 62% of companies using automation are actually hiring more people, not fewer. This isn’t a zero-sum game; it’s an expansion of opportunity, demanding new skills and fostering a more dynamic workforce.

Better Work Vibes: Engagement Over Exhaustion

When robots take on the grunt work, humans are liberated to focus on what they do best: supervision, quality control, and the creative problem solving that truly moves the business forward. Imagine a workplace where exhaustion is replaced by engagement, where repetitive tasks are replaced by strategic oversight. This shift leads to a more motivated, satisfied, and ultimately, more productive workforce. It’s about elevating the human element, allowing employees to contribute to their unique cognitive abilities rather than just their physical labor.

Real World Proof: Humans + Machines

This isn’t some far sci-fi fantasy, it’s the reality playing out in warehouses around the globe. Big players are already demonstrating the power of human-machine collaboration: Amazon, the e-commerce giant has deployed over 1 million robots in its operations and is using a new generative AI foundation model called DeepFleet to improve robot efficiency by 10%. This massive investment in automation has been accompanied by a commitment to its human workforce, with Amazon upskilling over 700,000 employees through various training initiatives, many focused on working with advanced technologies. In fact, at some of their next-generation fulfillment centers, advanced robotics require 30% more employees in reliability, maintenance, and engineering roles.

This isn’t just a trend it’s warehouse’s next phase of evolution.

Final Thought: Automation Is a Job Transformer

After more than eleven years in the field and over thirty automation projects, one truth has become undeniable to me: automation doesn’t erase human value but redefines it.

Through countless projects and collaborations, ISD has given me the platform to explore how people and technology can truly complement each other and it helped me reach this understanding firsthand.

I’ve seen robots lift, sort, and shuttle materials faster than any human could. I’ve also seen those same machines come to a standstill until a skilled person stepped in to adapt, optimize, and guide them. Every project reinforced the same lesson: technology may carry the load, but humans still drive the purpose.

The warehouses I’ve helped transform are no longer places of repetitive motion, they’re becoming ecosystems of collaboration where humans and machines work in sync. The roles have evolved, the skills have elevated, and the expectations have grown, but so have the opportunities.

Automation isn’t the end of work, it’s the evolution of it. It challenges us to think smarter, to learn continuously, and to design systems where people and machines amplify each other’s strengths. That’s not a story of replacement, it’s a story of transformation.

The post Automation in Warehousing: Job Slayer or Workplace Savior? (The Real Story) appeared first on ISD | Software Development.

Unlike most programming domains, this one requires us to occasionally leave our desks and go onsite, right where the system is used, to make sure that what we’ve built works in real life. These onsite visits are more than just part of the job. They’re opportunities to see the impact of software on people and operations.

In this article, I want to share some of my first onsite experiences, moments that shaped not just my technical skills, but my understanding of teamwork, responsibility, and how complex systems come alive when software meets the physical world.

The first leap in The Netherlands, January 2018

Before my first onsite experience, I had already visited warehouses operated by our long-term partner and customer, INTHER Group. Those earlier visits were purely observational, like walking through the aisles, watching the conveyors move, seeing the shuttle carts glide with precision. It was fascinating to see our systems in action.

This time, things were different. I wasn’t just a visitor anymore. I was part of the team responsible for delivering the new part of the system. It was my first ever onsite project, a warehouse in the Netherlands, where we had to deliver new inbound goods sorting functionality within an existing warehouse management system.

Standing there, I finally saw how a single line of code could influence something so complex. With just a small logic adjustment or configuration tweak, the flow of an entire operation could change. Seeing that immediate connection between digital and physical was a defining moment. It made the work tangible, almost alive.

Everything felt new: the customer, the pace, the direct responsibility. Suddenly, every line of code mattered in a visible way. When the system worked, boxes moved. When it didn’t, operations paused. That’s when I learned what “go-live” truly means, not just deploying, but standing beside people whose daily work depends on what you’ve built.

The experience was intense: long days, unexpected challenges, and plenty of moments that tested our resilience. But we learned to stay composed, to listen, and to act fast. One key lesson I’ll never forget came during a testing session when an unexpected incident occurred. My first instinct was to say, “I don’t know what’s happening.” That’s when a senior colleague calmly advised me: “Never tell the customer you don’t know. Tell them: We’re on it. We’ll investigate and come back with an answer shortly.’”

It’s a small shift in words, but it changes everything; it builds trust, confidence, and a sense of calm in moments that could easily turn stressful.

The go-live itself didn’t happen while we were there. Instead, it was scheduled a few weeks later, during the night, when warehouse operations paused. I still remember waiting for updates that night, knowing that everything we’d prepared was being put to the ultimate test. It went smoothly, with only minor adjustments needed afterward. For a first onsite experience, it couldn’t have ended better.

That trip taught me more than any documentation or sprint ever could. I left the Netherlands not just with new technical experience, but with a deeper sense of responsibility and a feeling of belonging to something much bigger than a single project.

Into the cold of Finland, May 2018

A few months later, I got the chance to join another onsite project, this time in Finland, near the small town of Kokkola. The customer’s business was food production and distribution for supermarkets across Finland and Sweden. The warehouse was connected to a meat processing facility, which meant that every product stored there had to stay within strict temperature limits.

