Operations | Monitoring | ITSM | DevOps | Cloud

As organizations adopt cloud technologies and modernize their applications, the data they generate and ingest often grows exponentially, leaving them with difficult choices for storing and using this data. Customers are beginning to explore moving away from traditional relational database management systems (RDBMS) because of the data volume to be ingested, as these RDBMS often cannot handle workloads.

Kubernetes made it much easier to deploy and scale containerized applications, but it also introduced new challenges for IT teams trying to keep tabs on these newly distributed systems. Ops teams need proper visibility into their Kubernetes clusters so they can track performance metrics, audit changes to deployed environments, and retrieve logs that help debug application crashes.

Welcome to day three of our very first Launch Week! The last two days we shared how alerting became so much better and how we moved one level up by completing our SOC 2 Type 1 audit. Are you curious what’s next? I’ll tell you, but first let’s set the stage and look at Microsoft’s Playwright.

For many workloads, using a time series database is a smart choice that saves time and storage space. Developers and companies have more database choices than ever. Choosing the right database for a project saves time when writing and querying data. As companies work with larger datasets to make increasingly intelligent and automated systems, efficiency is key. For many workloads, using a time series database is a smart choice that saves time and storage space.

In our inaugural State of Availability Report, we discovered that not only do metrics matter but the way we use them also does. Our research found that teams with fewer KPIs were more likely to meet their Service Level Agreements (SLAs) and provide their customers with higher levels of availability. The problem with having too many KPIs is that they cause information overload and noise.

Today, Cribl is releasing The State of Security Data Management 2022 in collaboration with CITE Research. The report examines the challenges that enterprises are facing as they work to balance evolving business priorities with cyber threats. The report was conducted in September 2022 and surveyed 1,000 senior-level IT and security decision-makers. The survey found that, although most organizations are confident in their data management strategy, few believe it’s actually sustainable.

You know that old adage about not seeing the forest for the trees? In our Authors’ Cut series, we’ve been looking at the trees that make up the observability forest—among them, CI/CD pipelines, Service Level Objectives, and the Core Analysis Loop. Today, I'd like to step back and take a look at how observability fits into the broader technical and cultural shifts in technology: cloud-native, DevOps, and SRE.

“I’m not a big enough business… I’m too small… no one will want to hack me.” “I don’t have anything of any importance that anyone would want… I’m not terribly concerned.” “It hasn’t happened to us yet, so it isn’t something I’m worried about.” “What you’re proposing seems like overkill to me. And besides, we don’t have the extra funds in our budget anyway.

As businesses generate, capture, and seek to analyze more data than ever before, they often find themselves limited by high data storage costs, expensive data processing fees, and high management overhead. For organizations who wish to expand their log analytics programs and become more data-driven, maximizing cost efficiency has become a critical operational objective.

When it comes to security, phishing is one of any IT team’s biggest concerns—as it targets the weakest link in the security chain: end-users. No matter how strong an organization’s technical defenses are, they can all be rendered useless if employees fall for a phishing attempt and hand over sensitive information. According to Cisco’s 2021 Cyber Security Threat Trends report, phishing is the second most prevalent cyber attack after crypto mining.