#devops software engineer

[heart-ghost-studyblr]

I found myself surrounded by companions daring to tackle a real software architecture challenge. We shared a good wine and cheese to conquer it together! (Unfortunately, there’s always something waiting to be dealt with on Monday.)

The glow of my Neovim terminal in Monokai theme reflects my rhythm — a guy who doesn’t stop on weekends but knows that balance isn’t about being all-in, all day.

The setup screams character: a seamless fusion of productivity and comfort. Lazygit commands at my fingertips, a Ghibli-esque avatar paired with Neofetch adding a touch of Tumblr aesthetic, and a playlist of Korean indie OSTs playing in the background to add depth to every keystroke.

This is how I drive — in code, creativity, and moments that are unapologetically mine.

[nixcraft]

The more coding and IT stuff you do it, the more you learn, the more you learn the more you realise how much you don’t know.

[antifataylorswift]

The developers i work with are asking chatgpt questions about my infrastructure that are in our docs. Unsurprisingly they are getting bad advice for our particular setup, and are bothering my team with a bunch of questions about if the advice is right and what would happen if they ran those commands.

[rajender123]

SPARK TECHNOLOGIES

We deliver value by identifying opportunities that align with business objectives and adopting an agile approach to implement them.

[upperthrust-technologies]

Leading the Way in IT- ChatGPT's Transformative Impact

In the dynamic world of Information Technology, a transformative force is reshaping the field: ChatGPT. This advanced AI, built on the sophisticated GPT-3.5 framework, is not just a revolutionary tool but a catalyst for unprecedented innovation, efficiency, and enhanced human-AI collaboration.

The ChatGPT Edge With its deep understanding of context, nuanced responses, and adaptive learning, ChatGPT stands as a groundbreaking advancement in natural language processing. It's a boon for IT professionals, enabling them to tackle complex problems, improve team communication, and offer solutions tailored to the unique challenges of the IT realm. Revolutionizing DevOps Communication   ChatGPT marks a significant leap in DevOps, facilitating smoother communication and collaboration. It excels in interpreting natural language, allowing real-time issue resolution, task automation, and fostering a culture of continuous improvement. DevOps teams can leverage ChatGPT for enhanced decision-making and adaptability in the ever-changing landscape of software development.  Enhancing Product Development Cycles   In product development, ChatGPT's contribution is invaluable. It streamlines the lifecycle by grasping complex requirements and generating structured specifications. Teams can use ChatGPT to refine ideas rapidly, leading to more effective development processes and innovative solutions that align with user expectations. Advancing Mobile and Web Application Development   For web and mobile app developers, ChatGPT accelerates the coding process. Its ability to understand context and generate code quickens development cycles. Integrating ChatGPT into workflows helps tackle coding challenges, troubleshoot, and enhance code quality, resulting in a more agile and responsive development process.  The Future of IT with ChatGPT Looking ahead, ChatGPT's role in IT is poised to expand significantly. This fusion of conversational AI and technical acumen will revolutionize collaboration and innovation across DevOps, product development, and app development. ChatGPT is set to be a key driver in creating an adaptable, efficient, and collaborative IT ecosystem.

ChatGPT is guiding the IT industry towards an era where efficiency and collaboration take center stage. As organizations adopt this transformative technology, the sectors of DevOps, product development, and app development are on the cusp of a major evolution. Embrace ChatGPT as it leads the charge in IT innovation, where efficiency meets creativity in the digital world.

[acquaintsofttech]

Trends to Follow for Staunch Scalability In Microservices Architecture

Scalability in microservices architecture isn’t just a trend—it’s a lifeline for modern software systems operating in unpredictable, high-demand environments. From streaming platforms handling millions of concurrent users to fintech apps responding to real-time transactions, scaling right means surviving and thriving.

As a software product engineering service provider, we’ve witnessed how startups and enterprises unlock growth with a scalable system architecture from day 1. It ensures performance under pressure, seamless deployment, and resilience against system-wide failures.

And as 2025 brings faster digital transformation, knowing how to scale smartly isn’t just beneficial—it’s vital.

At Acquaint Softtech, we don’t just write code—we craft scalable systems!