As a result, the entire logistics process operates in a refrigerated environment. We were literally working in a giant fridge. It was a unique and challenging experience. Every hour, we had to step out and take short breaks to warm up in the main office. The temperature difference between the warehouse and the office felt like stepping between two worlds, the frozen and the normal one.

This project was different from the first one. The system was already live, and operations were continuous, running in three shifts over 24 hours without a real pause. Our work had to happen in parallel with what the operators were doing. Testing, troubleshooting, and deploying fixes had to be done on the fly. Every incident had to be analyzed and resolved quickly, often while standing on the warehouse floor, surrounded by moving boxes and forklifts.

Some nights, we stayed late to monitor the system between shifts, making sure that even the smallest change wouldn’t disrupt the workflow. There was no room for delays. If a problem appeared, the team needed to react immediately, find the root cause, and restore normal operation before the next wave of orders started.

That constant rhythm of quick thinking, testing under pressure, and balancing between development and live operations was both exhausting and energizing. It taught me the value of staying pragmatic, focused, and communicative, especially when multiple teams, ours and the customer’s, depended on each other minute by minute.

Despite the tough conditions, there was warmth in another sense – the people. It was my first real experience of Finnish hospitality. The customer representatives were kind, patient, and truly collaborative. Even in the coldest working environment, there was a sense of shared purpose and respect that made everything easier.

Returning to familiar faces, Finland, September 2019

About a year later, I returned to the same customer site for a planned OS server upgrade. This time, I felt much more confident. The environment, the people, even the rhythm, all felt familiar. The goal was to make sure the upgrade would go smoothly without disrupting warehouse operations.

There was still tension, of course, as with any major infrastructure change, but it was also a moment of reflection. Standing there again, surrounded by the same friendly faces and humming conveyors, I realized how much had changed since my previous two onsite visits. I wasn’t just reacting to issues anymore; I was anticipating them, communicating more clearly, and understanding the bigger picture.

That trip felt less like an assignment and more like a reunion, with both the people and the experience itself. It was proof that onsite work isn’t just about systems; it’s about relationships, trust, and growth.

The Human Side of Engineering

Looking back at these early onsite experiences, I see them as milestones, not only in my technical journey, but in my understanding of what real collaboration means. Working onsite removes the distance that screens and emails create. You see how your code affects real processes, real people, and real products.

You also learn that success isn’t just about deploying something that works; it’s about how you work with others when it doesn’t.

Those lessons have stayed with me and continue to shape how I approach every project. Each onsite visit, from my first nervous steps in the Netherlands to the freezing shifts in Finland, helped me connect code to reality and teamwork to purpose.

Onsite experience is an example of stepping out of your comfort zone and facing the other side of the code you’ve written. In the end, engineering is as much about people as it is about systems, and the onsite work is where that becomes truly clear.

The post From Code to Conveyor Belts: What My First Onsite Taught Me About Real Engineering appeared first on ISD | Software Development.

“Meetings are long. Memory is short.”

We have all been there. You wrap up a 90‑minute meeting, after a long day of context‑switching, and someone suddenly asks: “So, who’s taking care of the meeting notes?”

Like many of us, juggling technical tasks and team check-ins, I often found myself in meetings trying to stay present, while quietly worrying about who’d remember all the important points. And when the meeting was in Romanian, but the notes had to be shared in English later… well, let’s just say my notes didn’t always survive the translation.

That recurring frustration sparked an internal research project at ISD: Can AI‑powered meeting assistants make this easier?

Why meeting minutes matter

Meeting minutes aren’t just paperwork; they’re an anchor for decision‑making and accountability. They help:

• Team members who were present confirmed what they agreed to.
• Colleagues who missed the meeting, maybe they had a conflicting call or a personal emergency, to catch up quickly without scheduling another recap.
• Project managers track progress and follow up on owners and deadlines.

When meeting minutes are delayed or unclear, important tasks often get overlooked, duplicated work creeps in, or deadlines slip. Multiply that by several meetings a week and you’ll have serious inefficiency.

Our experiment

I volunteered to lead a hands‑on test of three AI meeting assistants that explicitly claim Romanian speech recognition:

1. MeetGeek.ai
2. Fellow.app
3. Fireflies.ai

Meeting type: Up to 1h meeting held every 2 weeks (intensively using technical subjects and vocabulary).
Number of speakers: The group ranged from 4 to 6 people.
Scoring grid: After every meeting, every colleague had to come up with feedback on generated meeting minutes text. A score from 1 to 5 was used to appreciate the results obtained.
Time budget. The whole test series took around 2.5 months.

We ran all three in Microsoft Teams on their free plans, inviting each bot to:

1. Round 1: A typical stand‑up conducted mainly in Romanian.
2. Round 2: An equivalent meeting in English.
3. Round 3: Like Round 2, except that the meeting is entirely held online

Participants evaluated how accurately the generated summaries reflected the discussion.

