Operations | Monitoring | ITSM | DevOps | Cloud

MLOps pipelines are a set of steps that automate the process of creating and maintaining AI/ML models. In other words, Data Scientists create multiple notebooks while building their experiments, and naturally the next step is a transition from experiments to production-ready code. The best way to do this is to build an effective MLOps pipeline. What’s the alternative, I hear you ask? Well, each time you want to create a model, you run your notebooks manually.

The rolling thunder of cybersecurity warnings has built to a crescendo this year. According to HelpNetSecurity, cybercriminals launched over 9.75 million DDoS attacks in 2022. The Cloudflare Attack Trends 2022 Q1 Report published yesterday shows an alarming increase in application-layer DDoS attacks. And our own Doug Madory has been sharing analysis on the impact of cyberattacks, too.

I always tell people "Observability is not logs, metrics, and traces! Observability is empowering your team to ask questions." That's very aspirational and sounds good, but it's not at all clear. I now have a self-contained story that perfectly explains it!

When a startup is in its very early stages, rapid iteration and dynamism are at the top of its priorities. The ability to do so, while maintaining a stable and high-quality product, is a big challenge facing the R&D group. We want to release features as quickly as possible, but this rapid velocity cane cause conflicts when writing in-depth, comprehensive tests.

Cloud costs are a daily concern for companies running applications on Amazon Web Services (AWS). This makes sense because many organizations struggle with unexpected AWS charges. Although many organizations have a cloud budget in place, accurately controlling costs is difficult. Real-time cost remediation is often difficult for many, leading to inflated AWS costs every billing cycle. No matter where you are on your cloud journey, reducing AWS costs is something you’ll want to do continuously.

Last week, an article from SiliconAngle came out detailing the challenges facing cybersecurity professionals. Companies are in desperate need of solutions to deal with cloud-native applications that exist in fast-paced environments. The security and IT teams monitoring these applications need scalable and flexible solutions that drive actionable insights. That’s why we built Cribl Stream.

Simple questions can be overwhelming and not knowing the answer after a mouse click is no longer an option: Sustainability is top of mind for organizations across all verticals and Splunk can help with the power of data. Our upcoming Sustainability Toolkit based on the Splunk platform equips organizations with capabilities to gain deep insights into their carbon footprint and as such empowers them to take the necessary actions towards their carbon neutrality goals.

Cloud native is a term that’s been around for many years but really started gaining traction in 2015 and 2016. This could be attributed to the rise of Docker, which was released a few years prior. Still, many organizations started becoming more aware of the benefits of running their workloads in the cloud. Whether because of cost savings or ease of operations, companies were increasingly looking into whether they should be getting on this “cloud native” trend.

The industrial revolution was a watershed period in human history. The shift from piecemeal, cottage-industry work to mechanized manufacturing transformed the way humans work. Since the 18th century, successive waves of innovation, such as the assembly line and the computer, continued to alter and change the nature of manufacturing. Today, we find ourselves in the midst of another industrial transformation.

As an IT operations manager, you spend a lot of your time mitigating service outages and service level risks. You worked diligently to get the right people, products, processes, and partners in place to meet your goals. You managed to ensure continued uptime. You’ve reduced the number of tickets and the cost per ticket. And for your efforts, you’re rewarded with managing your company’s cybersecurity program. The problem? You’re not a security specialist.