Our team of expert engineers, DevOps specialists, and architectural consultants work with you to build the kind of microservices infrastructure that adapts, survives, and accelerates growth.

Let Talk!

Why Scalability in Microservices Architecture Is a Game-Changer

Picture this: your product’s user base doubles overnight. Traffic spikes. Transactions shoot up. What happens?

If you're relying on a traditional monolithic architecture, the entire system is under stress. But with microservices, you’re only scaling what needs to be scaled! 

That’s the real power of understanding database scalability in microservices architecture. You’re not just improving technical performance, you’re gaining business agility!

Here’s what that looks like for you in practice:

Targeted Scaling: If your search service is flooded with requests, scale that single microservice without touching the rest!

Fail-Safe Systems: A failure in your payment gateway won’t crash the whole platform—it’s isolated.

Faster Deployments: Teams can work on individual services independently and release updates without bottlenecks.

📊 Statistics to Know:

According to a 2024 Statista report, 87% of companies embracing microservices list scalability as the #1 reason for adoption—even ahead of speed or modularity. Clearly, modern tech teams know that growth means being ready. 

Scalability in microservices architecture ensures you’re ready—not just for today’s demand but for tomorrow’s expansion. 

But here’s the catch: achieving that kind of flexibility doesn’t happen by chance! 

You need the right systems, tools, and practices in place to make scalability effortless. That’s where staying updated with current trends becomes your competitive edge!

Core Principles that Drive Scalability in Microservices Architecture

Understanding the core fundamentals helps in leveraging the best practices for scalable system architecture. So, before you jump into trends, it's essential to understand the principles that enable true scalability. 

Without these foundations, even the most hyped system scalability tools and patterns won’t get you far in digital business!

1. Service Independence

It's essential for each microservice to operate in isolation. Decoupling allows you to scale, deploy, and debug individual services without impacting the whole system.

2. Elastic Infrastructure

Your system must incorporate efficient flexibility with demand. Auto-scaling and container orchestration (like Kubernetes) are vital to support traffic surges without overprovisioning.

3. Smart Data Handling

Scaling isn’t just compute—it’s efficient and smart data processing. Partitioning, replication, and eventual consistency ensure your data layer doesn’t become the bottleneck.

4. Observability First

Monitoring, logging, and tracing must be built in within every system to be highly scalable. Without visibility, scaling becomes reactive instead of strategic.

5. Built-in Resilience

Your services must fail gracefully, if its is destined to. Circuit breakers, retries, and redundancy aren’t extras—they’re essentials at scale.

These principles aren’t optional—they’re the baseline for every modern system architecture. Now you’re ready to explore the trends transforming how teams scale microservices in 2025!

Top Trends for Scalability in Microservices Architecture in 2025

As microservices continue to evolve, the focus on scalability has shifted from simply adding more instances to adopting intelligent, predictive, and autonomous scaling strategies. In 2025, the game is no longer about being cloud-native—it’s about scaling smartly!

Here are the trends that are redefining how you should approach scalability in microservices architecture.

🔹 1. Event-Driven Architecture—The New Default

Synchronous APIs once ruled microservices communication. Today, they’re a bottleneck. Event-driven systems using Kafka, NATS, or RabbitMQ are now essential for high-performance scaling.

With asynchronous communication:

Services don’t wait on each other, reducing latency.

You unlock horizontal scalability without database contention.

Failures become less contagious due to loose coupling.

By 2025, over 65% of cloud-native applications are expected to use event-driven approaches to handle extreme user loads efficiently. If you want to decouple scaling from system-wide dependencies, this is no longer optional—it’s foundational.

🔹 2. Service Mesh for Observability, Security, & Traffic Control

Managing service-to-service communication becomes complex during system scaling. That’s where service mesh solutions like Istio, Linkerd, and Consul step in. 

They enable:

Fine-grained traffic control (A/B testing, canary releases)

Built-in security through mTLS

Zero-instrumentation observability

A service mesh is more than just a networking tool. It acts like the operating system of your microservices, ensuring visibility, governance, and security as you scale your system. According to CNCF's 2024 report, Istio adoption increased by 80% year-over-year among enterprises with 50+ microservices in production.