1. Language understanding & summary accuracy

2. Helping the bots help us

Once we realized the bots could listen for cues, we began interacting with them directly inside the meeting:

• We would specifically say “AND NOW, THE ACTION POINTS” and mention the person’s name responsible for this item.
• Before moving on, someone would say: “NEXT ITEM ON AGENDA.” to help improving the summary structure.

Once we started speaking more clearly to the bots, things like, “OK, action items now” or “next agenda point”, something interesting happened. The notes got sharper. Less fluff, more structure. Turns out, these tools are like quiet teammates: they do their best work when we give them just a little help.

3. Speaker tracking

• In hybrid meetings (room mics + remote attendees), none of the tools hit 100 % accuracy.
• In a fully online format, MeetGeek nailed speaker attribution more accurately, compared to other Fireflies apps, for example.

4. User experience (UX) & UI

Fireflies felt “feature‑rich but menu‑heavy” while the others guided us straight to the recap.

5. What do you get for free, and how much does an upgrade cost?

One of the first questions we asked ourselves was simple: How far can we get without paying? Since most teams aren’t ready to commit budget until they’ve seen clear value, we decided to run all tests using only the free plans.

Here’s what each app offered out of the box:

We were impressed that all three tools offered essential functionality, like speech-to-text, summarization, and basic exports, even at the free tier. But there were subtle trade-offs.

• MeetGeek offers structured, well-organized summaries and integrations, but capped transcription at 3 hours limit.
• Fellow provided a clean interface that’s easy to onboard with, but had storage limited to five meetings on the free plan.
• Fireflies stood out for unlimited transcriptions but felt less intuitive and sometimes struggled with accuracy, especially in Romanian.

Now, when we looked beyond the free tiers, here’s how the pricing stacked up (per user/month):

From this, it’s clear:

• Fellow offers the lowest entry point, making it appealing for teams with tight budgets.
• MeetGeek, while pricier, appeared to give the best value for multilingual support and meeting structure.
• Fireflies sat in the middle but had the most generous transcription limits for those doing a lot of recordings.

In our case, we found the free plans sufficient for running a thorough pilot test, but we also saw where upgrading could add value, especially when dealing with a higher number of meetings or if storage and integrations become essential.

6. Best‑fit recommendations

My subjective pick: If you have a multilingual team and you want a more reliable tool between the 3 of them, MeetGeek would be your choice. In case you want a more structured agenda with smaller available budgets, you should probably consider using the Fellow.app.

MeetGeek.ai earned the highest marks across language accuracy, speaker tracking, and ease of use. In an all‑online meeting, each participant on their own mic and speaking English, its summary reflected the main topics of the discussion. Fellow app was almost close to the 1^st place as well. If I was to choose on upgrading the plan for one of these 3 apps, I would probably choose Fellow app, to check on further, due to its prices.

General remark: Romanian performance still needs polish for both applications, and I expect that to improve. Speech‑to‑text models keep evolving. English still wins today, but regional‑language accuracy improves with every model update. We fully expect Romanian transcription parity within the next product cycles.

What’s next at ISD

1. Paid‑tier trials. To see if premium models improve Romanian recognition.
2. Microsoft Teams built-in AI agent tool (only available via Premium subscription). Compare achieved results.
3. Larger sample. Promote the usage of AI meeting note taker apps and have a common template of meeting minutes generated at company level.

Stay tuned, more follow-ups will come over, and if you haven’t tried an AI meeting agent, this article will help you pick the tool that suits you best!

Dumitru Dirul

Senior Software Developer

in

The post The Meeting Ended. But Who’s Writing the Minutes? appeared first on ISD | Software Development.

Your most experienced maintenance engineer hurries to the location, but even for them, the immediate task is a difficult search. Is it a sensor problem? A motor fault? A PLC issue? It’s a high-pressure scenario that many of us who have worked in these environments can recognize.

I’ve certainly been there myself and have seen colleagues face these exact challenges, often during critical working hours, or even outside of them when keeping operations running is vital.

When Every Second Counts, Chaos Costs Money

In today’s fast-paced, high-volume warehouse operations, WMS/WCS hardware failures are not small inconveniences; they are serious operational and financial problems. The traditional troubleshooting process, unfortunately, often includes:

• The Manual Maze: Engineers searching through thick paper binders or complex network folders, trying to find the correct service manual or electrical diagram. I recall many instances where just locating the right document under pressure took up precious minutes.
• Deciphering Complex Codes: Engineers try to understand unclear error codes from the WMS (Warehouse Management System)/WCS (Warehouse Control System), often without immediate information about what those codes mean for that specific machine in its current operating state. We’ve all seen those cryptic messages that offer few clues.
• Relying on Memory: Depending on individual experience – “Did we have a similar issue on Line B last quarter? How did we fix it then?” – this system can have knowledge gaps, especially with new staff or less experienced team members. While experience is invaluable, it’s not always scalable or consistently available.
• Disconnected Data: Important information is often stored in different places (siloed). Real-time alerts from the WMS, past maintenance logs, OEM documents, and internal repair notes are in separate systems. This makes it very time-consuming to connect all the information.

