Operations | Monitoring | ITSM | DevOps | Cloud

Picking an SQLite ODBC driver is like choosing a key; you need one that opens every door cleanly, without snapping or jamming. The right driver must connect your data effortlessly—no errors, no limitations. It also has to withstand real challenges: complex queries, cross-platform environments, and large datasets. In this guide, we’ll show you which 2026 drivers stand up to these demands, so you can pick the one that won’t let you down.

Short Summary: This article explains how to expand your CLI query tool so it can handle multiple databases. First, we focus on key relational systems, then move to data warehouses. We’ll use dbForge Edge as a reference point, showing how different databases can be managed in one place while keeping automation simple.

Short Summary: In this guide, we address performance problems that occur when PostgreSQL queries very large tables containing low-cardinality boolean fields. It also demonstrates how composite indexes, created and tested with Devart tools, allow PostgreSQL to locate the required rows directly instead of scanning the entire table.

If you've worked with builds and deployments, then you already know how central Docker images, dependencies, and containers are to modern software delivery. The introduction of Docker revolutionised how we package and run software, while the Open Container Initiative (OCI) brought much-needed standardisation to container formats and distribution. Docker made containers mainstream; OCI made them universal.

Modern enterprises operate across an increasingly complex mix of hybrid cloud services, and productivity platforms. As environments scale, stakeholders need a single pane of glass (SPoG) to understand what’s happening across IT operations without jumping across dozens of disconnected tools.

The best engineering teams rely on data-driven frameworks like DORA metrics and SPACE to measure developer productivity and demonstrate business impact. This guide explores proven measurement approaches that move beyond vanity metrics to capture real engineering value and team performance. Your developer productivity initiative didn't collapse because the data was wrong. It stalled because it couldn't answer the business question. Leadership asked, "So what?".

Regression testing is the practice of re-running existing tests after a code change to confirm that previously working functionality hasn’t broken. It answers a single question: did this change break something that used to work? In CI/CD pipelines, regression tests run automatically on every commit, giving teams immediate feedback before code reaches production.

AI-first hybrid observability with proactive monitoring helps MSPs protect SLAs as they move toward autonomous IT by getting engineers the right alerts before issues impact service. Managed services lives and dies on timing. The difference between a minor issue and a customer-facing incident often comes down to how early an engineer gets the right signal and how quickly they can act on it. That timing shows up in SLAs, service credits, escalations, and the trust you earn when customers feel taken care of.