🔹 3. Kubernetes Goes Fully Autonomous with KEDA & VPA

Though Kubernetes is the gold standard for orchestrating containers, managing its scaling configurations manually can be a tedious job. That’s where KEDA (Kubernetes Event-Driven Autoscaling) and VPA (Vertical Pod Autoscaler) are stepping in.

These tools monitor event sources (queues, databases, API calls) and adjust your workloads in real time, ensuring that compute and memory resources always align with demand. The concept of the best software for automated scalability management say that automation isn't just helpful—it’s becoming essential for lean DevOps teams.

🔹 4. Edge Computing Starts to Influence Microservices Design

As latency-sensitive applications (like real-time analytics, AR/VR, or video processing) become more common, we’re seeing a shift toward edge-deployable microservices!

Scaling at the edge reduces the load on central clusters and enables ultra-fast user experiences by processing closer to the source. By the end of 2025, nearly 40% of enterprise applications are expected to deploy at least part of their stack on edge nodes. 

🔹 5. AI-Powered Scaling Decisions

AI-driven autoscaling based on the traditional metrics ensures a more predictive approach. Digital platforms are now learning from historical traffic metrics, usage patterns, error rates, and system load to:

Predict spikes before they happen

Allocate resources preemptively

Reduce both downtime and cost

Think: Machine learning meets Kubernetes HPA—helping your system scale before users feel the lag. Great!

Modern Database Solutions for High-Traffic Microservices

Data is the bloodstream of your system/application. Every user interaction, transaction, or API response relies on consistent, fast, and reliable access to data. In a microservices environment, things get exponentially more complex as you scale, as each service may need its separate database or shared access to a data source.

This is why your choice of database—and how you architect it—is a non-negotiable pillar in the system scaling strategy. You're not just selecting a tool; you're committing to a system that must support distributed workloads, global availability, real-time access, and failure recovery!

Modern database systems must support:

Elastic growth without manual intervention

Multi-region deployment to reduce latency and serve global traffic

High availability and automatic failover

Consistency trade-offs depending on workload (CAP theorem realities)

Support for eventual consistency, sharding, and replication in distributed environments

Now, let’s explore some of the top database solutions for handling high traffic—

MongoDB

Schema-less, horizontally scalable, and ideal for rapid development with flexible data models.

Built-in sharding and replication make it a go-to for user-centric platforms.

Cassandra

Distributed by design, Cassandra is engineered for write-heavy applications.

Its peer-to-peer architecture ensures zero downtime and linear scalability.

Redis (In-Memory Cache/DB)

Blazing-fast key-value store used for caching, session management, and real-time analytics.

Integrates well with primary databases to reduce latency.

CockroachDB 

A distributed SQL database that survives node failures with no manual intervention. 

Great for applications needing strong consistency and horizontal scale.

YugabyteDB 

Compatible with PostgreSQL, it offers global distribution, automatic failover, and multi-region writes—ideal for SaaS products operating across continents.

PostgreSQL + Citus

Citus transforms PostgreSQL into a horizontally scalable, distributed database—helpful for handling large analytical workloads with SQL familiarity.

Amazon Aurora

A managed, high-throughput version of MySQL and PostgreSQL with auto-scaling capabilities. 

Perfect for cloud-native microservices with relational needs.

Google Cloud Spanner

Combines SQL semantics with global horizontal scaling.

Offers strong consistency and uptime guarantees—ideal for mission-critical financial systems.

Vitess

Used by YouTube, Vitess runs MySQL underneath but enables sharding and horizontal scalability at a massive scale—well-suited for read-heavy architectures.

Bottomline

Scaling a modern digital product requires more than just technical upgrades—it demands architectural maturity. Scalability in microservices architecture is built on clear principles of—

service independence, 

data resilience, 

automated infrastructure, and 

real-time observability.

Microservices empower teams to scale components independently, deploy faster, and maintain stability under pressure. The result—Faster time to market, better fault isolation, and infrastructure that adjusts dynamically with demand.

What truly validates this approach are the countless case studies on successful product scaling from tech companies that prioritized scalability as a core design goal. From global SaaS platforms to mobile-first startups, the trend is clear—organizations that invest early in scalable microservices foundations consistently outperform those who patch their systems later.