This reactive, often disconnected way of handling critical hardware failures means valuable time is lost. In a modern warehouse, lost time directly means lost revenue, missed delivery targets, and unhappy customers. We understand the great pressure this puts on your maintenance teams and your whole operation. You need a faster, more intelligent method to get your systems working again.

An Expert Assistant, Always Available, Understanding Your Needs

Now, imagine the same critical failure happens, but this time, your engineers are not on their own. They have a new kind of support, one that many of us are already using in our daily lives. We already use AI chat applications for everyday tasks – perhaps to quickly explain a new concept, draft an email, or even suggest a vacation plan for a weekend city break. (I definitely do!)

Given this growing familiarity with AI in common scenarios, applying its power in a professional environment, especially when equipped with the correct, specialized knowledge, is a logical next step. So, imagine your engineer having an AI-Powered Intelligent Troubleshooting Assistant – a digital ‘co-pilot’, ready 24/7, accessible through a simple chat interface on a tablet or laptop.

This is not just another search tool or a generic chatbot. This AI assistant is specifically built to understand the details of your warehouse automation, your specific equipment, and your operational history. But how can an AI get such a deep, contextual understanding and interact effectively with complex machinery?

A Smart Protocol for AI and Live System Interaction

The core of this intelligent help lies in a key technology known as a Model Context Protocol (MCP). Think of this not just to feed data to an AI, but as a standardized protocol that enables the AI to intelligently interact with your live WMS and WCS systems. It defines how the AI can actively query these systems for the specific, real-time information it needs to understand the current operational state, diagnose issues, and access relevant historical context.

A significant advantage of such a protocol is its ability to bridge the gap between established operational technology and emerging AI capabilities. It allows your existing, proven WMS/WCS software to integrate with modern AI tools and agents, often through existing APIs, without necessarily requiring a complete and costly rewrite of systems that already work well. As an engineer, I find this iterative approach to modernization is far more practical and less disruptive.

Essentially, this type of protocol provides the “rules of engagement” and the “common language” for the AI to communicate effectively with your operational technology, ensuring it can query on demand, understand real-time status, and integrate diverse data sources.

To form a comprehensive understanding of WMS/WCS troubleshooting, an AI assistant leveraging MCP draws insights from a wide range of interconnected information. This begins with direct interaction with your live systems, allowing it to actively query the WMS/WCS for live error codes, sensor data, and the current operational status – seeking what it needs to understand what’s happening right now.

This live data is then intelligently cross-referenced with comprehensive historical maintenance data, including detailed records of past breakdowns, repairs, and parts replaced, allowing the AI to identify patterns and precedents. Furthermore, the assistant leverages digitized technical documentation – where techniques like Retrieval Augmented Generation (RAG) are powerful for efficiently searching OEM service manuals, operator guides, and schematics. The contextual protocol ensures this RAG-retrieved information is understood within the broader, dynamic context of the live issue. Finally, this is all synthesized with knowledge of your unique system specifications and configurations for your AGVs, conveyors, and other equipment, as well as your facility’s internal knowledge base and best practices, including SOPs and safety rules.

By using a MCP for interaction with live systems, and integrating RAG for document-based knowledge retrieval, the AI isn’t just matching keywords. It actively builds a rich, dynamic understanding of the situation, much like an experienced human engineer, but with the ability to process and recall huge amounts of data in milliseconds.

To better visualize how these components work together, here is a high-level conceptual architecture of the solution:

Figure 1: A conceptual view of the AI Co-pilot architecture. The ChatApp serves as the user interface, while the LLM/MCP Host orchestrates interactions. RAG techniques (Data Ingestor, Semantic Search, Vector DB) process static knowledge from wikis and manuals. The MCP Servers provide a standardized way for the AI to interact with live systems like WCS, ERP, and PLCs.

Troubleshooting Through Natural Conversation

This powerful contextual understanding is then made easy to use through a Natural Language Processing (NLP) chat interface. Your maintenance engineer can talk with the AI assistant like they would talk to a very knowledgeable colleague.

Instead of just typing “Error E-404,” they can ask:

• “The main sorter on Line C shows error E-404 after a reported chute jam. What are the top three most likely causes, considering current sensor readings and the maintenance history of this unit from the last six months?”
• “Okay, for the first likely cause, can you show me the correct section in the service manual for checking sensor alignment?” (Here, the AI might use RAG to find the exact page, and the system context helps it understand why that page is relevant to the live issue).
• “What was the exact solution when AGV #12 had a similar ‘drive motor overcurrent’ fault last Tuesday, and what were its telemetry readings just before that fault?”
• “Display the electrical diagram for the main power input to the broken conveyor section.”

The AI assistant, with its context-guided understanding and ability to interact with live data, can then give direct, practical answers, point to specific document pages, show relevant past examples, and even suggest diagnostic steps in a logical order. These changes troubleshoot from a hurried search to a guided, intelligent process.

