Operations | Monitoring | ITSM | DevOps | Cloud

Visibility into email performance is indispensable to any organization that counts on its ability to reach people through their inboxes, including Datadog. SREs, FinOps, and many other teams rely on email as a critical channel for communications from our platform, including monitor alerts, usage reports, and service account notifications. At Datadog, we depend on the visibility provided by our integrations for Mailgun, SendGrid, and Amazon SES to optimize our email performance and ensure deliverability.

Datadog Workflow Automation can automate processes and reduce the amount of time spent on time-consuming, repetitive tasks. You can trigger these workflows in real time by tying them to alerts, dashboards, Slack messages, and other signals.

In the healthcare sector, medical inventory management is far more than a simple logistical task. It directly impacts patient safety, quality of care, and cost control. A stockout of sterile gloves, syringes, or essential devices can delay a procedure, while overstocking leads to waste and ties up financial resources. With strict regulations, mandatory traceability, and urgent demands, healthcare facilities must find the right balance.

Over the years, Chaos Engineering has proven its effectiveness time and time again, uncovering risks and saving companies millions they would have lost in painful, brand-impacting outages. But as Chaos Engineering adoption increased, we found organizations running into the same stumbling blocks when they tried to scale. Individual teams would get great results with Chaos Engineering, then stall as they tried to get more teams involved.

Redis earns its place in modern stacks because it’s an in-memory data store with microsecond latency and rich data structures, making it perfect for things like caching, sessions, and rate limiting. Since it often sits on the request path, small issues (connection churn, blocked commands, memory pressure) can quickly ripple into user-visible incidents.

Extending Large Language Models (LLMs) with custom tools has become increasingly valuable in today’s AI landscape. Model Context Protocol (MCP) servers provide a standardized way to connect external tools and resources to LLMs. This can enhance their capabilities beyond basic text generation. While thousands of pre-built MCP servers exist, creating your own allows you to address specific workflows. You can implement use cases that off-the-shelf solutions cannot handle.

Business teams today move fast. Developers, site reliability engineers (SREs), and product owners expect to manage incidents, changes, and requests in a way that fits naturally into how they already work with tools like Jira and Confluence. Customers expect a seamless service experience powered by automation and AI. The result is a wave of teams adopting tools like Jira Service Management to get everything they need in one place without slowing down.

For a long time, public cloud has been the default answer to scaling infrastructure, but it's not the only path forward. As more teams weigh the risks of vendor lock-in, data residency, and dependence on US-based providers, the conversation around private cloud has taken on new urgency. However, building on private infrastructure doesn't have to mean sacrificing flexibility.

The third quarter of 2025 has been a busy one for VictoriaMetrics Cloud! We expanded globally, polished the user experience, introduced new enterprise debugging tools, and delivered smarter alerts to help users make the most of their observability data. If you missed our Quarterly Live Update, don’t worry! You can watch the full recording here: Let’s recap what’s new in VictoriaMetrics Cloud this quarter.