Operations | Monitoring | ITSM | DevOps | Cloud

Today, CISOs and security teams face a rapidly growing volume of logs from a variety of sources, all arriving in different formats. They write and maintain detection rules, build pipelines, and investigate threats across multiple environments and applications. Efficiently maintaining their security posture across multiple products and data formats has become increasingly challenging.

vLLM is a high-performance serving framework for large language models (LLMs). It optimizes token generation and resource management to deliver low-latency, scalable performance for AI-driven applications such as chatbots, virtual assistants, and recommendation systems. By efficiently managing concurrent requests and overlapping tasks, vLLM enables organizations to deploy LLMs in demanding environments with speed and efficiency.

Serverless or event-driven applications can comprise many different distributed components, including serverless compute services such as AWS Lambda and AWS Fargate for Amazon ECS, as well as managed data streams, data stores, workflow orchestration tools, queues, and more. Having full end-to-end visibility into requests as they propagate across all of these parts of your application is crucial to monitoring performance, locating affected up- or downstream services, and troubleshooting issues.

Progressive web applications (PWAs) are a modern frontend architecture designed to provide a similar user experience to that of a native iOS, Android, or other platform-specific app. PWAs are built using common web platform technologies—such as, HTML, CSS, and JavaScript—and are intended not only to run in a browser and be accessed from the web, but also to be installed on users’ devices and accessed offline.

AWS Lambda supports nearly any programming language by enabling developers to run serverless functions with either supported or custom runtimes. Once a runtime is deprecated, however, AWS will set dates for when you can no longer create or update functions using that runtime. You will then need to decide what course of action to take to ensure your Lambda functions continue running as expected.

As your IT environment scales, a proactive approach to monitoring becomes increasingly critical. If your infrastructure environment contains multiple service dependencies, disparate systems, or a busy CI/CD application delivery pipeline, overlooked anomalies can result in a domino effect that leads to unplanned downtime and an adverse impact on users.

Windows Blue Screen errors—also known as bug checks, STOP codes, kernel errors, or the Blue Screen of Death (BSOD)—are triggered when the operating system detects a critical issue that compromises system stability. To prevent further damage or data corruption, the OS determines that the safest course of action is to shut down immediately. The system then restarts and displays the well-known BSOD.

Web applications emit a wealth of metadata and user interaction information that’s critical to understanding user behavior. However, parsing this data to find what is most relevant to your product analytics project can be challenging—what one product analyst might find useful, another might consider unnecessary noise.

Custom resources are critical components in Kubernetes production environments. They enable users to tailor Kubernetes resources to their specific applications or infrastructure needs, automate processes through operators, simplify the management of complex applications, and integrate with non-native applications such as Kafka and Elasticsearch.

While overprovisioning Kubernetes workloads can provide stability during the launch of new products, it’s often only sustainable because large companies have substantial budgets and favorable deals with cloud providers. As highlighted in Datadog’s State of Cloud Costs report, cloud spending continues to grow, but a significant portion of that cost is often due to inefficiencies like overprovisioning.