From Hours of Downtime to Minutes of Guided Resolution – The Real Benefits

So, what is the practical impact of this AI-assisted approach on your warehouse operations and business results? We are looking at real improvements, not just theoretical ones. Let’s examine the key advantages:

• Dramatically Reduced Mean Time To Repair: Engineers pinpoint root causes faster with instant access to relevant information and intelligent diagnostic suggestions. This significantly cuts down resolution time, getting vital systems back online sooner, and minimizing operational impact.
• Improved First-Time Fix Rate: The AI’s comprehensive knowledge guides engineers to effective solutions, increasing the likelihood of a correct fix on the first attempt and reducing costly repeat failures or misdiagnoses.
• Empowered and Less Stressed Engineers: The AI assistant acts as a powerful support tool, providing clear guidance that reduces guesswork and stress during critical failures It also helps less experienced team members by making expert advice easier to access. From my experience with the pressure maintenance teams face, this kind of support is extremely valuable.
• Valuable Knowledge Capture and Consistency: Crucial troubleshooting knowledge, often “tribal knowledge” that can be lost when experienced staff move on, is centralized and scaled by the AI. This ensures consistent application of solutions and best practices, even with team changes.
• Better Resource Allocation: Faster problem resolution frees skilled technicians from lengthy troubleshooting, allowing them to focus on higher-value preventative maintenance and proactive tasks.
• Enhanced Safety in Maintenance Operations: Clearer, AI-guided diagnostic paths help engineers better understand issues before intervention. This reduces speculative work on potentially dangerous machinery, contributing to safer repair procedures.
• Increased Operational Resilience & Data-Driven Insights: Faster, higher-quality fixes make your warehouse operation more resilient to unexpected issues. Furthermore, data from AI-assisted interactions can reveal failure patterns, paving the way for more proactive maintenance strategies.

Collectively, these benefits contribute to a significantly more efficient, informed, and resilient maintenance operation. This isn’t about replacing your skilled engineers; it’s about augmenting their abilities, making their expertise more scalable, and providing them with a powerful AI tool. It’s about transforming a stressful, reactive troubleshooting process into a more controlled, efficient, safe, and intelligent operation. The aim is simple: keep your warehouse running smoothly and minimize the costly impact of hardware failures.

What Does the Future of WMS/WCS Troubleshooting Look Like for You?

The ideas we’ve discussed – leveraging smart protocols and AI to assist engineers – represent a significant step forward. Bringing such an advanced solution to life is an exciting journey, one that thrives on collaboration and continuous learning.

At Inther Software Development (ISD), our strength lies in building robust software solutions for warehouse automation and control systems. We are passionate about combining this deep domain knowledge with the exploration and application of the latest technologies, including AI.

We see these technologies not just as tools, but as opportunities to co-create significant improvements in operational efficiency and resilience alongside our clients. We are committed to learning and adapting in this rapidly evolving field, always focused on delivering real-world value.

How do these concepts resonate with your current WMS/WCS maintenance challenges?

• Do you see specific scenarios in your warehouse where an AI troubleshooting assistant could provide the most immediate impact?
• What are your thoughts on integrating real-time system data with historical knowledge and technical documentation in this way?
• Have you already explored similar AI-driven solutions or concepts for your maintenance operations, and what were your findings or challenges?
• What questions does this raise for you about practical implementation or the potential benefits?

We believe the best solutions emerge from open dialogue and a shared understanding of both the challenges and the possibilities. If you’re curious about how these emerging technologies could be applied to your specific environment, or if you have insights from your own experiences with advanced troubleshooting, we’d genuinely appreciate the opportunity to connect.

Let’s explore together. We are keen to learn about your unique operational needs and discuss how a partnership focused on innovation could help shape the future of maintenance in your facility.

You can reach out to us to share your thoughts or schedule an informal discussion at https://calendly.com/inther-software/30min.  We look forward to hearing your perspective.

The post AI in the Warehouse: Rethinking WMS/WCS Troubleshooting  appeared first on ISD | Software Development.

PLCs are designed to withstand harsh industrial environments and operate for long periods without interruption. However, even the most reliable PLCs become outdated over time, requiring upgrades to ensure efficiency, security, and integration with modern technology.

According to Advisory Group many industrial facilities still rely on aging PLC systems, with over 50% of them operating controllers that are more than a decade old. While these systems were once cutting-edge, the risks of running outdated automation technology are growing. Unplanned downtime alone costs industrial manufacturers a staggering $50 billion each year based on Deloitte, often stemming from failing components, obsolete software, and a lack of modern predictive maintenance strategies. Moreover, for manufacturers, the impact of downtime is relentless—on average, equipment failures result in 800 hours of lost productivity annually, or more than 15 hours every single week.

Beyond financial losses, outdated PLCs pose a serious security threat. Cyber-attacks on industrial organizations remained prime targets, with 70% of ransomware attacks affecting manufacturing entities across 33 unique manufacturing subsectors, leaving vulnerable systems exposed to operational disruptions, data breaches, and costly shutdowns (Source: Dragos Security Report). “Industrial and critical infrastructure has been moving away from highly customized facilities to ones that—for good economic and productivity reasons—share the same industrial devices, technologies, and facility designs across sites and sectors.” – said Robert M. Lee, Co-founder and CEO of Dragos.

