Operations | Monitoring | ITSM | DevOps | Cloud

Harness Database DevOps was born from a simple question - how can database delivery be as seamless and safe as application delivery? Through deep collaboration with design partners, open-source learnings, and relentless iteration, the team built a platform that unites developers, DBAs, and DevOps under a single, automated workflow. At its core, it’s a story of empathy-driven engineering - transforming database change management into a faster, more reliable, and collaborative experience.

Harness makes software delivery in AWS faster, safer, and more delightful. Harness, the AI Platform for Everything After Code, offers CI/CD, infrastructure-as-code management, and cloud cost management capabilities tailored to the AWS environment. Harness has come a long way since its 2019 debut on the AWS Marketplace. Back then, over half of Harness customers were already running on AWS, and Harness focused on delivering Continuous Delivery as a Service for AWS applications.

Your remote developer can't access the VPN. Is it his home router? His ISP? Your network? You have no idea and no way to find out. This is the reality of modern IT. Your network doesn't end at your office perimeter. It extends into hundreds of homes, coffee shops, branch offices, and third-party locations you'll never set foot in. And when performance tanks, you're troubleshooting blind.

Log management and Network Detection and Response (NDR) solutions are closely related but offer different layers of visibility. Rather than overlapping, they complement each other, together providing a connected view of what’s happening in your environment. How exactly? Let’s take a closer look.

Observability data has a habit of outgrowing everything else. As telemetry volume, variety, and velocity increases, staying organized gets harder. Governance becomes messy, and the cost of digging through “everything” keeps rising. Over the past year, Coralogix’s DataPrime engine has been addressing these challenges by laying a new foundation for observability at scale.

Tracing is one of the most transformative gifts of observability. It allows engineers to follow a single request through a distributed system and see every span and dependency along the way. However, even with that visibility, some of our most basic questions stay unanswered. Why did a specific span behave differently today than it did yesterday? Why did latency rise even when nothing “broke”?

Enterprise data volumes are doubling every two years, but security and observability budgets remain mostly flat (or in the worst-case scenario, are declining). As teams struggle to keep up, the challenge isn’t just the amount of data, it’s the inefficiency of how that data is collected, processed, and routed. Most organizations rely on a patchwork of agents, forwarders, and legacy collectors like Syslog to ingest telemetry from across the environment.

Your network is not a static entity. It is a living system that has been running for years, absorbing countless changes. While your infrastructure may appear healthy on the surface, a slow and silent saboteur is often at work, methodically undermining your infrastructure from within. This is not the work of a malicious actor. It’s the inevitable result of a process you may not even be tracking: configuration drift.