Operations | Monitoring | ITSM | DevOps | Cloud

Downtime on the Docket: The Death Sentence for Productivity in Legal Firms

When minutes matter, IT leaders need more than quick fixes; they need foresight. That’s where Teneo’s Managed DEX (Digital Experience Monitoring) comes in. Managed DEX is designed to detect what legal teams can’t afford to miss. It monitors for “ghost traffic”- those eerie, unexplained signals of abnormal network activity that often signal compromise or instability- and other anomalous device behaviors that can precede full-blown outages or cyber incidents.

AWS CloudFormation Pricing Breakdown (And How To Save)

Nearly every industry today uses AWS for different services. Developers, cloud architects, DevOps engineers, and IT teams all use it to provision servers, databases, and storage. However, doing this service by service and then wiring them together can get messy. That’s where AWS CloudFormation comes in to save time, enforce consistency, and lower the risk of misconfigurations. But beyond simplifying infrastructure management, one big question remains: at what cost?

5 Common Meraki Alert Problems and How to Fix Them

Cisco Meraki is built to simplify cloud-managed networking, but for many IT admins, its alerts can quickly become overwhelming. From false positives to duplicate notifications, these Meraki alert issues drain time and distract from real problems. The good news is that most of these challenges are preventable with the right Meraki troubleshooting and the addition of smart incident management. Let’s explore five of the most common Meraki alert problems and how to fix them.

What is API-First Networking?

When you build your network with APIs at its core, you give your business a competitive edge. Here’s how to do it. Application Programming Interfaces (APIs) have become ubiquitous with modern networks for good reason. As companies use more service providers, endpoints, and software platforms, APIs help them get the most possible utility from their data with the least possible effort.

How we use Datadog to get comprehensive, fine-grained visibility into our email delivery system

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.

Medical Inventory Management Guide: 6 Best Practices

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.

Chaos Engineering works, but it has to scale

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 Performance Monitoring: Combine Logs and Metrics for Complete Visibility

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.

Building and deploying a Python MCP server with FastMCP and CircleCI

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.