Scalability in microservices architecture starts with the right foundation—not reactive fixes. Consult the software experts at Acquaint Softtech to assess and align your system for scale. Contact us now to start building with long-term resilience in mind.

Get in Touch

FAQs

1. What is scalability in microservices architecture?

Scalability in microservices architecture refers to the ability of individual services within a system to scale independently based on workload. This allows you to optimize resource usage, reduce downtime, and ensure responsiveness during high-traffic conditions. It enables your application to adapt dynamically to user demand without overburdening the entire system.

2. Why are databases critical in scalable architectures?

A scalable system is only as strong as its data layer. If your services scale but your database can't handle distributed loads, your entire application can face performance bottlenecks. Scalable databases offer features like replication, sharding, caching, and automated failover to maintain performance under pressure.

3. What are the best practices for automated scalability?

Automated scalability involves using tools like Kubernetes HPA, KEDA, and VPA to auto-adjust resources based on real-time metrics. Best practices also include decoupling services, setting scaling thresholds, and implementing observability tools like Prometheus and Grafana. We just disclosed them all in the blog above!

4. Are there real-world case studies on successful product scaling?

Yes, many leading companies have adopted microservices and achieved remarkable scalability. For instance, Netflix, Amazon, and Uber are known for leveraging microservices to scale specific features independently. At Acquaint Softtech, we’ve also delivered tailored solutions backed by case studies on successful product scaling for startups and enterprises alike. Get in touch with our software expert to know more!

[screwdriver-cd]

New bug fixes and features - Q1 2025

The Screwdriver team is pleased to announce our newest release which brings in new features and bug fixes across various components.

New Features

UI

The new Pipeline landing page is now generally available. Once users opt in, they will be redirected to the new experience.

The expand and collapse feature has been added to pipeline stages. The stage's completion status is now reflected in its border.

The display of multiple banners has been modified from a stacked format to a paginated layout

API

Relax permission check to allow admins from other SCMs to update pipeline

Added APIs to create and delete buildCluster annotations, enabling Screwdriver admins to move jobs to specific clusters

New endpoint to update buildcluster of a pipeline

Improve pipeline searches by adding the 'scmUri' query parameter

Introduced a 'not equal' filter for pipeline events creator in the pipeline events list API

Changes to banner to include scope and scopeId

Bug Fixes

UI

Pipeline header updating issue resolved by adding necessary tracking to the pipeline header component, allowing proper updates when a pipeline changes, see PR

Pipeline root directory now included and displayed with branch name in new landing page, with additional CSS styling cleanup, see PR

Corrected the aggressive logic in the new landing page that was preventing jobs included in a stage from being started/restarted, now allowing these jobs to be started/restarted as needed, see PR

Fixed missing stages border when accessing pipeline from Collection by directly requesting stage data from the backend, see PR

Enhanced UI consistency by applying standardized CSS styling to the modal button within the build detail page, aligning it with the appearance of the workflow graph tooltip start modal, see PR

Ensured the start all children pipelines API call requests the entire error object, allowing more detailed analysis of the API call and returned status code, see PR

Fix: Remote trigger's pipeline name now uses 'remoteName' instead of 'displayName' to avoid confusion. See PR

Fix: Build status determination was updated by relaxing the build meta warning object check and included warning statuses in the event card warning count. See PR

Fix: The edges from stages to upstreams are now properly drawn by providing a solution for insufficient horizontal spacing between stages. See PR

Fix: The post body for PR events was improved by correctly including the job prefix in the `startFrom` value when restarting a PR job. See PR

Fix: Column name in event job display changed from 'HISTORY' to 'STATUS' for accuracy in new landing page. See PR

Fix: Long branch names on the search page are now truncated. See PR

Fix: API fetch updated to ignore scheduler events for configured pipeline. See PR

Fix: The new landing page now correctly reloads the workflow graph when starting a new event. See PR

Fix: Overflow handling for long messages added to prevent text overflow in event card. See PR

Fix: Pipeline data removed from route models due to direct injection into components. See PR

Fix: The maximum node depth issue was fixed, addressing problems with 0-based counted node depth and empty arrays for pipelines with detached jobs only. See PR

