Operations | Monitoring | ITSM | DevOps | Cloud

VMware is a leading platform for virtualization and cloud infrastructure, widely used to manage compute, storage, and networking resources across on-premises and hybrid environments. While it offers powerful capabilities and extensive telemetry through tools like vCenter, navigating this data can be overwhelming – especially when trying to spot performance issues, capacity trends, or VM sprawl in real time. That’s where a solution like SquaredUp can make a significant difference.

OutboundSync, a powerful platform that helps marketers sync outbound sales data to CRMs like HubSpot and Salesforce, knows that transparency is key component of delivering a service that hundreds of teams rely on. And as an integration platform, OutboundSync is deeply reliant on other providers, making vendor reliability a key part of their own transparency.

Note: Grafana Beyla has been donated to OpenTelemetry under the new project name OpenTelemetry eBPF Instrumentation. Beyla will continue to exist as Grafana Labs’ distribution of the upstream project. Grafana Beyla is an open source eBPF-based auto-instrumentation tool that helps you easily get started with application observability, allowing you to monitor and visualize traces without modifying the application code.

You did it. You added the latest AI agent into your product. Shipped it. Went to sleep. Woke up to find it returning a blank string, taking five seconds longer than yesterday, or confidently outputting lies in perfect JSON. Naturally, you check your logs. You see a prompt. You see a response. And you see nothing helpful. Surprise. Prompt in and response out is not observability. It is vibes.

The JFrog Security Research team has recently discovered and disclosed CVE-2025-6514 – a critical (CVSS 9.6) security vulnerability in the mcp-remote project – a popular tool used by Model Context Protocol clients. The vulnerability allows attackers to trigger arbitrary OS command execution on the machine running mcp-remote when it initiates a connection to an untrusted MCP server, posing a significant risk to users – a full system compromise.

Time series data underpins all real-time systems. From high-resolution telemetry to long-range trends, it’s essential for monitoring, automation, predictive maintenance, and operational insight. But it’s also hard to work with: high cardinality, shifting schemas, and time-based queries make even basic tasks feel heavy.

For today's leading service providers and large enterprises, ensuring peak performance requires navigating a labyrinth of data streams, monitoring tools, and legacy systems. This often leaves network operators spending more time searching for information than acting on it. A new AI-enabled network management is dawning, promising to upend these cumbersome workflows.