These numbers highlight a growing reality: upgrading to modern PLC systems isn’t just about improving efficiency—it’s about safeguarding operations.  If your PLC system in the industrial automation industry has been in place for years without a significant upgrade, it may be limiting your operational potential. Below, we explore the top five signs that indicate your PLC system needs modernization and how upgrading can enhance performance, reduce downtime, and ensure future scalability.

1. Obsolete Hardware or Software

One of the biggest warning signs that your PLC system needs an upgrade is hardware and software obsolescence. As technology advances, older PLC models lose manufacturer support, making maintenance, troubleshooting, and integration increasingly difficult.

Many businesses face the frustration of limited spare parts availability, where sourcing replacement components becomes both time-consuming and costly. Compatibility issues further complicate operations, as newer industrial devices and software struggle to integrate with outdated PLCs. Without firmware updates, security patches, or technical support, manufacturers are left with systems that lack reliability and resilience.

As Industry 4.0 continues to evolve, a significant portion of industrial automation systems will require upgrades to remain compatible with modern technologies. Companies that fail to modernize risk falling behind digital transformation (Source: McKinsey & Company).

Yet, many facilities still run on legacy S7-400 and S7-300 PLC’s systems, long discontinued by Siemens. Holding onto outdated technology may seem like a cost-saving measure, but in reality, it increases long-term risks and inefficiencies. Migrating to a modern PLC platform is no longer just an option—it’s a necessity for ensuring long-term support, seamless integration, and future-proof automation.

2. Frequent System Failures and Downtime

As PLC systems age, they become increasingly vulnerable to unplanned breakdowns, causing disruptions in production, costly downtime, and operational inefficiencies. An outdated PLC often exhibits warning signs—unexpected shutdowns halt operations, error messages become more frequent, and maintenance costs steadily rise due to failing components and limited spare parts availability.

These challenges are not just operational headaches—they are a clear sign that your PLC system needs an upgrade. According to Forbes, the financial impact of downtime is staggering. Industrial downtime costs industrial manufacturers up to $50 billion annually, leading to significant productivity losses, operational inefficiencies, and increased maintenance expenses with aging PLC systems being a major culprit.

In industries like automotive manufacturing, every minute of halted production can lead to losses of up to $22,000, claimed Deloitte. Even planned shutdowns come at a price, consuming 1%–10% of total available production time, time that cannot be recovered.

3. Inability to Integrate New Technology

As industrial automation evolves, technologies like IoT, AI, and cloud computing are reshaping the market. However, legacy PLC systems struggle to keep up, often lacking the necessary compatibility to integrate with modern industrial ecosystems. Without support for modern communication protocols such as Ethernet/IP, MQTT, or OPC UA, older PLCs become isolated, unable to connect with IoT sensors, analytics platforms, or cloud-based control systems.

This limitation extends beyond simple connectivity—remote monitoring and advanced diagnostics become increasingly difficult, forcing manufacturers to rely on manual interventions and outdated maintenance strategies. As industries push toward smart manufacturing and predictive maintenance, real-time data analysis is essential—yet many legacy PLCs simply weren’t designed to handle this level of integration.

The integration of PLCs with IoT is no longer a futuristic concept—it’s a critical step for manufacturers striving to remain competitive. Industrial automation investment is increasing, with 92% of businesses planning to maintain or increase their spending on automation in the next year, according to a survey by SMA Technologies. However, a significant portion of these organizations may still be relying on outdated PLCs, which could lack the necessary capabilities to fully support modern IoT-driven advancements. Without upgrades, these legacy systems create bottlenecks, limiting scalability, flexibility, and overall operational efficiency.

Failing to modernize PLC infrastructure means missing out on predictive analytics, real-time monitoring, and cloud-based automation, which are crucial for minimizing downtime, optimizing production, and driving profitability. The shift to smart manufacturing requires connected, data-driven automation, making IoT-integrated PLCs the foundation of next-generation industrial operations.

4. Decreased Performance and Efficiency

One of the clearest signs that your PLC needs an upgrade is sluggish processing times, which can lead to inefficiencies across your operations. When a PLC struggles to process commands quickly, it delays critical actions, causing bottlenecks in production and reducing overall system performance.

Imagine a high-speed packaging line where thousands of products move along the conveyor every hour, each relying on real-time sensor data to be sorted and labeled with precision. Everything runs smoothly—until an aging PLC begins to lag. Suddenly, labels are misapplied, barcodes don’t scan correctly, and sorting errors pile up. Workers scramble to fix mistakes, but the delays ripple through the entire operation. The once-efficient line slows to a crawl, waste bins fill with discarded packages, and production targets slip further out of reach. What was once a seamless process has now become a costly bottleneck—all because of an outdated PLC struggling to keep up with modern demands.

Modern automation upgrades have consistently demonstrated significant benefits. For example, Pfizer’s new high-containment manufacturing facility in Freiburg, Germany, implemented Siemens technology and services, resulting in a 40% reduction in energy use in its environmental control system compared to traditional facilities. This demonstrates how upgrading to more advanced systems can significantly improve efficiency, reduce operational waste, and lower energy consumption.