Fix: The creation of a sparse array with empty slots which caused downstream calculations to break was fixed. See PR

Fix: Parameters drop down issue resolved in new landing page by adjusting dropdown spacing and removing additional scroll logic. See PR

Fix: Build warning determination logic was fixed to correctly display warning status. See PR

Fix: Node depth calculation in workflow graph was improved by introducing 'Topological sort' for more accurate depth assignments. See PR

Fix: An issue preventing the use of anchor tags within the navigation banner was fixed. See PR

Fix: Job restart is now disabled for jobs with no builds in the new landing page. See PR

API

Upgrade of Node.js v22 and dependencies

Addressed a bug in build triggering in certain cases of restarts, ensuring the next build is correctly triggered from the latest child event, see PR

Fixed an issue where an external trigger couldn't trigger a pipeline stage due to a misinterpretation of the event associated with the pipeline the job belongs to, see PR

Avoided creation of empty events when changed file names match the source directory, see PR

ParentBuildId now set just before execution to ensure correct metadata capture from parent builds, especially when they finish simultaneously, see PR

Converted the 'isActive' parameter from string to boolean for MySQL on banner list endpoint to ensure proper banner list retrieval, see PR

Included a webhook executor to the admin group before retrieving the pipeline token. This resolved the 'Pipeline has no admin' error during the webhook process, see PR

The metadata from the job that directly precedes the virtual job is now prioritized over the event metadata, see PR

Proper handling of virtual jobs in remote triggers, see PR

Fixed duplicate build issue by preventing the build status from updating to RUNNING if a build with the same ID is already running, see PR

Virtual builds now marked as completed when triggered by webhook, resolving a regression introduced in a previous update, see PR

Compatibility List

In order to have these improvements, you will need these minimum versions:

API - v8.0.16

UI - v1.0.1241

Store - v7.0.0

Queue-Service - v5.0.1

Launcher - v6.0.221

Build Cluster Worker - v5.0.1

Contributors

Thanks to the following contributors for making this feature possible. 

Akinori

Keisuke

Ming

Pritam

Sagar

Vonny

Yuki

Yuta

Teppei Minegishi

Questions and Suggestions

We’d love to hear from you. If you have any questions, please feel free to reach out here. You can also visit us on Github and Slack.

Author

Vonny Jap, Senior Manager, Software Dev Engineering, Yahoo

[job24by7]

Future-Ready IT Hiring Solutions – Job24by7

Whether you're a developer, analyst, or IT recruiter, we streamline the hiring process with expertise, speed, and precision. Get matched with the right opportunities today.

[centlinux]

GitOps vs DevOps vs DevSecOps: Key Differences and Best Practices

Explore the key differences between GitOps vs DevOps vs DevSecOps, and understand their best practices for modern software development. Learn how each approach enhances automation, security, and collaboration in CI/CD pipelines.

[reformedtech]

Finding the Best Software Company in Bangladesh: A Complete Guide

Bangladesh has become a growing hub for software innovation, offering a wide range of services through leading software development companies in Bangladesh. Whether you’re looking for the best software company in Bangladesh or skilled software developers for your project, this guide will help you make an informed decision.

Why Choose a Software Company in Bangladesh?

With a strong talent pool of application developers, software designers, and software programmers, Bangladesh provides innovative and cost-effective solutions. From software app development to large-scale system development, companies in Bangladesh have the expertise to cater to diverse business needs.

How to Identify the Best Software Company in Bangladesh

Proven Expertise: A top software company in BD will showcase an impressive portfolio of successful software development projects, ranging from applications software development to advanced software product development.

Experienced Team: Look for skilled professionals like software application developers, software development managers, and creative software designers who can execute your project with precision.

Local Accessibility: If proximity matters, search for software development companies near me or a software developer near me to ensure seamless communication and collaboration.

Advantages of Working with a Top Software Company in BD

Tailored Services: Whether you need local software development, applications development, or custom software app development, companies in Bangladesh provide personalized solutions.

Cost Efficiency: The best software company in Bangladesh offers premium services at competitive rates.

Timely Delivery: Experienced software development managers ensure projects are completed on schedule without compromising quality.

