Friday the 13th - what can go wrong?
- Software Architecture
- Cloud ROI is Broken. Agentic AI Might Be the Fix.
The author explores AI's potential to automate day-to-day tasks like writing and reviewing infrastructure code, and monitoring for risks, freeing up teams and accelerating time to market. - Using Traffic Mirroring to Debug and Test Microservices in Production-Like Environments #PickOfTheWeek
Debug and test your microservices with confidence! This article dives into traffic mirroring, a powerful technique that duplicates live production requests to a test environment. Learn how to safely observe and compare service behavior for debugging complex bugs and performance profiling without impacting users. - When Caching Goes Wrong: How One Misconfigured Cache Took Down an Entire System #PickOfTheWeek
Discover how a small cache misconfiguration triggered a system-wide outage. This case study breaks down the failure, fix, and caching best practices.
- Cloud ROI is Broken. Agentic AI Might Be the Fix.
- Software Development
- How Agile Shift-Left Is Revolutionizing Software Development
By moving testing, security, and code reviews earlier in the development cycle, Agile shift-left strategies — powered by automation and AI — reduce risks, cut costs, and boost software quality. - Persistence Strategies for Aggregates
Choosing the right aggregate persistence strategy can be complex. This article breaks down various methods, including JPA Annotations, Document Databases like MongoDB, and Event Sourcing. Learn the advantages and disadvantages of each to find the best fit for your specific context. - AI Is Not Magic — But It’s a Tool Worth Knowing
This article shares a real-world hackathon experience, revealing how AI excels at small, well-defined tasks like code generation and documentation. Discover AI's practical strengths and when to leverage its power effectively. - MLOps: Practical Lessons from Bridging the Gap Between ML Development and Production #PickOfTheWeek
In this article, the author shares insights from implementing MLOps across organizations of different sizes and maturity levels, highlighting current trends and offering practical guidance based on real-world implementation challenges.
- How Agile Shift-Left Is Revolutionizing Software Development
- Testing
- Write Unit Tests, Don't Waste Our Money!
This article argues that every code change without a supporting unit test is a direct financial loss for the employer. Learn why automated tests are not just for programmers, but crucial for protecting your company's investment in its codebase. - Mutation Testing with PIT for Spring Boot Applications
Having tests isn’t the same as having effective tests. Mutation testing helps ensure your tests truly validate your code by deliberately introducing bugs and checking whether your tests catch them. In this guide, you’ll learn how to set up PIT, interpret results, and improve your test quality.
- Write Unit Tests, Don't Waste Our Money!
- Leadership
- Cultural Debt vs. Technical Debt in Infrastructure Automation #PickOfTheWeek
Beyond code, cultural debt can cripple your infrastructure automation. Discover how resistance to new tools, siloed teams, and unclear ownership impede progress and erode DevOps principles. This article unpacks the subtle but powerful ways cultural issues can manifest and impact your automation success.
- Cultural Debt vs. Technical Debt in Infrastructure Automation #PickOfTheWeek
- Communication
- Great Conversations Break the Rules #PickOfTheWeek
Want to have more powerful conversations? The author reveals six unconventional ways to break traditional rules, including getting 'nosey' with deeper questions and 'oversharing a little.' Learn how these techniques foster genuine connection and keep the conversation bouncing.
- Great Conversations Break the Rules #PickOfTheWeek
- Agile
- Better Estimates Are Possible on Agile Teams
This article explains that while we excel at estimating familiar tasks, unfamiliarity and overconfidence often lead to inaccuracies. Learn how consistent feedback and proper training can significantly improve estimation accuracy in agile environments
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