Operations | Monitoring | ITSM | DevOps | Cloud

Salesforce integration tools are now foundational to enterprise performance. With the average company managing over 1,000 apps, Salesforce must operate as a unified control layer that governs data, workflows, and customer intelligence across the stack. However, in reality most teams never realize this potential. According to Salesforce, 95% of IT leaders face integration challenges, and more than half say these issues directly block them from meeting customer expectations.

You’ve heard it before: ‘AI coding assistants aren’t here to replace you.’ And yes, it’s true, they’re not. They’re here to save your brain from 3 AM logic loops and the same bug fixes you’ve solved countless times. As application and database systems become more complex and timelines shrink, forward-thinking developers, data analysts, and DBAs are turning to these tools.

Having spent two decades in technical leadership, I’ve seen first hand what separates great development teams from merely good ones. It’s not about the number of features shipped or the elegance of the codebase — it’s about the ability to consistently deliver value to the customer through really great user experience.

Coralogix has released its APM Dependencies feature. This feature automatically surfaces and maps the relationships within and between your software and external services. It allows fine grained tracking of which endpoints within your APIs, depend on other endpoints, or external services and database tables.

It’s been a while since we’ve shared what’s been bubbling up behind these scenes are Scout. In this post, here’s an update on where we’ve been and where we’re going!

Isn’t the "Bring Your Own Cloud" (BYOC) model the latest hot topic in the evolution of cloud-native architecture, especially for companies offering cloud-hosted platforms that must be deployed in the customer’s cloud for privacy, control, or compliance reasons? Over the past few weeks, we have been rigorously researching and discussing how to build a secure BYOC model.

Modern data centers generate enormous volumes of telemetry from servers, switches, cooling systems, power infrastructure, and environmental sensors. Operations engineers must capture, store, and analyze this data in real-time to monitor uptime, maintain energy efficiency, and perform predictive maintenance using AI. Legacy monitoring systems struggle to meet today’s volume, cardinality, and latency demands.

It’s 2 AM. Your phone buzzes. A critical server’s CPU is maxing out again. But this time, the issue isn’t just high usage. It’s heat. As a network admin, you’re trained to monitor traffic patterns, patch vulnerabilities, and respond to performance slowdowns. But high CPU temperature? That’s the silent system killer many still underestimate. Without a proactive plan, it can knock out performance, rack up hardware costs, and shorten the lifespan of your infrastructure.

You write code. Open a PR. CI runs. PR merges. Prod’s on fire by 5pm. Maybe you skipped writing some tests. (It's tedious, sometimes unclear, and easy to ignore when you're racing to ship—until something breaks and you realize a test could’ve saved your Friday night.) Maybe the PR review was more of a drive-by from a teammate who barely had time to skim the diff. But reviews and tests matter.

Kentik CEO and co-founder Avi Freedman explains why observability is not enough in the age of AI.