Final Thoughts

Selecting the right software development company in Bangladesh is essential for achieving your business goals. Whether you need assistance with software app development, system development, or other software development projects, ensure the company has the skills, experience, and reputation to deliver.

Have more questions about finding the best software company in Bangladesh? Share your thoughts in the comments, and let’s discuss!

[nitor-infotech]

AI in DevSecOps: Revolutionizing Security Testing and Code Analysis

DevSecOps, short for Development, Security, and Operations, is an approach that integrates security practices within the DevOps workflow. You can think of it as an extra step necessary for integrating security. Before, software development focused on speed and efficiency, often delaying security to the final stages.  

However, the rise in cyber threats has made it essential to integrate security into every phase of the software lifecycle. This evolution gave rise to DevSecOps, ensuring that security is not an afterthought but a shared responsibility across teams. 

From DevOps to DevSecOps: The Main Goal 

The shift from DevOps to DevSecOps emphasizes applying security into continuous integration and delivery (CI/CD) pipelines. The main goal of DevSecOps is to build secure applications by automating security checks. This approach helps in fostering a culture where developers, operations teams, and security experts collaborate seamlessly.  

How is AI Reshaping the Security Testing & Code Analysis Industry? 

Artificial intelligence and generative AI are transforming the landscape of security testing and code analysis by enhancing precision, speed, and scalability. Before AI took over, manual code reviews and testing were time-consuming and prone to errors. AI-driven solutions, however, automate these processes, enabling real-time vulnerability detection and smarter decision-making. 

Let’s look at how AI does that in detail:  

AI models analyze code repositories to identify known and unknown vulnerabilities with higher accuracy. 

Machine learning algorithms predict potential attack vectors and their impact on applications. 

AI tools simulate attacks to assess application resilience, saving time and effort compared to manual testing. 

AI ensures code adheres to security and performance standards by analyzing patterns and dependencies. 

As you can imagine, there have been several benefits of this:  

Reducing False Positives: AI algorithms improve accuracy in identifying real threats. 

Accelerating Scans: Traditional methods could take hours, but AI-powered tools perform security scans in minutes. 

Self-Learning Capabilities: AI systems evolve based on new data, adapting to emerging threats. 

Now that we know about the benefits AI has, let’s look at some challenges AI could pose in security testing & code analysis: 

AI systems require large datasets for training, which can expose sensitive information if not properly secured. This could cause disastrous data leaks.  

AI models trained on incomplete or biased data may lead to blind spots and errors. 

While AI automates many processes, over-reliance can result in missed threats that require human intuition to detect. 

Cybercriminals are leveraging AI to create advanced malware that can bypass traditional security measures, posing a new level of risk. 

Now that we know the current scenario, let’s look at how AI in DevSecOps will look like in the future:  

The Future of AI in DevSecOps 

AI’s role in DevSecOps will expand with emerging trends as:  

Advanced algorithms will proactively search for threats across networks, to prevent attacks. 

Future systems will use AI to detect vulnerabilities and automatically patch them without human intervention. 

AI will monitor user and system behavior to identify anomalies, enhancing the detection of unusual activities. 

Integrated AI platforms will facilitate seamless communication between development, operations, and security teams for faster decision-making. 

AI is revolutionizing DevSecOps by making security testing and code analysis smarter, faster, and more effective. While challenges like data leaks and algorithm bias exist, its potential is much more than the risks it poses.  

To learn how our AI-driven solutions can elevate your DevSecOps practices, contact us at Nitor Infotech. 

[ganesh0609]

Mobile Application Development

This new chapter in the world of the Internet is overtaking other, more traditional, forms of Web Development. The real magic is in creating apps that predict users’ behaviours, making smart decisions based on data.

[nixcraft]

How to Become a Farmer 🧑‍🌾

00. Learn Python 01. Write code day and night 02. Become a senior developer 03. Burn out solving problems 04. Finally had enough of this. Quit. 05. Become a farmer. Work with trees and animals and grow crops.

[algoson]

Algoson Software, a leading web and Software Development Company Based in India, is dedicated to crafting innovative websites, applications, and software tailored to your business needs. Serving clients in Switzerland, Canada, the USA, Portugal, France, Germany, and Italy, we are here to help. Email us at contact@algoson.com for more information.