A blog site on our Real life experiences with various phases of DevOps starting from VCS, Build & Release, CI/CD, Cloud, Monitoring, Containerization.
Running a growing e-commerce platform like Opszilla is thrilling. You’re processing thousands of orders daily across the US and Canada, scaling infrastructure, and expanding into new markets. But amidst all that momentum, something starts to break: your data infrastructure and database performance.
At first, it’s subtle—slower queries, lagging reports, a few scaling hiccups. Then the real issue surfaces: you’re still running on MySQL 5.7, a version nearing its end-of-life in October 2023.
In this second part of our blog, we’ll walk through how we automated the migration process using Apache Airflow. We’ll cover everything from unloading data from Amazon Redshift to S3, transferring it to Google Cloud Storage (GCS), and finally loading it into Google BigQuery. This comprehensive process was orchestrated with Airflow to make sure every step was executed smoothly, automatically, and without error.
Continue reading “Automating Data Migration Using Apache Airflow: A Step-by-Step Guide”
When it comes to handling massive datasets, choosing the right approach can make or break your system’s performance. In this blog, I’ll take you through the first half of my Proof of Concept (PoC) journey—preparing data in Amazon Redshift for migration to Google BigQuery. From setting up Redshift to crafting an efficient data ingestion pipeline, this was a hands-on experience that taught me a lot about Redshift’s power (and quirks). Let’s dive into the details, and I promise it won’t be boring!
Continue reading “How to Optimize Amazon Redshift for Faster and Seamless Data Migration”
Integrating data from different sources can be a tough job, especially when dealing with a mix of old legacy systems, modern cloud platforms, and third-party APIs.
Each system stores data differently, making it hard to combine everything into one clear dataset.
If data integration isn’t handled well, businesses can end up with data silos—where important information is stuck in one place and can’t be accessed by those who need it.
This can lead to inconsistencies, making it difficult to trust the data used for decision-making.
This blog post discusses common integration challenges that can hamper your business efficiency. Also, we will be shedding light on solutions for the challenges.
Continue reading “10 Data Integration Challenges That Can Derail Your Business Success”
As we step into 2025, several data engineering trends are set to transform how we collect, process, and analyze data.
From breakthroughs in AI and machine learning to innovative data storage solutions and real-time analytics, these trends are making waves and driving advancements across industries.
These developments promise to enhance the efficiency and insights gained from data, making it more valuable than ever.
In this blog post, we’ll explore eight key data engineering trends to watch for in 2025, providing insights into how they will shape the future of data management and utilization.
Continue reading “Top Data Engineering Trends to Watch in 2025 and Beyond”
