Operations | Monitoring | ITSM | DevOps | Cloud

The Amazon Redshift data cloud provides a fast, secure, and widely accessible data warehouse solution. It is an ideal platform for performing complex analytics and processing large data sets. In addition to supporting multi-parallel processing (MPP), Redshift is also a type of Online Analytical Processing (OLAP) database. Yet, one of Redshift’s main selling points is its cost-effectiveness over alternatives like Snowflake and BigQuery. Is this the case? What is the actual cost of Amazon Redshift?

Open-source log management tools provide cost-effective, customizable approaches for collecting and analyzing log data. They help teams quickly identify patterns, spot anomalies, and resolve issues. With numerous options available, it's important to understand their strengths and limitations. This article examines the top open-source log management tools in 2025, focusing on their capabilities, performance, and best use cases.

Your website is your business’ storefront, sales team, customer service department, and potentially even your primary revenue channel. Just like you’d protect the physical presence of these aspects of your business with a security system, you also need to protect the online aspects too. That means keeping an eye on your website with monitoring.

You've got systems spitting out more logs, metrics, and traces than you can handle. Your monitoring costs are through the roof. And somehow, when something breaks at 3 AM, you still can't find the exact data you need. Sound familiar? Welcome to the observability pipeline conversation—no jargon, no fluff.

Have you ever struggled with systems that fail to tell you what went wrong? The kind where you’re digging through logs at 2 AM while alerts keep piling up. In DevOps, clear visibility into your applications isn’t a luxury—it’s essential. This is where instrumentation without code changes can help. It simplifies observability, reducing the manual effort needed to track down issues. If you haven’t explored it yet, you might be making troubleshooting harder than it needs to be.

Have you ever dealt with an outage in the middle of the night with no clear cause? Or struggled to understand why your application suddenly slowed down? End-to-end monitoring helps you connect the dots, ensuring you’re not left guessing when things go wrong.

Across companies of all shapes and sizes, observability practices are maturing and getting attention at the highest levels. At the same time, cost and complexity continue to hinder efforts as teams look to emerging tools to help simplify their processes in hopes of better outcomes. With so much in flux, we went into our third annual Observability Survey hoping to get a window into the ways the community is approaching observability and where it wants it to go next.

Network operations centers (NOCs) are under increasing pressure to improve efficiency, reduce downtime, and accelerate incident resolution. Yet many struggle to define a clear NOC automation strategy. When your team is deep in the trenches, it’s easy to lose sight of the long term: The answers lie within our framework: the Resolve Capabilities Model. This model was developed in tandem with customer conversations about NOC automation, aspirations, broader tech challenges, and more.

Regulatory compliance is a moving target, and keeping up with evolving security policies and industry regulations can feel like a never-ending battle. Manual network audits? They’re slow, error-prone, and a major time sink. But skipping them isn’t an option—compliance failures can lead to security breaches, hefty fines, and reputational damage. So, how can IT teams ensure they stay ahead without burning out? The answer: automation and real-time observability.

While incidents like last year’s CrowdStrike outage tend to dominate headlines, far more often, the real battle for Internet Resilience isn’t fought on a global stage. It’s waged in the shadows of financial districts, within overloaded cloud data centers, or a rural ISP’s overtaxed peering points. Traditional monitoring tools, designed for broad strokes, miss these hyper-specific failures.