Operations | Monitoring | ITSM | DevOps | Cloud

As large language models (LLMs) grow more powerful, organizations are deploying agentic AI applications to tackle complex, multi-step tasks. With Amazon Bedrock Agents, developers can orchestrate these agents to manage tasks such as triggering serverless functions, calling APIs, accessing knowledge bases, and maintaining contextual conversations—all while breaking down complex user requests or tasks into manageable steps.

Businesses across industries rely on time-stamped data to track system health, monitor performance, and improve operations. Whether it’s sensors on a factory floor or usage logs from a SaaS platform, time series data reveals how things change. As businesses digitize operations and add connected devices, sensors produce growing streams of time-based data. This opens the door to faster analytics and smarter automation. But legacy approaches can’t keep up.

As India emerges as a significant player in the global public cloud landscape, with its public cloud services market projected to reach $25.5 billion by 2028 at a CAGR of 24.3% for 2023-28, the country is witnessing a surge in tech events. This growth is mirrored in the live events market, which is experiencing a 15% YoY growth, fostering a stronger community and facilitating the exchange of ideas and innovation in the public cloud sector.

“It started as an experiment.” That’s how it begins at most companies. A small team spins up a few GPU instances to train a proof-of-concept model. Maybe it’s a fraud detection algorithm. Maybe it’s GenAI for support tickets. Either way, it’s just a test. Then the results come in, and they’re promising. Suddenly, that model is powering new features. Teams are fine-tuning LLMs in parallel.

“It’s always DNS.” That’s the running joke in IT. When websites won’t load and apps grind to a halt, DNS—the internet’s address book—is often the first to get blamed. That’s because DNS translates human-friendly names like google.com into IP addresses that computers use to route traffic.

APM stands for Application Performance Monitoring or Application Performance Management. It helps engineering teams track key metrics, detect slowdowns, and improve the overall performance of their applications. With Atatus APM, you get complete visibility into your application, from backend code and databases to external services and frontend performance.

When our organization – a mid-sized, fast-scaling technology company specializing in enterprise service management solutions, serving clients in regulated industries like finance and healthcare – faced its first serious cybersecurity breach in early 2024, we realized our incident response management approach wasn’t just outdated – it was putting the business at risk. Back then, we had alerts. We had logs.

Kentik transforms real-time network telemetry into actionable alerts for AI-optimized data centers. By converting database queries into custom alerts, engineers can detect issues like elephant flows, idle links, and packet loss before performance suffers and triggers alerts in systems like ServiceNow or PagerDuty.

Production AI needs a network that can keep up. Learn why private, scalable connectivity is the key in our webinar recap with Vultr. AI is no longer a proof-of-concept hiding in a developer lab. It’s a full-fledged production workload, and it’s hungry for data. But as enterprises move their AI strategies from theory to reality, they’re hitting a wall that isn’t about algorithms or processing power – it’s about the network.

In the cloud, Kafka’s promise of “never lose a byte” quietly morphs into “always pay for two.” Every time the leader syncs followers across zones, you get hit with premium egress charges that can dwarf compute costs. Diskless Kafka turns that upside-down: brokers replicate data straight into S3, so the pricey cross-zone hops vanish. Yes, object storage is slower than a local SSD, but the swap buys you on-demand elasticity and a bill that finally makes sense.