5. Limited Data Processing and Storage Capabilities

Real-time data collection, analytics, and predictive maintenance have become essential for optimizing efficiency. However, many older PLCs struggle to keep up with these demands due to their limited processing power, memory capacity, and storage capabilities. As industrial operations generate vast amounts of data, legacy PLCs often run out of memory, causing slowdowns, system crashes, and incomplete data logs. This makes troubleshooting difficult and prevents manufacturers from leveraging valuable insights to improve efficiency.

Beyond performance issues, outdated PLCs also limit automation scalability, as they lack the ability to handle large-scale sensor inputs or integrate with AI-driven automation. Without edge computing and cloud integration, industrial systems relying on legacy PLCs remain disconnected from advanced data analytics and real-time monitoring, significantly impacting productivity. According to the Manufacturing Institute, real-time data access can boost production efficiency by up to 20%, yet many struggle to achieve these results due to outdated automation infrastructure.

To stay competitive, businesses must upgrade to modern PLCs equipped with enhanced data processing, cloud connectivity, and AI-driven automation capabilities. These upgrades eliminate bottlenecks, improve system reliability, and unlock the full potential of data-driven industrial operations. Holding onto legacy systems may seem cost-effective in the short term, but in reality, it leads to missed opportunities, operational inefficiencies, and reduced competitiveness in an increasingly digital industrial world.

Is It Time to Upgrade?

If your PLC system shows any of these warning signs, delaying an upgrade could cost you more in downtime, maintenance, and lost efficiency. Investing in modernization ensures your industrial processes remain efficient, secure, and competitive in the digital era.

Need Expert Assistance?

Not sure if your system needs an upgrade? Our PLC specialists can conduct a comprehensive assessment of your current setup, identifying weak points, inefficiencies, and security vulnerabilities. We’ll provide a detailed upgrade strategy tailored to your industry, ensuring seamless integration with modern automation technologies. Schedule your Industrial PLC Assessment today.

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DevSecOps improves culture and collaboration

A part of applying DevSecOps involves changing the culture of security in your organisation, meaning that ‘Security is now everyone’s responsibility’, as we hear more and more in DevSecOps-related discussions. The process is not an easy one and getting people to change their behaviour might be quite challenging. But let’s take a look into it.

Thinking about security as a continuously evolving product is a major shift when talking about a culture mindset. DevSecOps team players usually approach it from a product management perspective. They don’t look at security as project-driven audits and reactive incident responses, but mostly see the developers as their customers and the security process as a product they are creating and delivering for the developer’s use.

Fir starters, what does “culture” mean? The school of DevOps has gradually reduced the importance of clearly defining ‘culture’ in an application-delivery context. I won’t list the attributes here, but I would like instead to point out what I see as a major mindset shift: thinking about security as a continuously evolving product. DevSecOps team players usually have a product management approach to security. They don’t look at security as project-driven audits and reactive incident responses, but mostly see the developers as their customers and the security process as a product they are creating and delivering for the developer’s use.

Applying a product management approach to security shifts the focus from enforcing compliance to focusing the workflow on faster and more accurate actions. This is the reason the tools and automation components of DevSecOps are so important, as they play the role of products. Moreover, the practices of product management are so widely understood and proven over decades, that you don’t need to reinvent the wheel when it comes to applying them in DevSecOps.

Once you take a product management perspective in security, you understand better the reasons why culture tends to focus on empathy, kindness, and more communication with people, when it comes to DevSecOps. These three elements also happen to be key tools in product management. A good product manager has a clear idea about the needs people using their products have, where they are using them, and how all that links to the organisations’ goals those people are working in. They can “get into the mind” of their customers. In this context, if we think that a DevSecOps has a similar role with the one of a product manager, its focus should be oriented towards creating and delivering secure applications. So, instead of rolling your eyes at “those developers” who “don’t know anything about security,” you should put more efforts into creating products that make developers awesome at security.

The product-oriented mindset regarding security is a helpful way to think about one of the most popular phrases in DevSecOps, that says ‘shift left’. At first glance, ‘shifting left’ suggests giving developers more responsibility over writing secure code, ensuring compliance and controls. I think that’s sort of true. Part of DevSecOps involves getting developers to write more secure code, indeed. Though, expecting developers to handle most of the security tasks is too much to put on their shoulders. To be more precise, ‘shifting left’ means moving security activities and policy enforcement closer to developers, treating them as ‘customers’, and building out the guardrails, platforms, and tools they need to develop secure applications. Let’s go over some of these tools and platforms.

DevSecOps enables automated verification

With all the tracking that goes on in a secure software supply chain, you can automate much of the verification and governance that security teams require to check and release software. This verification has been done manually for years. Often, literally, with email and spreadsheets, that is time consuming, error prone, and generally unpleasant. For organisations that want to start deploying their software weekly, if not daily, manual security checks are impossible to work with.

Thankfully, the automation that comes with DevSecOps build pipelines helps reduce the toil of governance. It makes it easy, for example, to create a bill of materials (BoM) and sign container images. You can store all of that in a repository, even add it to version control, and security staff can create starter application designs and configurations that template out security best practices.

