Operations | Monitoring | ITSM | DevOps | Cloud

When your company’s help desk receives fifteen "my connection is slow" tickets from remote employees in a single morning. Your network monitoring dashboard shows everything green; VPN concentrators running smoothly, bandwidth usage normal, no alerts. Yet employees can't get their work done. You try to ping their home routers. Nothing. Attempt a traceroute to diagnose the path. It dies at the ISP edge. Check your SNMP queries. They never make it past the residential gateway.

Google SecOps (formerly Chronicle) is widely used for large-scale security analytics, long-term telemetry retention, and detection across diverse environments. Its Unified Data Model (UDM) enables correlation across sources and supports analytics that operate over long time horizons. To take full advantage of these capabilities, security data must arrive in a consistent and well-structured UDM format. In practice, this is rarely the case.

A repository for this article can be found here.‍ When most developers think about request tracing, they picture instrumentation hooks inside familiar libraries. This allows us to track familiar metrics we see in application performance monitoring (APM) tools such as the duration of an HTTP call or how long a database query takes. But what if you could go deeper and instrument your own Ruby code automatically, without sprinkling timing calls everywhere?

High-performance computing (HPC) clusters rely on fast, reliable shared storage so that expensive CPU cores and GPUs aren’t left idle waiting for data. When bandwidth or I/O bottlenecks emerge, your workloads can slow down as your cluster spends more time on blocked reads, metadata lookups, and sync operations than actually computing.

A newly analyzed threat, Chrysalis, is a sophisticated backdoor attributed to the Chinese APT group Lotus Blossom. The malware employs advanced evasion techniques including heavy obfuscation, API hashing, dynamic DNS resolution, custom encryption and stealthy C2 communication disguised as legitimate traffic.

The secret to hyperscaler success isn’t magic. Kentik Co-founder and CEO Avi Freedman explains how organizations can adopt the same operating principles and empower network teams to drive results that far exceeds their headcount.

The 2025 Gartner Market Guide for Event Intelligence Solutions reflects a shift in how IT operations leaders evaluate AI-driven technologies. As AI hype gives way to more practical evaluation, we are seeing a natural departure from broad promises about AI capabilities toward clearly defined use cases and outcomes.

As Event Intelligence Solutions (EIS) move from early adoption to operational necessity, many enterprises are realizing that success depends on more than selecting the right technology. For Banking and Financial Services organizations, effective adoption requires a clear strategy, disciplined execution and a strong alignment to business priorities and regulatory demands and not least, customer expectations.