Navigating the realm of Windows observability often referred to as O11y (short for observability), can be a complicated journey. Windows environments are known for their complexity, with various services, applications, and workloads running on each host.

Kubernetes (K8s) is at the forefront of modern infrastructure, but with its capabilities comes a deluge of telemetry data. Efficiently managing and optimizing this data is crucial to harnessing the full potential of your Kubernetes deployments.

In today's digital landscape, Observability and telemetry data play a crucial role in ensuring the performance, reliability, and security of modern applications and services. However, as data volumes explode due to the proliferation of micro-services, cloud-based applications, and connected devices, existing architectures are hitting a scalability wall.

Mezmo Edge enables users to deploy telemetry pipelines and process data in their own environment. A significant advancement in Mezmo’s capabilities, Edge is especially useful when working with sensitive medical or financial records. Organizations that need to comply with PCI, GDPR, or CCPA or that generally work with PII will benefit from Edge’s secure approach to data protection. Edge also provides the telemetry data optimization benefits of a pipeline without cloud data egress charges.

Cloud computing changed the way enterprise IT works. Investments in public technologies are forecasted to grow by 21.7% to reach the $600 billion mark by the end of this year. The trend is driven by two major factors: Business organizations view these capabilities as an imperative for digital transformation — especially the domain-specific IT services that solve problems unique to their industry verticals.

Setting meaningful goals for your technology investment decisions requires an understanding of your requirements. Primarily, that’s… Measuring your IT maturity is one way to advance your IT performance — in a way that aligns with your organizational goals and minimizes the risk of failure. You can compare your current situation to a group of peers or competitors and also to industry benchmarks. Let’s take a look.

The cybersecurity industry is experiencing an explosion of innovative tools designed to tackle complex security challenges. However, the hype surrounding these tools has outpaced their actual capabilities, leading many teams to struggle with complexity and extracting value from their investment. In this conversation with Optiv‘s Randy Lariar, we explore the potential and dangers of bringing advanced data analytics and artificial intelligence tools to the cybersecurity space.

As we venture deeper into the data-driven era, the traditional systems we have employed to store, search, and analyze data are being challenged by revolutionary advancements in Artificial Intelligence. One such groundbreaking development is the notable advent of Large Language Models (LLMs), specifically those with Multi-Mod[a]l abilities (e.g., Image & Audio).

The story of how we simplified database system monitoring for generalists while making it flexible enough for specialists.