Automating these activities got easier because of the infrastructure standardisation that stays at the heart of Kubernetes. The configuration enforcement that Kubernetes performs improves your security capabilities. and in case of any configuration drift, it can usually kill and then redeploy applications into their secure, trusted state. This doesn’t solve all of your problems, of course, but it does make cleaning up production easier and deploying patches much faster. And if you regularly redeploy, or “repave,” all of production from scratch, you reduce the window of time people have to mess around.
In the third part of this article, I am going to talk about how DevSecOps can empower security through guardrails, and about the transition from DevOps to DevSecOps. Stay tuned!

The post DevOps vs. DevSecOps: A New Security Concept (Part II) appeared first on ISD | Software Development.

I’ve never really been sure how DevSecOps differs from plain-old DevOps, but over the past year I think I finally studied the topic enough to have a definition.

DevOps is the combination of cultural philosophies, practices, and tools that increase an organization’s ability to deliver applications and services at a high velocity. It allows to evolve and improve products at a faster pace than the use of traditional software development and infrastructure management processes. This is exactly the speed that enables organizations to better serve their customers and compete more effectively on the market.

DevSecOps stands for development, security, and operations. It’s an approach to culture, automation, and platform design that integrates security as a shared responsibility throughout the entire IT lifecycle.

The main difference between DevOps and DevSecOps is security automation, but the nuances and benefits are just as important. To be concise, the DevOps mindset improves software delivery by moving operations concerns closer to development with the help of a lot of automation and process change. What I think makes DevSecOps different, and at the same time, additive to DevOps are the three reasons below:

1. A secure software supply chain

This is a fancy way of saying “we know all the components that went into building and deploying this software and we rely on those components.” It also includes the actual trusted CI/CD pipeline, that is resistant to third parties, including malicious code, as we have seen happening during the recent years.

2. Improved culture and collaboration

DevSecOps increases the collaboration and understanding between developers and security staff. As with many governance practices, because of security, the developers and the security staff usually have an antagonistic relationship. Developers see the security staff as unstoppable masters of “no”, while security people see developers as mindless coders. Well, this relationship doesn’t help, but the good news is that DevSecOps assists in transforming this culture, as DevOps does.

3. Automation and guardrails

Automation of the security policy enforcement, and provision of defaults and templates are also important DevSecOps tasks. They aim to make the writing of secure code and applications’ configuration as easy as possible for developers, from the start. Historically, verifying that developers are writing secure code has been a manual, error-prone process, but much of this can be now automated with the use of good platforms.

DevSecOps integrates a secure software supply chain into DevOps

During the recent years, the idea of a “secure software supply chain” became a fundamental part of DevSecOps. A secure software supply chain starts with a “supply chain,” which is, mostly, just another name for a “build pipeline.” A pipeline is filled with the activities that go into compiling, integrating, testing, and eventually releasing software. Let’s look at the three parts a secure software supply chain includes.

1. Governing inputs and dependencies

First, you should think of a “software supply chain” as all the inputs that go into building and deploying an application. These inputs start with the code your developers write, the configuration used throughout the application lifecycle, third-party frameworks, libraries, and other services your application relies on (e.g., to send text messages), as well as any other ingredients that go into making that application. Developers depend on open source and third-party services more than ever, meaning that your supply chain also needs to verify and trust that third-party code.

Dependencies on third-party code bring in quickly the transitive dependency problem. For example, let’s say you’re using a PDF-generation library that needs a font-rendering library depending on a logging framework. If that logging framework has a security problem, you’re also having that security problem regardless of how secure, verified, and trusted the PDF-generation and font-rendering libraries are. This is exactly what happened recently with the Log4j security problem.

One of the major innovations in the DevOps-mindset is treating the configuration needed to deploy and run the application’s code as well. Since there are different groups involved in developing, testing, deploying, and even managing applications in production, it is easy to lose track of this configuration throughout the application lifecycle. This is the less cool part in the DevSecOps mindset: that configuration is a major input to be tracked and secured.

1. Building

The second part of a software supply chain is the build process used to compile and verify your applications, known as continuous integration. This is a decades-old, well-established practice and set of tools. In the DevSecOps mindset, this build phase might enforce policies and swap out different components for the software. For example, when a security issue comes out, an advanced secure software supply chain can rebuild your applications with patches for operating systems and frameworks, without the need to trouble developers. This is exactly what Netflix and others (Amazon, etc) have been doing, which enables them to not only patch production quickly, but to rebuild production entirely several times a week to blow out any malware.

• Secure delivery

Third, a software supply chain usually consists of another part: continuous delivery. This means automating the   releasing of the application builds to production.

The main part of a secure supply chain is ensuring that the inputs – code, configuration, and third-party frameworks and services – are protected and follow your guarded policy. This largely means tracking and verifying that those inputs are what you think they are, and that random people haven’t inserted malware into your applications.

Obviously, a secure software supply chain seeks to prevent these and other security problems.
Did you find this article useful? Stay tuned, because the other two reasons that state the differences between DevOps and DevSecOps are going to be developed in the next articles.

The post DevOps vs. DevSecOps: What Are the Differences? (Part I) appeared first on ISD | Software Development.